* The `SqlLexical.allCaseVersions` will cause `StackOverflowException` if the key word is too long, the patch will fix that by normalizing all of the keywords in `SqlLexical`.
* And make a unified SparkSQLParser for sharing the common code.
Author: Cheng Hao <hao.cheng@intel.com>
Closes#3926 from chenghao-intel/long_keyword and squashes the following commits:
686660f [Cheng Hao] Support Long Keyword and Refactor the SQLParsers
Author: Daoyuan Wang <daoyuan.wang@intel.com>
Closes#4040 from adrian-wang/coalesce and squashes the following commits:
0ac8e8f [Daoyuan Wang] add coalesce() in sql parser
JIRA: https://issues.apache.org/jira/browse/SPARK-5287
This PR only add `defaultSizeOf` to data types and make those internal type classes `protected[sql]`. I will use another PR to cleanup the type hierarchy of data types.
Author: Yin Huai <yhuai@databricks.com>
Closes#4081 from yhuai/SPARK-5287 and squashes the following commits:
90cec75 [Yin Huai] Update unit test.
e1c600c [Yin Huai] Make internal classes protected[sql].
7eaba68 [Yin Huai] Add `defaultSize` method to data types.
fd425e0 [Yin Huai] Add all native types to NativeType.defaultSizeOf.
Author: Jacky Li <jacky.likun@gmail.com>
Closes#4100 from jackylk/patch-9 and squashes the following commits:
b13b9d6 [Jacky Li] Update SQLConf.scala
4d3f83d [Jacky Li] Update SQLConf.scala
fcc8c85 [Jacky Li] [SQL] fix typo in class description
Author: Reynold Xin <rxin@databricks.com>
Closes#4092 from rxin/bigdecimal and squashes the following commits:
27b08c9 [Reynold Xin] Fixed test.
10cb496 [Reynold Xin] [SPARK-5279][SQL] Use java.math.BigDecimal as the exposed Decimal type.
As part of SPARK-5193:
1. Removed UDFRegistration as a mixin in SQLContext and made it a field ("udf").
2. For Java UDFs, renamed dataType to returnType.
3. For Scala UDFs, added type tags.
4. Added all Java UDF registration methods to Scala's UDFRegistration.
5. Documentation
Author: Reynold Xin <rxin@databricks.com>
Closes#4056 from rxin/udf-registration and squashes the following commits:
ae9c556 [Reynold Xin] Updated example.
675a3c9 [Reynold Xin] Style fix
47c24ff [Reynold Xin] Python fix.
5f00c45 [Reynold Xin] Restore data type position in java udf and added typetags.
032f006 [Reynold Xin] [SPARK-5193][SQL] Reconcile Java and Scala UDFRegistration.
1. Removed 2 implicits (logicalPlanToSparkQuery and baseRelationToSchemaRDD)
2. Moved extraStrategies into ExperimentalMethods.
3. Made private methods protected[sql] so they don't show up in javadocs.
4. Removed createParquetFile.
5. Added Java version of applySchema to SQLContext.
Author: Reynold Xin <rxin@databricks.com>
Closes#4049 from rxin/sqlContext-refactor and squashes the following commits:
a326a1a [Reynold Xin] Remove createParquetFile and add applySchema for Java to SQLContext.
ecd6685 [Reynold Xin] Added baseRelationToSchemaRDD back.
4a38c9b [Reynold Xin] [SPARK-5193][SQL] Tighten up SQLContext API
Declare SQLConf to be serializable to fix "Task not serializable" exceptions in SparkSQL
Author: Alex Baretta <alexbaretta@gmail.com>
Closes#4031 from alexbaretta/SPARK-5235-SQLConf and squashes the following commits:
c2103f5 [Alex Baretta] [SPARK-5235] Make SQLConf Serializable
`TaskContext.attemptId` is misleadingly-named, since it currently returns a taskId, which uniquely identifies a particular task attempt within a particular SparkContext, instead of an attempt number, which conveys how many times a task has been attempted.
This patch deprecates `TaskContext.attemptId` and add `TaskContext.taskId` and `TaskContext.attemptNumber` fields. Prior to this change, it was impossible to determine whether a task was being re-attempted (or was a speculative copy), which made it difficult to write unit tests for tasks that fail on early attempts or speculative tasks that complete faster than original tasks.
Earlier versions of the TaskContext docs suggest that `attemptId` behaves like `attemptNumber`, so there's an argument to be made in favor of changing this method's implementation. Since we've decided against making that change in maintenance branches, I think it's simpler to add better-named methods and retain the old behavior for `attemptId`; if `attemptId` behaved differently in different branches, then this would cause confusing build-breaks when backporting regression tests that rely on the new `attemptId` behavior.
Most of this patch is fairly straightforward, but there is a bit of trickiness related to Mesos tasks: since there's no field in MesosTaskInfo to encode the attemptId, I packed it into the `data` field alongside the task binary.
Author: Josh Rosen <joshrosen@databricks.com>
Closes#3849 from JoshRosen/SPARK-4014 and squashes the following commits:
89d03e0 [Josh Rosen] Merge remote-tracking branch 'origin/master' into SPARK-4014
5cfff05 [Josh Rosen] Introduce wrapper for serializing Mesos task launch data.
38574d4 [Josh Rosen] attemptId -> taskAttemptId in PairRDDFunctions
a180b88 [Josh Rosen] Merge remote-tracking branch 'origin/master' into SPARK-4014
1d43aa6 [Josh Rosen] Merge remote-tracking branch 'origin/master' into SPARK-4014
eee6a45 [Josh Rosen] Merge remote-tracking branch 'origin/master' into SPARK-4014
0b10526 [Josh Rosen] Use putInt instead of putLong (silly mistake)
8c387ce [Josh Rosen] Use local with maxRetries instead of local-cluster.
cbe4d76 [Josh Rosen] Preserve attemptId behavior and deprecate it:
b2dffa3 [Josh Rosen] Address some of Reynold's minor comments
9d8d4d1 [Josh Rosen] Doc typo
1e7a933 [Josh Rosen] [SPARK-4014] Change TaskContext.attemptId to return attempt number instead of task ID.
fd515a5 [Josh Rosen] Add failing test for SPARK-4014
rxin follow up of #3732
Author: Daoyuan Wang <daoyuan.wang@intel.com>
Closes#4041 from adrian-wang/decimal and squashes the following commits:
aa3d738 [Daoyuan Wang] fix auto refactor
7777a58 [Daoyuan Wang] move sql.types.decimal.Decimal to sql.types.Decimal
Mostly just moving stuff around. This should still be source compatible since we type aliased Row previously in org.apache.spark.sql.Row.
Added the following APIs to Row:
```scala
def getMap[K, V](i: Int): scala.collection.Map[K, V]
def getJavaMap[K, V](i: Int): java.util.Map[K, V]
def getSeq[T](i: Int): Seq[T]
def getList[T](i: Int): java.util.List[T]
def getStruct(i: Int): StructType
```
Author: Reynold Xin <rxin@databricks.com>
Closes#4030 from rxin/sql-row and squashes the following commits:
6c85c29 [Reynold Xin] Fixed style violation by adding a new line to Row.scala.
82b064a [Reynold Xin] [SPARK-5167][SQL] Move Row into sql package and make it usable for Java.
Having two versions of the data type APIs (one for Java, one for Scala) requires downstream libraries to also have two versions of the APIs if the library wants to support both Java and Scala. I took a look at the Scala version of the data type APIs - it can actually work out pretty well for Java out of the box.
As part of the PR, I created a sql.types package and moved all type definitions there. I then removed the Java specific data type API along with a lot of the conversion code.
This subsumes https://github.com/apache/spark/pull/3925
Author: Reynold Xin <rxin@databricks.com>
Closes#3958 from rxin/SPARK-5123-datatype-2 and squashes the following commits:
66505cc [Reynold Xin] [SPARK-5123] Expose only one version of the data type APIs (i.e. remove the Java-specific API).
This change should be binary and source backward compatible since we didn't change any user facing APIs.
Author: Reynold Xin <rxin@databricks.com>
Closes#3965 from rxin/SPARK-5168-sqlconf and squashes the following commits:
42eec09 [Reynold Xin] Fix default conf value.
0ef86cc [Reynold Xin] Fix constructor ordering.
4d7f910 [Reynold Xin] Properly override config.
ccc8e6a [Reynold Xin] [SPARK-5168] Make SQLConf a field rather than mixin in SQLContext
With changes in this PR, users can persist metadata of tables created based on the data source API in metastore through DDLs.
Author: Yin Huai <yhuai@databricks.com>
Author: Michael Armbrust <michael@databricks.com>
Closes#3960 from yhuai/persistantTablesWithSchema2 and squashes the following commits:
069c235 [Yin Huai] Make exception messages user friendly.
c07cbc6 [Yin Huai] Get the location of test file in a correct way.
4456e98 [Yin Huai] Test data.
5315dfc [Yin Huai] rxin's comments.
7fc4b56 [Yin Huai] Add DDLStrategy and HiveDDLStrategy to plan DDLs based on the data source API.
aeaf4b3 [Yin Huai] Add comments.
06f9b0c [Yin Huai] Revert unnecessary changes.
feb88aa [Yin Huai] Merge remote-tracking branch 'apache/master' into persistantTablesWithSchema2
172db80 [Yin Huai] Fix unit test.
49bf1ac [Yin Huai] Unit tests.
8f8f1a1 [Yin Huai] [SPARK-4574][SQL] Adding support for defining schema in foreign DDL commands. #3431
f47fda1 [Yin Huai] Unit tests.
2b59723 [Michael Armbrust] Set external when creating tables
c00bb1b [Michael Armbrust] Don't use reflection to read options
1ea6e7b [Michael Armbrust] Don't fail when trying to uncache a table that doesn't exist
6edc710 [Michael Armbrust] Add tests.
d7da491 [Michael Armbrust] First draft of persistent tables.
Followup to #3870. Props to rahulaggarwalguavus for identifying the issue.
Author: Michael Armbrust <michael@databricks.com>
Closes#3990 from marmbrus/SPARK-5049 and squashes the following commits:
dd03e4e [Michael Armbrust] Fill in the partition values of parquet scans instead of using JoinedRow
Enable from follow multiple brackets:
```
select key from ((select * from testData limit 1) union all (select * from testData limit 1)) x limit 1
```
Author: scwf <wangfei1@huawei.com>
Closes#3853 from scwf/from and squashes the following commits:
14f110a [scwf] enable from follow multiple brackets
https://issues.apache.org/jira/browse/SPARK-4963
SchemaRDD.sample() return wrong results due to GapSamplingIterator operating on mutable row.
HiveTableScan make RDD with SpecificMutableRow and SchemaRDD.sample() will return GapSamplingIterator for iterating.
override def next(): T = {
val r = data.next()
advance
r
}
GapSamplingIterator.next() return the current underlying element and assigned it to r.
However if the underlying iterator is mutable row just like what HiveTableScan returned, underlying iterator and r will point to the same object.
After advance operation, we drop some underlying elments and it also changed r which is not expected. Then we return the wrong value different from initial r.
To fix this issue, the most direct way is to make HiveTableScan return mutable row with copy just like the initial commit that I have made. This solution will make HiveTableScan can not get the full advantage of reusable MutableRow, but it can make sample operation return correct result.
Further more, we need to investigate GapSamplingIterator.next() and make it can implement copy operation inside it. To achieve this, we should define every elements that RDD can store implement the function like cloneable and it will make huge change.
Author: Yanbo Liang <yanbohappy@gmail.com>
Closes#3827 from yanbohappy/spark-4963 and squashes the following commits:
0912ca0 [Yanbo Liang] code format keep
65c4e7c [Yanbo Liang] import file and clear annotation
55c7c56 [Yanbo Liang] better output of test case
cea7e2e [Yanbo Liang] SchemaRDD add copy operation before Sample operator
e840829 [Yanbo Liang] HiveTableScan return mutable row with copy
Follow up for #3712.
This PR finally remove ```CommandStrategy``` and make all commands follow ```RunnableCommand``` so they can go with ```case r: RunnableCommand => ExecutedCommand(r) :: Nil```.
One exception is the ```DescribeCommand``` of hive, which is a special case and need to distinguish hive table and temporary table, so still keep ```HiveCommandStrategy``` here.
Author: scwf <wangfei1@huawei.com>
Closes#3948 from scwf/followup-SPARK-4861 and squashes the following commits:
6b48e64 [scwf] minor style fix
2c62e9d [scwf] fix for hive module
5a7a819 [scwf] Refactory command in spark sql
Adding support for defining schema in foreign DDL commands. Now foreign DDL support commands like:
```
CREATE TEMPORARY TABLE avroTable
USING org.apache.spark.sql.avro
OPTIONS (path "../hive/src/test/resources/data/files/episodes.avro")
```
With this PR user can define schema instead of infer from file, so support ddl command as follows:
```
CREATE TEMPORARY TABLE avroTable(a int, b string)
USING org.apache.spark.sql.avro
OPTIONS (path "../hive/src/test/resources/data/files/episodes.avro")
```
Author: scwf <wangfei1@huawei.com>
Author: Yin Huai <yhuai@databricks.com>
Author: Fei Wang <wangfei1@huawei.com>
Author: wangfei <wangfei1@huawei.com>
Closes#3431 from scwf/ddl and squashes the following commits:
7e79ce5 [Fei Wang] Merge pull request #22 from yhuai/pr3431yin
38f634e [Yin Huai] Remove Option from createRelation.
65e9c73 [Yin Huai] Revert all changes since applying a given schema has not been testd.
a852b10 [scwf] remove cleanIdentifier
f336a16 [Fei Wang] Merge pull request #21 from yhuai/pr3431yin
baf79b5 [Yin Huai] Test special characters quoted by backticks.
50a03b0 [Yin Huai] Use JsonRDD.nullTypeToStringType to convert NullType to StringType.
1eeb769 [Fei Wang] Merge pull request #20 from yhuai/pr3431yin
f5c22b0 [Yin Huai] Refactor code and update test cases.
f1cffe4 [Yin Huai] Revert "minor refactory"
b621c8f [scwf] minor refactory
d02547f [scwf] fix HiveCompatibilitySuite test failure
8dfbf7a [scwf] more tests for complex data type
ddab984 [Fei Wang] Merge pull request #19 from yhuai/pr3431yin
91ad91b [Yin Huai] Parse data types in DDLParser.
cf982d2 [scwf] fixed test failure
445b57b [scwf] address comments
02a662c [scwf] style issue
44eb70c [scwf] fix decimal parser issue
83b6fc3 [scwf] minor fix
9bf12f8 [wangfei] adding test case
7787ec7 [wangfei] added SchemaRelationProvider
0ba70df [wangfei] draft version
The pull only fixes the parsing error and changes API to use tableIdentifier. Joining different catalog datasource related change is not done in this pull.
Author: Alex Liu <alex_liu68@yahoo.com>
Closes#3941 from alexliu68/SPARK-SQL-4943-3 and squashes the following commits:
343ae27 [Alex Liu] [SPARK-4943][SQL] refactoring according to review
29e5e55 [Alex Liu] [SPARK-4943][SQL] fix failed Hive CTAS tests
6ae77ce [Alex Liu] [SPARK-4943][SQL] fix TestHive matching error
3652997 [Alex Liu] [SPARK-4943][SQL] Allow table name having dot to support db/catalog ...
CaseInsensitiveMap throws java.io.NotSerializableException.
Author: luogankun <luogankun@gmail.com>
Closes#3944 from luogankun/SPARK-5141 and squashes the following commits:
b6d63d5 [luogankun] [SPARK-5141]CaseInsensitiveMap throws java.io.NotSerializableException
This change does a few things to make the hadoop-provided profile more useful:
- Create new profiles for other libraries / services that might be provided by the infrastructure
- Simplify and fix the poms so that the profiles are only activated while building assemblies.
- Fix tests so that they're able to run when the profiles are activated
- Add a new env variable to be used by distributions that use these profiles to provide the runtime
classpath for Spark jobs and daemons.
Author: Marcelo Vanzin <vanzin@cloudera.com>
Closes#2982 from vanzin/SPARK-4048 and squashes the following commits:
82eb688 [Marcelo Vanzin] Add a comment.
eb228c0 [Marcelo Vanzin] Fix borked merge.
4e38f4e [Marcelo Vanzin] Merge branch 'master' into SPARK-4048
9ef79a3 [Marcelo Vanzin] Alternative way to propagate test classpath to child processes.
371ebee [Marcelo Vanzin] Review feedback.
52f366d [Marcelo Vanzin] Merge branch 'master' into SPARK-4048
83099fc [Marcelo Vanzin] Merge branch 'master' into SPARK-4048
7377e7b [Marcelo Vanzin] Merge branch 'master' into SPARK-4048
322f882 [Marcelo Vanzin] Fix merge fail.
f24e9e7 [Marcelo Vanzin] Merge branch 'master' into SPARK-4048
8b00b6a [Marcelo Vanzin] Merge branch 'master' into SPARK-4048
9640503 [Marcelo Vanzin] Cleanup child process log message.
115fde5 [Marcelo Vanzin] Simplify a comment (and make it consistent with another pom).
e3ab2da [Marcelo Vanzin] Fix hive-thriftserver profile.
7820d58 [Marcelo Vanzin] Fix CliSuite with provided profiles.
1be73d4 [Marcelo Vanzin] Restore flume-provided profile.
d1399ed [Marcelo Vanzin] Restore jetty dependency.
82a54b9 [Marcelo Vanzin] Remove unused profile.
5c54a25 [Marcelo Vanzin] Fix HiveThriftServer2Suite with *-provided profiles.
1fc4d0b [Marcelo Vanzin] Update dependencies for hive-thriftserver.
f7b3bbe [Marcelo Vanzin] Add snappy to hadoop-provided list.
9e4e001 [Marcelo Vanzin] Remove duplicate hive profile.
d928d62 [Marcelo Vanzin] Redirect child stderr to parent's log.
4d67469 [Marcelo Vanzin] Propagate SPARK_DIST_CLASSPATH on Yarn.
417d90e [Marcelo Vanzin] Introduce "SPARK_DIST_CLASSPATH".
2f95f0d [Marcelo Vanzin] Propagate classpath to child processes during testing.
1adf91c [Marcelo Vanzin] Re-enable maven-install-plugin for a few projects.
284dda6 [Marcelo Vanzin] Rework the "hadoop-provided" profile, add new ones.
This PR:
- Reenables `surefire`, and copies config from `scalatest` (which is itself an old fork of `surefire`, so similar)
- Tells `surefire` to test only Java tests
- Enables `surefire` and `scalatest` for all children, and in turn eliminates some duplication.
For me this causes the Scala and Java tests to be run once each, it seems, as desired. It doesn't affect the SBT build but works for Maven. I still need to verify that all of the Scala tests and Java tests are being run.
Author: Sean Owen <sowen@cloudera.com>
Closes#3651 from srowen/SPARK-4159 and squashes the following commits:
2e8a0af [Sean Owen] Remove specialized SPARK_HOME setting for REPL, YARN tests as it appears to be obsolete
12e4558 [Sean Owen] Append to unit-test.log instead of overwriting, so that both surefire and scalatest output is preserved. Also standardize/correct comments a bit.
e6f8601 [Sean Owen] Reenable Java tests by reenabling surefire with config cloned from scalatest; centralize test config in the parent
Author: Reynold Xin <rxin@databricks.com>
Closes#3862 from rxin/stringcontext-attr and squashes the following commits:
9b10f57 [Reynold Xin] Rename StrongToAttributeConversionHelper
72121af [Reynold Xin] [SPARK-5040][SQL] Support expressing unresolved attributes using $"attribute name" notation in SQL DSL.
As we learned in https://github.com/apache/spark/pull/3580, not explicitly typing implicit functions can lead to compiler bugs and potentially unexpected runtime behavior.
Author: Reynold Xin <rxin@databricks.com>
Closes#3859 from rxin/sql-implicits and squashes the following commits:
30c2c24 [Reynold Xin] [SPARK-5038] Add explicit return type for implicit functions in Spark SQL.
JIRA issue: [SPARK-4570](https://issues.apache.org/jira/browse/SPARK-4570)
We are planning to create a `BroadcastLeftSemiJoinHash` to implement the broadcast join for `left semijoin`
In left semijoin :
If the size of data from right side is smaller than the user-settable threshold `AUTO_BROADCASTJOIN_THRESHOLD`,
the planner would mark it as the `broadcast` relation and mark the other relation as the stream side. The broadcast table will be broadcasted to all of the executors involved in the join, as a `org.apache.spark.broadcast.Broadcast` object. It will use `joins.BroadcastLeftSemiJoinHash`.,else it will use `joins.LeftSemiJoinHash`.
The benchmark suggests these made the optimized version 4x faster when `left semijoin`
<pre><code>
Original:
left semi join : 9288 ms
Optimized:
left semi join : 1963 ms
</code></pre>
The micro benchmark load `data1/kv3.txt` into a normal Hive table.
Benchmark code:
<pre><code>
def benchmark(f: => Unit) = {
val begin = System.currentTimeMillis()
f
val end = System.currentTimeMillis()
end - begin
}
val sc = new SparkContext(
new SparkConf()
.setMaster("local")
.setAppName(getClass.getSimpleName.stripSuffix("$")))
val hiveContext = new HiveContext(sc)
import hiveContext._
sql("drop table if exists left_table")
sql("drop table if exists right_table")
sql( """create table left_table (key int, value string)
""".stripMargin)
sql( s"""load data local inpath "/data1/kv3.txt" into table left_table""")
sql( """create table right_table (key int, value string)
""".stripMargin)
sql(
"""
|from left_table
|insert overwrite table right_table
|select left_table.key, left_table.value
""".stripMargin)
val leftSimeJoin = sql(
"""select a.key from left_table a
|left semi join right_table b on a.key = b.key""".stripMargin)
val leftSemiJoinDuration = benchmark(leftSimeJoin.count())
println(s"left semi join : $leftSemiJoinDuration ms ")
</code></pre>
Author: wangxiaojing <u9jing@gmail.com>
Closes#3442 from wangxiaojing/SPARK-4570 and squashes the following commits:
a4a43c9 [wangxiaojing] rebase
f103983 [wangxiaojing] change style
fbe4887 [wangxiaojing] change style
ff2e618 [wangxiaojing] add testsuite
1a8da2a [wangxiaojing] add BroadcastLeftSemiJoinHash
Convert type of RowWriteSupport.attributes to Array.
Analysis of performance for writing very wide tables shows that time is spent predominantly in apply method on attributes var. Type of attributes previously was LinearSeqOptimized and apply is O(N) which made write O(N squared).
Measurements on 575 column table showed this change made a 6x improvement in write times.
Author: Michael Davies <Michael.BellDavies@gmail.com>
Closes#3843 from MickDavies/SPARK-4386 and squashes the following commits:
892519d [Michael Davies] [SPARK-4386] Improve performance when writing Parquet files
This PR is a simplified version of several filter optimization rules introduced in #3778 authored by scwf. Newly introduced optimizations include:
1. `a && a` => `a`
2. `a || a` => `a`
3. `(a || b || c || ...) && (a || b || d || ...)` => `a && b && (c || d || ...)`
The 3rd rule is particularly useful for optimizing the following query, which is planned into a cartesian product
```sql
SELECT *
FROM t1, t2
WHERE (t1.key = t2.key AND t1.value > 10)
OR (t1.key = t2.key AND t2.value < 20)
```
to the following one, which is planned into an equi-join:
```sql
SELECT *
FROM t1, t2
WHERE t1.key = t2.key
AND (t1.value > 10 OR t2.value < 20)
```
The example above is quite artificial, but common predicates are likely to appear in real life complex queries (like the one mentioned in #3778).
A difference between this PR and #3778 is that these optimizations are not limited to `Filter`, but are generalized to all logical plan nodes. Thanks to scwf for bringing up these optimizations, and chenghao-intel for the generalization suggestion.
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Author: Cheng Lian <lian@databricks.com>
Closes#3784 from liancheng/normalize-filters and squashes the following commits:
caca560 [Cheng Lian] Moves filter normalization into BooleanSimplification rule
4ab3a58 [Cheng Lian] Fixes test failure, adds more tests
5d54349 [Cheng Lian] Fixes typo in comment
2abbf8e [Cheng Lian] Forgot our sacred Apache licence header...
cf95639 [Cheng Lian] Adds an optimization rule for filter normalization
This is a follow-up of #3367 and #3644.
At the time #3644 was written, #3367 hadn't been merged yet, thus `IsNull` and `IsNotNull` filters are not covered in the first version of `ParquetFilterSuite`. This PR adds corresponding test cases.
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Author: Cheng Lian <lian@databricks.com>
Closes#3748 from liancheng/test-null-filters and squashes the following commits:
1ab943f [Cheng Lian] IsNull and IsNotNull Parquet filter test case for boolean type
bcd616b [Cheng Lian] Adds Parquet filter pushedown tests for IsNull and IsNotNull
It will cause exception while do query like:
SELECT key+key FROM src sort by value;
Author: Cheng Hao <hao.cheng@intel.com>
Closes#3386 from chenghao-intel/sort and squashes the following commits:
38c78cc [Cheng Hao] revert the SortPartition in SparkStrategies
7e9dd15 [Cheng Hao] update the typo
fcd1d64 [Cheng Hao] rebase the latest master and update the SortBy unit test
spark sql does not support ```SELECT a, b FROM testData2 ORDER BY a desc, b```.
Author: wangfei <wangfei1@huawei.com>
Closes#3838 from scwf/orderby and squashes the following commits:
114b64a [wangfei] remove nouse methods
48145d3 [wangfei] fix order, using asc by default
There are a number of warnings generated in a normal, successful build right now. They're mostly Java unchecked cast warnings, which can be suppressed. But there's a grab bag of other Scala language warnings and so on that can all be easily fixed. The forthcoming PR fixes about 90% of the build warnings I see now.
Author: Sean Owen <sowen@cloudera.com>
Closes#3157 from srowen/SPARK-4297 and squashes the following commits:
8c9e469 [Sean Owen] Suppress unchecked cast warnings, and several other build warning fixes
This PR modifies the python `SchemaRDD` to use `sample()` and `takeSample()` from Scala instead of the slower python implementations from `rdd.py`. This is worthwhile because the `Row`'s are already serialized as Java objects.
In order to use the faster `takeSample()`, a `takeSampleToPython()` method was implemented in `SchemaRDD.scala` following the pattern of `collectToPython()`.
Author: jbencook <jbenjamincook@gmail.com>
Author: J. Benjamin Cook <jbenjamincook@gmail.com>
Closes#3764 from jbencook/master and squashes the following commits:
6fbc769 [J. Benjamin Cook] [SPARK-4860][pyspark][sql] fixing sloppy indentation for takeSampleToPython() arguments
5170da2 [J. Benjamin Cook] [SPARK-4860][pyspark][sql] fixing typo: from RDD to SchemaRDD
de22f70 [jbencook] [SPARK-4860][pyspark][sql] using sample() method from JavaSchemaRDD
b916442 [jbencook] [SPARK-4860][pyspark][sql] adding sample() to JavaSchemaRDD
020cbdf [jbencook] [SPARK-4860][pyspark][sql] using Scala implementations of `sample()` and `takeSample()`
...arquetFile accept hadoop glob pattern in path.
Author: Thu Kyaw <trk007@gmail.com>
Closes#3407 from tkyaw/master and squashes the following commits:
19115ad [Thu Kyaw] Merge https://github.com/apache/spark
ceded32 [Thu Kyaw] [SPARK-3928][SQL] Support wildcard matches on Parquet files.
d322c28 [Thu Kyaw] [SPARK-3928][SQL] Support wildcard matches on Parquet files.
ce677c6 [Thu Kyaw] [SPARK-3928][SQL] Support wildcard matches on Parquet files.
Add support for `GROUPING SETS`, `ROLLUP`, `CUBE` and the the virtual column `GROUPING__ID`.
More details on how to use the `GROUPING SETS" can be found at: https://cwiki.apache.org/confluence/display/Hive/Enhanced+Aggregation,+Cube,+Grouping+and+Rolluphttps://issues.apache.org/jira/secure/attachment/12676811/grouping_set.pdf
The generic idea of the implementations are :
1 Replace the `ROLLUP`, `CUBE` with `GROUPING SETS`
2 Explode each of the input row, and then feed them to `Aggregate`
* Each grouping set are represented as the bit mask for the `GroupBy Expression List`, for each bit, `1` means the expression is selected, otherwise `0` (left is the lower bit, and right is the higher bit in the `GroupBy Expression List`)
* Several of projections are constructed according to the grouping sets, and within each projection(Seq[Expression), we replace those expressions with `Literal(null)` if it's not selected in the grouping set (based on the bit mask)
* Output Schema of `Explode` is `child.output :+ grouping__id`
* GroupBy Expressions of `Aggregate` is `GroupBy Expression List :+ grouping__id`
* Keep the `Aggregation expressions` the same for the `Aggregate`
The expressions substitutions happen in Logic Plan analyzing, so we will benefit from the Logical Plan optimization (e.g. expression constant folding, and map side aggregation etc.), Only an `Explosive` operator added for Physical Plan, which will explode the rows according the pre-set projections.
A known issue will be done in the follow up PR:
* Optimization `ColumnPruning` is not supported yet for `Explosive` node.
Author: Cheng Hao <hao.cheng@intel.com>
Closes#1567 from chenghao-intel/grouping_sets and squashes the following commits:
fe65fcc [Cheng Hao] Remove the extra space
3547056 [Cheng Hao] Add more doc and Simplify the Expand
a7c869d [Cheng Hao] update code as feedbacks
d23c672 [Cheng Hao] Add GroupingExpression to replace the Seq[Expression]
414b165 [Cheng Hao] revert the unnecessary changes
ec276c6 [Cheng Hao] Support Rollup/Cube/GroupingSets
```
TestSQLContext.sparkContext.parallelize(
"""{"ip":"27.31.100.29","headers":{"Host":"1.abc.com","Charset":"UTF-8"}}""" ::
"""{"ip":"27.31.100.29","headers":{}}""" ::
"""{"ip":"27.31.100.29","headers":""}""" :: Nil)
```
As empty string (the "headers") will be considered as String in the beginning (in line 2 and 3), it ignores the real nested data type (struct type "headers" in line 1), and also take the line 1 (the "headers") as String Type, which is not our expected.
Author: Cheng Hao <hao.cheng@intel.com>
Closes#3708 from chenghao-intel/json and squashes the following commits:
e7a72e9 [Cheng Hao] add more concise unit test
853de51 [Cheng Hao] NullType instead of StringType when sampling against empty string or null value
Author: Michael Armbrust <michael@databricks.com>
Closes#3727 from marmbrus/parquetNotEq and squashes the following commits:
2157bfc [Michael Armbrust] Fix parquet filter suite
Predicates like `a = NULL` and `a < NULL` can't be pushed down since Parquet `Lt`, `LtEq`, `Gt`, `GtEq` doesn't accept null value. Note that `Eq` and `NotEq` can only be used with `null` to represent predicates like `a IS NULL` and `a IS NOT NULL`.
However, normally this issue doesn't cause NPE because any value compared to `NULL` results `NULL`, and Spark SQL automatically optimizes out `NULL` predicate in the `SimplifyFilters` rule. Only testing code that intentionally disables the optimizer may trigger this issue. (That's why this issue is not marked as blocker and I do **NOT** think we need to backport this to branch-1.1
This PR restricts `Lt`, `LtEq`, `Gt` and `GtEq` to non-null values only, and only uses `Eq` with null value to pushdown `IsNull` and `IsNotNull`. Also, added support for Parquet `NotEq` filter for completeness and (tiny) performance gain, it's also used to pushdown `IsNotNull`.
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Author: Cheng Lian <lian@databricks.com>
Closes#3367 from liancheng/filters-with-null and squashes the following commits:
cc41281 [Cheng Lian] Fixes several styling issues
de7de28 [Cheng Lian] Adds stricter rules for Parquet filters with null
Add `sort by` support for both DSL & SqlParser.
This PR is relevant with #3386, either one merged, will cause the other rebased.
Author: Cheng Hao <hao.cheng@intel.com>
Closes#3481 from chenghao-intel/sortby and squashes the following commits:
041004f [Cheng Hao] Add sort by for DSL & SimpleSqlParser
Using lowercase for ```options``` key to make it case-insensitive, then we should use lower case to get value from parameters.
So flowing cmd work
```
create temporary table normal_parquet
USING org.apache.spark.sql.parquet
OPTIONS (
PATH '/xxx/data'
)
```
Author: scwf <wangfei1@huawei.com>
Author: wangfei <wangfei1@huawei.com>
Closes#3470 from scwf/ddl-ulcase and squashes the following commits:
ae78509 [scwf] address comments
8f4f585 [wangfei] address comments
3c132ef [scwf] minor fix
a0fc20b [scwf] Merge branch 'master' of https://github.com/apache/spark into ddl-ulcase
4f86401 [scwf] adding CaseInsensitiveMap
e244e8d [wangfei] using lower case in json
e0cb017 [wangfei] make options in-casesensitive
This PR brings support of using StructType(and other hashable types) as key in MapType.
Author: Davies Liu <davies@databricks.com>
Closes#3714 from davies/fix_struct_in_map and squashes the following commits:
68585d7 [Davies Liu] fix primitive types in MapType
9601534 [Davies Liu] support StructType as key in MapType
Author: Cheng Hao <hao.cheng@intel.com>
Closes#3595 from chenghao-intel/udf0 and squashes the following commits:
a858973 [Cheng Hao] Add 0 arguments support for udf
This PR provides a set Parquet testing API (see trait `ParquetTest`) that enables developers to write more concise test cases. A new set of Parquet test suites built upon this API are added and aim to replace the old `ParquetQuerySuite`. To avoid potential merge conflicts, old testing code are not removed yet. The following classes can be safely removed after most Parquet related PRs are handled:
- `ParquetQuerySuite`
- `ParquetTestData`
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Author: Cheng Lian <lian@databricks.com>
Closes#3644 from liancheng/parquet-tests and squashes the following commits:
800e745 [Cheng Lian] Enforces ordering of test output
3bb8731 [Cheng Lian] Refactors HiveParquetSuite
aa2cb2e [Cheng Lian] Decouples ParquetTest and TestSQLContext
7b43a68 [Cheng Lian] Updates ParquetTest Scaladoc
7f07af0 [Cheng Lian] Adds a new set of Parquet test suites
In BroadcastHashJoin, currently it is using a hard coded value (5 minutes) to wait for the execution and broadcast of the small table.
In my opinion, it should be a configurable value since broadcast may exceed 5 minutes in some case, like in a busy/congested network environment.
Author: Jacky Li <jacky.likun@huawei.com>
Closes#3133 from jackylk/timeout-config and squashes the following commits:
733ac08 [Jacky Li] add spark.sql.broadcastTimeout in SQLConf.scala
557acd4 [Jacky Li] switch to sqlContext.getConf
81a5e20 [Jacky Li] make wait time configurable in BroadcastHashJoin
In `HashOuterJoin.scala`, spark read data from both side of join operation before zip them together. It is a waste for memory. We are trying to read data from only one side, put them into a hashmap, and then generate the `JoinedRow` with data from other side one by one.
Currently, we could only do this optimization for `left outer join` and `right outer join`. For `full outer join`, we will do something in another issue.
for
table test_csv contains 1 million records
table dim_csv contains 10 thousand records
SQL:
`select * from test_csv a left outer join dim_csv b on a.key = b.key`
the result is:
master:
```
CSV: 12671 ms
CSV: 9021 ms
CSV: 9200 ms
Current Mem Usage:787788984
```
after patch：
```
CSV: 10382 ms
CSV: 7543 ms
CSV: 7469 ms
Current Mem Usage:208145728
```
Author: tianyi <tianyi@asiainfo-linkage.com>
Author: tianyi <tianyi.asiainfo@gmail.com>
Closes#3375 from tianyi/SPARK-4483 and squashes the following commits:
72a8aec [tianyi] avoid having mutable state stored inside of the task
99c5c97 [tianyi] performance optimization
d2f94d7 [tianyi] fix bug: missing output when the join-key is null.
2be45d1 [tianyi] fix spell bug
1f2c6f1 [tianyi] remove commented codes
a676de6 [tianyi] optimize some codes
9e7d5b5 [tianyi] remove commented old codes
838707d [tianyi] Optimization about reduce memory costs during the HashOuterJoin
The problem is `codegenEnabled` is `val`, but it uses a `val` `sqlContext`, which can be override by subclasses. Here is a simple example to show this issue.
```Scala
scala> :paste
// Entering paste mode (ctrl-D to finish)
abstract class Foo {
protected val sqlContext = "Foo"
val codegenEnabled: Boolean = {
println(sqlContext) // it will call subclass's `sqlContext` which has not yet been initialized.
if (sqlContext != null) {
true
} else {
false
}
}
}
class Bar extends Foo {
override val sqlContext = "Bar"
}
println(new Bar().codegenEnabled)
// Exiting paste mode, now interpreting.
null
false
defined class Foo
defined class Bar
```
We should make `sqlContext` `final` to prevent subclasses from overriding it incorrectly.
Author: zsxwing <zsxwing@gmail.com>
Closes#3660 from zsxwing/SPARK-4812 and squashes the following commits:
1cbb623 [zsxwing] Make `sqlContext` final to prevent subclasses from overriding it incorrectly
Author: jerryshao <saisai.shao@intel.com>
Closes#3698 from jerryshao/SPARK-4847 and squashes the following commits:
4741130 [jerryshao] Make later added extraStrategies effect when calling strategies
When I use Parquet File as a output file using ParquetOutputFormat#getDefaultWorkFile, the file name is not zero padded while RDD#saveAsText does zero padding.
Author: Sasaki Toru <sasakitoa@nttdata.co.jp>
Closes#3602 from sasakitoa/parquet-zeroPadding and squashes the following commits:
6b0e58f [Sasaki Toru] Merge branch 'master' of git://github.com/apache/spark into parquet-zeroPadding
20dc79d [Sasaki Toru] Fixed the name of Parquet File generated by AppendingParquetOutputFormat
Unpersist a uncached RDD, will not raise exception, for example:
```
val data = Array(1, 2, 3, 4, 5)
val distData = sc.parallelize(data)
distData.unpersist(true)
```
But the `SchemaRDD` will raise exception if the `SchemaRDD` is not cached. Since `SchemaRDD` is the subclasses of the `RDD`, we should follow the same behavior.
Author: Cheng Hao <hao.cheng@intel.com>
Closes#3572 from chenghao-intel/try_uncache and squashes the following commits:
50a7a89 [Cheng Hao] SchemaRDD.unpersist() should not raise exception if it is not persisted
Author: Jacky Li <jacky.likun@huawei.com>
Closes#3630 from jackylk/remove and squashes the following commits:
150e7e0 [Jacky Li] remove unnecessary import
Author: Michael Armbrust <michael@databricks.com>
Closes#3613 from marmbrus/parquetPartitionPruning and squashes the following commits:
4f138f8 [Michael Armbrust] Use catalyst for partition pruning in newParquet.
Author: Jacky Li <jacky.likun@huawei.com>
Closes#3585 from jackylk/remove and squashes the following commits:
045423d [Jacky Li] remove unnecessary import
This is a very small fix that catches one specific exception and returns an empty table. #3441 will address this in a more principled way.
Author: Michael Armbrust <michael@databricks.com>
Closes#3586 from marmbrus/fixEmptyParquet and squashes the following commits:
2781d9f [Michael Armbrust] Handle empty lists for newParquet
04dd376 [Michael Armbrust] Avoid exception when reading empty parquet data through Hive
val jsc = new org.apache.spark.api.java.JavaSparkContext(sc)
val jhc = new org.apache.spark.sql.hive.api.java.JavaHiveContext(jsc)
val nrdd = jhc.hql("select null from spark_test.for_test")
println(nrdd.schema)
Then the error is thrown as follows:
scala.MatchError: NullType (of class org.apache.spark.sql.catalyst.types.NullType$)
at org.apache.spark.sql.types.util.DataTypeConversions$.asJavaDataType(DataTypeConversions.scala:43)
Author: YanTangZhai <hakeemzhai@tencent.com>
Author: yantangzhai <tyz0303@163.com>
Author: Michael Armbrust <michael@databricks.com>
Closes#3538 from YanTangZhai/MatchNullType and squashes the following commits:
e052dff [yantangzhai] [SPARK-4676] [SQL] JavaSchemaRDD.schema may throw NullType MatchError if sql has null
4b4bb34 [yantangzhai] [SPARK-4676] [SQL] JavaSchemaRDD.schema may throw NullType MatchError if sql has null
896c7b7 [yantangzhai] fix NullType MatchError in JavaSchemaRDD when sql has null
6e643f8 [YanTangZhai] Merge pull request #11 from apache/master
e249846 [YanTangZhai] Merge pull request #10 from apache/master
d26d982 [YanTangZhai] Merge pull request #9 from apache/master
76d4027 [YanTangZhai] Merge pull request #8 from apache/master
03b62b0 [YanTangZhai] Merge pull request #7 from apache/master
8a00106 [YanTangZhai] Merge pull request #6 from apache/master
cbcba66 [YanTangZhai] Merge pull request #3 from apache/master
cdef539 [YanTangZhai] Merge pull request #1 from apache/master
Author: baishuo <vc_java@hotmail.com>
Closes#3526 from baishuo/master-trycatch and squashes the following commits:
d446e14 [baishuo] correct the code style
b36bf96 [baishuo] correct the code style
ae0e447 [baishuo] add finally to avoid resource leak
Spark SQL has embeded sqrt and abs but DSL doesn't support those functions.
Author: Kousuke Saruta <sarutak@oss.nttdata.co.jp>
Closes#3401 from sarutak/dsl-missing-operator and squashes the following commits:
07700cf [Kousuke Saruta] Modified Literal(null, NullType) to Literal(null) in DslQuerySuite
8f366f8 [Kousuke Saruta] Merge branch 'master' of git://git.apache.org/spark into dsl-missing-operator
1b88e2e [Kousuke Saruta] Merge branch 'master' of git://git.apache.org/spark into dsl-missing-operator
0396f89 [Kousuke Saruta] Added sqrt and abs to Spark SQL DSL
A very small nit update.
Author: Reynold Xin <rxin@databricks.com>
Closes#3552 from rxin/license-header and squashes the following commits:
df8d1a4 [Reynold Xin] Indent license header properly for interfaces.scala.
Author: ravipesala <ravindra.pesala@huawei.com>
Closes#3516 from ravipesala/ddl_doc and squashes the following commits:
d101fdf [ravipesala] Style issues fixed
d2238cd [ravipesala] Corrected documentation
Supporting multi column support in countDistinct function like count(distinct c1,c2..) in Spark SQL
Author: ravipesala <ravindra.pesala@huawei.com>
Author: Michael Armbrust <michael@databricks.com>
Closes#3511 from ravipesala/countdistinct and squashes the following commits:
cc4dbb1 [ravipesala] style
070e12a [ravipesala] Supporting multi column support in count(distinct c1,c2..) in Spark SQL
group tab is missing for scaladoc
Author: Jacky Li <jacky.likun@gmail.com>
Closes#3458 from jackylk/patch-7 and squashes the following commits:
0121a70 [Jacky Li] add @group tab in limit() and count()
Re-implement the Python broadcast using file:
1) serialize the python object using cPickle, write into disks.
2) Create a wrapper in JVM (for the dumped file), it read data from during serialization
3) Using TorrentBroadcast or HttpBroadcast to transfer the data (compressed) into executors
4) During deserialization, writing the data into disk.
5) Passing the path into Python worker, read data from disk and unpickle it into python object, until the first access.
It fixes the performance regression introduced in #2659, has similar performance as 1.1, but support object larger than 2G, also improve the memory efficiency (only one compressed copy in driver and executor).
Testing with a 500M broadcast and 4 tasks (excluding the benefit from reused worker in 1.2):
name | 1.1 | 1.2 with this patch | improvement
---------|--------|---------|--------
python-broadcast-w-bytes | 25.20 | 9.33 | 170.13% |
python-broadcast-w-set | 4.13 | 4.50 | -8.35% |
Testing with 100 tasks (16 CPUs):
name | 1.1 | 1.2 with this patch | improvement
---------|--------|---------|--------
python-broadcast-w-bytes | 38.16 | 8.40 | 353.98%
python-broadcast-w-set | 23.29 | 9.59 | 142.80%
Author: Davies Liu <davies@databricks.com>
Closes#3417 from davies/pybroadcast and squashes the following commits:
50a58e0 [Davies Liu] address comments
b98de1d [Davies Liu] disable gc while unpickle
e5ee6b9 [Davies Liu] support large string
09303b8 [Davies Liu] read all data into memory
dde02dd [Davies Liu] improve performance of python broadcast
When we use ORDER BY clause, at first, attributes referenced by projection are resolved (1).
And then, attributes referenced at ORDER BY clause are resolved (2).
But when resolving attributes referenced at ORDER BY clause, the resolution result generated in (1) is discarded so for example, following query fails.
SELECT c1 + c2 FROM mytable ORDER BY c1;
The query above fails because when resolving the attribute reference 'c1', the resolution result of 'c2' is discarded.
Author: Kousuke Saruta <sarutak@oss.nttdata.co.jp>
Closes#3363 from sarutak/SPARK-4487 and squashes the following commits:
fd314f3 [Kousuke Saruta] Fixed attribute resolution logic in Analyzer
6e60c20 [Kousuke Saruta] Fixed conflicts
cb5b7e9 [Kousuke Saruta] Added test case for SPARK-4487
282d529 [Kousuke Saruta] Fixed attributes reference resolution error
b6123e6 [Kousuke Saruta] Merge branch 'master' of git://git.apache.org/spark into concat-feature
317b7fb [Kousuke Saruta] WIP
This PR is a workaround for SPARK-4479. Two changes are introduced: when merge sort is bypassed in `ExternalSorter`,
1. also bypass RDD elements buffering as buffering is the reason that `MutableRow` backed row objects must be copied, and
2. avoids defensive copies in `Exchange` operator
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Author: Cheng Lian <lian@databricks.com>
Closes#3422 from liancheng/avoids-defensive-copies and squashes the following commits:
591f2e9 [Cheng Lian] Passes all shuffle suites
0c3c91e [Cheng Lian] Fixes shuffle write metrics when merge sort is bypassed
ed5df3c [Cheng Lian] Fixes styling changes
f75089b [Cheng Lian] Avoids unnecessary defensive copies when sort based shuffle is on
Goals:
- Support for accessing parquet using SQL but not requiring Hive (thus allowing support of parquet tables with decimal columns)
- Support for folder based partitioning with automatic discovery of available partitions
- Caching of file metadata
See scaladoc of `ParquetRelation2` for more details.
Author: Michael Armbrust <michael@databricks.com>
Closes#3269 from marmbrus/newParquet and squashes the following commits:
1dd75f1 [Michael Armbrust] Pass all paths for FileInputFormat at once.
645768b [Michael Armbrust] Review comments.
abd8e2f [Michael Armbrust] Alternative implementation of parquet based on the datasources API.
938019e [Michael Armbrust] Add an experimental interface to data sources that exposes catalyst expressions.
e9d2641 [Michael Armbrust] logging / formatting improvements.
Sample code in the description of SchemaRDD.where is not correct
Author: Jacky Li <jacky.likun@gmail.com>
Closes#3344 from jackylk/patch-6 and squashes the following commits:
62cd126 [Jacky Li] [SQL] fix function description mistake
Executing sum distinct for empty table throws `java.lang.UnsupportedOperationException: empty.reduceLeft`.
Author: Takuya UESHIN <ueshin@happy-camper.st>
Closes#3184 from ueshin/issues/SPARK-4318 and squashes the following commits:
8168c42 [Takuya UESHIN] Merge branch 'master' into issues/SPARK-4318
66fdb0a [Takuya UESHIN] Re-refine aggregate functions.
6186eb4 [Takuya UESHIN] Fix Sum of GeneratedAggregate.
d2975f6 [Takuya UESHIN] Refine Sum and Average of GeneratedAggregate.
1bba675 [Takuya UESHIN] Refine Sum, SumDistinct and Average functions.
917e533 [Takuya UESHIN] Use aggregate instead of groupBy().
1a5f874 [Takuya UESHIN] Add tests to be executed as non-partial aggregation.
a5a57d2 [Takuya UESHIN] Fix empty Average.
22799dc [Takuya UESHIN] Fix empty Sum and SumDistinct.
65b7dd2 [Takuya UESHIN] Fix empty sum distinct.
The relational operator '<=>' is not working in Spark SQL. Same works in Spark HiveQL
Author: ravipesala <ravindra.pesala@huawei.com>
Closes#3387 from ravipesala/<=> and squashes the following commits:
7198e90 [ravipesala] Supporting relational operator '<=>' in Spark SQL
This PR enables the Web UI storage tab to show the in-memory table name instead of the mysterious query plan string as the name of the in-memory columnar RDD.
Note that after #2501, a single columnar RDD can be shared by multiple in-memory tables, as long as their query results are the same. In this case, only the first cached table name is shown. For example:
```sql
CACHE TABLE first AS SELECT * FROM src;
CACHE TABLE second AS SELECT * FROM src;
```
The Web UI only shows "In-memory table first".
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Author: Cheng Lian <lian@databricks.com>
Closes#3383 from liancheng/columnar-rdd-name and squashes the following commits:
071907f [Cheng Lian] Fixes tests
12ddfa6 [Cheng Lian] Names in-memory columnar RDD with corresponding table name
Author: Marcelo Vanzin <vanzin@cloudera.com>
Closes#3277 from vanzin/version-1.3 and squashes the following commits:
7c3c396 [Marcelo Vanzin] Added temp repo to sbt build.
5f404ff [Marcelo Vanzin] Add another exclusion.
19457e7 [Marcelo Vanzin] Update old version to 1.2, add temporary 1.2 repo.
3c8d705 [Marcelo Vanzin] Workaround for MIMA checks.
e940810 [Marcelo Vanzin] Bumping version to 1.3.0-SNAPSHOT.
For expressions like `10 < someVar`, we should create an `Operators.Gt` filter, but right now an `Operators.Lt` is created. This issue affects all inequality predicates with literals on the left hand side.
(This bug existed before #3317 and affects branch-1.1. #3338 was opened to backport this to branch-1.1.)
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Author: Cheng Lian <lian@databricks.com>
Closes#3334 from liancheng/fix-parquet-comp-filter and squashes the following commits:
0130897 [Cheng Lian] Fixes Parquet comparison filter generation
This patch will bring support for broadcasting objects larger than 2G.
pickle, zlib, FrameSerializer and Array[Byte] all can not support objects larger than 2G, so this patch introduce LargeObjectSerializer to serialize broadcast objects, the object will be serialized and compressed into small chunks, it also change the type of Broadcast[Array[Byte]]] into Broadcast[Array[Array[Byte]]]].
Testing for support broadcast objects larger than 2G is slow and memory hungry, so this is tested manually, could be added into SparkPerf.
Author: Davies Liu <davies@databricks.com>
Author: Davies Liu <davies.liu@gmail.com>
Closes#2659 from davies/huge and squashes the following commits:
7b57a14 [Davies Liu] add more tests for broadcast
28acff9 [Davies Liu] Merge branch 'master' of github.com:apache/spark into huge
a2f6a02 [Davies Liu] bug fix
4820613 [Davies Liu] Merge branch 'master' of github.com:apache/spark into huge
5875c73 [Davies Liu] address comments
10a349b [Davies Liu] address comments
0c33016 [Davies Liu] Merge branch 'master' of github.com:apache/spark into huge
6182c8f [Davies Liu] Merge branch 'master' into huge
d94b68f [Davies Liu] Merge branch 'master' of github.com:apache/spark into huge
2514848 [Davies Liu] address comments
fda395b [Davies Liu] Merge branch 'master' of github.com:apache/spark into huge
1c2d928 [Davies Liu] fix scala style
091b107 [Davies Liu] broadcast objects larger than 2G
While reviewing PR #3083 and #3161, I noticed that Parquet record filter generation code can be simplified significantly according to the clue stated in [SPARK-4453](https://issues.apache.org/jira/browse/SPARK-4213). This PR addresses both SPARK-4453 and SPARK-4213 with this simplification.
While generating `ParquetTableScan` operator, we need to remove all Catalyst predicates that have already been pushed down to Parquet. Originally, we first generate the record filter, and then call `findExpression` to traverse the generated filter to find out all pushed down predicates [[1](64c6b9bad5/sql/core/src/main/scala/org/apache/spark/sql/execution/SparkStrategies.scala (L213-L228))]. In this way, we have to introduce the `CatalystFilter` class hierarchy to bind the Catalyst predicates together with their generated Parquet filter, and complicate the code base a lot.
The basic idea of this PR is that, we don't need `findExpression` after filter generation, because we already know a predicate can be pushed down if we can successfully generate its corresponding Parquet filter. SPARK-4213 is fixed by returning `None` for any unsupported predicate type.
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Author: Cheng Lian <lian@databricks.com>
Closes#3317 from liancheng/simplify-parquet-filters and squashes the following commits:
d6a9499 [Cheng Lian] Fixes import styling issue
43760e8 [Cheng Lian] Simplifies Parquet filter generation logic
Adds a new operator that uses Spark's `ExternalSort` class. It is off by default now, but we might consider making it the default if benchmarks show that it does not regress performance.
Author: Michael Armbrust <michael@databricks.com>
Closes#3268 from marmbrus/externalSort and squashes the following commits:
48b9726 [Michael Armbrust] comments
b98799d [Michael Armbrust] Add test
afd7562 [Michael Armbrust] Add support for external sort.
The Spark ParquetRelation.scala code makes the assumption that the parquet.Log class has already been loaded. If ParquetRelation.enableLogForwarding executes prior to the parquet.Log class being loaded then the code in enableLogForwarding has no affect.
ParquetRelation.scala attempts to override the parquet logger but, at least currently (and if your application simply reads a parquet file before it does anything else with Parquet), the parquet.Log class hasn't been loaded yet. Therefore the code in ParquetRelation.enableLogForwarding has no affect. If you look at the code in parquet.Log there's a static initializer that needs to be called prior to enableLogForwarding or whatever enableLogForwarding does gets undone by this static initializer.
The "fix" would be to force the static initializer to get called in parquet.Log as part of enableForwardLogging.
Author: Jim Carroll <jim@dontcallme.com>
Closes#3271 from jimfcarroll/parquet-logging and squashes the following commits:
37bdff7 [Jim Carroll] Fix Spark's control of Parquet logging.
Since parquet library has been updated , we no longer need to filter the records returned from parquet library for null records , as now the library skips those :
from parquet-hadoop/src/main/java/parquet/hadoop/InternalParquetRecordReader.java
public boolean nextKeyValue() throws IOException, InterruptedException {
boolean recordFound = false;
while (!recordFound) {
// no more records left
if (current >= total)
{ return false; }
try {
checkRead();
currentValue = recordReader.read();
current ++;
if (recordReader.shouldSkipCurrentRecord())
{
// this record is being filtered via the filter2 package
if (DEBUG) LOG.debug("skipping record");
continue;
}
if (currentValue == null)
{
// only happens with FilteredRecordReader at end of block current = totalCountLoadedSoFar;
if (DEBUG) LOG.debug("filtered record reader reached end of block");
continue;
}
recordFound = true;
if (DEBUG) LOG.debug("read value: " + currentValue);
} catch (RuntimeException e)
{ throw new ParquetDecodingException(format("Can not read value at %d in block %d in file %s", current, currentBlock, file), e); }
}
return true;
}
Author: Yash Datta <Yash.Datta@guavus.com>
Closes#3229 from saucam/remove_filter and squashes the following commits:
8909ae9 [Yash Datta] SPARK-4365: Remove unnecessary filter call on records returned from parquet library
If you profile the writing of a Parquet file, the single worst time consuming call inside of org.apache.spark.sql.parquet.MutableRowWriteSupport.write is actually in the scala.collection.AbstractSequence.size call. This is because the size call actually ends up COUNTING the elements in a scala.collection.LinearSeqOptimized.length ("optimized?").
This doesn't need to be done. "size" is called repeatedly where needed rather than called once at the top of the method and stored in a 'val'.
Author: Jim Carroll <jim@dontcallme.com>
Closes#3254 from jimfcarroll/parquet-perf and squashes the following commits:
30cc0b5 [Jim Carroll] Improve performance when writing Parquet files.
While resolving struct fields, the resulted `GetField` expression is wrapped with an `Alias` to make it a named expression. Assume `a` is a struct instance with a field `b`, then `"a.b"` will be resolved as `Alias(GetField(a, "b"), "b")`. Thus, for this following SQL query:
```sql
SELECT a.b + 1 FROM t GROUP BY a.b + 1
```
the grouping expression is
```scala
Add(GetField(a, "b"), Literal(1, IntegerType))
```
while the aggregation expression is
```scala
Add(Alias(GetField(a, "b"), "b"), Literal(1, IntegerType))
```
This mismatch makes the above SQL query fail during the both analysis and execution phases. This PR fixes this issue by removing the alias when substituting aggregation expressions.
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Author: Cheng Lian <lian@databricks.com>
Closes#3248 from liancheng/spark-4322 and squashes the following commits:
23a46ea [Cheng Lian] Code simplification
dd20a79 [Cheng Lian] Should only trim aliases around `GetField`s
7f46532 [Cheng Lian] Enables struct fields as sub expressions of grouping fields
When sort based shuffle and code gen are on we were trying to ship the code generated rows during a shuffle. This doesn't work because the classes don't exist on the other side. Instead we now copy into a generic row before shipping.
Author: Michael Armbrust <michael@databricks.com>
Closes#3263 from marmbrus/aggCodeGen and squashes the following commits:
f6ba8cf [Michael Armbrust] fix and test
This is more uniform with the rest of SQL configuration and allows it to be turned on and off without restarting the SparkContext. In this PR I also turn off filter pushdown by default due to a number of outstanding issues (in particular SPARK-4258). When those are fixed we should turn it back on by default.
Author: Michael Armbrust <michael@databricks.com>
Closes#3258 from marmbrus/parquetFilters and squashes the following commits:
5655bfe [Michael Armbrust] Remove extra line.
15e9a98 [Michael Armbrust] Enable filters for tests
75afd39 [Michael Armbrust] Fix comments
78fa02d [Michael Armbrust] off by default
e7f9e16 [Michael Armbrust] First draft of correctly configuring parquet filter pushdown
This PR adds two features to the data sources API:
- Support for pushing down `IN` filters
- The ability for relations to optionally provide information about their `sizeInBytes`.
Author: Michael Armbrust <michael@databricks.com>
Closes#3260 from marmbrus/sourcesImprovements and squashes the following commits:
9a5e171 [Michael Armbrust] Use method instead of configuration directly
99c0e6b [Michael Armbrust] Add support for sizeInBytes.
416f167 [Michael Armbrust] Support for IN in data sources API.
2a04ab3 [Michael Armbrust] Simplify implementation of InSet.
Author: Cheng Hao <hao.cheng@intel.com>
Closes#3139 from chenghao-intel/comparison_test and squashes the following commits:
f5d7146 [Cheng Hao] avoid exception in printing the codegen enabled
This implement the feature davies mentioned in https://github.com/apache/spark/pull/2901#discussion-diff-19313312
Author: Daoyuan Wang <daoyuan.wang@intel.com>
Closes#3012 from adrian-wang/iso8601 and squashes the following commits:
50df6e7 [Daoyuan Wang] json data timestamp ISO8601 support
it generates warnings at compile time marmbrus
Author: Xiangrui Meng <meng@databricks.com>
Closes#3192 from mengxr/dtc-decimal and squashes the following commits:
955e9fb [Xiangrui Meng] remove a decimal case branch that has no effect
Author: Takuya UESHIN <ueshin@happy-camper.st>
Closes#3185 from ueshin/issues/SPARK-4319 and squashes the following commits:
a44a38e [Takuya UESHIN] Enable an ignored test "null count".
andrewor14 Another try at SPARK-1209, to address https://github.com/apache/spark/pull/2814#issuecomment-61197619
I successfully tested with `mvn -Dhadoop.version=1.0.4 -DskipTests clean package; mvn -Dhadoop.version=1.0.4 test` I assume that is what failed Jenkins last time. I also tried `-Dhadoop.version1.2.1` and `-Phadoop-2.4 -Pyarn -Phive` for more coverage.
So this is why the class was put in `org.apache.hadoop` to begin with, I assume. One option is to leave this as-is for now and move it only when Hadoop 1.0.x support goes away.
This is the other option, which adds a call to force the constructor to be public at run-time. It's probably less surprising than putting Spark code in `org.apache.hadoop`, but, does involve reflection. A `SecurityManager` might forbid this, but it would forbid a lot of stuff Spark does. This would also only affect Hadoop 1.0.x it seems.
Author: Sean Owen <sowen@cloudera.com>
Closes#3048 from srowen/SPARK-1209 and squashes the following commits:
0d48f4b [Sean Owen] For Hadoop 1.0.x, make certain constructors public, which were public in later versions
466e179 [Sean Owen] Disable MIMA warnings resulting from moving the class -- this was also part of the PairRDDFunctions type hierarchy though?
eb61820 [Sean Owen] Move SparkHadoopMapRedUtil / SparkHadoopMapReduceUtil from org.apache.hadoop to org.apache.spark
Following description is quoted from JIRA:
When I issue a hql query against a HiveContext where my predicate uses a column of string type with one of LT, LTE, GT, or GTE operator, I get the following error:
scala.MatchError: StringType (of class org.apache.spark.sql.catalyst.types.StringType$)
Looking at the code in org.apache.spark.sql.parquet.ParquetFilters, StringType is absent from the corresponding functions for creating these filters.
To reproduce, in a Hive 0.13.1 shell, I created the following table (at a specified DB):
create table sparkbug (
id int,
event string
) stored as parquet;
Insert some sample data:
insert into table sparkbug select 1, '2011-06-18' from <some table> limit 1;
insert into table sparkbug select 2, '2012-01-01' from <some table> limit 1;
Launch a spark shell and create a HiveContext to the metastore where the table above is located.
import org.apache.spark.sql._
import org.apache.spark.sql.SQLContext
import org.apache.spark.sql.hive.HiveContext
val hc = new HiveContext(sc)
hc.setConf("spark.sql.shuffle.partitions", "10")
hc.setConf("spark.sql.hive.convertMetastoreParquet", "true")
hc.setConf("spark.sql.parquet.compression.codec", "snappy")
import hc._
hc.hql("select * from <db>.sparkbug where event >= '2011-12-01'")
A scala.MatchError will appear in the output.
Author: Kousuke Saruta <sarutak@oss.nttdata.co.jp>
Closes#3083 from sarutak/SPARK-4213 and squashes the following commits:
4ab6e56 [Kousuke Saruta] WIP
b6890c6 [Kousuke Saruta] Merge branch 'master' of git://git.apache.org/spark into SPARK-4213
9a1fae7 [Kousuke Saruta] Fixed ParquetFilters so that compare Strings
marmbrus
Author: Xiangrui Meng <meng@databricks.com>
Closes#3125 from mengxr/SPARK-4262 and squashes the following commits:
307695e [Xiangrui Meng] add .schemaRDD to JavaSchemaRDD
This PR simplify serializer, always use batched serializer (AutoBatchedSerializer as default), even batch size is 1.
Author: Davies Liu <davies@databricks.com>
This patch had conflicts when merged, resolved by
Committer: Josh Rosen <joshrosen@databricks.com>
Closes#2920 from davies/fix_autobatch and squashes the following commits:
e544ef9 [Davies Liu] revert unrelated change
6880b14 [Davies Liu] Merge branch 'master' of github.com:apache/spark into fix_autobatch
1d557fc [Davies Liu] fix tests
8180907 [Davies Liu] Merge branch 'master' of github.com:apache/spark into fix_autobatch
76abdce [Davies Liu] clean up
53fa60b [Davies Liu] Merge branch 'master' of github.com:apache/spark into fix_autobatch
d7ac751 [Davies Liu] Merge branch 'master' of github.com:apache/spark into fix_autobatch
2cc2497 [Davies Liu] Merge branch 'master' of github.com:apache/spark into fix_autobatch
b4292ce [Davies Liu] fix bug in master
d79744c [Davies Liu] recover hive tests
be37ece [Davies Liu] refactor
eb3938d [Davies Liu] refactor serializer in scala
8d77ef2 [Davies Liu] simplify serializer, use AutoBatchedSerializer by default.
Following #2919, this PR adds Python UDT (for internal use only) with tests under "pyspark.tests". Before `SQLContext.applySchema`, we check whether we need to convert user-type instances into SQL recognizable data. In the current implementation, a Python UDT must be paired with a Scala UDT for serialization on the JVM side. A following PR will add VectorUDT in MLlib for both Scala and Python.
marmbrus jkbradley davies
Author: Xiangrui Meng <meng@databricks.com>
Closes#3068 from mengxr/SPARK-4192-sql and squashes the following commits:
acff637 [Xiangrui Meng] merge master
dba5ea7 [Xiangrui Meng] only use pyClass for Python UDT output sqlType as well
2c9d7e4 [Xiangrui Meng] move import to global setup; update needsConversion
7c4a6a9 [Xiangrui Meng] address comments
75223db [Xiangrui Meng] minor update
f740379 [Xiangrui Meng] remove UDT from default imports
e98d9d0 [Xiangrui Meng] fix py style
4e84fce [Xiangrui Meng] remove local hive tests and add more tests
39f19e0 [Xiangrui Meng] add tests
b7f666d [Xiangrui Meng] add Python UDT
Author: Michael Armbrust <michael@databricks.com>
Closes#3077 from marmbrus/udfsWithUdts and squashes the following commits:
34b5f27 [Michael Armbrust] style
504adef [Michael Armbrust] Convert arguments to Scala UDFs
- Turns on compression for in-memory cached data by default
- Changes the default parquet compression format back to gzip (we have seen more OOMs with production workloads due to the way Snappy allocates memory)
- Ups the batch size to 10,000 rows
- Increases the broadcast threshold to 10mb.
- Uses our parquet implementation instead of the hive one by default.
- Cache parquet metadata by default.
Author: Michael Armbrust <michael@databricks.com>
Closes#3064 from marmbrus/fasterDefaults and squashes the following commits:
97ee9f8 [Michael Armbrust] parquet codec docs
e641694 [Michael Armbrust] Remote also
a12866a [Michael Armbrust] Cache metadata.
2d73acc [Michael Armbrust] Update docs defaults.
d63d2d5 [Michael Armbrust] document parquet option
da373f9 [Michael Armbrust] More aggressive defaults
This feature is based on an offline discussion with mengxr, hopefully can be useful for the new MLlib pipeline API.
For the following test snippet
```scala
case class KeyValue(key: Int, value: String)
val testData = sc.parallelize(1 to 10).map(i => KeyValue(i, i.toString)).toSchemaRDD
def foo(a: Int, b: String) => a.toString + b
```
the newly introduced DSL enables the following syntax
```scala
import org.apache.spark.sql.catalyst.dsl._
testData.select(Star(None), foo.call('key, 'value) as 'result)
```
which is equivalent to
```scala
testData.registerTempTable("testData")
sqlContext.registerFunction("foo", foo)
sql("SELECT *, foo(key, value) AS result FROM testData")
```
Author: Cheng Lian <lian@databricks.com>
Closes#3067 from liancheng/udf-dsl and squashes the following commits:
f132818 [Cheng Lian] Adds DSL support for Scala UDF
Queries which has 'not like' is not working spark sql.
sql("SELECT * FROM records where value not like 'val%'")
same query works in Spark HiveQL
Author: ravipesala <ravindra.pesala@huawei.com>
Closes#3075 from ravipesala/SPARK-4207 and squashes the following commits:
35c11e7 [ravipesala] Supported 'not like' syntax in sql
This PR adds User-Defined Types (UDTs) to SQL. It is a precursor to using SchemaRDD as a Dataset for the new MLlib API. Currently, the UDT API is private since there is incomplete support (e.g., no Java or Python support yet).
Author: Joseph K. Bradley <joseph@databricks.com>
Author: Michael Armbrust <michael@databricks.com>
Author: Xiangrui Meng <meng@databricks.com>
Closes#3063 from marmbrus/udts and squashes the following commits:
7ccfc0d [Michael Armbrust] remove println
46a3aee [Michael Armbrust] Slightly easier to read test output.
6cc434d [Michael Armbrust] Recursively convert rows.
e369b91 [Michael Armbrust] Merge remote-tracking branch 'origin/master' into udts
15c10a6 [Joseph K. Bradley] Merge remote-tracking branch 'upstream/master' into sql-udt2
f3c72fe [Joseph K. Bradley] Fixing merge
e13cd8a [Joseph K. Bradley] Removed Vector UDTs
5817b2b [Joseph K. Bradley] style edits
30ce5b2 [Joseph K. Bradley] updates based on code review
d063380 [Joseph K. Bradley] Cleaned up Java UDT Suite, and added warning about element ordering when creating schema from Java Bean
a571bb6 [Joseph K. Bradley] Removed old UDT code (registry and Java UDTs). Cleaned up other code. Extended JavaUserDefinedTypeSuite
6fddc1c [Joseph K. Bradley] Made MyLabeledPoint into a Java Bean
20630bc [Joseph K. Bradley] fixed scalastyle
fa86b20 [Joseph K. Bradley] Removed Java UserDefinedType, and made UDTs private[spark] for now
8de957c [Joseph K. Bradley] Modified UserDefinedType to store Java class of user type so that registerUDT takes only the udt argument.
8b242ea [Joseph K. Bradley] Fixed merge error after last merge. Note: Last merge commit also removed SQL UDT examples from mllib.
7f29656 [Joseph K. Bradley] Moved udt case to top of all matches. Small cleanups
b028675 [Xiangrui Meng] allow any type in UDT
4500d8a [Xiangrui Meng] update example code
87264a5 [Xiangrui Meng] remove debug code
3143ac3 [Xiangrui Meng] remove unnecessary changes
cfbc321 [Xiangrui Meng] support UDT in parquet
db16139 [Joseph K. Bradley] Added more doc for UserDefinedType. Removed unused code in Suite
759af7a [Joseph K. Bradley] Added more doc to UserDefineType
63626a4 [Joseph K. Bradley] Updated ScalaReflectionsSuite per @marmbrus suggestions
51e5282 [Joseph K. Bradley] fixed 1 test
f025035 [Joseph K. Bradley] Cleanups before PR. Added new tests
85872f6 [Michael Armbrust] Allow schema calculation to be lazy, but ensure its available on executors.
dff99d6 [Joseph K. Bradley] Added UDTs for Vectors in MLlib, plus DatasetExample using the UDTs
cd60cb4 [Joseph K. Bradley] Trying to get other SQL tests to run
34a5831 [Joseph K. Bradley] Added MLlib dependency on SQL.
e1f7b9c [Joseph K. Bradley] blah
2f40c02 [Joseph K. Bradley] renamed UDT types
3579035 [Joseph K. Bradley] udt annotation now working
b226b9e [Joseph K. Bradley] Changing UDT to annotation
fea04af [Joseph K. Bradley] more cleanups
964b32e [Joseph K. Bradley] some cleanups
893ee4c [Joseph K. Bradley] udt finallly working
50f9726 [Joseph K. Bradley] udts
04303c9 [Joseph K. Bradley] udts
39f8707 [Joseph K. Bradley] removed old udt suite
273ac96 [Joseph K. Bradley] basic UDT is working, but deserialization has yet to be done
8bebf24 [Joseph K. Bradley] commented out convertRowToScala for debugging
53de70f [Joseph K. Bradley] more udts...
982c035 [Joseph K. Bradley] still working on UDTs
19b2f60 [Joseph K. Bradley] still working on UDTs
0eaeb81 [Joseph K. Bradley] Still working on UDTs
105c5a3 [Joseph K. Bradley] Adding UserDefinedType to SQL, not done yet.
This PR adds an API for unregistering temporary tables. If a temporary table has been cached before, it's unpersisted as well.
Author: Cheng Lian <lian.cs.zju@gmail.com>
Closes#3039 from liancheng/unregister-temp-table and squashes the following commits:
54ae99f [Cheng Lian] Fixes Scala styling issue
1948c14 [Cheng Lian] Removes the unpersist argument
aca41d3 [Cheng Lian] Ensures thread safety
7d4fb2b [Cheng Lian] Adds unregisterTempTable API
JIRA: https://issues.apache.org/jira/browse/SPARK-4185.
This PR also has the fix of #3052.
Author: Yin Huai <huai@cse.ohio-state.edu>
Closes#3056 from yhuai/SPARK-4185 and squashes the following commits:
ed3a5a8 [Yin Huai] Correctly handle type conflicts between structs and primitive types in an array.
This PR overrides the `GetInfo` Hive Thrift API to provide correct version information. Another property `spark.sql.hive.version` is added to reveal the underlying Hive version. These are generally useful for Spark SQL ODBC driver providers. The Spark version information is extracted from the jar manifest. Also took the chance to remove the `SET -v` hack, which was a workaround for Simba ODBC driver connectivity.
TODO
- [x] Find a general way to figure out Hive (or even any dependency) version.
This [blog post](http://blog.soebes.de/blog/2014/01/02/version-information-into-your-appas-with-maven/) suggests several methods to inspect application version. In the case of Spark, this can be tricky because the chosen method:
1. must applies to both Maven build and SBT build
For Maven builds, we can retrieve the version information from the META-INF/maven directory within the assembly jar. But this doesn't work for SBT builds.
2. must not rely on the original jars of dependencies to extract specific dependency version, because Spark uses assembly jar.
This implies we can't read Hive version from Hive jar files since standard Spark distribution doesn't include them.
3. should play well with `SPARK_PREPEND_CLASSES` to ease local testing during development.
`SPARK_PREPEND_CLASSES` prevents classes to be loaded from the assembly jar, thus we can't locate the jar file and read its manifest.
Given these, maybe the only reliable method is to generate a source file containing version information at build time. pwendell Do you have any suggestions from the perspective of the build process?
**Update** Hive version is now retrieved from the newly introduced `HiveShim` object.
Author: Cheng Lian <lian.cs.zju@gmail.com>
Author: Cheng Lian <lian@databricks.com>
Closes#2843 from liancheng/get-info and squashes the following commits:
a873d0f [Cheng Lian] Updates test case
53f43cd [Cheng Lian] Retrieves underlying Hive verson via HiveShim
1d282b8 [Cheng Lian] Removes the Simba ODBC "SET -v" hack
f857fce [Cheng Lian] Overrides Hive GetInfo Thrift API and adds Hive version property
`NoopColumnStats` was once used for binary, boolean and complex data types. This `ColumnStats` doesn't return properly shaped column statistics and causes caching failure if a table contains columns of the aforementioned types.
This PR adds `BooleanColumnStats`, `BinaryColumnStats` and `GenericColumnStats`, used for boolean, binary and all complex data types respectively. In addition, `NoopColumnStats` returns properly shaped column statistics containing null count and row count, but this class is now used for testing purpose only.
Author: Cheng Lian <lian@databricks.com>
Closes#3059 from liancheng/spark-4182 and squashes the following commits:
b398cfd [Cheng Lian] Fixes failed test case
fb3ee85 [Cheng Lian] Fixes SPARK-4182
This PR introduces a new set of APIs to Spark SQL to allow other developers to add support for reading data from new sources in `org.apache.spark.sql.sources`.
New sources must implement the interface `BaseRelation`, which is responsible for describing the schema of the data. BaseRelations have three `Scan` subclasses, which are responsible for producing an RDD containing row objects. The [various Scan interfaces](https://github.com/marmbrus/spark/blob/foreign/sql/core/src/main/scala/org/apache/spark/sql/sources/package.scala#L50) allow for optimizations such as column pruning and filter push down, when the underlying data source can handle these operations.
By implementing a class that inherits from RelationProvider these data sources can be accessed using using pure SQL. I've used the functionality to update the JSON support so it can now be used in this way as follows:
```sql
CREATE TEMPORARY TABLE jsonTableSQL
USING org.apache.spark.sql.json
OPTIONS (
path '/home/michael/data.json'
)
```
Further example usage can be found in the test cases: https://github.com/marmbrus/spark/tree/foreign/sql/core/src/test/scala/org/apache/spark/sql/sources
There is also a library that uses this new API to read avro data available here:
https://github.com/marmbrus/sql-avro
Author: Michael Armbrust <michael@databricks.com>
Closes#2475 from marmbrus/foreign and squashes the following commits:
1ed6010 [Michael Armbrust] Merge remote-tracking branch 'origin/master' into foreign
ab2c31f [Michael Armbrust] fix test
1d41bb5 [Michael Armbrust] unify argument names
5b47901 [Michael Armbrust] Remove sealed, more filter types
fab154a [Michael Armbrust] Merge remote-tracking branch 'origin/master' into foreign
e3e690e [Michael Armbrust] Add hook for extraStrategies
a70d602 [Michael Armbrust] Fix style, more tests, FilteredSuite => PrunedFilteredSuite
70da6d9 [Michael Armbrust] Modify API to ease binary compatibility and interop with Java
7d948ae [Michael Armbrust] Fix equality of AttributeReference.
5545491 [Michael Armbrust] Address comments
5031ac3 [Michael Armbrust] Merge remote-tracking branch 'origin/master' into foreign
22963ef [Michael Armbrust] package objects compile wierdly...
b069146 [Michael Armbrust] traits => abstract classes
34f836a [Michael Armbrust] Make @DeveloperApi
0d74bcf [Michael Armbrust] Add documention on object life cycle
3e06776 [Michael Armbrust] remove line wraps
de3b68c [Michael Armbrust] Remove empty file
360cb30 [Michael Armbrust] style and java api
2957875 [Michael Armbrust] add override
0fd3a07 [Michael Armbrust] Draft of data sources API
- Adds optional precision and scale to Spark SQL's decimal type, which behave similarly to those in Hive 13 (https://cwiki.apache.org/confluence/download/attachments/27362075/Hive_Decimal_Precision_Scale_Support.pdf)
- Replaces our internal representation of decimals with a Decimal class that can store small values in a mutable Long, saving memory in this situation and letting some operations happen directly on Longs
This is still marked WIP because there are a few TODOs, but I'll remove that tag when done.
Author: Matei Zaharia <matei@databricks.com>
Closes#2983 from mateiz/decimal-1 and squashes the following commits:
35e6b02 [Matei Zaharia] Fix issues after merge
227f24a [Matei Zaharia] Review comments
31f915e [Matei Zaharia] Implement Davies's suggestions in Python
eb84820 [Matei Zaharia] Support reading/writing decimals as fixed-length binary in Parquet
4dc6bae [Matei Zaharia] Fix decimal support in PySpark
d1d9d68 [Matei Zaharia] Fix compile error and test issues after rebase
b28933d [Matei Zaharia] Support decimal precision/scale in Hive metastore
2118c0d [Matei Zaharia] Some test and bug fixes
81db9cb [Matei Zaharia] Added mutable Decimal that will be more efficient for small precisions
7af0c3b [Matei Zaharia] Add optional precision and scale to DecimalType, but use Unlimited for now
ec0a947 [Matei Zaharia] Make the result of AVG on Decimals be Decimal, not Double
Add `metadata: Metadata` to `StructField` to store extra information of columns. `Metadata` is a simple wrapper over `Map[String, Any]` with value types restricted to Boolean, Long, Double, String, Metadata, and arrays of those types. SerDe is via JSON.
Metadata is preserved through simple operations like `SELECT`.
marmbrus liancheng
Author: Xiangrui Meng <meng@databricks.com>
Author: Michael Armbrust <michael@databricks.com>
Closes#2701 from mengxr/structfield-metadata and squashes the following commits:
dedda56 [Xiangrui Meng] merge remote
5ef930a [Xiangrui Meng] Merge remote-tracking branch 'apache/master' into structfield-metadata
c35203f [Xiangrui Meng] Merge pull request #1 from marmbrus/pr/2701
886b85c [Michael Armbrust] Expose Metadata and MetadataBuilder through the public scala and java packages.
589f314 [Xiangrui Meng] Merge remote-tracking branch 'apache/master' into structfield-metadata
1e2abcf [Xiangrui Meng] change default value of metadata to None in python
611d3c2 [Xiangrui Meng] move metadata from Expr to NamedExpr
ddfcfad [Xiangrui Meng] Merge remote-tracking branch 'apache/master' into structfield-metadata
a438440 [Xiangrui Meng] Merge remote-tracking branch 'apache/master' into structfield-metadata
4266f4d [Xiangrui Meng] add StructField.toString back for backward compatibility
3f49aab [Xiangrui Meng] remove StructField.toString
24a9f80 [Xiangrui Meng] Merge remote-tracking branch 'apache/master' into structfield-metadata
473a7c5 [Xiangrui Meng] merge master
c9d7301 [Xiangrui Meng] organize imports
1fcbf13 [Xiangrui Meng] change metadata type in StructField for Scala/Java
60cc131 [Xiangrui Meng] add doc and header
60614c7 [Xiangrui Meng] add metadata
e42c452 [Xiangrui Meng] merge master
93518fb [Xiangrui Meng] support metadata in python
905bb89 [Xiangrui Meng] java conversions
618e349 [Xiangrui Meng] make tests work in scala
61b8e0f [Xiangrui Meng] merge master
7e5a322 [Xiangrui Meng] do not output metadata in StructField.toString
c41a664 [Xiangrui Meng] merge master
d8af0ed [Xiangrui Meng] move tests to SQLQuerySuite
67fdebb [Xiangrui Meng] add test on join
d65072e [Xiangrui Meng] remove Map.empty
367d237 [Xiangrui Meng] add test
c194d5e [Xiangrui Meng] add metadata field to StructField and Attribute
if the query contains "not between" does not work like.
SELECT * FROM src where key not between 10 and 20'
Author: ravipesala <ravindra.pesala@huawei.com>
Closes#3017 from ravipesala/SPARK-4154 and squashes the following commits:
65fc89e [ravipesala] Handled admin comments
32e6d42 [ravipesala] 'not between' is not working
The parquet-mr project has introduced a new filter api (https://github.com/apache/incubator-parquet-mr/pull/4), along with several fixes . It can also eliminate entire RowGroups depending on certain statistics like min/max
We can leverage that to further improve performance of queries with filters.
Also filter2 api introduces ability to create custom filters. We can create a custom filter for the optimized In clause (InSet) , so that elimination happens in the ParquetRecordReader itself
Author: Yash Datta <Yash.Datta@guavus.com>
Closes#2841 from saucam/master and squashes the following commits:
8282ba0 [Yash Datta] SPARK-3968: fix scala code style and add some more tests for filtering on optional columns
515df1c [Yash Datta] SPARK-3968: Add a test case for filter pushdown on optional column
5f4530e [Yash Datta] SPARK-3968: Fix scala code style
f304667 [Yash Datta] SPARK-3968: Using task metadata strategy for row group filtering
ec53e92 [Yash Datta] SPARK-3968: No push down should result in case we are unable to create a record filter
48163c3 [Yash Datta] SPARK-3968: Code cleanup
cc7b596 [Yash Datta] SPARK-3968: 1. Fix RowGroupFiltering not working 2. Use the serialization/deserialization from Parquet library for filter pushdown
caed851 [Yash Datta] Revert "SPARK-3968: Not pushing the filters in case of OPTIONAL columns" since filtering on optional columns is now supported in filter2 api
49703c9 [Yash Datta] SPARK-3968: Not pushing the filters in case of OPTIONAL columns
9d09741 [Yash Datta] SPARK-3968: Change parquet filter pushdown to use filter2 api of parquet-mr
Right now it works for only 2 tables like below query.
sql("SELECT * FROM records1 as a,records2 as b where a.key=b.key ")
But it does not work for more than 2 tables like below query
sql("SELECT * FROM records1 as a,records2 as b,records3 as c where a.key=b.key and a.key=c.key").
Author: ravipesala <ravindra.pesala@huawei.com>
Closes#2987 from ravipesala/multijoin and squashes the following commits:
429b005 [ravipesala] Support multiple joins
(This is just a look at what completely moving the classes would look like. I know Patrick flagged that as maybe not OK, although, it's private?)
Author: Sean Owen <sowen@cloudera.com>
Closes#2814 from srowen/SPARK-1209 and squashes the following commits:
ead1115 [Sean Owen] Disable MIMA warnings resulting from moving the class -- this was also part of the PairRDDFunctions type hierarchy though?
2d42c1d [Sean Owen] Move SparkHadoopMapRedUtil / SparkHadoopMapReduceUtil from org.apache.hadoop to org.apache.spark
In JavaSqlContext, we need to let java program use big decimal, timestamp, date types.
Author: Daoyuan Wang <daoyuan.wang@intel.com>
Closes#2850 from adrian-wang/javacontext and squashes the following commits:
4c4292c [Daoyuan Wang] change underlying type of JavaSchemaRDD as scala
bb0508f [Daoyuan Wang] add test cases
3c58b0d [Daoyuan Wang] add 3 types for java SQL context
Call Python UDF on ArrayType/MapType/PrimitiveType, the returnType can also be ArrayType/MapType/PrimitiveType.
For StructType, it will act as tuple (without attributes). If returnType is StructType, it also should be tuple.
Author: Davies Liu <davies@databricks.com>
Closes#2973 from davies/udf_array and squashes the following commits:
306956e [Davies Liu] Merge branch 'master' of github.com:apache/spark into udf_array
2c00e43 [Davies Liu] fix merge
11395fa [Davies Liu] Merge branch 'master' of github.com:apache/spark into udf_array
9df50a2 [Davies Liu] address comments
79afb4e [Davies Liu] type conversionfor python udf
Currently, `CTAS` (Create Table As Select) doesn't support specifying the `SerDe` in HQL. This PR will pass down the `ASTNode` into the physical operator `execution.CreateTableAsSelect`, which will extract the `CreateTableDesc` object via Hive `SemanticAnalyzer`. In the meantime, I also update the `HiveMetastoreCatalog.createTable` to optionally support the `CreateTableDesc` for table creation.
Author: Cheng Hao <hao.cheng@intel.com>
Closes#2570 from chenghao-intel/ctas_serde and squashes the following commits:
e011ef5 [Cheng Hao] shim for both 0.12 & 0.13.1
cfb3662 [Cheng Hao] revert to hive 0.12
c8a547d [Cheng Hao] Support SerDe properties within CTAS
Add json and python api for date type.
By using Pickle, `java.sql.Date` was serialized as calendar, and recognized in python as `datetime.datetime`.
Author: Daoyuan Wang <daoyuan.wang@intel.com>
Closes#2901 from adrian-wang/spark3988 and squashes the following commits:
c51a24d [Daoyuan Wang] convert datetime to date
5670626 [Daoyuan Wang] minor line combine
f760d8e [Daoyuan Wang] fix indent
444f100 [Daoyuan Wang] fix a typo
1d74448 [Daoyuan Wang] fix scala style
8d7dd22 [Daoyuan Wang] add json and python api for date type
Currently there is no support of Bitwise & , | in Spark HiveQl and Spark SQL as well. So this PR support the same.
I am closing https://github.com/apache/spark/pull/2926 as it has conflicts to merge. And also added support for Bitwise AND(&), OR(|) ,XOR(^), NOT(~) And I handled all review comments in that PR
Author: ravipesala <ravindra.pesala@huawei.com>
Closes#2961 from ravipesala/SPARK-3814-NEW4 and squashes the following commits:
a391c7a [ravipesala] Rebase with master
`schemaRDD2` is not tested because `schemaRDD1` is registered again.
Author: Yin Huai <huai@cse.ohio-state.edu>
Closes#2869 from yhuai/JavaApplySchemaSuite and squashes the following commits:
95fe894 [Yin Huai] Correct variable name.
PR #2860 refines in-memory table statistics and enables broader broadcasted hash join optimization for in-memory tables. This makes `JoinSuite` fail when some test suite caches test table `testData` and gets executed before `JoinSuite`. Because expected `ShuffledHashJoin`s are optimized to `BroadcastedHashJoin` according to collected in-memory table statistics.
This PR fixes this issue by clearing the cache before testing join operator selection. A separate test case is also added to test broadcasted hash join operator selection.
Author: Cheng Lian <lian@databricks.com>
Closes#2960 from liancheng/fix-join-suite and squashes the following commits:
715b2de [Cheng Lian] Fixes caching related JoinSuite failure
SqlParser fails to parse -9223372036854775808 (Long.MinValue) so we cannot write queries such like as follows.
SELECT value FROM someTable WHERE value > -9223372036854775808
Additionally, because of the wrong syntax definition, we cannot apply unary minus only to literal. So, we cannot write such expressions.
-(value1 + value2) // Parenthesized expressions
-column // Columns
-MAX(column) // Functions
Author: Kousuke Saruta <sarutak@oss.nttdata.co.jp>
Closes#2816 from sarutak/spark-sql-dsl-improvement2 and squashes the following commits:
32a5005 [Kousuke Saruta] Remove test setting for thriftserver
c2bab5e [Kousuke Saruta] Fixed SPARK-3959 and SPARK-3960
Supporting special chars in column names by using back ticks. Closed https://github.com/apache/spark/pull/2804 and created this PR as it has merge conflicts
Author: ravipesala <ravindra.pesala@huawei.com>
Closes#2927 from ravipesala/SPARK-3483-NEW and squashes the following commits:
f6329f3 [ravipesala] Rebased with master
Please refer to added tests for cases that can trigger the bug.
JIRA: https://issues.apache.org/jira/browse/SPARK-4068
Author: Yin Huai <huai@cse.ohio-state.edu>
Closes#2918 from yhuai/SPARK-4068 and squashes the following commits:
d360eae [Yin Huai] Handle nulls when building key paths from elements of an array.
Please check https://issues.apache.org/jira/browse/SPARK-4052 for cases triggering this bug.
Author: Yin Huai <huai@cse.ohio-state.edu>
Closes#2899 from yhuai/SPARK-4052 and squashes the following commits:
1188f70 [Yin Huai] Address liancheng's comments.
b6712be [Yin Huai] Use scala.collection.Map instead of Predef.Map (scala.collection.immutable.Map).
This PR refines in-memory columnar table statistics:
1. adds 2 more statistics for in-memory table columns: `count` and `sizeInBytes`
1. adds filter pushdown support for `IS NULL` and `IS NOT NULL`.
1. caches and propagates statistics in `InMemoryRelation` once the underlying cached RDD is materialized.
Statistics are collected to driver side with an accumulator.
This PR also fixes SPARK-3914 by properly propagating in-memory statistics.
Author: Cheng Lian <lian@databricks.com>
Closes#2860 from liancheng/propagates-in-mem-stats and squashes the following commits:
0cc5271 [Cheng Lian] Restricts visibility of o.a.s.s.c.p.l.Statistics
c5ff904 [Cheng Lian] Fixes test table name conflict
a8c818d [Cheng Lian] Refines tests
1d01074 [Cheng Lian] Bug fix: shouldn't call STRING.actualSize on null string value
7dc6a34 [Cheng Lian] Adds more in-memory table statistics and propagates them properly
This follows https://github.com/apache/spark/pull/2893 , but does not completely fix SPARK-3359 either. This fixes minor scaladoc/javadoc issues that Javadoc 8 will treat as errors.
Author: Sean Owen <sowen@cloudera.com>
Closes#2909 from srowen/SPARK-3359 and squashes the following commits:
f62c347 [Sean Owen] Fix some javadoc issues that javadoc 8 considers errors. This is not all of the errors turned up when javadoc 8 runs on output of genjavadoc.
As part of the upgrade I also copy the newest version of the query tests, and whitelist a bunch of new ones that are now passing.
Author: Michael Armbrust <michael@databricks.com>
Closes#2936 from marmbrus/fix13tests and squashes the following commits:
d9cbdab [Michael Armbrust] Remove user specific tests
65801cd [Michael Armbrust] style and rat
8f6b09a [Michael Armbrust] Update test harness to work with both Hive 12 and 13.
f044843 [Michael Armbrust] Update Hive query tests and golden files to 0.13
Previously cached data was found by `sameResult` plan matching on optimized plans. This technique however fails to locate the cached data when a temporary table with a projection is queried with a further reduced projection. The failure is due to the fact that optimization will collapse the projections, producing a plan that no longer produces the sameResult as the cached data (though the cached data still subsumes the desired data). For example consider the following previously failing test case.
```scala
sql("CACHE TABLE tempTable AS SELECT key FROM testData")
assertCached(sql("SELECT COUNT(*) FROM tempTable"))
```
In this PR I change the matching to occur after analysis instead of optimization, so that in the case of temporary tables, the plans will always match. I think this should work generally, however, this error does raise questions about the need to do more thorough subsumption checking when locating cached data.
Another question is what sort of semantics we want to provide when uncaching data from temporary tables. For example consider the following sequence of commands:
```scala
testData.select('key).registerTempTable("tempTable1")
testData.select('key).registerTempTable("tempTable2")
cacheTable("tempTable1")
// This obviously works.
assertCached(sql("SELECT COUNT(*) FROM tempTable1"))
// It seems good that this works ...
assertCached(sql("SELECT COUNT(*) FROM tempTable2"))
// ... but is this valid?
uncacheTable("tempTable2")
// Should this still be cached?
assertCached(sql("SELECT COUNT(*) FROM tempTable1"), 0)
```
Author: Michael Armbrust <michael@databricks.com>
Closes#2912 from marmbrus/cachingBug and squashes the following commits:
9c822d4 [Michael Armbrust] remove commented out code
5c72fb7 [Michael Armbrust] Add a test case / question about uncaching semantics.
63a23e4 [Michael Armbrust] Perform caching on analyzed instead of optimized plan.
03f1cfe [Michael Armbrust] Clean-up / add tests to SameResult suite.
Some developers want to replace `Optimizer` to fit their projects but can't do so because currently `Optimizer` is an `object`.
Author: Takuya UESHIN <ueshin@happy-camper.st>
Closes#2825 from ueshin/issues/SPARK-3969 and squashes the following commits:
abbc53c [Takuya UESHIN] Re-rename Optimizer object.
4d2e1bc [Takuya UESHIN] Rename Optimizer object.
9547a23 [Takuya UESHIN] Extract abstract class from Optimizer for developers to be able to replace Optimizer.
Author: Michael Armbrust <michael@databricks.com>
Closes#2658 from marmbrus/nestedAggs and squashes the following commits:
862b763 [Michael Armbrust] Merge remote-tracking branch 'origin/master' into nestedAggs
3234521 [Michael Armbrust] Merge remote-tracking branch 'origin/master' into nestedAggs
8b06fdc [Michael Armbrust] possible fix for grouping on nested fields
Author: Cheng Lian <lian.cs.zju@gmail.com>
Closes#2767 from liancheng/multi-join and squashes the following commits:
9dc0d18 [Cheng Lian] Adds multiple join support for SQLContext
Make JavaPairRDD.collectAsMap result Serializable since Java Maps generally are
Author: Sean Owen <sowen@cloudera.com>
Closes#2805 from srowen/SPARK-3926 and squashes the following commits:
ecb78ee [Sean Owen] Fix conflict between java.io.Serializable and use of Scala's Serializable
f4717f9 [Sean Owen] Oops, fix compile problem
ae1b36f [Sean Owen] Expand to cover Maps returned from other Java API methods as well
51c26c2 [Sean Owen] Make JavaPairRDD.collectAsMap result Serializable since Java Maps generally are
In the current implementation it was possible for the reference to change after analysis.
Author: Michael Armbrust <michael@databricks.com>
Closes#2717 from marmbrus/pythonUdfResults and squashes the following commits:
da14879 [Michael Armbrust] Fix test
6343bcb [Michael Armbrust] add test
9533286 [Michael Armbrust] Correctly preserve the result attribute of python UDFs though transformations
This is a small number of clean-up changes on top of #2782. Closes#2782.
Author: Prashant Sharma <prashant.s@imaginea.com>
Author: Patrick Wendell <pwendell@gmail.com>
Closes#2803 from pwendell/pr-2782 and squashes the following commits:
56d5b7a [Patrick Wendell] Minor clean-up
44089ec [Patrick Wendell] Clean-up the TaskContext API.
ed551ce [Prashant Sharma] Fixed a typo
df261d0 [Prashant Sharma] Josh's suggestion
facf3b1 [Prashant Sharma] Fixed the mima issue.
7ecc2fe [Prashant Sharma] CR, Moved implementations to TaskContextImpl
bbd9e05 [Prashant Sharma] adding missed out files to git.
ef633f5 [Prashant Sharma] SPARK-3874, Provide stable TaskContext API
Adds some functions that were very useful when trying to track down the bug from #2656. This change also changes the tree output for query plans to include the `'` prefix to unresolved nodes and `!` prefix to nodes that refer to non-existent attributes.
Author: Michael Armbrust <michael@databricks.com>
Closes#2657 from marmbrus/debugging and squashes the following commits:
654b926 [Michael Armbrust] Clean-up, add tests
763af15 [Michael Armbrust] Add typeChecking debugging functions
8c69303 [Michael Armbrust] Add inputSet, references to QueryPlan. Improve tree string with a prefix to denote invalid or unresolved nodes.
fbeab54 [Michael Armbrust] Better toString, factories for AttributeSet.
Original problem is [SPARK-3764](https://issues.apache.org/jira/browse/SPARK-3764).
`AppendingParquetOutputFormat` uses a binary-incompatible method `context.getTaskAttemptID`.
This causes binary-incompatible of Spark itself, i.e. if Spark itself is built against hadoop-1, the artifact is for only hadoop-1, and vice versa.
Author: Takuya UESHIN <ueshin@happy-camper.st>
Closes#2638 from ueshin/issues/SPARK-3771 and squashes the following commits:
efd3784 [Takuya UESHIN] Add a comment to explain the reason to use reflection.
ec213c1 [Takuya UESHIN] Use reflection to prevent breaking binary-compatibility.
This PR adds a new rule `CheckAggregation` to the analyzer to provide better error message for non-aggregate attributes with aggregation.
Author: Cheng Lian <lian.cs.zju@gmail.com>
Closes#2774 from liancheng/non-aggregate-attr and squashes the following commits:
5246004 [Cheng Lian] Passes test suites
bf1878d [Cheng Lian] Adds checks for non-aggregate attributes with aggregation
Author: Daoyuan Wang <daoyuan.wang@intel.com>
Closes#2344 from adrian-wang/date and squashes the following commits:
f15074a [Daoyuan Wang] remove outdated lines
2038085 [Daoyuan Wang] update return type
00fe81f [Daoyuan Wang] address lian cheng's comments
0df6ea1 [Daoyuan Wang] rebase and remove simple string
bb1b1ef [Daoyuan Wang] remove failing test
aa96735 [Daoyuan Wang] not cast for same type compare
30bf48b [Daoyuan Wang] resolve rebase conflict
617d1a8 [Daoyuan Wang] add date_udf case to white list
c37e848 [Daoyuan Wang] comment update
5429212 [Daoyuan Wang] change to long
f8f219f [Daoyuan Wang] revise according to Cheng Hao
0e0a4f5 [Daoyuan Wang] minor format
4ddcb92 [Daoyuan Wang] add java api for date
0e3110e [Daoyuan Wang] try to fix timezone issue
17fda35 [Daoyuan Wang] set test list
2dfbb5b [Daoyuan Wang] support date type
Author: Reynold Xin <rxin@apache.org>
Closes#2727 from rxin/SPARK-3861-broadcast-hash-2 and squashes the following commits:
9c7b1a2 [Reynold Xin] Revert "Reuse CompactBuffer in UniqueKeyHashedRelation."
97626a1 [Reynold Xin] Reuse CompactBuffer in UniqueKeyHashedRelation.
7fcffb5 [Reynold Xin] Make UniqueKeyHashedRelation private[joins].
18eb214 [Reynold Xin] Merge branch 'SPARK-3861-broadcast-hash' into SPARK-3861-broadcast-hash-1
4b9d0c9 [Reynold Xin] UniqueKeyHashedRelation.get should return null if the value is null.
e0ebdd1 [Reynold Xin] Added a test case.
90b58c0 [Reynold Xin] [SPARK-3861] Avoid rebuilding hash tables on each partition
0c0082b [Reynold Xin] Fix line length.
cbc664c [Reynold Xin] Rename join -> joins package.
a070d44 [Reynold Xin] Fix line length in HashJoin
a39be8c [Reynold Xin] [SPARK-3857] Create a join package for various join operators.
Using `MEMORY_AND_DISK` as default storage level for in-memory table caching. Due to the in-memory columnar representation, recomputing an in-memory cached table partitions can be very expensive.
Author: Cheng Lian <lian.cs.zju@gmail.com>
Closes#2686 from liancheng/spark-3824 and squashes the following commits:
35d2ed0 [Cheng Lian] Removes extra space
1ab7967 [Cheng Lian] Reduces test data size to fit DiskStore.getBytes()
ba565f0 [Cheng Lian] Maks CachedBatch serializable
07f0204 [Cheng Lian] Sets in-memory table default storage level to MEMORY_AND_DISK
This PR is a follow up of #2590, and tries to introduce a top level SQL parser entry point for all SQL dialects supported by Spark SQL.
A top level parser `SparkSQLParser` is introduced to handle the syntaxes that all SQL dialects should recognize (e.g. `CACHE TABLE`, `UNCACHE TABLE` and `SET`, etc.). For all the syntaxes this parser doesn't recognize directly, it fallbacks to a specified function that tries to parse arbitrary input to a `LogicalPlan`. This function is typically another parser combinator like `SqlParser`. DDL syntaxes introduced in #2475 can be moved to here.
The `ExtendedHiveQlParser` now only handle Hive specific extensions.
Also took the chance to refactor/reformat `SqlParser` for better readability.
Author: Cheng Lian <lian.cs.zju@gmail.com>
Closes#2698 from liancheng/gen-sql-parser and squashes the following commits:
ceada76 [Cheng Lian] Minor styling fixes
9738934 [Cheng Lian] Minor refactoring, removes optional trailing ";" in the parser
bb2ab12 [Cheng Lian] SET property value can be empty string
ce8860b [Cheng Lian] Passes test suites
e86968e [Cheng Lian] Removes debugging code
8bcace5 [Cheng Lian] Replaces digit.+ to rep1(digit) (Scala style checking doesn't like it)
d15d54f [Cheng Lian] Unifies SQL and HiveQL parsers
This prevents it from changing during serialization, leading to corrupted results.
Author: Michael Armbrust <michael@databricks.com>
Closes#2656 from marmbrus/generateBug and squashes the following commits:
efa32eb [Michael Armbrust] Store the output of a generator in a val. This prevents it from changing during serialization.
"case when" conditional function is already supported in Spark SQL but there is no support in SqlParser. So added parser support to it.
Author : ravipesala ravindra.pesalahuawei.com
Author: ravipesala <ravindra.pesala@huawei.com>
Closes#2678 from ravipesala/SPARK-3813 and squashes the following commits:
70c75a7 [ravipesala] Fixed styles
713ea84 [ravipesala] Updated as per admin comments
709684f [ravipesala] Changed parser to support case when function.
The alias parameter is being ignored, which makes it more difficult to specify a qualifier for Generator expressions.
Author: Nathan Howell <nhowell@godaddy.com>
Closes#2721 from NathanHowell/SPARK-3858 and squashes the following commits:
8aa0f43 [Nathan Howell] [SPARK-3858][SQL] Pass the generator alias into logical plan node
This PR aims to provide a way to skip/query corrupt JSON records. To do so, we introduce an internal column to hold corrupt records (the default name is `_corrupt_record`. This name can be changed by setting the value of `spark.sql.columnNameOfCorruptRecord`). When there is a parsing error, we will put the corrupt record in its unparsed format to the internal column. Users can skip/query this column through SQL.
* To query those corrupt records
```
-- For Hive parser
SELECT `_corrupt_record`
FROM jsonTable
WHERE `_corrupt_record` IS NOT NULL
-- For our SQL parser
SELECT _corrupt_record
FROM jsonTable
WHERE _corrupt_record IS NOT NULL
```
* To skip corrupt records and query regular records
```
-- For Hive parser
SELECT field1, field2
FROM jsonTable
WHERE `_corrupt_record` IS NULL
-- For our SQL parser
SELECT field1, field2
FROM jsonTable
WHERE _corrupt_record IS NULL
```
Generally, it is not recommended to change the name of the internal column. If the name has to be changed to avoid possible name conflicts, you can use `sqlContext.setConf(SQLConf.COLUMN_NAME_OF_CORRUPT_RECORD, <new column name>)` or `sqlContext.sql(SET spark.sql.columnNameOfCorruptRecord=<new column name>)`.
Author: Yin Huai <huai@cse.ohio-state.edu>
Closes#2680 from yhuai/corruptJsonRecord and squashes the following commits:
4c9828e [Yin Huai] Merge remote-tracking branch 'upstream/master' into corruptJsonRecord
309616a [Yin Huai] Change the default name of corrupt record to "_corrupt_record".
b4a3632 [Yin Huai] Merge remote-tracking branch 'upstream/master' into corruptJsonRecord
9375ae9 [Yin Huai] Set the column name of corrupt json record back to the default one after the unit test.
ee584c0 [Yin Huai] Provide a way to query corrupt json records as unparsed strings.
In JSONRDD.scala, add 'case TimestampType' in the enforceCorrectType function and a toTimestamp function.
Author: Mike Timper <mike@aurorafeint.com>
Closes#2720 from mtimper/master and squashes the following commits:
9386ab8 [Mike Timper] Fix and tests for SPARK-3853
Author: Reynold Xin <rxin@apache.org>
Closes#2719 from rxin/sql-join-break and squashes the following commits:
0c0082b [Reynold Xin] Fix line length.
cbc664c [Reynold Xin] Rename join -> joins package.
a070d44 [Reynold Xin] Fix line length in HashJoin
a39be8c [Reynold Xin] [SPARK-3857] Create a join package for various join operators.
This PR uses JSON instead of `toString` to serialize `DataType`s. The latter is not only hard to parse but also flaky in many cases.
Since we already write schema information to Parquet metadata in the old style, we have to reserve the old `DataType` parser and ensure downward compatibility. The old parser is now renamed to `CaseClassStringParser` and moved into `object DataType`.
JoshRosen davies Please help review PySpark related changes, thanks!
Author: Cheng Lian <lian.cs.zju@gmail.com>
Closes#2563 from liancheng/datatype-to-json and squashes the following commits:
fc92eb3 [Cheng Lian] Reverts debugging code, simplifies primitive type JSON representation
438c75f [Cheng Lian] Refactors PySpark DataType JSON SerDe per comments
6b6387b [Cheng Lian] Removes debugging code
6a3ee3a [Cheng Lian] Addresses per review comments
dc158b5 [Cheng Lian] Addresses PEP8 issues
99ab4ee [Cheng Lian] Adds compatibility est case for Parquet type conversion
a983a6c [Cheng Lian] Adds PySpark support
f608c6e [Cheng Lian] De/serializes DataType objects from/to JSON
If we write the filter which is always FALSE like
SELECT * from person WHERE FALSE;
200 tasks will run. I think, 1 task is enough.
And current optimizer cannot optimize the case NOT is duplicated like
SELECT * from person WHERE NOT ( NOT (age > 30));
The filter rule above should be simplified
Author: Kousuke Saruta <sarutak@oss.nttdata.co.jp>
Closes#2692 from sarutak/SPARK-3831 and squashes the following commits:
25f3e20 [Kousuke Saruta] Merge branch 'master' of git://git.apache.org/spark into SPARK-3831
23c750c [Kousuke Saruta] Improved unsupported predicate test case
a11b9f3 [Kousuke Saruta] Modified NOT predicate test case in PartitionBatchPruningSuite
8ea872b [Kousuke Saruta] Fixed the number of tasks when the data of LocalRelation is empty.
Although lazy caching for in-memory table seems consistent with the `RDD.cache()` API, it's relatively confusing for users who mainly work with SQL and not familiar with Spark internals. The `CACHE TABLE t; SELECT COUNT(*) FROM t;` pattern is also commonly seen just to ensure predictable performance.
This PR makes both the `CACHE TABLE t [AS SELECT ...]` statement and the `SQLContext.cacheTable()` API eager by default, and adds a new `CACHE LAZY TABLE t [AS SELECT ...]` syntax to provide lazy in-memory table caching.
Also, took the chance to make some refactoring: `CacheCommand` and `CacheTableAsSelectCommand` are now merged and renamed to `CacheTableCommand` since the former is strictly a special case of the latter. A new `UncacheTableCommand` is added for the `UNCACHE TABLE t` statement.
Author: Cheng Lian <lian.cs.zju@gmail.com>
Closes#2513 from liancheng/eager-caching and squashes the following commits:
fe92287 [Cheng Lian] Makes table caching eager by default and adds syntax for lazy caching
_Also addresses: SPARK-1671, SPARK-1379 and SPARK-3641_
This PR introduces a new trait, `CacheManger`, which replaces the previous temporary table based caching system. Instead of creating a temporary table that shadows an existing table with and equivalent cached representation, the cached manager maintains a separate list of logical plans and their cached data. After optimization, this list is searched for any matching plan fragments. When a matching plan fragment is found it is replaced with the cached data.
There are several advantages to this approach:
- Calling .cache() on a SchemaRDD now works as you would expect, and uses the more efficient columnar representation.
- Its now possible to provide a list of temporary tables, without having to decide if a given table is actually just a cached persistent table. (To be done in a follow-up PR)
- In some cases it is possible that cached data will be used, even if a cached table was not explicitly requested. This is because we now look at the logical structure instead of the table name.
- We now correctly invalidate when data is inserted into a hive table.
Author: Michael Armbrust <michael@databricks.com>
Closes#2501 from marmbrus/caching and squashes the following commits:
63fbc2c [Michael Armbrust] Merge remote-tracking branch 'origin/master' into caching.
0ea889e [Michael Armbrust] Address comments.
1e23287 [Michael Armbrust] Add support for cache invalidation for hive inserts.
65ed04a [Michael Armbrust] fix tests.
bdf9a3f [Michael Armbrust] Merge remote-tracking branch 'origin/master' into caching
b4b77f2 [Michael Armbrust] Address comments
6923c9d [Michael Armbrust] More comments / tests
80f26ac [Michael Armbrust] First draft of improved semantics for Spark SQL caching.
The following code gives error.
```
sqlContext.registerFunction("len", (s: String) => s.length)
sqlContext.sql("select len(foo) as a, count(1) from t1 group by len(foo)").collect()
```
Because SQl parser creates the aliases to the functions in grouping expressions with generated alias names. So if user gives the alias names to the functions inside projection then it does not match the generated alias name of grouping expression.
This kind of queries are working in Hive.
So the fix I have given that if user provides alias to the function in projection then don't generate alias in grouping expression,use the same alias.
Author: ravipesala <ravindra.pesala@huawei.com>
Closes#2511 from ravipesala/SPARK-3371 and squashes the following commits:
9fb973f [ravipesala] Removed aliases to grouping expressions.
f8ace79 [ravipesala] Fixed the testcase issue
bad2fd0 [ravipesala] SPARK-3371 : Fixed Renaming a function expression with group by gives error
Considering `Command.executeCollect()` simply delegates to `Command.sideEffectResult`, we no longer need to leave the latter `protected[sql]`.
Author: Cheng Lian <lian.cs.zju@gmail.com>
Closes#2431 from liancheng/narrow-scope and squashes the following commits:
1bfc16a [Cheng Lian] Made Command.sideEffectResult protected
BinaryType is derived from NativeType and added Ordering support.
Author: Venkata Ramana G <ramana.gollamudihuawei.com>
Author: Venkata Ramana Gollamudi <ramana.gollamudi@huawei.com>
Closes#2617 from gvramana/binarytype_sort and squashes the following commits:
1cf26f3 [Venkata Ramana Gollamudi] Supported Sorting of BinaryType
Thread names are useful for correlating failures.
Author: Reynold Xin <rxin@apache.org>
Closes#2600 from rxin/log4j and squashes the following commits:
83ffe88 [Reynold Xin] [SPARK-3748] Log thread name in unit test logs
Author: Reynold Xin <rxin@apache.org>
Closes#2560 from rxin/TaskContext and squashes the following commits:
9eff95a [Reynold Xin] [SPARK-3543] remaining cleanup work.
This will allow us to take advantage of things like the spark.defaults file.
Author: Michael Armbrust <michael@databricks.com>
Closes#2493 from marmbrus/copySparkConf and squashes the following commits:
0bd1377 [Michael Armbrust] Copy SQL configuration from SparkConf when a SQLContext is created.
It returns null metadata from parquet if querying on empty parquet file while calculating splits.So added null check and returns the empty splits.
Author : ravipesala ravindra.pesalahuawei.com
Author: ravipesala <ravindra.pesala@huawei.com>
Closes#2456 from ravipesala/SPARK-3536 and squashes the following commits:
1e81a50 [ravipesala] Fixed the issue when querying on empty parquet file.
**This PR introduces a subtle change in semantics for HiveContext when using the results in Python or Scala. Specifically, while resolution remains case insensitive, it is now case preserving.**
_This PR is a follow up to #2293 (and to a lesser extent #2262#2334)._
In #2293 the catalog was changed to store analyzed logical plans instead of unresolved ones. While this change fixed the reported bug (which was caused by yet another instance of us forgetting to put in a `LowerCaseSchema` operator) it had the consequence of breaking assumptions made by `MultiInstanceRelation`. Specifically, we can't replace swap out leaf operators in a tree without rewriting changed expression ids (which happens when you self join the same RDD that has been registered as a temp table).
In this PR, I instead remove the need to insert `LowerCaseSchema` operators at all, by moving the concern of matching up identifiers completely into analysis. Doing so allows the test cases from both #2293 and #2262 to pass at the same time (and likely fixes a slew of other "unknown unknown" bugs).
While it is rolled back in this PR, storing the analyzed plan might actually be a good idea. For instance, it is kind of confusing if you register a temporary table, change the case sensitivity of resolution and now you can't query that table anymore. This can be addressed in a follow up PR.
Follow-ups:
- Configurable case sensitivity
- Consider storing analyzed plans for temp tables
Author: Michael Armbrust <michael@databricks.com>
Closes#2382 from marmbrus/lowercase and squashes the following commits:
c21171e [Michael Armbrust] Ensure the resolver is used for field lookups and ensure that case insensitive resolution is still case preserving.
d4320f1 [Michael Armbrust] Merge remote-tracking branch 'origin/master' into lowercase
2de881e [Michael Armbrust] Address comments.
219805a [Michael Armbrust] style
5b93711 [Michael Armbrust] Replace LowerCaseSchema with Resolver.
This helps to replace shuffled hash joins with broadcast hash joins in some cases.
Author: Cheng Lian <lian.cs.zju@gmail.com>
Closes#2468 from liancheng/more-stats and squashes the following commits:
32687dc [Cheng Lian] Moved the test case to PlannerSuite
5595a91 [Cheng Lian] Removes debugging code
73faf69 [Cheng Lian] Test case for auto choosing broadcast hash join
f30fe1d [Cheng Lian] Adds sizeInBytes estimation for Limit when all output types are native types
Author: Sandy Ryza <sandy@cloudera.com>
Closes#2460 from sryza/sandy-spark-3605 and squashes the following commits:
09d940b [Sandy Ryza] SPARK-3605. Fix typo in SchemaRDD.
This feature allows user to add cache table from the select query.
Example : ```CACHE TABLE testCacheTable AS SELECT * FROM TEST_TABLE```
Spark takes this type of SQL as command and it does lazy caching just like ```SQLContext.cacheTable```, ```CACHE TABLE <name>``` does.
It can be executed from both SQLContext and HiveContext.
Recreated the pull request after rebasing with master.And fixed all the comments raised in previous pull requests.
https://github.com/apache/spark/pull/2381https://github.com/apache/spark/pull/2390
Author : ravipesala ravindra.pesalahuawei.com
Author: ravipesala <ravindra.pesala@huawei.com>
Closes#2397 from ravipesala/SPARK-2594 and squashes the following commits:
a5f0beb [ravipesala] Simplified the code as per Admin comment.
8059cd2 [ravipesala] Changed the behaviour from eager caching to lazy caching.
d6e469d [ravipesala] Code review comments by Admin are handled.
c18aa38 [ravipesala] Merge remote-tracking branch 'remotes/ravipesala/Add-Cache-table-as' into SPARK-2594
394d5ca [ravipesala] Changed style
fb1759b [ravipesala] Updated as per Admin comments
8c9993c [ravipesala] Changed the style
d8b37b2 [ravipesala] Updated as per the comments by Admin
bc0bffc [ravipesala] Merge remote-tracking branch 'ravipesala/Add-Cache-table-as' into Add-Cache-table-as
e3265d0 [ravipesala] Updated the code as per the comments by Admin in pull request.
724b9db [ravipesala] Changed style
aaf5b59 [ravipesala] Added comment
dc33895 [ravipesala] Updated parser to support add cache table command
b5276b2 [ravipesala] Updated parser to support add cache table command
eebc0c1 [ravipesala] Add CACHE TABLE <name> AS SELECT ...
6758f80 [ravipesala] Changed style
7459ce3 [ravipesala] Added comment
13c8e27 [ravipesala] Updated parser to support add cache table command
4e858d8 [ravipesala] Updated parser to support add cache table command
b803fc8 [ravipesala] Add CACHE TABLE <name> AS SELECT ...
SchemaRDD overrides RDD functions, including collect, count, and take, with optimized versions making use of the query optimizer. The java and python interface classes wrapping SchemaRDD need to ensure the optimized versions are called as well. This patch overrides relevant calls in the python and java interfaces with optimized versions.
Adds a new Row serialization pathway between python and java, based on JList[Array[Byte]] versus the existing RDD[Array[Byte]]. I wasn’t overjoyed about doing this, but I noticed that some QueryPlans implement optimizations in executeCollect(), which outputs an Array[Row] rather than the typical RDD[Row] that can be shipped to python using the existing serialization code. To me it made sense to ship the Array[Row] over to python directly instead of converting it back to an RDD[Row] just for the purpose of sending the Rows to python using the existing serialization code.
Author: Aaron Staple <aaron.staple@gmail.com>
Closes#1592 from staple/SPARK-2314 and squashes the following commits:
89ff550 [Aaron Staple] Merge with master.
6bb7b6c [Aaron Staple] Fix typo.
b56d0ac [Aaron Staple] [SPARK-2314][SQL] Override count in JavaSchemaRDD, forwarding to SchemaRDD's count.
0fc9d40 [Aaron Staple] Fix comment typos.
f03cdfa [Aaron Staple] [SPARK-2314][SQL] Override collect and take in sql.py, forwarding to SchemaRDD's collect.
This PR aims to support reading top level JSON arrays and take every element in such an array as a row (an empty array will not generate a row).
JIRA: https://issues.apache.org/jira/browse/SPARK-3308
Author: Yin Huai <huai@cse.ohio-state.edu>
Closes#2400 from yhuai/SPARK-3308 and squashes the following commits:
990077a [Yin Huai] Handle top level JSON arrays.
Author: Cheng Hao <hao.cheng@intel.com>
Closes#2392 from chenghao-intel/trim and squashes the following commits:
e52024f [Cheng Hao] trim the string message
Author: Michael Armbrust <michael@databricks.com>
Closes#2164 from marmbrus/shufflePartitions and squashes the following commits:
0da1e8c [Michael Armbrust] test hax
ef2d985 [Michael Armbrust] more test hacks.
2dabae3 [Michael Armbrust] more test fixes
0bdbf21 [Michael Armbrust] Make parquet tests less order dependent
b42eeab [Michael Armbrust] increase test parallelism
80453d5 [Michael Armbrust] Decrease partitions when testing
This is a major refactoring of the in-memory columnar storage implementation, aims to eliminate boxing costs from critical paths (building/accessing column buffers) as much as possible. The basic idea is to refactor all major interfaces into a row-based form and use them together with `SpecificMutableRow`. The difficult part is how to adapt all compression schemes, esp. `RunLengthEncoding` and `DictionaryEncoding`, to this design. Since in-memory compression is disabled by default for now, and this PR should be strictly better than before no matter in-memory compression is enabled or not, maybe I'll finish that part in another PR.
**UPDATE** This PR also took the chance to optimize `HiveTableScan` by
1. leveraging `SpecificMutableRow` to avoid boxing cost, and
1. building specific `Writable` unwrapper functions a head of time to avoid per row pattern matching and branching costs.
TODO
- [x] Benchmark
- [ ] ~~Eliminate boxing costs in `RunLengthEncoding`~~ (left to future PRs)
- [ ] ~~Eliminate boxing costs in `DictionaryEncoding` (seems not easy to do without specializing `DictionaryEncoding` for every supported column type)~~ (left to future PRs)
## Micro benchmark
The benchmark uses a 10 million line CSV table consists of bytes, shorts, integers, longs, floats and doubles, measures the time to build the in-memory version of this table, and the time to scan the whole in-memory table.
Benchmark code can be found [here](https://gist.github.com/liancheng/fe70a148de82e77bd2c8#file-hivetablescanbenchmark-scala). Script used to generate the input table can be found [here](https://gist.github.com/liancheng/fe70a148de82e77bd2c8#file-tablegen-scala).
Speedup:
- Hive table scanning + column buffer building: **18.74%**
The original benchmark uses 1K as in-memory batch size, when increased to 10K, it can be 28.32% faster.
- In-memory table scanning: **7.95%**
Before:
| Building | Scanning
------- | -------- | --------
1 | 16472 | 525
2 | 16168 | 530
3 | 16386 | 529
4 | 16184 | 538
5 | 16209 | 521
Average | 16283.8 | 528.6
After:
| Building | Scanning
------- | -------- | --------
1 | 13124 | 458
2 | 13260 | 529
3 | 12981 | 463
4 | 13214 | 483
5 | 13583 | 500
Average | 13232.4 | 486.6
Author: Cheng Lian <lian.cs.zju@gmail.com>
Closes#2327 from liancheng/prevent-boxing/unboxing and squashes the following commits:
4419fe4 [Cheng Lian] Addressing comments
e5d2cf2 [Cheng Lian] Bug fix: should call setNullAt when field value is null to avoid NPE
8b8552b [Cheng Lian] Only checks for partition batch pruning flag once
489f97b [Cheng Lian] Bug fix: TableReader.fillObject uses wrong ordinals
97bbc4e [Cheng Lian] Optimizes hive.TableReader by by providing specific Writable unwrappers a head of time
3dc1f94 [Cheng Lian] Minor changes to eliminate row object creation
5b39cb9 [Cheng Lian] Lowers log level of compression scheme details
f2a7890 [Cheng Lian] Use SpecificMutableRow in InMemoryColumnarTableScan to avoid boxing
9cf30b0 [Cheng Lian] Added row based ColumnType.append/extract
456c366 [Cheng Lian] Made compression decoder row based
edac3cd [Cheng Lian] Makes ColumnAccessor.extractSingle row based
8216936 [Cheng Lian] Removes boxing cost in IntDelta and LongDelta by providing specialized implementations
b70d519 [Cheng Lian] Made some in-memory columnar storage interfaces row-based
This PR aims to correctly handle JSON arrays in the type of `ArrayType(...(ArrayType(StructType)))`.
JIRA: https://issues.apache.org/jira/browse/SPARK-3390.
Author: Yin Huai <huai@cse.ohio-state.edu>
Closes#2364 from yhuai/SPARK-3390 and squashes the following commits:
46db418 [Yin Huai] Handle JSON arrays in the type of ArrayType(...(ArrayType(StructType))).
Author: Cheng Hao <hao.cheng@intel.com>
Closes#1846 from chenghao-intel/ctas and squashes the following commits:
56a0578 [Cheng Hao] remove the unused imports
9a57abc [Cheng Hao] Avoid table creation in logical plan analyzing
LogicalPlan contains a ‘resolved’ attribute indicating that all of its execution requirements have been resolved. This attribute is not checked before query execution. The analyzer contains a step to check that all Expressions are resolved, but this is not equivalent to checking all LogicalPlans. In particular, the Union plan’s implementation of ‘resolved’ verifies that the types of its children’s columns are compatible. Because the analyzer does not check that a Union plan is resolved, it is possible to execute a Union plan that outputs different types in the same column. See SPARK-2781 for an example.
This patch adds two checks to the analyzer’s CheckResolution rule. First, each logical plan is checked to see if it is not resolved despite its children being resolved. This allows the ‘problem’ unresolved plan to be included in the TreeNodeException for reporting. Then as a backstop the root plan is checked to see if it is resolved, which recursively checks that the entire plan tree is resolved. Note that the resolved attribute is implemented recursively, and this patch also explicitly checks the resolved attribute on each logical plan in the tree. I assume the query plan trees will not be large enough for this redundant checking to meaningfully impact performance.
Because this patch starts validating that LogicalPlans are resolved before execution, I had to fix some cases where unresolved plans were passing through the analyzer as part of the implementation of the hive query system. In particular, HiveContext applies the CreateTables and PreInsertionCasts, and ExtractPythonUdfs rules manually after the analyzer runs. I moved these rules to the analyzer stage (for hive queries only), in the process completing a code TODO indicating the rules should be moved to the analyzer.
It’s worth noting that moving the CreateTables rule means introducing an analyzer rule with a significant side effect - in this case the side effect is creating a hive table. The rule will only attempt to create a table once even if its batch is executed multiple times, because it converts the InsertIntoCreatedTable plan it matches against into an InsertIntoTable. Additionally, these hive rules must be added to the Resolution batch rather than as a separate batch because hive rules rules may be needed to resolve non-root nodes, leaving the root to be resolved on a subsequent batch iteration. For example, the hive compatibility test auto_smb_mapjoin_14, and others, make use of a query plan where the root is a Union and its children are each a hive InsertIntoTable.
Mixing the custom hive rules with standard analyzer rules initially resulted in an additional failure because of policy differences between spark sql and hive when casting a boolean to a string. Hive casts booleans to strings as “true” / “false” while spark sql casts booleans to strings as “1” / “0” (causing the cast1.q test to fail). This behavior is a result of the BooleanCasts rule in HiveTypeCoercion.scala, and from looking at the implementation of BooleanCasts I think converting to to “1”/“0” is potentially a programming mistake. (If the BooleanCasts rule is disabled, casting produces “true”/“false” instead.) I believe “true” / “false” should be the behavior for spark sql - I changed the behavior so bools are converted to “true”/“false” to be consistent with hive, and none of the existing spark tests failed.
Finally, in some initial testing with hive it appears that an implicit type coercion of boolean to string results in a lowercase string, e.g. CONCAT( TRUE, “” ) -> “true” while an explicit cast produces an all caps string, e.g. CAST( TRUE AS STRING ) -> “TRUE”. The change I’ve made just converts to lowercase strings in all cases. I believe it is at least more correct than the existing spark sql implementation where all Cast expressions become “1” / “0”.
Author: Aaron Staple <aaron.staple@gmail.com>
Closes#1706 from staple/SPARK-2781 and squashes the following commits:
32683c4 [Aaron Staple] Fix compilation failure due to merge.
7c77fda [Aaron Staple] Move ExtractPythonUdfs to Analyzer's extendedRules in HiveContext.
d49bfb3 [Aaron Staple] Address review comments.
915b690 [Aaron Staple] Fix merge issue causing compilation failure.
701dcd2 [Aaron Staple] [SPARK-2781][SQL] Check resolution of LogicalPlans in Analyzer.
First let me write down the current `projections` grammar of spark sql:
expression : orExpression
orExpression : andExpression {"or" andExpression}
andExpression : comparisonExpression {"and" comparisonExpression}
comparisonExpression : termExpression | termExpression "=" termExpression | termExpression ">" termExpression | ...
termExpression : productExpression {"+"|"-" productExpression}
productExpression : baseExpression {"*"|"/"|"%" baseExpression}
baseExpression : expression "[" expression "]" | ... | ident | ...
ident : identChar {identChar | digit} | delimiters | ...
identChar : letter | "_" | "."
delimiters : "," | ";" | "(" | ")" | "[" | "]" | ...
projection : expression [["AS"] ident]
projections : projection { "," projection}
For something like `a.b.c[1]`, it will be parsed as:
<img src="http://img51.imgspice.com/i/03008/4iltjsnqgmtt_t.jpg" border=0>
But for something like `a[1].b`, the current grammar can't parse it correctly.
A simple solution is written in `ParquetQuerySuite#NestedSqlParser`, changed grammars are:
delimiters : "." | "," | ";" | "(" | ")" | "[" | "]" | ...
identChar : letter | "_"
baseExpression : expression "[" expression "]" | expression "." ident | ... | ident | ...
This works well, but can't cover some corner case like `select t.a.b from table as t`:
<img src="http://img51.imgspice.com/i/03008/v2iau3hoxoxg_t.jpg" border=0>
`t.a.b` parsed as `GetField(GetField(UnResolved("t"), "a"), "b")` instead of `GetField(UnResolved("t.a"), "b")` using this new grammar.
However, we can't resolve `t` as it's not a filed, but the whole table.(if we could do this, then `select t from table as t` is legal, which is unexpected)
My solution is:
dotExpressionHeader : ident "." ident
baseExpression : expression "[" expression "]" | expression "." ident | ... | dotExpressionHeader | ident | ...
I passed all test cases under sql locally and add a more complex case.
"arrayOfStruct.field1 to access all values of field1" is not supported yet. Since this PR has changed a lot of code, I will open another PR for it.
I'm not familiar with the latter optimize phase, please correct me if I missed something.
Author: Wenchen Fan <cloud0fan@163.com>
Author: Michael Armbrust <michael@databricks.com>
Closes#2230 from cloud-fan/dot and squashes the following commits:
e1a8898 [Wenchen Fan] remove support for arbitrary nested arrays
ee8a724 [Wenchen Fan] rollback LogicalPlan, support dot operation on nested array type
a58df40 [Michael Armbrust] add regression test for doubly nested data
16bc4c6 [Wenchen Fan] some enhance
95d733f [Wenchen Fan] split long line
dc31698 [Wenchen Fan] SPARK-2096 Correctly parse dot notations
Type Coercion should support every type to have null value
Author: Daoyuan Wang <daoyuan.wang@intel.com>
Author: Michael Armbrust <michael@databricks.com>
Closes#2246 from adrian-wang/spark3363-0 and squashes the following commits:
c6241de [Daoyuan Wang] minor code clean
595b417 [Daoyuan Wang] Merge pull request #2 from marmbrus/pr/2246
832e640 [Michael Armbrust] reduce code duplication
ef6f986 [Daoyuan Wang] make double boolean miss in jsonRDD compatibleType
c619f0a [Daoyuan Wang] Type Coercion should support every type to have null value
This resolves https://issues.apache.org/jira/browse/SPARK-3395
Author: Eric Liang <ekl@google.com>
Closes#2266 from ericl/spark-3395 and squashes the following commits:
7f2b6f0 [Eric Liang] add regression test
05bd1e4 [Eric Liang] in the dsl, create a new schema instance in each applySchema
`SpecificMutableRow.update` doesn't check for null, and breaks existing `MutableRow` contract.
The tricky part here is that for performance considerations, the `update` method of all subclasses of `MutableValue` doesn't check for null and sets the null bit to false.
Author: Cheng Lian <lian.cs.zju@gmail.com>
Closes#2325 from liancheng/check-for-null and squashes the following commits:
9366c44 [Cheng Lian] Check for null in SpecificMutableRow.update
Add support for the mathematical function"ABS" and the analytic function "last" to return a subset of the rows satisfying a query within spark sql. Test-cases included.
Author: xinyunh <xinyun.huang@huawei.com>
Author: bomeng <golf8lover>
Closes#2099 from xinyunh/sqlTest and squashes the following commits:
71d15e7 [xinyunh] remove POWER part
8843643 [xinyunh] fix the code style issue
39f0309 [bomeng] Modify the code of POWER and ABS. Move them to the file arithmetic
ff8e51e [bomeng] add abs() function support
7f6980a [xinyunh] fix the bug in 'Last' component
b3df91b [xinyunh] add 'Last' component
Unit test failed due to can not resolve the attribute references. Temporally disable this test case for a quick fixing, otherwise it will block the others.
Author: Cheng Hao <hao.cheng@intel.com>
Closes#2334 from chenghao-intel/unit_test_failure and squashes the following commits:
661f784 [Cheng Hao] temporally disable the failed test case
Case insensitivity breaks when unresolved relation contains attributes with uppercase letters in their names, because we store unanalyzed logical plan when registering temp tables while the `CaseInsensitivityAttributeReferences` batch runs before the `Resolution` batch. To fix this issue, we need to store analyzed logical plan.
Author: Cheng Lian <lian.cs.zju@gmail.com>
Closes#2293 from liancheng/spark-3414 and squashes the following commits:
d9fa1d6 [Cheng Lian] Stores analyzed logical plan when registering a temp table
This patch improves the SQLParser by adding support for BETWEEN conditions
Author: William Benton <willb@redhat.com>
Closes#2295 from willb/sql-between and squashes the following commits:
0016d30 [William Benton] Implement BETWEEN for SQLParser
This resolves https://issues.apache.org/jira/browse/SPARK-3349
Author: Eric Liang <ekl@google.com>
Closes#2262 from ericl/spark-3349 and squashes the following commits:
3e1b05c [Eric Liang] add regression test
ac32723 [Eric Liang] make limit/takeOrdered output SinglePartition
Author: Reynold Xin <rxin@apache.org>
Closes#2281 from rxin/sql-limit-sort and squashes the following commits:
1ef7780 [Reynold Xin] [SPARK-3408] Fixed Limit operator so it works with sort-based shuffle.
Author: GuoQiang Li <witgo@qq.com>
Closes#2268 from witgo/SPARK-3397 and squashes the following commits:
eaf913f [GuoQiang Li] Bump pom.xml version number of master branch to 1.2.0-SNAPSHOT
This is a tiny teeny optimization to move the if check of sortBasedShuffledOn to outside the closures so the closures don't need to pull in the entire Exchange operator object.
Author: Reynold Xin <rxin@apache.org>
Closes#2282 from rxin/SPARK-3409 and squashes the following commits:
1de3f88 [Reynold Xin] [SPARK-3409][SQL] Avoid pulling in Exchange operator itself in Exchange's closures.
This is a tiny fix for getting the value of "mapred.reduce.tasks", which make more sense for the hive user.
As well as the command "set -v", which should output verbose information for all of the key/values.
Author: Cheng Hao <hao.cheng@intel.com>
Closes#2261 from chenghao-intel/set_mapreduce_tasks and squashes the following commits:
653858a [Cheng Hao] show value spark.sql.shuffle.partitions for mapred.reduce.tasks
We can directly use currentTable there without unnecessary implicit conversion.
Author: Liang-Chi Hsieh <viirya@gmail.com>
Closes#2203 from viirya/direct_use_inmemoryrelation and squashes the following commits:
4741d02 [Liang-Chi Hsieh] Merge remote-tracking branch 'upstream/master' into direct_use_inmemoryrelation
b671f67 [Liang-Chi Hsieh] Can directly use currentTable there without unnecessary implicit conversion.
Author: Kousuke Saruta <sarutak@oss.nttdata.co.jp>
Closes#2251 from sarutak/SPARK-3378 and squashes the following commits:
0bfe234 [Kousuke Saruta] Merge branch 'master' of git://git.apache.org/spark into SPARK-3378
bb5938f [Kousuke Saruta] Replaced rest of "SparkSQL" with "Spark SQL"
6df66de [Kousuke Saruta] Replaced "SparkSQL" with "Spark SQL"
After this patch, broadcast can be used in Python UDF.
Author: Davies Liu <davies.liu@gmail.com>
Closes#2243 from davies/udf_broadcast and squashes the following commits:
7b88861 [Davies Liu] support broadcast in UDF
This PR is based on #1883 authored by marmbrus. Key differences:
1. Batch pruning instead of partition pruning
When #1883 was authored, batched column buffer building (#1880) hadn't been introduced. This PR combines these two and provide partition batch level pruning, which leads to smaller memory footprints and can generally skip more elements. The cost is that the pruning predicates are evaluated more frequently (partition number multiplies batch number per partition).
1. More filters are supported
Filter predicates consist of `=`, `<`, `<=`, `>`, `>=` and their conjunctions and disjunctions are supported.
Author: Cheng Lian <lian.cs.zju@gmail.com>
Closes#2188 from liancheng/in-mem-batch-pruning and squashes the following commits:
68cf019 [Cheng Lian] Marked sqlContext as @transient
4254f6c [Cheng Lian] Enables in-memory partition pruning in PartitionBatchPruningSuite
3784105 [Cheng Lian] Overrides InMemoryColumnarTableScan.sqlContext
d2a1d66 [Cheng Lian] Disables in-memory partition pruning by default
062c315 [Cheng Lian] HiveCompatibilitySuite code cleanup
16b77bf [Cheng Lian] Fixed pruning predication conjunctions and disjunctions
16195c5 [Cheng Lian] Enabled both disjunction and conjunction
89950d0 [Cheng Lian] Worked around Scala style check
9c167f6 [Cheng Lian] Minor code cleanup
3c4d5c7 [Cheng Lian] Minor code cleanup
ea59ee5 [Cheng Lian] Renamed PartitionSkippingSuite to PartitionBatchPruningSuite
fc517d0 [Cheng Lian] More test cases
1868c18 [Cheng Lian] Code cleanup, bugfix, and adding tests
cb76da4 [Cheng Lian] Added more predicate filters, fixed table scan stats for testing purposes
385474a [Cheng Lian] Merge branch 'inMemStats' into in-mem-batch-pruning
By overriding `executeCollect()` in physical plan classes of all commands, we can avoid to kick off a distributed job when collecting result of a SQL command, e.g. `sql("SET").collect()`.
Previously, `Command.sideEffectResult` returns a `Seq[Any]`, and the `execute()` method in sub-classes of `Command` typically convert that to a `Seq[Row]` then parallelize it to an RDD. Now with this PR, `sideEffectResult` is required to return a `Seq[Row]` directly, so that `executeCollect()` can directly leverage that and be factored to the `Command` parent class.
Author: Cheng Lian <lian.cs.zju@gmail.com>
Closes#2215 from liancheng/lightweight-commands and squashes the following commits:
3fbef60 [Cheng Lian] Factored execute() method of physical commands to parent class Command
5a0e16c [Cheng Lian] Passes test suites
e0e12e9 [Cheng Lian] Refactored Command.sideEffectResult and Command.executeCollect
995bdd8 [Cheng Lian] Cleaned up DescribeHiveTableCommand
542977c [Cheng Lian] Avoids confusion between logical and physical plan by adding package prefixes
55b2aa5 [Cheng Lian] Avoids distributed jobs when execution SQL commands
The function `ensureFreeSpace` in object `ColumnBuilder` clears old buffer before copying its content to new buffer. This PR fixes it.
Author: Liang-Chi Hsieh <viirya@gmail.com>
Closes#2195 from viirya/fix_buffer_clear and squashes the following commits:
792f009 [Liang-Chi Hsieh] no need to call clear(). use flip() instead of calling limit(), position() and rewind().
df2169f [Liang-Chi Hsieh] should clean old buffer after copying its content.
Class names of these two are just too similar.
Author: Cheng Lian <lian.cs.zju@gmail.com>
Closes#2189 from liancheng/column-metrics and squashes the following commits:
8bb3b21 [Cheng Lian] Renamed ColumnStat to ColumnMetrics to avoid confusion between ColumnStats
Author: Cheng Lian <lian.cs.zju@gmail.com>
Closes#2213 from liancheng/spark-3320 and squashes the following commits:
45a0139 [Cheng Lian] Fixed typo in InMemoryColumnarQuerySuite
f67067d [Cheng Lian] Fixed SPARK-3320
If you have a table with TIMESTAMP column, that column can't be used in WHERE clause properly - it is not evaluated properly. [More](https://issues.apache.org/jira/browse/SPARK-3173)
Motivation: http://www.aproint.com/aggregation-with-spark-sql/
- [x] modify SqlParser so it supports casting to TIMESTAMP (workaround for item 2)
- [x] the string literal should be converted into Timestamp if the column is Timestamp.
Author: Zdenek Farana <zdenek.farana@gmail.com>
Author: Zdenek Farana <zdenek.farana@aproint.com>
Closes#2084 from byF/SPARK-3173 and squashes the following commits:
442b59d [Zdenek Farana] Fixed test merge conflict
2dbf4f6 [Zdenek Farana] Merge remote-tracking branch 'origin/SPARK-3173' into SPARK-3173
65b6215 [Zdenek Farana] Fixed timezone sensitivity in the test
47b27b4 [Zdenek Farana] Now works in the case of "StringLiteral=TimestampColumn"
96a661b [Zdenek Farana] Code style change
491dfcf [Zdenek Farana] Added test cases for SPARK-3173
4446b1e [Zdenek Farana] A string literal is casted into Timestamp when the column is Timestamp.
59af397 [Zdenek Farana] Added a new TIMESTAMP keyword; CAST to TIMESTAMP now can be used in SQL expression.
Thus id property of the TreeNode API does save time in a faster way to compare 2 TreeNodes, it is kind of performance bottleneck during the expression object creation in a multi-threading env (because of the memory barrier).
Fortunately, the tree node comparison only happen once in master, so even we remove it, the entire performance will not be affected.
Author: Cheng Hao <hao.cheng@intel.com>
Closes#2155 from chenghao-intel/treenode and squashes the following commits:
7cf2cd2 [Cheng Hao] Remove the implicit keyword for TreeNodeRef and some other small issues
5873415 [Cheng Hao] Remove the TreeNode.id
This PR adds a native implementation for SQL SQRT() and thus avoids delegating this function to Hive.
Author: William Benton <willb@redhat.com>
Closes#1750 from willb/spark-2813 and squashes the following commits:
22c8a79 [William Benton] Fixed missed newline from rebase
d673861 [William Benton] Added string coercions for SQRT and associated test case
e125df4 [William Benton] Added ExpressionEvaluationSuite test cases for SQRT
7b84bcd [William Benton] SQL SQRT now properly returns NULL for NULL inputs
8256971 [William Benton] added SQRT test to SqlQuerySuite
504d2e5 [William Benton] Added native SQRT implementation
We need to convert the case classes into Rows.
Author: Michael Armbrust <michael@databricks.com>
Closes#2133 from marmbrus/structUdfs and squashes the following commits:
189722f [Michael Armbrust] Merge remote-tracking branch 'origin/master' into structUdfs
8e29b1c [Michael Armbrust] Use existing function
d8d0b76 [Michael Armbrust] Fix udfs that return structs
Author: Cheng Lian <lian.cs.zju@gmail.com>
Closes#2172 from liancheng/sqlconf-typo and squashes the following commits:
115cc71 [Cheng Lian] Fixed 2 comment typos in SQLConf
Author: Michael Armbrust <michael@databricks.com>
Closes#2147 from marmbrus/inMemDefaultSize and squashes the following commits:
5390360 [Michael Armbrust] Merge remote-tracking branch 'origin/master' into inMemDefaultSize
14204d3 [Michael Armbrust] Set the context before creating SparkLogicalPlans.
8da4414 [Michael Armbrust] Make sure we throw errors when leaf nodes fail to provide statistcs
18ce029 [Michael Armbrust] Ensure in-memory tables don't always broadcast.
```if (!fs.getFileStatus(path).isDir) throw Exception``` make no sense after this commit #1370
be careful if someone is working on SPARK-2551, make sure the new change passes test case ```test("Read a parquet file instead of a directory")```
Author: chutium <teng.qiu@gmail.com>
Closes#2044 from chutium/parquet-singlefile and squashes the following commits:
4ae477f [chutium] [SPARK-3138][SQL] sqlContext.parquetFile should be able to take a single file as parameter
Author: Michael Armbrust <michael@databricks.com>
Closes#2153 from marmbrus/parquetFilters and squashes the following commits:
712731a [Michael Armbrust] Use closure serializer for sending filters.
1e83f80 [Michael Armbrust] Clean udf functions.
JIRA:
- https://issues.apache.org/jira/browse/SPARK-3036
- https://issues.apache.org/jira/browse/SPARK-3037
Currently this uses the following Parquet schema for `MapType` when `valueContainsNull` is `true`:
```
message root {
optional group a (MAP) {
repeated group map (MAP_KEY_VALUE) {
required int32 key;
optional int32 value;
}
}
}
```
for `ArrayType` when `containsNull` is `true`:
```
message root {
optional group a (LIST) {
repeated group bag {
optional int32 array;
}
}
}
```
We have to think about compatibilities with older version of Spark or Hive or others I mentioned in the JIRA issues.
Notice:
This PR is based on #1963 and #1889.
Please check them first.
/cc marmbrus, yhuai
Author: Takuya UESHIN <ueshin@happy-camper.st>
Closes#2032 from ueshin/issues/SPARK-3036_3037 and squashes the following commits:
4e8e9e7 [Takuya UESHIN] Add ArrayType containing null value support to Parquet.
013c2ca [Takuya UESHIN] Add MapType containing null value support to Parquet.
62989de [Takuya UESHIN] Merge branch 'issues/SPARK-2969' into issues/SPARK-3036_3037
8e38b53 [Takuya UESHIN] Merge branch 'issues/SPARK-3063' into issues/SPARK-3036_3037
It is common to want to describe sets of attributes that are in various parts of a query plan. However, the semantics of putting `AttributeReference` objects into a standard Scala `Set` result in subtle bugs when references differ cosmetically. For example, with case insensitive resolution it is possible to have two references to the same attribute whose names are not equal.
In this PR I introduce a new abstraction, an `AttributeSet`, which performs all comparisons using the globally unique `ExpressionId` instead of case class equality. (There is already a related class, [`AttributeMap`](https://github.com/marmbrus/spark/blob/inMemStats/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/AttributeMap.scala#L32)) This new type of set is used to fix a bug in the optimizer where needed attributes were getting projected away underneath join operators.
I also took this opportunity to refactor the expression and query plan base classes. In all but one instance the logic for computing the `references` of an `Expression` were the same. Thus, I moved this logic into the base class.
For query plans the semantics of the `references` method were ill defined (is it the references output? or is it those used by expression evaluation? or what?). As a result, this method wasn't really used very much. So, I removed it.
TODO:
- [x] Finish scala doc for `AttributeSet`
- [x] Scan the code for other instances of `Set[Attribute]` and refactor them.
- [x] Finish removing `references` from `QueryPlan`
Author: Michael Armbrust <michael@databricks.com>
Closes#2109 from marmbrus/attributeSets and squashes the following commits:
1c0dae5 [Michael Armbrust] work on serialization bug.
9ba868d [Michael Armbrust] Merge remote-tracking branch 'origin/master' into attributeSets
3ae5288 [Michael Armbrust] review comments
40ce7f6 [Michael Armbrust] style
d577cc7 [Michael Armbrust] Scaladoc
cae5d22 [Michael Armbrust] remove more references implementations
d6e16be [Michael Armbrust] Remove more instances of "def references" and normal sets of attributes.
fc26b49 [Michael Armbrust] Add AttributeSet class, remove references from Expression.
Currently `ExistingRdd.convertToCatalyst` doesn't convert `Map` value.
Author: Takuya UESHIN <ueshin@happy-camper.st>
Closes#1963 from ueshin/issues/SPARK-3063 and squashes the following commits:
3ba41f2 [Takuya UESHIN] Merge branch 'master' into issues/SPARK-3063
4d7bae2 [Takuya UESHIN] Merge branch 'master' into issues/SPARK-3063
9321379 [Takuya UESHIN] Merge branch 'master' into issues/SPARK-3063
d8a900a [Takuya UESHIN] Make ExistingRdd.convertToCatalyst be able to convert Map value.
Make `ScalaReflection` be able to handle like:
- `Seq[Int]` as `ArrayType(IntegerType, containsNull = false)`
- `Seq[java.lang.Integer]` as `ArrayType(IntegerType, containsNull = true)`
- `Map[Int, Long]` as `MapType(IntegerType, LongType, valueContainsNull = false)`
- `Map[Int, java.lang.Long]` as `MapType(IntegerType, LongType, valueContainsNull = true)`
Author: Takuya UESHIN <ueshin@happy-camper.st>
Closes#1889 from ueshin/issues/SPARK-2969 and squashes the following commits:
24f1c5c [Takuya UESHIN] Change the default value of ArrayType.containsNull to true in Python API.
79f5b65 [Takuya UESHIN] Change the default value of ArrayType.containsNull to true in Java API.
7cd1a7a [Takuya UESHIN] Fix json test failures.
2cfb862 [Takuya UESHIN] Change the default value of ArrayType.containsNull to true.
2f38e61 [Takuya UESHIN] Revert the default value of MapTypes.valueContainsNull.
9fa02f5 [Takuya UESHIN] Fix a test failure.
1a9a96b [Takuya UESHIN] Modify ScalaReflection to handle ArrayType.containsNull and MapType.valueContainsNull.
There are 4 different compression codec available for ```ParquetOutputFormat```
in Spark SQL, it was set as a hard-coded value in ```ParquetRelation.defaultCompression```
original discuss:
https://github.com/apache/spark/pull/195#discussion-diff-11002083
i added a new config property in SQLConf to allow user to change this compression codec, and i used similar short names syntax as described in SPARK-2953 #1873 (https://github.com/apache/spark/pull/1873/files#diff-0)
btw, which codec should we use as default? it was set to GZIP (https://github.com/apache/spark/pull/195/files#diff-4), but i think maybe we should change this to SNAPPY, since SNAPPY is already the default codec for shuffling in spark-core (SPARK-2469, #1415), and parquet-mr supports Snappy codec natively (e440108de5).
Author: chutium <teng.qiu@gmail.com>
Closes#2039 from chutium/parquet-compression and squashes the following commits:
2f44964 [chutium] [SPARK-3131][SQL] parquet compression default codec set to snappy, also in test suite
e578e21 [chutium] [SPARK-3131][SQL] compression codec config property name and default codec set to snappy
21235dc [chutium] [SPARK-3131][SQL] Allow user to set parquet compression codec for writing ParquetFile in SQLContext
fix compile error on hadoop 0.23 for the pull request #1924.
Author: Chia-Yung Su <chiayung@appier.com>
Closes#1959 from joesu/bugfix-spark3011 and squashes the following commits:
be30793 [Chia-Yung Su] remove .* and _* except _metadata
8fe2398 [Chia-Yung Su] add note to explain
40ea9bd [Chia-Yung Su] fix hadoop-0.23 compile error
c7e44f2 [Chia-Yung Su] match syntax
f8fc32a [Chia-Yung Su] filter out tmp dir
Provide `extended` keyword support for `explain` command in SQL. e.g.
```
explain extended select key as a1, value as a2 from src where key=1;
== Parsed Logical Plan ==
Project ['key AS a1#3,'value AS a2#4]
Filter ('key = 1)
UnresolvedRelation None, src, None
== Analyzed Logical Plan ==
Project [key#8 AS a1#3,value#9 AS a2#4]
Filter (CAST(key#8, DoubleType) = CAST(1, DoubleType))
MetastoreRelation default, src, None
== Optimized Logical Plan ==
Project [key#8 AS a1#3,value#9 AS a2#4]
Filter (CAST(key#8, DoubleType) = 1.0)
MetastoreRelation default, src, None
== Physical Plan ==
Project [key#8 AS a1#3,value#9 AS a2#4]
Filter (CAST(key#8, DoubleType) = 1.0)
HiveTableScan [key#8,value#9], (MetastoreRelation default, src, None), None
Code Generation: false
== RDD ==
(2) MappedRDD[14] at map at HiveContext.scala:350
MapPartitionsRDD[13] at mapPartitions at basicOperators.scala:42
MapPartitionsRDD[12] at mapPartitions at basicOperators.scala:57
MapPartitionsRDD[11] at mapPartitions at TableReader.scala:112
MappedRDD[10] at map at TableReader.scala:240
HadoopRDD[9] at HadoopRDD at TableReader.scala:230
```
It's the sub task of #1847. But can go without any dependency.
Author: Cheng Hao <hao.cheng@intel.com>
Closes#1962 from chenghao-intel/explain_extended and squashes the following commits:
295db74 [Cheng Hao] Fix bug in printing the simple execution plan
48bc989 [Cheng Hao] Support EXTENDED for EXPLAIN
Follow-up to #2066
Author: Michael Armbrust <michael@databricks.com>
Closes#2072 from marmbrus/sortShuffle and squashes the following commits:
2ff8114 [Michael Armbrust] Fix bug
Add explicit row copies when sort based shuffle is on.
Author: Michael Armbrust <michael@databricks.com>
Closes#2066 from marmbrus/sortShuffle and squashes the following commits:
fcd7bb2 [Michael Armbrust] Fix sort based shuffle for spark sql.
Refer to:
http://stackoverflow.com/questions/510632/whats-the-difference-between-concurrenthashmap-and-collections-synchronizedmap
Collections.synchronizedMap(map) creates a blocking Map which will degrade performance, albeit ensure consistency. So use ConcurrentHashMap(a more effective thread-safe hashmap) instead.
also update HiveQuerySuite to fix test error when changed to ConcurrentHashMap.
Author: wangfei <wangfei_hello@126.com>
Author: scwf <wangfei1@huawei.com>
Closes#1996 from scwf/sqlconf and squashes the following commits:
93bc0c5 [wangfei] revert change of HiveQuerySuite
0cc05dd [wangfei] add note for use synchronizedMap
3c224d31 [scwf] fix formate
a7bcb98 [scwf] use ConcurrentHashMap in sql conf, intead synchronizedMap
This PR adds an experimental flag `spark.sql.hive.convertMetastoreParquet` that when true causes the planner to detects tables that use Hive's Parquet SerDe and instead plans them using Spark SQL's native `ParquetTableScan`.
Author: Michael Armbrust <michael@databricks.com>
Author: Yin Huai <huai@cse.ohio-state.edu>
Closes#1819 from marmbrus/parquetMetastore and squashes the following commits:
1620079 [Michael Armbrust] Revert "remove hive parquet bundle"
cc30430 [Michael Armbrust] Merge remote-tracking branch 'origin/master' into parquetMetastore
4f3d54f [Michael Armbrust] fix style
41ebc5f [Michael Armbrust] remove hive parquet bundle
a43e0da [Michael Armbrust] Merge remote-tracking branch 'origin/master' into parquetMetastore
4c4dc19 [Michael Armbrust] Fix bug with tree splicing.
ebb267e [Michael Armbrust] include parquet hive to tests pass (Remove this later).
c0d9b72 [Michael Armbrust] Avoid creating a HadoopRDD per partition. Add dirty hacks to retrieve partition values from the InputSplit.
8cdc93c [Michael Armbrust] Merge pull request #8 from yhuai/parquetMetastore
a0baec7 [Yin Huai] Partitioning columns can be resolved.
1161338 [Michael Armbrust] Add a test to make sure conversion is actually happening
212d5cd [Michael Armbrust] Initial support for using ParquetTableScan to read HiveMetaStore tables.
For larger Parquet files, reading the file footers (which is done in parallel on up to 5 threads) and HDFS block locations (which is serial) can take multiple seconds. We can add an option to cache this data within FilteringParquetInputFormat. Unfortunately ParquetInputFormat only caches footers within each instance of ParquetInputFormat, not across them.
Note: this PR leaves this turned off by default for 1.1, but I believe it's safe to turn it on after. The keys in the hash maps are FileStatus objects that include a modification time, so this will work fine if files are modified. The location cache could become invalid if files have moved within HDFS, but that's rare so I just made it invalidate entries every 15 minutes.
Author: Matei Zaharia <matei@databricks.com>
Closes#2005 from mateiz/parquet-cache and squashes the following commits:
dae8efe [Matei Zaharia] Bug fix
c71e9ed [Matei Zaharia] Handle empty statuses directly
22072b0 [Matei Zaharia] Use Guava caches and add a config option for caching metadata
8fb56ce [Matei Zaharia] Cache file block locations too
453bd21 [Matei Zaharia] Bug fix
4094df6 [Matei Zaharia] First attempt at caching Parquet footers
This definitely needs review as I am not familiar with this part of Spark.
I tested this locally and it did seem to work.
Author: Patrick Wendell <pwendell@gmail.com>
Closes#1937 from pwendell/scheduler and squashes the following commits:
b858e33 [Patrick Wendell] SPARK-3025: Allow JDBC clients to set a fair scheduler pool
This reuses the CompactBuffer from Spark Core to save memory and pointer
dereferences. I also tried AppendOnlyMap instead of java.util.HashMap
but unfortunately that slows things down because it seems to do more
equals() calls and the equals on GenericRow, and especially JoinedRow,
is pretty expensive.
Author: Matei Zaharia <matei@databricks.com>
Closes#1993 from mateiz/spark-3085 and squashes the following commits:
188221e [Matei Zaharia] Remove unneeded import
5f903ee [Matei Zaharia] [SPARK-3085] [SQL] Use compact data structures in SQL joins
BroadcastHashJoin has a broadcastFuture variable that tries to collect
the broadcasted table in a separate thread, but this doesn't help
because it's a lazy val that only gets initialized when you attempt to
build the RDD. Thus queries that broadcast multiple tables would collect
and broadcast them sequentially. I changed this to a val to let it start
collecting right when the operator is created.
Author: Matei Zaharia <matei@databricks.com>
Closes#1990 from mateiz/spark-3084 and squashes the following commits:
f468766 [Matei Zaharia] [SPARK-3084] Collect broadcasted tables in parallel in joins
Reverts #1924 due to build failures with hadoop 0.23.
Author: Michael Armbrust <michael@databricks.com>
Closes#1949 from marmbrus/revert1924 and squashes the following commits:
6bff940 [Michael Armbrust] Revert "[SPARK-3011][SQL] _temporary directory should be filtered out by sqlContext.parquetFile"
This PR adds a new conf flag `spark.sql.parquet.binaryAsString`. When it is `true`, if there is no parquet metadata file available to provide the schema of the data, we will always treat binary fields stored in parquet as string fields. This conf is used to provide a way to read string fields generated without UTF8 decoration.
JIRA: https://issues.apache.org/jira/browse/SPARK-2927
Author: Yin Huai <huai@cse.ohio-state.edu>
Closes#1855 from yhuai/parquetBinaryAsString and squashes the following commits:
689ffa9 [Yin Huai] Add missing "=".
80827de [Yin Huai] Unit test.
1765ca4 [Yin Huai] Use .toBoolean.
9d3f199 [Yin Huai] Merge remote-tracking branch 'upstream/master' into parquetBinaryAsString
5d436a1 [Yin Huai] The initial support of adding a conf to treat binary columns stored in Parquet as string columns.
Author: Chia-Yung Su <chiayung@appier.com>
Closes#1924 from joesu/bugfix-spark3011 and squashes the following commits:
c7e44f2 [Chia-Yung Su] match syntax
f8fc32a [Chia-Yung Su] filter out tmp dir
Author: Michael Armbrust <michael@databricks.com>
Closes#1863 from marmbrus/parquetPredicates and squashes the following commits:
10ad202 [Michael Armbrust] left <=> right
f249158 [Michael Armbrust] quiet parquet tests.
802da5b [Michael Armbrust] Add test case.
eab2eda [Michael Armbrust] Fix parquet predicate push down bug
This is a follow up of #1880.
Since the row number within a single batch is known, we can estimate a much more precise initial buffer size when building an in-memory column buffer.
Author: Cheng Lian <lian.cs.zju@gmail.com>
Closes#1901 from liancheng/precise-init-buffer-size and squashes the following commits:
d5501fa [Cheng Lian] More precise initial buffer size estimation for in-memory column buffer
This is a follow up for #1147 , this PR will improve the performance about 10% - 15% in my local tests.
```
Before:
LeftOuterJoin: took 16750 ms ([3000000] records)
LeftOuterJoin: took 15179 ms ([3000000] records)
RightOuterJoin: took 15515 ms ([3000000] records)
RightOuterJoin: took 15276 ms ([3000000] records)
FullOuterJoin: took 19150 ms ([6000000] records)
FullOuterJoin: took 18935 ms ([6000000] records)
After:
LeftOuterJoin: took 15218 ms ([3000000] records)
LeftOuterJoin: took 13503 ms ([3000000] records)
RightOuterJoin: took 13663 ms ([3000000] records)
RightOuterJoin: took 14025 ms ([3000000] records)
FullOuterJoin: took 16624 ms ([6000000] records)
FullOuterJoin: took 16578 ms ([6000000] records)
```
Besides the performance improvement, I also do some clean up as suggested in #1147
Author: Cheng Hao <hao.cheng@intel.com>
Closes#1765 from chenghao-intel/hash_outer_join_fixing and squashes the following commits:
ab1f9e0 [Cheng Hao] Reduce the memory copy while building the hashmap
Author: Michael Armbrust <michael@databricks.com>
Closes#1880 from marmbrus/columnBatches and squashes the following commits:
0649987 [Michael Armbrust] add test
4756fad [Michael Armbrust] fix compilation
2314532 [Michael Armbrust] Build column buffers in smaller batches
Output attributes of opposite side of `OuterJoin` should be nullable.
Author: Takuya UESHIN <ueshin@happy-camper.st>
Closes#1887 from ueshin/issues/SPARK-2965 and squashes the following commits:
bcb2d37 [Takuya UESHIN] Fix HashOuterJoin output nullabilities.
Author: chutium <teng.qiu@gmail.com>
Closes#1691 from chutium/SPARK-2700 and squashes the following commits:
b76ae8c [chutium] [SPARK-2700] [SQL] fixed styling issue
d75a8bd [chutium] [SPARK-2700] [SQL] Hidden files (such as .impala_insert_staging) should be filtered out by sqlContext.parquetFile
JIRA: https://issues.apache.org/jira/browse/SPARK-2908
Author: Yin Huai <huai@cse.ohio-state.edu>
Closes#1840 from yhuai/SPARK-2908 and squashes the following commits:
86e833e [Yin Huai] Update test.
cb11759 [Yin Huai] nullTypeToStringType should check columns with the type of array of structs.
Handle null in schemaRDD during converting them into Python.
Author: Davies Liu <davies.liu@gmail.com>
Closes#1802 from davies/json and squashes the following commits:
88e6b1f [Davies Liu] handle null in schemaRDD()
Author: Reynold Xin <rxin@apache.org>
Closes#1794 from rxin/sql-conf and squashes the following commits:
3ac11ef [Reynold Xin] getAllConfs return an immutable Map instead of an Array.
4b19d6c [Reynold Xin] Tighten the visibility of various SQLConf methods and renamed setter/getters.
This PR aims to finalize accepted data value types in Python RDDs provided to Python `applySchema`.
JIRA: https://issues.apache.org/jira/browse/SPARK-2854
Author: Yin Huai <huai@cse.ohio-state.edu>
Closes#1793 from yhuai/SPARK-2854 and squashes the following commits:
32f0708 [Yin Huai] LongType only accepts long values.
c2b23dd [Yin Huai] Do data type conversions based on the specified Spark SQL data type.
JIRA issue: [SPARK-2650](https://issues.apache.org/jira/browse/SPARK-2650)
Please refer to [comments](https://issues.apache.org/jira/browse/SPARK-2650?focusedCommentId=14084397&page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel#comment-14084397) of SPARK-2650 for some other details.
This PR adjusts the initial in-memory columnar buffer size to 1MB, same as the default value of Shark's `shark.column.partitionSize.mb` property when running in local mode. Will add Shark style partition size estimation in another PR.
Also, before this PR, `NullableColumnBuilder` copies the whole buffer to add the null positions section, and then `CompressibleColumnBuilder` copies and compresses the buffer again, even if compression is disabled (`PassThrough` compression scheme is used to disable compression). In this PR the first buffer copy is eliminated to reduce memory consumption.
Author: Cheng Lian <lian.cs.zju@gmail.com>
Closes#1769 from liancheng/spark-2650 and squashes the following commits:
88a042e [Cheng Lian] Fixed method visibility and removed dead code
001f2e5 [Cheng Lian] Try fixing SPARK-2650 by adjusting initial buffer size and reducing memory allocation
Many users have reported being confused by the distinction between the `sql` and `hql` methods. Specifically, many users think that `sql(...)` cannot be used to read hive tables. In this PR I introduce a new configuration option `spark.sql.dialect` that picks which dialect with be used for parsing. For SQLContext this must be set to `sql`. In `HiveContext` it defaults to `hiveql` but can also be set to `sql`.
The `hql` and `hiveql` methods continue to act the same but are now marked as deprecated.
**This is a possibly breaking change for some users unless they set the dialect manually, though this is unlikely.**
For example: `hiveContex.sql("SELECT 1")` will now throw a parsing exception by default.
Author: Michael Armbrust <michael@databricks.com>
Closes#1746 from marmbrus/sqlLanguageConf and squashes the following commits:
ad375cc [Michael Armbrust] Merge remote-tracking branch 'apache/master' into sqlLanguageConf
20c43f8 [Michael Armbrust] override function instead of just setting the value
7e4ae93 [Michael Armbrust] Deprecate hql() method in favor of a config option, 'spark.sql.dialect'
There have been user complaints that the difference between `registerAsTable` and `saveAsTable` is too subtle. This PR addresses this by renaming `registerAsTable` to `registerTempTable`, which more clearly reflects what is happening. `registerAsTable` remains, but will cause a deprecation warning.
Author: Michael Armbrust <michael@databricks.com>
Closes#1743 from marmbrus/registerTempTable and squashes the following commits:
d031348 [Michael Armbrust] Merge remote-tracking branch 'apache/master' into registerTempTable
4dff086 [Michael Armbrust] Fix .java files too
89a2f12 [Michael Armbrust] Merge remote-tracking branch 'apache/master' into registerTempTable
0b7b71e [Michael Armbrust] Rename registerAsTable to registerTempTable
This is a follow up of #1636.
Author: Cheng Lian <lian.cs.zju@gmail.com>
Closes#1738 from liancheng/test-for-spark-2729 and squashes the following commits:
b13692a [Cheng Lian] Added test case for SPARK-2729
This patch adds the ability to register lambda functions written in Python, Java or Scala as UDFs for use in SQL or HiveQL.
Scala:
```scala
registerFunction("strLenScala", (_: String).length)
sql("SELECT strLenScala('test')")
```
Python:
```python
sqlCtx.registerFunction("strLenPython", lambda x: len(x), IntegerType())
sqlCtx.sql("SELECT strLenPython('test')")
```
Java:
```java
sqlContext.registerFunction("stringLengthJava", new UDF1<String, Integer>() {
Override
public Integer call(String str) throws Exception {
return str.length();
}
}, DataType.IntegerType);
sqlContext.sql("SELECT stringLengthJava('test')");
```
Author: Michael Armbrust <michael@databricks.com>
Closes#1063 from marmbrus/udfs and squashes the following commits:
9eda0fe [Michael Armbrust] newline
747c05e [Michael Armbrust] Add some scala UDF tests.
d92727d [Michael Armbrust] Merge remote-tracking branch 'apache/master' into udfs
005d684 [Michael Armbrust] Fix naming and formatting.
d14dac8 [Michael Armbrust] Fix last line of autogened java files.
8135c48 [Michael Armbrust] Move UDF unit tests to pyspark.
40b0ffd [Michael Armbrust] Merge remote-tracking branch 'apache/master' into udfs
6a36890 [Michael Armbrust] Switch logging so that SQLContext can be serializable.
7a83101 [Michael Armbrust] Drop toString
795fd15 [Michael Armbrust] Try to avoid capturing SQLContext.
e54fb45 [Michael Armbrust] Docs and tests.
437cbe3 [Michael Armbrust] Update use of dataTypes, fix some python tests, address review comments.
01517d6 [Michael Armbrust] Merge remote-tracking branch 'origin/master' into udfs
8e6c932 [Michael Armbrust] WIP
3f96a52 [Michael Armbrust] Merge remote-tracking branch 'origin/master' into udfs
6237c8d [Michael Armbrust] WIP
2766f0b [Michael Armbrust] Move udfs support to SQL from hive. Add support for Java UDFs.
0f7d50c [Michael Armbrust] Draft of native Spark SQL UDFs for Scala and Python.
This also Closes#1701.
Author: GuoQiang Li <witgo@qq.com>
Closes#1208 from witgo/SPARK-1470 and squashes the following commits:
422646b [GuoQiang Li] Remove scalalogging-slf4j dependency
I think we will not generate the plan triggering this bug at this moment. But, let me explain it...
Right now, we are using `left.outputPartitioning` as the `outputPartitioning` of a `BroadcastHashJoin`. We may have a wrong physical plan for cases like...
```sql
SELECT l.key, count(*)
FROM (SELECT key, count(*) as cnt
FROM src
GROUP BY key) l // This is buildPlan
JOIN r // This is the streamedPlan
ON (l.cnt = r.value)
GROUP BY l.key
```
Let's say we have a `BroadcastHashJoin` on `l` and `r`. For this case, we will pick `l`'s `outputPartitioning` for the `outputPartitioning`of the `BroadcastHashJoin` on `l` and `r`. Also, because the last `GROUP BY` is using `l.key` as the key, we will not introduce an `Exchange` for this aggregation. However, `r`'s outputPartitioning may not match the required distribution of the last `GROUP BY` and we fail to group data correctly.
JIRA is being reindexed. I will create a JIRA ticket once it is back online.
Author: Yin Huai <huai@cse.ohio-state.edu>
Closes#1735 from yhuai/BroadcastHashJoin and squashes the following commits:
96d9cb3 [Yin Huai] Set outputPartitioning correctly.
Author: GuoQiang Li <witgo@qq.com>
Closes#1369 from witgo/SPARK-1470_new and squashes the following commits:
66a1641 [GuoQiang Li] IncompatibleResultTypeProblem
73a89ba [GuoQiang Li] Use the scala-logging wrapper instead of the directly sfl4j api.
We need to carefully set the ouputPartitioning of the HashOuterJoin Operator. Otherwise, we may not correctly handle nulls.
Author: Yin Huai <huai@cse.ohio-state.edu>
Closes#1721 from yhuai/SPARK-2212-BugFix and squashes the following commits:
ed5eef7 [Yin Huai] Correctly choosing outputPartitioning for the HashOuterJoin operator.
Convert Row in JavaSchemaRDD into Array[Any] and unpickle them as tuple in Python, then convert them into namedtuple, so use can access fields just like attributes.
This will let nested structure can be accessed as object, also it will reduce the size of serialized data and better performance.
root
|-- field1: integer (nullable = true)
|-- field2: string (nullable = true)
|-- field3: struct (nullable = true)
| |-- field4: integer (nullable = true)
| |-- field5: array (nullable = true)
| | |-- element: integer (containsNull = false)
|-- field6: array (nullable = true)
| |-- element: struct (containsNull = false)
| | |-- field7: string (nullable = true)
Then we can access them by row.field3.field5[0] or row.field6[5].field7
It also will infer the schema in Python, convert Row/dict/namedtuple/objects into tuple before serialization, then call applySchema in JVM. During inferSchema(), the top level of dict in row will be StructType, but any nested dictionary will be MapType.
You can use pyspark.sql.Row to convert unnamed structure into Row object, make the RDD can be inferable. Such as:
ctx.inferSchema(rdd.map(lambda x: Row(a=x[0], b=x[1]))
Or you could use Row to create a class just like namedtuple, for example:
Person = Row("name", "age")
ctx.inferSchema(rdd.map(lambda x: Person(*x)))
Also, you can call applySchema to apply an schema to a RDD of tuple/list and turn it into a SchemaRDD. The `schema` should be StructType, see the API docs for details.
schema = StructType([StructField("name, StringType, True),
StructType("age", IntegerType, True)])
ctx.applySchema(rdd, schema)
PS: In order to use namedtuple to inferSchema, you should make namedtuple picklable.
Author: Davies Liu <davies.liu@gmail.com>
Closes#1598 from davies/nested and squashes the following commits:
f1d15b6 [Davies Liu] verify schema with the first few rows
8852aaf [Davies Liu] check type of schema
abe9e6e [Davies Liu] address comments
61b2292 [Davies Liu] add @deprecated to pythonToJavaMap
1e5b801 [Davies Liu] improve cache of classes
51aa135 [Davies Liu] use Row to infer schema
e9c0d5c [Davies Liu] remove string typed schema
353a3f2 [Davies Liu] fix code style
63de8f8 [Davies Liu] fix typo
c79ca67 [Davies Liu] fix serialization of nested data
6b258b5 [Davies Liu] fix pep8
9d8447c [Davies Liu] apply schema provided by string of names
f5df97f [Davies Liu] refactor, address comments
9d9af55 [Davies Liu] use arrry to applySchema and infer schema in Python
84679b3 [Davies Liu] Merge branch 'master' of github.com:apache/spark into nested
0eaaf56 [Davies Liu] fix doc tests
b3559b4 [Davies Liu] use generated Row instead of namedtuple
c4ddc30 [Davies Liu] fix conflict between name of fields and variables
7f6f251 [Davies Liu] address all comments
d69d397 [Davies Liu] refactor
2cc2d45 [Davies Liu] refactor
182fb46 [Davies Liu] refactor
bc6e9e1 [Davies Liu] switch to new Schema API
547bf3e [Davies Liu] Merge branch 'master' into nested
a435b5a [Davies Liu] add docs and code refactor
2c8debc [Davies Liu] Merge branch 'master' into nested
644665a [Davies Liu] use tuple and namedtuple for schemardd
just a match forgot, found after SPARK-2710 , TimestampType can be used by a SchemaRDD generated from JDBC ResultSet
Author: chutium <teng.qiu@gmail.com>
Closes#1636 from chutium/SPARK-2729 and squashes the following commits:
71af77a [chutium] [SPARK-2729] [SQL] added Timestamp in NullableColumnAccessorSuite
39cf9f8 [chutium] [SPARK-2729] add Timestamp Type into ColumnBuilder TestSuite, ref. #1636
ab6ff97 [chutium] [SPARK-2729] Forgot to match Timestamp type in ColumnBuilder
This patch is to support the hash based outer join. Currently, outer join for big relations are resort to `BoradcastNestedLoopJoin`, which is super slow. This PR will create 2 hash tables for both relations in the same partition, which greatly reduce the table scans.
Here is the testing code that I used:
```
package org.apache.spark.sql.hive
import org.apache.spark.SparkContext
import org.apache.spark.SparkConf
import org.apache.spark.sql._
case class Record(key: String, value: String)
object JoinTablePrepare extends App {
import TestHive2._
val rdd = sparkContext.parallelize((1 to 3000000).map(i => Record(s"${i % 828193}", s"val_$i")))
runSqlHive("SHOW TABLES")
runSqlHive("DROP TABLE if exists a")
runSqlHive("DROP TABLE if exists b")
runSqlHive("DROP TABLE if exists result")
rdd.registerAsTable("records")
runSqlHive("""CREATE TABLE a (key STRING, value STRING)
| ROW FORMAT SERDE
| 'org.apache.hadoop.hive.serde2.columnar.LazyBinaryColumnarSerDe'
| STORED AS RCFILE
""".stripMargin)
runSqlHive("""CREATE TABLE b (key STRING, value STRING)
| ROW FORMAT SERDE
| 'org.apache.hadoop.hive.serde2.columnar.LazyBinaryColumnarSerDe'
| STORED AS RCFILE
""".stripMargin)
runSqlHive("""CREATE TABLE result (key STRING, value STRING)
| ROW FORMAT SERDE
| 'org.apache.hadoop.hive.serde2.columnar.LazyBinaryColumnarSerDe'
| STORED AS RCFILE
""".stripMargin)
hql(s"""from records
| insert into table a
| select key, value
""".stripMargin)
hql(s"""from records
| insert into table b select key + 100000, value
""".stripMargin)
}
object JoinTablePerformanceTest extends App {
import TestHive2._
hql("SHOW TABLES")
hql("set spark.sql.shuffle.partitions=20")
val leftOuterJoin = "insert overwrite table result select a.key, b.value from a left outer join b on a.key=b.key"
val rightOuterJoin = "insert overwrite table result select a.key, b.value from a right outer join b on a.key=b.key"
val fullOuterJoin = "insert overwrite table result select a.key, b.value from a full outer join b on a.key=b.key"
val results = ("LeftOuterJoin", benchmark(leftOuterJoin)) :: ("LeftOuterJoin", benchmark(leftOuterJoin)) ::
("RightOuterJoin", benchmark(rightOuterJoin)) :: ("RightOuterJoin", benchmark(rightOuterJoin)) ::
("FullOuterJoin", benchmark(fullOuterJoin)) :: ("FullOuterJoin", benchmark(fullOuterJoin)) :: Nil
val explains = hql(s"explain $leftOuterJoin").collect ++ hql(s"explain $rightOuterJoin").collect ++ hql(s"explain $fullOuterJoin").collect
println(explains.mkString(",\n"))
results.foreach { case (prompt, result) => {
println(s"$prompt: took ${result._1} ms (${result._2} records)")
}
}
def benchmark(cmd: String) = {
val begin = System.currentTimeMillis()
val result = hql(cmd)
val end = System.currentTimeMillis()
val count = hql("select count(1) from result").collect.mkString("")
((end - begin), count)
}
}
```
And the result as shown below:
```
[Physical execution plan:],
[InsertIntoHiveTable (MetastoreRelation default, result, None), Map(), true],
[ Project [key#95,value#98]],
[ HashOuterJoin [key#95], [key#97], LeftOuter, None],
[ Exchange (HashPartitioning [key#95], 20)],
[ HiveTableScan [key#95], (MetastoreRelation default, a, None), None],
[ Exchange (HashPartitioning [key#97], 20)],
[ HiveTableScan [key#97,value#98], (MetastoreRelation default, b, None), None],
[Physical execution plan:],
[InsertIntoHiveTable (MetastoreRelation default, result, None), Map(), true],
[ Project [key#102,value#105]],
[ HashOuterJoin [key#102], [key#104], RightOuter, None],
[ Exchange (HashPartitioning [key#102], 20)],
[ HiveTableScan [key#102], (MetastoreRelation default, a, None), None],
[ Exchange (HashPartitioning [key#104], 20)],
[ HiveTableScan [key#104,value#105], (MetastoreRelation default, b, None), None],
[Physical execution plan:],
[InsertIntoHiveTable (MetastoreRelation default, result, None), Map(), true],
[ Project [key#109,value#112]],
[ HashOuterJoin [key#109], [key#111], FullOuter, None],
[ Exchange (HashPartitioning [key#109], 20)],
[ HiveTableScan [key#109], (MetastoreRelation default, a, None), None],
[ Exchange (HashPartitioning [key#111], 20)],
[ HiveTableScan [key#111,value#112], (MetastoreRelation default, b, None), None]
LeftOuterJoin: took 16072 ms ([3000000] records)
LeftOuterJoin: took 14394 ms ([3000000] records)
RightOuterJoin: took 14802 ms ([3000000] records)
RightOuterJoin: took 14747 ms ([3000000] records)
FullOuterJoin: took 17715 ms ([6000000] records)
FullOuterJoin: took 17629 ms ([6000000] records)
```
Without this PR, the benchmark will run seems never end.
Author: Cheng Hao <hao.cheng@intel.com>
Closes#1147 from chenghao-intel/hash_based_outer_join and squashes the following commits:
65c599e [Cheng Hao] Fix issues with the community comments
72b1394 [Cheng Hao] Fix bug of stale value in joinedRow
55baef7 [Cheng Hao] Add HashOuterJoin
It is a follow-up PR of SPARK-2179 (https://issues.apache.org/jira/browse/SPARK-2179). It makes package names of data type APIs more consistent across languages (Scala: `org.apache.spark.sql`, Java: `org.apache.spark.sql.api.java`, Python: `pyspark.sql`).
Author: Yin Huai <huai@cse.ohio-state.edu>
Closes#1712 from yhuai/javaDataType and squashes the following commits:
62eb705 [Yin Huai] Move package-info.
add4bcb [Yin Huai] Make the package names of data type classes consistent across languages by moving all Java data type classes to package sql.api.java.
Since we let users create Rows. It makes sense to accept mutable Maps as values of MapType columns.
JIRA: https://issues.apache.org/jira/browse/SPARK-2779
Author: Yin Huai <huai@cse.ohio-state.edu>
Closes#1705 from yhuai/SPARK-2779 and squashes the following commits:
00d72fd [Yin Huai] Use scala.collection.Map.
This PR resolves the following two tickets:
- [SPARK-2531](https://issues.apache.org/jira/browse/SPARK-2531): BNLJ currently assumes the build side is the right relation. This patch refactors some of its logic to take into account a BuildSide properly.
- [SPARK-2436](https://issues.apache.org/jira/browse/SPARK-2436): building on top of the above, we simply use the physical size statistics (if available) of both relations, and make the smaller relation the build side in the planner.
Author: Zongheng Yang <zongheng.y@gmail.com>
Closes#1448 from concretevitamin/bnlj-buildSide and squashes the following commits:
1780351 [Zongheng Yang] Use size estimation to decide optimal build side of BNLJ.
68e6c5b [Zongheng Yang] Consolidate two adjacent pattern matchings.
96d312a [Zongheng Yang] Use a while loop instead of collection methods chaining.
4bc525e [Zongheng Yang] Make BroadcastNestedLoopJoin take a BuildSide.
Author: Michael Armbrust <michael@databricks.com>
Closes#1647 from marmbrus/parquetCase and squashes the following commits:
a1799b7 [Michael Armbrust] move comment
2a2a68b [Michael Armbrust] Merge remote-tracking branch 'apache/master' into parquetCase
bb35d5b [Michael Armbrust] Fix test case that produced an invalid plan.
e6870bf [Michael Armbrust] Better error message.
539a2e1 [Michael Armbrust] Resolve original attributes in ParquetTableScan
This adds a new ShuffleManager based on sorting, as described in https://issues.apache.org/jira/browse/SPARK-2045. The bulk of the code is in an ExternalSorter class that is similar to ExternalAppendOnlyMap, but sorts key-value pairs by partition ID and can be used to create a single sorted file with a map task's output. (Longer-term I think this can take on the remaining functionality in ExternalAppendOnlyMap and replace it so we don't have code duplication.)
The main TODOs still left are:
- [x] enabling ExternalSorter to merge across spilled files
- [x] with an Ordering
- [x] without an Ordering, using the keys' hash codes
- [x] adding more tests (e.g. a version of our shuffle suite that runs on this)
- [x] rebasing on top of the size-tracking refactoring in #1165 when that is merged
- [x] disabling spilling if spark.shuffle.spill is set to false
Despite this though, this seems to work pretty well (running successfully in cases where the hash shuffle would OOM, such as 1000 reduce tasks on executors with only 1G memory), and it seems to be comparable in speed or faster than hash-based shuffle (it will create much fewer files for the OS to keep track of). So I'm posting it to get some early feedback.
After these TODOs are done, I'd also like to enable ExternalSorter to sort data within each partition by a key as well, which will allow us to use it to implement external spilling in reduce tasks in `sortByKey`.
Author: Matei Zaharia <matei@databricks.com>
Closes#1499 from mateiz/sort-based-shuffle and squashes the following commits:
bd841f9 [Matei Zaharia] Various review comments
d1c137fd [Matei Zaharia] Various review comments
a611159 [Matei Zaharia] Compile fixes due to rebase
62c56c8 [Matei Zaharia] Fix ShuffledRDD sometimes not returning Tuple2s.
f617432 [Matei Zaharia] Fix a failing test (seems to be due to change in SizeTracker logic)
9464d5f [Matei Zaharia] Simplify code and fix conflicts after latest rebase
0174149 [Matei Zaharia] Add cleanup behavior and cleanup tests for sort-based shuffle
eb4ee0d [Matei Zaharia] Remove customizable element type in ShuffledRDD
fa2e8db [Matei Zaharia] Allow nextBatchStream to be called after we're done looking at all streams
a34b352 [Matei Zaharia] Fix tracking of indices within a partition in SpillReader, and add test
03e1006 [Matei Zaharia] Add a SortShuffleSuite that runs ShuffleSuite with sort-based shuffle
3c7ff1f [Matei Zaharia] Obey the spark.shuffle.spill setting in ExternalSorter
ad65fbd [Matei Zaharia] Rebase on top of Aaron's Sorter change, and use Sorter in our buffer
44d2a93 [Matei Zaharia] Use estimateSize instead of atGrowThreshold to test collection sizes
5686f71 [Matei Zaharia] Optimize merging phase for in-memory only data:
5461cbb [Matei Zaharia] Review comments and more tests (e.g. tests with 1 element per partition)
e9ad356 [Matei Zaharia] Update ContextCleanerSuite to make sure shuffle cleanup tests use hash shuffle (since they were written for it)
c72362a [Matei Zaharia] Added bug fix and test for when iterators are empty
de1fb40 [Matei Zaharia] Make trait SizeTrackingCollection private[spark]
4988d16 [Matei Zaharia] tweak
c1b7572 [Matei Zaharia] Small optimization
ba7db7f [Matei Zaharia] Handle null keys in hash-based comparator, and add tests for collisions
ef4e397 [Matei Zaharia] Support for partial aggregation even without an Ordering
4b7a5ce [Matei Zaharia] More tests, and ability to sort data if a total ordering is given
e1f84be [Matei Zaharia] Fix disk block manager test
5a40a1c [Matei Zaharia] More tests
614f1b4 [Matei Zaharia] Add spill metrics to map tasks
cc52caf [Matei Zaharia] Add more error handling and tests for error cases
bbf359d [Matei Zaharia] More work
3a56341 [Matei Zaharia] More partial work towards sort-based shuffle
7a0895d [Matei Zaharia] Some more partial work towards sort-based shuffle
b615476 [Matei Zaharia] Scaffolding for sort-based shuffle
The Maven-based builds in the build matrix have been failing for a few days:
https://amplab.cs.berkeley.edu/jenkins/view/Spark/
On inspection, it looks like the Spark SQL Java tests don't compile:
https://amplab.cs.berkeley.edu/jenkins/view/Spark/job/Spark-Master-Maven-pre-YARN/hadoop.version=1.0.4,label=centos/244/consoleFull
I confirmed it by repeating the command vs master:
`mvn -Dhadoop.version=1.0.4 -Dlabel=centos -DskipTests clean package`
The problem is that this module doesn't depend on JUnit. In fact, none of the modules do, but `com.novocode:junit-interface` (the SBT-JUnit bridge) pulls it in, in most places. However this module doesn't depend on `com.novocode:junit-interface`
Adding the `junit:junit` dependency fixes the compile problem. In fact, the other modules with Java tests should probably depend on it explicitly instead of happening to get it via `com.novocode:junit-interface`, since that is a bit SBT/Scala-specific (and I am not even sure it's needed).
Author: Sean Owen <srowen@gmail.com>
Closes#1660 from srowen/SPARK-2749 and squashes the following commits:
858ff7c [Sean Owen] Add explicit junit dep to other modules with Java tests for robustness
9636794 [Sean Owen] Add junit dep so that Spark SQL Java tests compile
The current PR contains the following changes:
* Expose `DataType`s in the sql package (internal details are private to sql).
* Users can create Rows.
* Introduce `applySchema` to create a `SchemaRDD` by applying a `schema: StructType` to an `RDD[Row]`.
* Add a function `simpleString` to every `DataType`. Also, the schema represented by a `StructType` can be visualized by `printSchema`.
* `ScalaReflection.typeOfObject` provides a way to infer the Catalyst data type based on an object. Also, we can compose `typeOfObject` with some custom logics to form a new function to infer the data type (for different use cases).
* `JsonRDD` has been refactored to use changes introduced by this PR.
* Add a field `containsNull` to `ArrayType`. So, we can explicitly mark if an `ArrayType` can contain null values. The default value of `containsNull` is `false`.
New APIs are introduced in the sql package object and SQLContext. You can find the scaladoc at
[sql package object](http://yhuai.github.io/site/api/scala/index.html#org.apache.spark.sql.package) and [SQLContext](http://yhuai.github.io/site/api/scala/index.html#org.apache.spark.sql.SQLContext).
An example of using `applySchema` is shown below.
```scala
import org.apache.spark.sql._
val sqlContext = new org.apache.spark.sql.SQLContext(sc)
val schema =
StructType(
StructField("name", StringType, false) ::
StructField("age", IntegerType, true) :: Nil)
val people = sc.textFile("examples/src/main/resources/people.txt").map(_.split(",")).map(p => Row(p(0), p(1).trim.toInt))
val peopleSchemaRDD = sqlContext. applySchema(people, schema)
peopleSchemaRDD.printSchema
// root
// |-- name: string (nullable = false)
// |-- age: integer (nullable = true)
peopleSchemaRDD.registerAsTable("people")
sqlContext.sql("select name from people").collect.foreach(println)
```
I will add new contents to the SQL programming guide later.
JIRA: https://issues.apache.org/jira/browse/SPARK-2179
Author: Yin Huai <huai@cse.ohio-state.edu>
Closes#1346 from yhuai/dataTypeAndSchema and squashes the following commits:
1d45977 [Yin Huai] Clean up.
a6e08b4 [Yin Huai] Merge remote-tracking branch 'upstream/master' into dataTypeAndSchema
c712fbf [Yin Huai] Converts types of values based on defined schema.
4ceeb66 [Yin Huai] Merge remote-tracking branch 'upstream/master' into dataTypeAndSchema
e5f8df5 [Yin Huai] Scaladoc.
122d1e7 [Yin Huai] Address comments.
03bfd95 [Yin Huai] Merge remote-tracking branch 'upstream/master' into dataTypeAndSchema
2476ed0 [Yin Huai] Minor updates.
ab71f21 [Yin Huai] Format.
fc2bed1 [Yin Huai] Merge remote-tracking branch 'upstream/master' into dataTypeAndSchema
bd40a33 [Yin Huai] Address comments.
991f860 [Yin Huai] Move "asJavaDataType" and "asScalaDataType" to DataTypeConversions.scala.
1cb35fe [Yin Huai] Add "valueContainsNull" to MapType.
3edb3ae [Yin Huai] Python doc.
692c0b9 [Yin Huai] Merge remote-tracking branch 'upstream/master' into dataTypeAndSchema
1d93395 [Yin Huai] Python APIs.
246da96 [Yin Huai] Add java data type APIs to javadoc index.
1db9531 [Yin Huai] Merge remote-tracking branch 'upstream/master' into dataTypeAndSchema
d48fc7b [Yin Huai] Minor updates.
33c4fec [Yin Huai] Merge remote-tracking branch 'upstream/master' into dataTypeAndSchema
b9f3071 [Yin Huai] Java API for applySchema.
1c9f33c [Yin Huai] Java APIs for DataTypes and Row.
624765c [Yin Huai] Tests for applySchema.
aa92e84 [Yin Huai] Update data type tests.
8da1a17 [Yin Huai] Add Row.fromSeq.
9c99bc0 [Yin Huai] Several minor updates.
1d9c13a [Yin Huai] Update applySchema API.
85e9b51 [Yin Huai] Merge remote-tracking branch 'upstream/master' into dataTypeAndSchema
e495e4e [Yin Huai] More comments.
42d47a3 [Yin Huai] Merge remote-tracking branch 'upstream/master' into dataTypeAndSchema
c3f4a02 [Yin Huai] Merge remote-tracking branch 'upstream/master' into dataTypeAndSchema
2e58dbd [Yin Huai] Merge remote-tracking branch 'upstream/master' into dataTypeAndSchema
b8b7db4 [Yin Huai] 1. Move sql package object and package-info to sql-core. 2. Minor updates on APIs. 3. Update scala doc.
68525a2 [Yin Huai] Update JSON unit test.
3209108 [Yin Huai] Add unit tests.
dcaf22f [Yin Huai] Add a field containsNull to ArrayType to indicate if an array can contain null values or not. If an ArrayType is constructed by "ArrayType(elementType)" (the existing constructor), the value of containsNull is false.
9168b83 [Yin Huai] Update comments.
fc649d7 [Yin Huai] Merge remote-tracking branch 'upstream/master' into dataTypeAndSchema
eca7d04 [Yin Huai] Add two apply methods which will be used to extract StructField(s) from a StructType.
949d6bb [Yin Huai] When creating a SchemaRDD for a JSON dataset, users can apply an existing schema.
7a6a7e5 [Yin Huai] Fix bug introduced by the change made on SQLContext.inferSchema.
43a45e1 [Yin Huai] Remove sql.util.package introduced in a previous commit.
0266761 [Yin Huai] Format
03eec4c [Yin Huai] Merge remote-tracking branch 'upstream/master' into dataTypeAndSchema
90460ac [Yin Huai] Infer the Catalyst data type from an object and cast a data value to the expected type.
3fa0df5 [Yin Huai] Provide easier ways to construct a StructType.
16be3e5 [Yin Huai] This commit contains three changes: * Expose `DataType`s in the sql package (internal details are private to sql). * Introduce `createSchemaRDD` to create a `SchemaRDD` from an `RDD` with a provided schema (represented by a `StructType`) and a provided function to construct `Row`, * Add a function `simpleString` to every `DataType`. Also, the schema represented by a `StructType` can be visualized by `printSchema`.
Author: Michael Armbrust <michael@databricks.com>
Closes#1646 from marmbrus/nullDebug and squashes the following commits:
49050a8 [Michael Armbrust] Handle null values in debug()
Adds a new method for evaluating expressions using code that is generated though Scala reflection. This functionality is configured by the SQLConf option `spark.sql.codegen` and is currently turned off by default.
Evaluation can be done in several specialized ways:
- *Projection* - Given an input row, produce a new row from a set of expressions that define each column in terms of the input row. This can either produce a new Row object or perform the projection in-place on an existing Row (MutableProjection).
- *Ordering* - Compares two rows based on a list of `SortOrder` expressions
- *Condition* - Returns `true` or `false` given an input row.
For each of the above operations there is both a Generated and Interpreted version. When generation for a given expression type is undefined, the code generator falls back on calling the `eval` function of the expression class. Even without custom code, there is still a potential speed up, as loops are unrolled and code can still be inlined by JIT.
This PR also contains a new type of Aggregation operator, `GeneratedAggregate`, that performs aggregation by using generated `Projection` code. Currently the required expression rewriting only works for simple aggregations like `SUM` and `COUNT`. This functionality will be extended in a future PR.
This PR also performs several clean ups that simplified the implementation:
- The notion of `Binding` all expressions in a tree automatically before query execution has been removed. Instead it is the responsibly of an operator to provide the input schema when creating one of the specialized evaluators defined above. In cases when the standard eval method is going to be called, binding can still be done manually using `BindReferences`. There are a few reasons for this change: First, there were many operators where it just didn't work before. For example, operators with more than one child, and operators like aggregation that do significant rewriting of the expression. Second, the semantics of equality with `BoundReferences` are broken. Specifically, we have had a few bugs where partitioning breaks because of the binding.
- A copy of the current `SQLContext` is automatically propagated to all `SparkPlan` nodes by the query planner. Before this was done ad-hoc for the nodes that needed this. However, this required a lot of boilerplate as one had to always remember to make it `transient` and also had to modify the `otherCopyArgs`.
Author: Michael Armbrust <michael@databricks.com>
Closes#993 from marmbrus/newCodeGen and squashes the following commits:
96ef82c [Michael Armbrust] Merge remote-tracking branch 'apache/master' into newCodeGen
f34122d [Michael Armbrust] Merge remote-tracking branch 'apache/master' into newCodeGen
67b1c48 [Michael Armbrust] Use conf variable in SQLConf object
4bdc42c [Michael Armbrust] Merge remote-tracking branch 'origin/master' into newCodeGen
41a40c9 [Michael Armbrust] Merge remote-tracking branch 'origin/master' into newCodeGen
de22aac [Michael Armbrust] Merge remote-tracking branch 'origin/master' into newCodeGen
fed3634 [Michael Armbrust] Inspectors are not serializable.
ef8d42b [Michael Armbrust] comments
533fdfd [Michael Armbrust] More logging of expression rewriting for GeneratedAggregate.
3cd773e [Michael Armbrust] Allow codegen for Generate.
64b2ee1 [Michael Armbrust] Implement copy
3587460 [Michael Armbrust] Drop unused string builder function.
9cce346 [Michael Armbrust] Merge remote-tracking branch 'origin/master' into newCodeGen
1a61293 [Michael Armbrust] Address review comments.
0672e8a [Michael Armbrust] Address comments.
1ec2d6e [Michael Armbrust] Address comments
033abc6 [Michael Armbrust] off by default
4771fab [Michael Armbrust] Docs, more test coverage.
d30fee2 [Michael Armbrust] Merge remote-tracking branch 'origin/master' into newCodeGen
d2ad5c5 [Michael Armbrust] Refactor putting SQLContext into SparkPlan. Fix ordering, other test cases.
be2cd6b [Michael Armbrust] WIP: Remove old method for reference binding, more work on configuration.
bc88ecd [Michael Armbrust] Style
6cc97ca [Michael Armbrust] Merge remote-tracking branch 'origin/master' into newCodeGen
4220f1e [Michael Armbrust] Better config, docs, etc.
ca6cc6b [Michael Armbrust] WIP
9d67d85 [Michael Armbrust] Fix hive planner
fc522d5 [Michael Armbrust] Hook generated aggregation in to the planner.
e742640 [Michael Armbrust] Remove unneeded changes and code.
675e679 [Michael Armbrust] Upgrade paradise.
0093376 [Michael Armbrust] Comment / indenting cleanup.
d81f998 [Michael Armbrust] include schema for binding.
0e889e8 [Michael Armbrust] Use typeOf instead tq
f623ffd [Michael Armbrust] Quiet logging from test suite.
efad14f [Michael Armbrust] Remove some half finished functions.
92e74a4 [Michael Armbrust] add overrides
a2b5408 [Michael Armbrust] WIP: Code generation with scala reflection.
Author: Michael Armbrust <michael@databricks.com>
Closes#1638 from marmbrus/cachedConfig and squashes the following commits:
2362082 [Michael Armbrust] Use SQLConf to configure in-memory columnar caching
The idea is that every Catalyst logical plan gets hold of a Statistics class, the usage of which provides useful estimations on various statistics. See the implementations of `MetastoreRelation`.
This patch also includes several usages of the estimation interface in the planner. For instance, we now use physical table sizes from the estimate interface to convert an equi-join to a broadcast join (when doing so is beneficial, as determined by a size threshold).
Finally, there are a couple minor accompanying changes including:
- Remove the not-in-use `BaseRelation`.
- Make SparkLogicalPlan take a `SQLContext` in the second param list.
Author: Zongheng Yang <zongheng.y@gmail.com>
Closes#1238 from concretevitamin/estimates and squashes the following commits:
329071d [Zongheng Yang] Address review comments; turn config name from string to field in SQLConf.
8663e84 [Zongheng Yang] Use BigInt for stat; for logical leaves, by default throw an exception.
2f2fb89 [Zongheng Yang] Fix statistics for SparkLogicalPlan.
9951305 [Zongheng Yang] Remove childrenStats.
16fc60a [Zongheng Yang] Avoid calling statistics on plans if auto join conversion is disabled.
8bd2816 [Zongheng Yang] Add a note on performance of statistics.
6e594b8 [Zongheng Yang] Get size info from metastore for MetastoreRelation.
01b7a3e [Zongheng Yang] Update scaladoc for a field and move it to @param section.
549061c [Zongheng Yang] Remove numTuples in Statistics for now.
729a8e2 [Zongheng Yang] Update docs to be more explicit.
573e644 [Zongheng Yang] Remove singleton SQLConf and move back `settings` to the trait.
2d99eb5 [Zongheng Yang] {Cleanup, use synchronized in, enrich} StatisticsSuite.
ca5b825 [Zongheng Yang] Inject SQLContext into SparkLogicalPlan, removing SQLConf mixin from it.
43d38a6 [Zongheng Yang] Revert optimization for BroadcastNestedLoopJoin (this fixes tests).
0ef9e5b [Zongheng Yang] Use multiplication instead of sum for default estimates.
4ef0d26 [Zongheng Yang] Make Statistics a case class.
3ba8f3e [Zongheng Yang] Add comment.
e5bcf5b [Zongheng Yang] Fix optimization conditions & update scala docs to explain.
7d9216a [Zongheng Yang] Apply estimation to planning ShuffleHashJoin & BroadcastNestedLoopJoin.
73cde01 [Zongheng Yang] Move SQLConf back. Assign default sizeInBytes to SparkLogicalPlan.
73412be [Zongheng Yang] Move SQLConf to Catalyst & add default val for sizeInBytes.
7a60ab7 [Zongheng Yang] s/Estimates/Statistics, s/cardinality/numTuples.
de3ae13 [Zongheng Yang] Add parquetAfter() properly in test.
dcff9bd [Zongheng Yang] Cleanups.
84301a4 [Zongheng Yang] Refactors.
5bf5586 [Zongheng Yang] Typo.
56a8e6e [Zongheng Yang] Prototype impl of estimations for Catalyst logical plans.
Datetime and time in Python will be converted into java.util.Calendar after serialization, it will be converted into java.sql.Timestamp during inferSchema().
In javaToPython(), Timestamp will be converted into Calendar, then be converted into datetime in Python after pickling.
Author: Davies Liu <davies.liu@gmail.com>
Closes#1601 from davies/date and squashes the following commits:
f0599b0 [Davies Liu] remove tests for sets and tuple in sql, fix list of list
c9d607a [Davies Liu] convert datetype for runtime
709d40d [Davies Liu] remove brackets
96db384 [Davies Liu] support datetime type for SchemaRDD
JIRA issue: [SPARK-2410](https://issues.apache.org/jira/browse/SPARK-2410)
Another try for #1399 & #1600. Those two PR breaks Jenkins builds because we made a separate profile `hive-thriftserver` in sub-project `assembly`, but the `hive-thriftserver` module is defined outside the `hive-thriftserver` profile. Thus every time a pull request that doesn't touch SQL code will also execute test suites defined in `hive-thriftserver`, but tests fail because related .class files are not included in the assembly jar.
In the most recent commit, module `hive-thriftserver` is moved into its own profile to fix this problem. All previous commits are squashed for clarity.
Author: Cheng Lian <lian.cs.zju@gmail.com>
Closes#1620 from liancheng/jdbc-with-maven-fix and squashes the following commits:
629988e [Cheng Lian] Moved hive-thriftserver module definition into its own profile
ec3c7a7 [Cheng Lian] Cherry picked the Hive Thrift server
(This is a replacement of #1399, trying to fix potential `HiveThriftServer2` port collision between parallel builds. Please refer to [these comments](https://github.com/apache/spark/pull/1399#issuecomment-50212572) for details.)
JIRA issue: [SPARK-2410](https://issues.apache.org/jira/browse/SPARK-2410)
Merging the Hive Thrift/JDBC server from [branch-1.0-jdbc](https://github.com/apache/spark/tree/branch-1.0-jdbc).
Thanks chenghao-intel for his initial contribution of the Spark SQL CLI.
Author: Cheng Lian <lian.cs.zju@gmail.com>
Closes#1600 from liancheng/jdbc and squashes the following commits:
ac4618b [Cheng Lian] Uses random port for HiveThriftServer2 to avoid collision with parallel builds
090beea [Cheng Lian] Revert changes related to SPARK-2678, decided to move them to another PR
21c6cf4 [Cheng Lian] Updated Spark SQL programming guide docs
fe0af31 [Cheng Lian] Reordered spark-submit options in spark-shell[.cmd]
199e3fb [Cheng Lian] Disabled MIMA for hive-thriftserver
1083e9d [Cheng Lian] Fixed failed test suites
7db82a1 [Cheng Lian] Fixed spark-submit application options handling logic
9cc0f06 [Cheng Lian] Starts beeline with spark-submit
cfcf461 [Cheng Lian] Updated documents and build scripts for the newly added hive-thriftserver profile
061880f [Cheng Lian] Addressed all comments by @pwendell
7755062 [Cheng Lian] Adapts test suites to spark-submit settings
40bafef [Cheng Lian] Fixed more license header issues
e214aab [Cheng Lian] Added missing license headers
b8905ba [Cheng Lian] Fixed minor issues in spark-sql and start-thriftserver.sh
f975d22 [Cheng Lian] Updated docs for Hive compatibility and Shark migration guide draft
3ad4e75 [Cheng Lian] Starts spark-sql shell with spark-submit
a5310d1 [Cheng Lian] Make HiveThriftServer2 play well with spark-submit
61f39f4 [Cheng Lian] Starts Hive Thrift server via spark-submit
2c4c539 [Cheng Lian] Cherry picked the Hive Thrift server
This reverts commit 06dc0d2c6b.
#1399 is making Jenkins fail. We should investigate and put this back after its passing tests.
Author: Michael Armbrust <michael@databricks.com>
Closes#1594 from marmbrus/revertJDBC and squashes the following commits:
59748da [Michael Armbrust] Revert "[SPARK-2410][SQL] Merging Hive Thrift/JDBC server"
JIRA issue:
- Main: [SPARK-2410](https://issues.apache.org/jira/browse/SPARK-2410)
- Related: [SPARK-2678](https://issues.apache.org/jira/browse/SPARK-2678)
Cherry picked the Hive Thrift/JDBC server from [branch-1.0-jdbc](https://github.com/apache/spark/tree/branch-1.0-jdbc).
(Thanks chenghao-intel for his initial contribution of the Spark SQL CLI.)
TODO
- [x] Use `spark-submit` to launch the server, the CLI and beeline
- [x] Migration guideline draft for Shark users
----
Hit by a bug in `SparkSubmitArguments` while working on this PR: all application options that are recognized by `SparkSubmitArguments` are stolen as `SparkSubmit` options. For example:
```bash
$ spark-submit --class org.apache.hive.beeline.BeeLine spark-internal --help
```
This actually shows usage information of `SparkSubmit` rather than `BeeLine`.
~~Fixed this bug here since the `spark-internal` related stuff also touches `SparkSubmitArguments` and I'd like to avoid conflict.~~
**UPDATE** The bug mentioned above is now tracked by [SPARK-2678](https://issues.apache.org/jira/browse/SPARK-2678). Decided to revert changes to this bug since it involves more subtle considerations and worth a separate PR.
Author: Cheng Lian <lian.cs.zju@gmail.com>
Closes#1399 from liancheng/thriftserver and squashes the following commits:
090beea [Cheng Lian] Revert changes related to SPARK-2678, decided to move them to another PR
21c6cf4 [Cheng Lian] Updated Spark SQL programming guide docs
fe0af31 [Cheng Lian] Reordered spark-submit options in spark-shell[.cmd]
199e3fb [Cheng Lian] Disabled MIMA for hive-thriftserver
1083e9d [Cheng Lian] Fixed failed test suites
7db82a1 [Cheng Lian] Fixed spark-submit application options handling logic
9cc0f06 [Cheng Lian] Starts beeline with spark-submit
cfcf461 [Cheng Lian] Updated documents and build scripts for the newly added hive-thriftserver profile
061880f [Cheng Lian] Addressed all comments by @pwendell
7755062 [Cheng Lian] Adapts test suites to spark-submit settings
40bafef [Cheng Lian] Fixed more license header issues
e214aab [Cheng Lian] Added missing license headers
b8905ba [Cheng Lian] Fixed minor issues in spark-sql and start-thriftserver.sh
f975d22 [Cheng Lian] Updated docs for Hive compatibility and Shark migration guide draft
3ad4e75 [Cheng Lian] Starts spark-sql shell with spark-submit
a5310d1 [Cheng Lian] Make HiveThriftServer2 play well with spark-submit
61f39f4 [Cheng Lian] Starts Hive Thrift server via spark-submit
2c4c539 [Cheng Lian] Cherry picked the Hive Thrift server
In JsonRDD.scalafy, we are using toMap/toList to convert a Java Map/List to a Scala one. These two operations are pretty expensive because they read elements from a Java Map/List and then load to a Scala Map/List. We can use Scala wrappers to wrap those Java collections instead of using toMap/toList.
I did a quick test to see the performance. I had a 2.9GB cached RDD[String] storing one JSON object per record (twitter dataset). My simple test program is attached below.
```scala
val sqlContext = new org.apache.spark.sql.SQLContext(sc)
import sqlContext._
val jsonData = sc.textFile("...")
jsonData.cache.count
val jsonSchemaRDD = sqlContext.jsonRDD(jsonData)
jsonSchemaRDD.registerAsTable("jt")
sqlContext.sql("select count(*) from jt").collect
```
Stages for the schema inference and the table scan both had 48 tasks. These tasks were executed sequentially. For the current implementation, scanning the JSON dataset will materialize values of all fields of a record. The inferred schema of the dataset can be accessed at https://gist.github.com/yhuai/05fe8a57c638c6666f8d.
From the result, there was no significant difference on running `jsonRDD`. For the simple aggregation query, results are attached below.
```
Original:
Run 1: 26.1s
Run 2: 27.03s
Run 3: 27.035s
With this change:
Run 1: 21.086s
Run 2: 21.035s
Run 3: 21.029s
```
JIRA: https://issues.apache.org/jira/browse/SPARK-2603
Author: Yin Huai <huai@cse.ohio-state.edu>
Closes#1504 from yhuai/removeToMapToList and squashes the following commits:
6831b77 [Yin Huai] Fix failed tests.
09b9bca [Yin Huai] Merge remote-tracking branch 'upstream/master' into removeToMapToList
d1abdb8 [Yin Huai] Remove unnecessary toMap and toList.
Author: Ian O Connell <ioconnell@twitter.com>
Closes#1377 from ianoc/feature/SPARK-2102 and squashes the following commits:
5498566 [Ian O Connell] Docs update suggested by Patrick
20e8555 [Ian O Connell] Slight style change
f92c294 [Ian O Connell] Add docs for new KryoSerializer option
f3735c8 [Ian O Connell] Add using a kryo resource pool for the SqlSerializer
4e5c342 [Ian O Connell] Register the SparkConf for kryo, it gets swept into serialization
665805a [Ian O Connell] Add a spark.kryo.registrationRequired option for configuring the Kryo Serializer
Author: Takuya UESHIN <ueshin@happy-camper.st>
Closes#1491 from ueshin/issues/SPARK-2588 and squashes the following commits:
43d0a46 [Takuya UESHIN] Merge branch 'master' into issues/SPARK-2588
1023ea0 [Takuya UESHIN] Modify tests to use DSLs.
2310bf1 [Takuya UESHIN] Add some more DSLs.
We need to use the analyzed attributes otherwise we end up with a tree that will never resolve.
Author: Michael Armbrust <michael@databricks.com>
Closes#1470 from marmbrus/fixApplySchema and squashes the following commits:
f968195 [Michael Armbrust] Use analyzed attributes when applying the schema.
4969015 [Michael Armbrust] Add test case.
JIRA: https://issues.apache.org/jira/browse/SPARK-2525.
Author: Yin Huai <huai@cse.ohio-state.edu>
Closes#1444 from yhuai/SPARK-2517 and squashes the following commits:
edbac3f [Yin Huai] Removed some compiler type erasure warnings.
JIRA issue: [SPARK-2119](https://issues.apache.org/jira/browse/SPARK-2119)
Essentially this PR fixed three issues to gain much better performance when reading large Parquet file off S3.
1. When reading the schema, fetching Parquet metadata from a part-file rather than the `_metadata` file
The `_metadata` file contains metadata of all row groups, and can be very large if there are many row groups. Since schema information and row group metadata are coupled within a single Thrift object, we have to read the whole `_metadata` to fetch the schema. On the other hand, schema is replicated among footers of all part-files, which are fairly small.
1. Only add the root directory of the Parquet file rather than all the part-files to input paths
HDFS API can automatically filter out all hidden files and underscore files (`_SUCCESS` & `_metadata`), there's no need to filter out all part-files and add them individually to input paths. What make it much worse is that, `FileInputFormat.listStatus()` calls `FileSystem.globStatus()` on each individual input path sequentially, each results a blocking remote S3 HTTP request.
1. Worked around [PARQUET-16](https://issues.apache.org/jira/browse/PARQUET-16)
Essentially PARQUET-16 is similar to the above issue, and results lots of sequential `FileSystem.getFileStatus()` calls, which are further translated into a bunch of remote S3 HTTP requests.
`FilteringParquetRowInputFormat` should be cleaned up once PARQUET-16 is fixed.
Below is the micro benchmark result. The dataset used is a S3 Parquet file consists of 3,793 partitions, about 110MB per partition in average. The benchmark is done with a 9-node AWS cluster.
- Creating a Parquet `SchemaRDD` (Parquet schema is fetched)
```scala
val tweets = parquetFile(uri)
```
- Before: 17.80s
- After: 8.61s
- Fetching partition information
```scala
tweets.getPartitions
```
- Before: 700.87s
- After: 21.47s
- Counting the whole file (both steps above are executed altogether)
```scala
parquetFile(uri).count()
```
- Before: ??? (haven't test yet)
- After: 53.26s
Author: Cheng Lian <lian.cs.zju@gmail.com>
Closes#1370 from liancheng/faster-parquet and squashes the following commits:
94a2821 [Cheng Lian] Added comments about schema consistency
d2c4417 [Cheng Lian] Worked around PARQUET-16 to improve Parquet performance
1c0d1b9 [Cheng Lian] Accelerated Parquet schema retrieving
5bd3d29 [Cheng Lian] Fixed Parquet log level
Author: Aaron Staple <aaron.staple@gmail.com>
Closes#1421 from staple/SPARK-2314 and squashes the following commits:
73e04dc [Aaron Staple] [SPARK-2314] Override collect and take in JavaSchemaRDD, forwarding to SchemaRDD implementations.
Author: Michael Armbrust <michael@databricks.com>
Closes#1414 from marmbrus/exprIdResolution and squashes the following commits:
97b47bc [Michael Armbrust] Attribute equality comparisons should be done by exprId.
Note that this commit changes the semantics when loading in data that was created with prior versions of Spark SQL. Before, we were writing out strings as Binary data without adding any other annotations. Thus, when data is read in from prior versions, data that was StringType will now become BinaryType. Users that need strings can CAST that column to a String. It was decided that while this breaks compatibility, it does make us compatible with other systems (Hive, Thrift, etc) and adds support for Binary data, so this is the right decision long term.
To support `BinaryType`, the following changes are needed:
- Make `StringType` use `OriginalType.UTF8`
- Add `BinaryType` using `PrimitiveTypeName.BINARY` without `OriginalType`
Author: Takuya UESHIN <ueshin@happy-camper.st>
Closes#1373 from ueshin/issues/SPARK-2446 and squashes the following commits:
ecacb92 [Takuya UESHIN] Add BinaryType support to Parquet I/O.
616e04a [Takuya UESHIN] Make StringType use OriginalType.UTF8.
Reuse byte buffers when creating unique attributes for multiple instances of an InMemoryRelation in a single query plan.
Author: Michael Armbrust <michael@databricks.com>
Closes#1332 from marmbrus/doubleCache and squashes the following commits:
4a19609 [Michael Armbrust] Clean up concurrency story by calculating buffersn the constructor.
b39c931 [Michael Armbrust] Allocations are kind of a side effect.
f67eff7 [Michael Armbrust] Reusue same byte buffers when creating new instance of InMemoryRelation
Author: Michael Armbrust <michael@databricks.com>
Closes#1366 from marmbrus/partialDistinct and squashes the following commits:
12a31ab [Michael Armbrust] Add more efficient distinct operator.
Author: Takuya UESHIN <ueshin@happy-camper.st>
Closes#1355 from ueshin/issues/SPARK-2428 and squashes the following commits:
b6fa264 [Takuya UESHIN] Add except and intersect methods to SchemaRDD.
`RowWriteSupport` doesn't write empty `ArrayType` value, so the read value becomes `null`.
It should write empty `ArrayType` value as it is.
Author: Takuya UESHIN <ueshin@happy-camper.st>
Closes#1339 from ueshin/issues/SPARK-2415 and squashes the following commits:
32afc87 [Takuya UESHIN] Merge branch 'master' into issues/SPARK-2415
2f05196 [Takuya UESHIN] Fix RowWriteSupport to handle empty ArrayType correctly.
Patch introduces the new way of working also retaining the existing ways of doing things.
For example build instruction for yarn in maven is
`mvn -Pyarn -PHadoop2.2 clean package -DskipTests`
in sbt it can become
`MAVEN_PROFILES="yarn, hadoop-2.2" sbt/sbt clean assembly`
Also supports
`sbt/sbt -Pyarn -Phadoop-2.2 -Dhadoop.version=2.2.0 clean assembly`
Author: Prashant Sharma <prashant.s@imaginea.com>
Author: Patrick Wendell <pwendell@gmail.com>
Closes#772 from ScrapCodes/sbt-maven and squashes the following commits:
a8ac951 [Prashant Sharma] Updated sbt version.
62b09bb [Prashant Sharma] Improvements.
fa6221d [Prashant Sharma] Excluding sql from mima
4b8875e [Prashant Sharma] Sbt assembly no longer builds tools by default.
72651ca [Prashant Sharma] Addresses code reivew comments.
acab73d [Prashant Sharma] Revert "Small fix to run-examples script."
ac4312c [Prashant Sharma] Revert "minor fix"
6af91ac [Prashant Sharma] Ported oldDeps back. + fixes issues with prev commit.
65cf06c [Prashant Sharma] Servelet API jars mess up with the other servlet jars on the class path.
446768e [Prashant Sharma] minor fix
89b9777 [Prashant Sharma] Merge conflicts
d0a02f2 [Prashant Sharma] Bumped up pom versions, Since the build now depends on pom it is better updated there. + general cleanups.
dccc8ac [Prashant Sharma] updated mima to check against 1.0
a49c61b [Prashant Sharma] Fix for tools jar
a2f5ae1 [Prashant Sharma] Fixes a bug in dependencies.
cf88758 [Prashant Sharma] cleanup
9439ea3 [Prashant Sharma] Small fix to run-examples script.
96cea1f [Prashant Sharma] SPARK-1776 Have Spark's SBT build read dependencies from Maven.
36efa62 [Patrick Wendell] Set project name in pom files and added eclipse/intellij plugins.
4973dbd [Patrick Wendell] Example build using pom reader.
Author: Reynold Xin <rxin@apache.org>
Closes#1334 from rxin/sqlConfThreadSafetuy and squashes the following commits:
c1e0a5a [Reynold Xin] Fixed the duplicate comment.
7614372 [Reynold Xin] [SPARK-2409] Make SQLConf thread safe.
Using Spark's take can result in an entire in-memory partition to be shipped in order to retrieve a single row.
Author: Michael Armbrust <michael@databricks.com>
Closes#1318 from marmbrus/takeLimit and squashes the following commits:
77289a5 [Michael Armbrust] Update scala doc
32f0674 [Michael Armbrust] Custom take implementation for LIMIT queries.
Author: witgo <witgo@qq.com>
Closes#1153 from witgo/expectResult and squashes the following commits:
97541d8 [witgo] merge master
ead26e7 [witgo] Resolve sbt warnings during build
Hi all,
I want to submit a basic operator Intersect
For example , in sql case
select * from table1
intersect
select * from table2
So ,i want use this operator support this function in Spark SQL
This operator will return the the intersection of SparkPlan child table RDD .
JIRA:https://issues.apache.org/jira/browse/SPARK-2235
Author: Yanjie Gao <gaoyanjie55@163.com>
Author: YanjieGao <396154235@qq.com>
Closes#1150 from YanjieGao/patch-5 and squashes the following commits:
4629afe [YanjieGao] reformat the code
bdc2ac0 [YanjieGao] reformat the code as Michael's suggestion
3b29ad6 [YanjieGao] Merge remote branch 'upstream/master' into patch-5
1cfbfe6 [YanjieGao] refomat some files
ea78f33 [YanjieGao] resolve conflict and add annotation on basicOperator and remove HiveQl
0c7cca5 [YanjieGao] modify format problem
a802ca8 [YanjieGao] Merge remote branch 'upstream/master' into patch-5
5e374c7 [YanjieGao] resolve conflict in SparkStrategies and basicOperator
f7961f6 [Yanjie Gao] update the line less than
bdc4a05 [Yanjie Gao] Update basicOperators.scala
0b49837 [Yanjie Gao] delete the annotation
f1288b4 [Yanjie Gao] delete annotation
e2b64be [Yanjie Gao] Update basicOperators.scala
4dd453e [Yanjie Gao] Update SQLQuerySuite.scala
790765d [Yanjie Gao] Update SparkStrategies.scala
ac73e60 [Yanjie Gao] Update basicOperators.scala
d4ac5e5 [Yanjie Gao] Update HiveQl.scala
61e88e7 [Yanjie Gao] Update SqlParser.scala
469f099 [Yanjie Gao] Update basicOperators.scala
e5bff61 [Yanjie Gao] Spark SQL basicOperator add Intersect operator
For example, for
```
{"array": [{"field":214748364700}, {"field":1}]}
```
the type of field is resolved as IntType. While, for
```
{"array": [{"field":1}, {"field":214748364700}]}
```
the type of field is resolved as LongType.
JIRA: https://issues.apache.org/jira/browse/SPARK-2375
Author: Yin Huai <huaiyin.thu@gmail.com>
Closes#1308 from yhuai/SPARK-2375 and squashes the following commits:
3e2e312 [Yin Huai] Update unit test.
1b2ff9f [Yin Huai] Merge remote-tracking branch 'upstream/master' into SPARK-2375
10794eb [Yin Huai] Correctly resolve the type of a field inside an array of structs.
When execute `saveAsParquetFile` with non-primitive type, `RowWriteSupport` uses wrong type `Int` for `ByteType` and `ShortType`.
Author: Takuya UESHIN <ueshin@happy-camper.st>
Closes#1315 from ueshin/issues/SPARK-2386 and squashes the following commits:
20d89ec [Takuya UESHIN] Use None instead of null.
bd88741 [Takuya UESHIN] Add a test.
323d1d2 [Takuya UESHIN] Modify RowWriteSupport to use the exact types to cast.
Reported by http://apache-spark-user-list.1001560.n3.nabble.com/Spark-SQL-Join-throws-exception-td8599.html
After we get the table from the catalog, because the table has an alias, we will temporarily insert a Subquery. Then, we convert the table alias to lower case no matter if the parser is case sensitive or not.
To see the issue ...
```
val sqlContext = new org.apache.spark.sql.SQLContext(sc)
import sqlContext.createSchemaRDD
case class Person(name: String, age: Int)
val people = sc.textFile("examples/src/main/resources/people.txt").map(_.split(",")).map(p => Person(p(0), p(1).trim.toInt))
people.registerAsTable("people")
sqlContext.sql("select PEOPLE.name from people PEOPLE")
```
The plan is ...
```
== Query Plan ==
Project ['PEOPLE.name]
ExistingRdd [name#0,age#1], MapPartitionsRDD[4] at mapPartitions at basicOperators.scala:176
```
You can find that `PEOPLE.name` is not resolved.
This PR introduces three changes.
1. If a table has an alias, the catalog will not lowercase the alias. If a lowercase alias is needed, the analyzer will do the work.
2. A catalog has a new val caseSensitive that indicates if this catalog is case sensitive or not. For example, a SimpleCatalog is case sensitive, but
3. Corresponding unit tests.
With this PR, case sensitivity of database names and table names is handled by the catalog. Case sensitivity of other identifiers are handled by the analyzer.
JIRA: https://issues.apache.org/jira/browse/SPARK-2339
Author: Yin Huai <huai@cse.ohio-state.edu>
Closes#1317 from yhuai/SPARK-2339 and squashes the following commits:
12d8006 [Yin Huai] Handling case sensitivity correctly. This patch introduces three changes. 1. If a table has an alias, the catalog will not lowercase the alias. If a lowercase alias is needed, the analyzer will do the work. 2. A catalog has a new val caseSensitive that indicates if this catalog is case sensitive or not. For example, a SimpleCatalog is case sensitive, but 3. Corresponding unit tests. With this patch, case sensitivity of database names and table names is handled by the catalog. Case sensitivity of other identifiers is handled by the analyzer.
Fix nullabilities of `Join`/`Generate`/`Aggregate` because:
- Output attributes of opposite side of `OuterJoin` should be nullable.
- Output attributes of generater side of `Generate` should be nullable if `join` is `true` and `outer` is `true`.
- `AttributeReference` of `computedAggregates` of `Aggregate` should be the same as `aggregateExpression`'s.
Author: Takuya UESHIN <ueshin@happy-camper.st>
Closes#1266 from ueshin/issues/SPARK-2327 and squashes the following commits:
3ace83a [Takuya UESHIN] Add withNullability to Attribute and use it to change nullabilities.
df1ae53 [Takuya UESHIN] Modify nullabilize to leave attribute if not resolved.
799ce56 [Takuya UESHIN] Add nullabilization to Generate of SparkPlan.
a0fc9bc [Takuya UESHIN] Fix scalastyle errors.
0e31e37 [Takuya UESHIN] Fix Aggregate resultAttribute nullabilities.
09532ec [Takuya UESHIN] Fix Generate output nullabilities.
f20f196 [Takuya UESHIN] Fix Join output nullabilities.
This is a fix for the problem revealed by PR #1265.
Currently `HiveComparisonSuite` ignores output of `ExplainCommand` since Catalyst query plan is quite different from Hive query plan. But exceptions throw from `CheckResolution` still breaks test cases. This PR catches any `TreeNodeException` and reports it as part of the query explanation.
After merging this PR, PR #1265 can also be merged safely.
For a normal query:
```
scala> hql("explain select key from src").foreach(println)
...
[Physical execution plan:]
[HiveTableScan [key#9], (MetastoreRelation default, src, None), None]
```
For a wrong query with unresolved attribute(s):
```
scala> hql("explain select kay from src").foreach(println)
...
[Error occurred during query planning: ]
[Unresolved attributes: 'kay, tree:]
[Project ['kay]]
[ LowerCaseSchema ]
[ MetastoreRelation default, src, None]
```
Author: Cheng Lian <lian.cs.zju@gmail.com>
Closes#1294 from liancheng/safe-explain and squashes the following commits:
4318911 [Cheng Lian] Don't throw TreeNodeException in `execution.ExplainCommand`
**Description** This patch enables using the `.select()` function in SchemaRDD with functions such as `Sum`, `Count` and other.
**Testing** Unit tests added.
Author: Ximo Guanter Gonzalbez <ximo@tid.es>
Closes#1211 from edrevo/add-expression-support-in-select and squashes the following commits:
fe4a1e1 [Ximo Guanter Gonzalbez] Extend SQL DSL to functions
e1d344a [Ximo Guanter Gonzalbez] SPARK-2186: Spark SQL DSL support for simple aggregations such as SUM and AVG
Extract the join keys from equality conditions, that can be evaluated using equi-join.
Author: Cheng Hao <hao.cheng@intel.com>
Closes#1190 from chenghao-intel/extract_join_keys and squashes the following commits:
4a1060a [Cheng Hao] Fix some of the small issues
ceb4924 [Cheng Hao] Remove the redundant pattern of join keys extraction
cec34e8 [Cheng Hao] Update the code style issues
dcc4584 [Cheng Hao] Extract the joinkeys from join condition
Author: Takuya UESHIN <ueshin@happy-camper.st>
Closes#1235 from ueshin/issues/SPARK-2295 and squashes the following commits:
201c508 [Takuya UESHIN] Make JavaBeans nullability stricter.
This PR is based off Michael's [PR 734](https://github.com/apache/spark/pull/734) and includes a bunch of cleanups.
Moreover, this PR also
- makes `SparkLogicalPlan` take a `tableName: String`, which facilitates testing.
- moves join-related tests to a single file.
Author: Zongheng Yang <zongheng.y@gmail.com>
Author: Michael Armbrust <michael@databricks.com>
Closes#1163 from concretevitamin/auto-broadcast-hash-join and squashes the following commits:
d0f4991 [Zongheng Yang] Fix bug in broadcast hash join & add test to cover it.
af080d7 [Zongheng Yang] Fix in joinIterators()'s next().
440d277 [Zongheng Yang] Fixes to imports; add back requiredChildDistribution (lost when merging)
208d5f6 [Zongheng Yang] Make LeftSemiJoinHash mix in HashJoin.
ad6c7cc [Zongheng Yang] Minor cleanups.
814b3bf [Zongheng Yang] Merge branch 'master' into auto-broadcast-hash-join
a8a093e [Zongheng Yang] Minor cleanups.
6fd8443 [Zongheng Yang] Cut down size estimation related stuff.
a4267be [Zongheng Yang] Add test for broadcast hash join and related necessary refactorings:
0e64b08 [Zongheng Yang] Scalastyle fix.
91461c2 [Zongheng Yang] Merge branch 'master' into auto-broadcast-hash-join
7c7158b [Zongheng Yang] Prototype of auto conversion to broadcast hash join.
0ad122f [Zongheng Yang] Merge branch 'master' into auto-broadcast-hash-join
3e5d77c [Zongheng Yang] WIP: giant and messy WIP.
a92ed0c [Michael Armbrust] Formatting.
76ca434 [Michael Armbrust] A simple strategy that broadcasts tables only when they are found in a configuration hint.
cf6b381 [Michael Armbrust] Split out generic logic for hash joins and create two concrete physical operators: BroadcastHashJoin and ShuffledHashJoin.
a8420ca [Michael Armbrust] Copy records in executeCollect to avoid issues with mutable rows.
Author: Michael Armbrust <michael@databricks.com>
Closes#1201 from marmbrus/fixCacheTests and squashes the following commits:
9d87ed1 [Michael Armbrust] Use analyzer (which runs to fixed point) instead of manually removing analysis operators.
This PR is a sub-task of SPARK-2044 to move the execution of aggregation into shuffle implementations.
I leave `CoGoupedRDD` and `SubtractedRDD` unchanged because they have their implementations of aggregation. I'm not sure is it suitable to change these two RDDs.
Also I do not move sort related code of `OrderedRDDFunctions` into shuffle, this will be solved in another sub-task.
Author: jerryshao <saisai.shao@intel.com>
Closes#1064 from jerryshao/SPARK-2124 and squashes the following commits:
4a05a40 [jerryshao] Modify according to comments
1f7dcc8 [jerryshao] Style changes
50a2fd6 [jerryshao] Fix test suite issue after moving aggregator to Shuffle reader and writer
1a96190 [jerryshao] Code modification related to the ShuffledRDD
308f635 [jerryshao] initial works of move combiner to ShuffleManager's reader and writer
This makes it easier to use config options in operators.
Author: Reynold Xin <rxin@apache.org>
Closes#1164 from rxin/sqlcontext and squashes the following commits:
797b2fd [Reynold Xin] Pass SQLContext instead of SparkContext into physical operators.
Due to the existence of scala.Equals, it is very error prone to name the expression Equals, especially because we use a lot of partial functions and pattern matching in the optimizer.
Note that this sits on top of #1144.
Author: Reynold Xin <rxin@apache.org>
Closes#1146 from rxin/equals and squashes the following commits:
f8583fd [Reynold Xin] Merge branch 'master' of github.com:apache/spark into equals
326b388 [Reynold Xin] Merge branch 'master' of github.com:apache/spark into equals
bd19807 [Reynold Xin] Rename EqualsTo to EqualTo.
81148d1 [Reynold Xin] [SPARK-2218] rename Equals to EqualsTo in Spark SQL expressions.
c4e543d [Reynold Xin] [SPARK-2210] boolean cast on boolean value should be removed.
It should be possible to import and export data stored in Parquet's columnar format that contains nested types. For example:
```java
message AddressBook {
required binary owner;
optional group ownerPhoneNumbers {
repeated binary array;
}
optional group contacts {
repeated group array {
required binary name;
optional binary phoneNumber;
}
}
optional group nameToApartmentNumber {
repeated group map {
required binary key;
required int32 value;
}
}
}
```
The example could model a type (AddressBook) that contains records made of strings (owner), lists (ownerPhoneNumbers) and a table of contacts (e.g., a list of pairs or a map that can contain null values but keys must not be null). The list of tasks are as follows:
<h6>Implement support for converting nested Parquet types to Spark/Catalyst types:</h6>
- [x] Structs
- [x] Lists
- [x] Maps (note: currently keys need to be Strings)
<h6>Implement import (via ``parquetFile``) of nested Parquet types (first version in this PR)</h6>
- [x] Initial version
<h6>Implement export (via ``saveAsParquetFile``)</h6>
- [x] Initial version
<h6>Test support for AvroParquet, etc.</h6>
- [x] Initial testing of import of avro-generated Parquet data (simple + nested)
Example:
```scala
val data = TestSQLContext
.parquetFile("input.dir")
.toSchemaRDD
data.registerAsTable("data")
sql("SELECT owner, contacts[1].name, nameToApartmentNumber['John'] FROM data").collect()
```
Author: Andre Schumacher <andre.schumacher@iki.fi>
Author: Michael Armbrust <michael@databricks.com>
Closes#360 from AndreSchumacher/nested_parquet and squashes the following commits:
30708c8 [Andre Schumacher] Taking out AvroParquet test for now to remove Avro dependency
95c1367 [Andre Schumacher] Changes to ParquetRelation and its metadata
7eceb67 [Andre Schumacher] Review feedback
94eea3a [Andre Schumacher] Scalastyle
403061f [Andre Schumacher] Fixing some issues with tests and schema metadata
b8a8b9a [Andre Schumacher] More fixes to short and byte conversion
63d1b57 [Andre Schumacher] Cleaning up and Scalastyle
88e6bdb [Andre Schumacher] Attempting to fix loss of schema
37e0a0a [Andre Schumacher] Cleaning up
14c3fd8 [Andre Schumacher] Attempting to fix Spark-Parquet schema conversion
3e1456c [Michael Armbrust] WIP: Directly serialize catalyst attributes.
f7aeba3 [Michael Armbrust] [SPARK-1982] Support for ByteType and ShortType.
3104886 [Michael Armbrust] Nested Rows should be Rows, not Seqs.
3c6b25f [Andre Schumacher] Trying to reduce no-op changes wrt master
31465d6 [Andre Schumacher] Scalastyle: fixing commented out bottom
de02538 [Andre Schumacher] Cleaning up ParquetTestData
2f5a805 [Andre Schumacher] Removing stripMargin from test schemas
191bc0d [Andre Schumacher] Changing to Seq for ArrayType, refactoring SQLParser for nested field extension
cbb5793 [Andre Schumacher] Code review feedback
32229c7 [Andre Schumacher] Removing Row nested values and placing by generic types
0ae9376 [Andre Schumacher] Doc strings and simplifying ParquetConverter.scala
a6b4f05 [Andre Schumacher] Cleaning up ArrayConverter, moving classTag to NativeType, adding NativeRow
431f00f [Andre Schumacher] Fixing problems introduced during rebase
c52ff2c [Andre Schumacher] Adding native-array converter
619c397 [Andre Schumacher] Completing Map testcase
79d81d5 [Andre Schumacher] Replacing field names for array and map in WriteSupport
f466ff0 [Andre Schumacher] Added ParquetAvro tests and revised Array conversion
adc1258 [Andre Schumacher] Optimizing imports
e99cc51 [Andre Schumacher] Fixing nested WriteSupport and adding tests
1dc5ac9 [Andre Schumacher] First version of WriteSupport for nested types
d1911dc [Andre Schumacher] Simplifying ArrayType conversion
f777b4b [Andre Schumacher] Scalastyle
824500c [Andre Schumacher] Adding attribute resolution for MapType
b539fde [Andre Schumacher] First commit for MapType
a594aed [Andre Schumacher] Scalastyle
4e25fcb [Andre Schumacher] Adding resolution of complex ArrayTypes
f8f8911 [Andre Schumacher] For primitive rows fall back to more efficient converter, code reorg
6dbc9b7 [Andre Schumacher] Fixing some problems intruduced during rebase
b7fcc35 [Andre Schumacher] Documenting conversions, bugfix, wrappers of Rows
ee70125 [Andre Schumacher] fixing one problem with arrayconverter
98219cf [Andre Schumacher] added struct converter
5d80461 [Andre Schumacher] fixing one problem with nested structs and breaking up files
1b1b3d6 [Andre Schumacher] Fixing one problem with nested arrays
ddb40d2 [Andre Schumacher] Extending tests for nested Parquet data
745a42b [Andre Schumacher] Completing testcase for nested data (Addressbook(
6125c75 [Andre Schumacher] First working nested Parquet record input
4d4892a [Andre Schumacher] First commit nested Parquet read converters
aa688fe [Andre Schumacher] Adding conversion of nested Parquet schemas
```
scala> hql("describe src").collect().foreach(println)
[key string None ]
[value string None ]
```
The result should contain 3 columns instead of one. This screws up JDBC or even the downstream consumer of the Scala/Java/Python APIs.
I am providing a workaround. We handle a subset of describe commands in Spark SQL, which are defined by ...
```
DESCRIBE [EXTENDED] [db_name.]table_name
```
All other cases are treated as Hive native commands.
Also, if we upgrade Hive to 0.13, we need to check the results of context.sessionState.isHiveServerQuery() to determine how to split the result. This method is introduced by https://issues.apache.org/jira/browse/HIVE-4545. We may want to set Hive to use JsonMetaDataFormatter for the output of a DDL statement (`set hive.ddl.output.format=json` introduced by https://issues.apache.org/jira/browse/HIVE-2822).
The link to JIRA: https://issues.apache.org/jira/browse/SPARK-2177
Author: Yin Huai <huai@cse.ohio-state.edu>
Closes#1118 from yhuai/SPARK-2177 and squashes the following commits:
fd2534c [Yin Huai] Merge remote-tracking branch 'upstream/master' into SPARK-2177
b9b9aa5 [Yin Huai] rxin's comments.
e7c4e72 [Yin Huai] Fix unit test.
656b068 [Yin Huai] 100 characters.
6387217 [Yin Huai] Merge remote-tracking branch 'upstream/master' into SPARK-2177
8003cf3 [Yin Huai] Generate strings with the format like Hive for unit tests.
9787fff [Yin Huai] Merge remote-tracking branch 'upstream/master' into SPARK-2177
440c5af [Yin Huai] rxin's comments.
f1a417e [Yin Huai] Update doc.
83adb2f [Yin Huai] Merge remote-tracking branch 'upstream/master' into SPARK-2177
366f891 [Yin Huai] Add describe command.
74bd1d4 [Yin Huai] Merge remote-tracking branch 'upstream/master' into SPARK-2177
342fdf7 [Yin Huai] Split to up to 3 parts.
725e88c [Yin Huai] Merge remote-tracking branch 'upstream/master' into SPARK-2177
bb8bbef [Yin Huai] Split every string in the result of a describe command.
Author: Reynold Xin <rxin@apache.org>
Closes#1139 from rxin/sparksqldoc and squashes the following commits:
c3049d8 [Reynold Xin] Fixed line length.
66dc72c [Reynold Xin] A few minor Spark SQL Scaladoc fixes.
@yhuai @marmbrus @concretevitamin
Author: Reynold Xin <rxin@apache.org>
Closes#1123 from rxin/explain and squashes the following commits:
def83b0 [Reynold Xin] Update unit tests for explain.
a9d3ba8 [Reynold Xin] [SPARK-2187] Explain should not run the optimizer twice.
...redPartitioning.
Author: Michael Armbrust <michael@databricks.com>
Closes#1122 from marmbrus/fixAddExchange and squashes the following commits:
3417537 [Michael Armbrust] Don't bind partitioning expressions as that breaks comparison with requiredPartitioning.
```
hql("explain select * from src group by key").collect().foreach(println)
[ExplainCommand [plan#27:0]]
[ Aggregate false, [key#25], [key#25,value#26]]
[ Exchange (HashPartitioning [key#25:0], 200)]
[ Exchange (HashPartitioning [key#25:0], 200)]
[ Aggregate true, [key#25], [key#25]]
[ HiveTableScan [key#25,value#26], (MetastoreRelation default, src, None), None]
```
There are two exchange operators.
However, if we do not use explain...
```
hql("select * from src group by key")
res4: org.apache.spark.sql.SchemaRDD =
SchemaRDD[8] at RDD at SchemaRDD.scala:100
== Query Plan ==
Aggregate false, [key#8], [key#8,value#9]
Exchange (HashPartitioning [key#8:0], 200)
Aggregate true, [key#8], [key#8]
HiveTableScan [key#8,value#9], (MetastoreRelation default, src, None), None
```
The plan is fine.
The cause of this bug is explained below.
When we create an `execution.ExplainCommand`, we use the `executedPlan` as the child of this `ExplainCommand`. But, this `executedPlan` is prepared for execution again when we generate the `executedPlan` for the `ExplainCommand`. Basically, `prepareForExecution` is called twice on a physical plan. Because after `prepareForExecution` we have already bounded those references (in `BoundReference`s), `AddExchange` cannot figure out we are using the same partitioning (we use `AttributeReference`s to create an `ExchangeOperator` and then those references will be changed to `BoundReference`s after `prepareForExecution` is called). So, an extra `ExchangeOperator` is inserted.
I think in `CommandStrategy`, we should just use the `sparkPlan` (`sparkPlan` is the input of `prepareForExecution`) to initialize the `ExplainCommand` instead of using `executedPlan`.
The link to JIRA: https://issues.apache.org/jira/browse/SPARK-2176
Author: Yin Huai <huai@cse.ohio-state.edu>
Closes#1116 from yhuai/SPARK-2176 and squashes the following commits:
197c19c [Yin Huai] Use sparkPlan to initialize a Physical Explain Command instead of using executedPlan.
JIRA: https://issues.apache.org/jira/browse/SPARK-2060
Programming guide: http://yhuai.github.io/site/sql-programming-guide.html
Scala doc of SQLContext: http://yhuai.github.io/site/api/scala/index.html#org.apache.spark.sql.SQLContext
Author: Yin Huai <huai@cse.ohio-state.edu>
Closes#999 from yhuai/newJson and squashes the following commits:
227e89e [Yin Huai] Merge remote-tracking branch 'upstream/master' into newJson
ce8eedd [Yin Huai] rxin's comments.
bc9ac51 [Yin Huai] Merge remote-tracking branch 'upstream/master' into newJson
94ffdaa [Yin Huai] Remove "get" from method names.
ce31c81 [Yin Huai] Merge remote-tracking branch 'upstream/master' into newJson
e2773a6 [Yin Huai] Merge remote-tracking branch 'upstream/master' into newJson
79ea9ba [Yin Huai] Fix typos.
5428451 [Yin Huai] Newline
1f908ce [Yin Huai] Remove extra line.
d7a005c [Yin Huai] Merge remote-tracking branch 'upstream/master' into newJson
7ea750e [Yin Huai] marmbrus's comments.
6a5f5ef [Yin Huai] Merge remote-tracking branch 'upstream/master' into newJson
83013fb [Yin Huai] Update Java Example.
e7a6c19 [Yin Huai] SchemaRDD.javaToPython should convert a field with the StructType to a Map.
6d20b85 [Yin Huai] Merge remote-tracking branch 'upstream/master' into newJson
4fbddf0 [Yin Huai] Programming guide.
9df8c5a [Yin Huai] Python API.
7027634 [Yin Huai] Java API.
cff84cc [Yin Huai] Use a SchemaRDD for a JSON dataset.
d0bd412 [Yin Huai] Merge remote-tracking branch 'upstream/master' into newJson
ab810b0 [Yin Huai] Make JsonRDD private.
6df0891 [Yin Huai] Apache header.
8347f2e [Yin Huai] Merge remote-tracking branch 'upstream/master' into newJson
66f9e76 [Yin Huai] Update docs and use the entire dataset to infer the schema.
8ffed79 [Yin Huai] Update the example.
a5a4b52 [Yin Huai] Merge remote-tracking branch 'upstream/master' into newJson
4325475 [Yin Huai] If a sampled dataset is used for schema inferring, update the schema of the JsonTable after first execution.
65b87f0 [Yin Huai] Fix sampling...
8846af5 [Yin Huai] API doc.
52a2275 [Yin Huai] Merge remote-tracking branch 'upstream/master' into newJson
0387523 [Yin Huai] Address PR comments.
666b957 [Yin Huai] Merge remote-tracking branch 'upstream/master' into newJson
a2313a6 [Yin Huai] Address PR comments.
f3ce176 [Yin Huai] After type conflict resolution, if a NullType is found, StringType is used.
0576406 [Yin Huai] Add Apache license header.
af91b23 [Yin Huai] Merge remote-tracking branch 'upstream/master' into newJson
f45583b [Yin Huai] Infer the schema of a JSON dataset (a text file with one JSON object per line or a RDD[String] with one JSON object per string) and returns a SchemaRDD.
f31065f [Yin Huai] A query plan or a SchemaRDD can print out its schema.
Fixed the broken JDBC output. Test from Shark `beeline`:
```
beeline> !connect jdbc:hive2://localhost:10000/
scan complete in 2ms
Connecting to jdbc:hive2://localhost:10000/
Enter username for jdbc:hive2://localhost:10000/: lian
Enter password for jdbc:hive2://localhost:10000/:
Connected to: Hive (version 0.12.0)
Driver: Hive (version 0.12.0)
Transaction isolation: TRANSACTION_REPEATABLE_READ
0: jdbc:hive2://localhost:10000/>
0: jdbc:hive2://localhost:10000/> explain select * from src;
+-------------------------------------------------------------------------------+
| plan |
+-------------------------------------------------------------------------------+
| ExplainCommand [plan#2:0] |
| HiveTableScan [key#0,value#1], (MetastoreRelation default, src, None), None |
+-------------------------------------------------------------------------------+
2 rows selected (1.386 seconds)
```
Before this change, the output looked something like this:
```
+-------------------------------------------------------------------------------+
| plan |
+-------------------------------------------------------------------------------+
| ExplainCommand [plan#2:0]
HiveTableScan [key#0,value#1], (MetastoreRelation default, src, None), None |
+-------------------------------------------------------------------------------+
```
Author: Cheng Lian <lian.cs.zju@gmail.com>
Closes#1097 from liancheng/multiLineExplain and squashes the following commits:
eb37967 [Cheng Lian] Made output of "EXPLAIN" play well with JDBC output format
Updated `JavaSQLContext` and `JavaHiveContext` similar to what we've done to `SQLContext` and `HiveContext` in PR #1071. Added corresponding test case for Spark SQL Java API.
Author: Cheng Lian <lian.cs.zju@gmail.com>
Closes#1085 from liancheng/spark-2094-java and squashes the following commits:
29b8a51 [Cheng Lian] Avoided instantiating JavaSparkContext & JavaHiveContext to workaround test failure
92bb4fb [Cheng Lian] Marked test cases in JavaHiveQLSuite with "ignore"
22aec97 [Cheng Lian] Follow up of PR #1071 for Java API
Added batching with default batch size 10 in SchemaRDD.javaToPython
Author: Kan Zhang <kzhang@apache.org>
Closes#1023 from kanzhang/SPARK-2079 and squashes the following commits:
2d1915e [Kan Zhang] [SPARK-2079] Add batching in SchemaRDD.javaToPython
19b0c09 [Kan Zhang] [SPARK-2079] Removing unnecessary wrapping in SchemaRDD.javaToPython
## Related JIRA issues
- Main issue:
- [SPARK-2094](https://issues.apache.org/jira/browse/SPARK-2094): Ensure exactly once semantics for DDL/Commands
- Issues resolved as dependencies:
- [SPARK-2081](https://issues.apache.org/jira/browse/SPARK-2081): Undefine output() from the abstract class Command and implement it in concrete subclasses
- [SPARK-2128](https://issues.apache.org/jira/browse/SPARK-2128): No plan for DESCRIBE
- [SPARK-1852](https://issues.apache.org/jira/browse/SPARK-1852): SparkSQL Queries with Sorts run before the user asks them to
- Other related issue:
- [SPARK-2129](https://issues.apache.org/jira/browse/SPARK-2129): NPE thrown while lookup a view
Two test cases, `join_view` and `mergejoin_mixed`, within the `HiveCompatibilitySuite` are removed from the whitelist to workaround this issue.
## PR Overview
This PR defines physical plans for DDL statements and commands and wraps their side effects in a lazy field `PhysicalCommand.sideEffectResult`, so that they are executed eagerly and exactly once. Also, as a positive side effect, now DDL statements and commands can be turned into proper `SchemaRDD`s and let user query the execution results.
This PR defines schemas for the following DDL/commands:
- EXPLAIN command
- `plan`: String, the plan explanation
- SET command
- `key`: String, the key(s) of the propert(y/ies) being set or queried
- `value`: String, the value(s) of the propert(y/ies) being queried
- Other Hive native command
- `result`: String, execution result returned by Hive
**NOTE**: We should refine schemas for different native commands by defining physical plans for them in the future.
## Examples
### EXPLAIN command
Take the "EXPLAIN" command as an example, we first execute the command and obtain a `SchemaRDD` at the same time, then query the `plan` field with the schema DSL:
```
scala> loadTestTable("src")
...
scala> val q0 = hql("EXPLAIN SELECT key, COUNT(*) FROM src GROUP BY key")
...
q0: org.apache.spark.sql.SchemaRDD =
SchemaRDD[0] at RDD at SchemaRDD.scala:98
== Query Plan ==
ExplainCommandPhysical [plan#11:0]
Aggregate false, [key#4], [key#4,SUM(PartialCount#6L) AS c_1#2L]
Exchange (HashPartitioning [key#4:0], 200)
Exchange (HashPartitioning [key#4:0], 200)
Aggregate true, [key#4], [key#4,COUNT(1) AS PartialCount#6L]
HiveTableScan [key#4], (MetastoreRelation default, src, None), None
scala> q0.select('plan).collect()
...
[ExplainCommandPhysical [plan#24:0]
Aggregate false, [key#17], [key#17,SUM(PartialCount#19L) AS c_1#2L]
Exchange (HashPartitioning [key#17:0], 200)
Exchange (HashPartitioning [key#17:0], 200)
Aggregate true, [key#17], [key#17,COUNT(1) AS PartialCount#19L]
HiveTableScan [key#17], (MetastoreRelation default, src, None), None]
scala>
```
### SET command
In this example we query all the properties set in `SQLConf`, register the result as a table, and then query the table with HiveQL:
```
scala> val q1 = hql("SET")
...
q1: org.apache.spark.sql.SchemaRDD =
SchemaRDD[7] at RDD at SchemaRDD.scala:98
== Query Plan ==
<SET command: executed by Hive, and noted by SQLContext>
scala> q1.registerAsTable("properties")
scala> hql("SELECT key, value FROM properties ORDER BY key LIMIT 10").foreach(println)
...
== Query Plan ==
TakeOrdered 10, [key#51:0 ASC]
Project [key#51:0,value#52:1]
SetCommandPhysical None, None, [key#55:0,value#56:1]), which has no missing parents
14/06/12 12:19:27 INFO scheduler.DAGScheduler: Submitting 1 missing tasks from Stage 5 (SchemaRDD[21] at RDD at SchemaRDD.scala:98
== Query Plan ==
TakeOrdered 10, [key#51:0 ASC]
Project [key#51:0,value#52:1]
SetCommandPhysical None, None, [key#55:0,value#56:1])
...
[datanucleus.autoCreateSchema,true]
[datanucleus.autoStartMechanismMode,checked]
[datanucleus.cache.level2,false]
[datanucleus.cache.level2.type,none]
[datanucleus.connectionPoolingType,BONECP]
[datanucleus.fixedDatastore,false]
[datanucleus.identifierFactory,datanucleus1]
[datanucleus.plugin.pluginRegistryBundleCheck,LOG]
[datanucleus.rdbms.useLegacyNativeValueStrategy,true]
[datanucleus.storeManagerType,rdbms]
scala>
```
### "Exactly once" semantics
At last, an example of the "exactly once" semantics:
```
scala> val q2 = hql("CREATE TABLE t1(key INT, value STRING)")
...
q2: org.apache.spark.sql.SchemaRDD =
SchemaRDD[28] at RDD at SchemaRDD.scala:98
== Query Plan ==
<Native command: executed by Hive>
scala> table("t1")
...
res9: org.apache.spark.sql.SchemaRDD =
SchemaRDD[32] at RDD at SchemaRDD.scala:98
== Query Plan ==
HiveTableScan [key#58,value#59], (MetastoreRelation default, t1, None), None
scala> q2.collect()
...
res10: Array[org.apache.spark.sql.Row] = Array([])
scala>
```
As we can see, the "CREATE TABLE" command is executed eagerly right after the `SchemaRDD` is created, and referencing the `SchemaRDD` again won't trigger a duplicated execution.
Author: Cheng Lian <lian.cs.zju@gmail.com>
Closes#1071 from liancheng/exactlyOnceCommand and squashes the following commits:
d005b03 [Cheng Lian] Made "SET key=value" returns the newly set key value pair
f6c7715 [Cheng Lian] Added test cases for DDL/command statement RDDs
1d00937 [Cheng Lian] Makes SchemaRDD DSLs work for DDL/command statement RDDs
5c7e680 [Cheng Lian] Bug fix: wrong type used in pattern matching
48aa2e5 [Cheng Lian] Refined SQLContext.emptyResult as an empty RDD[Row]
cc64f32 [Cheng Lian] Renamed physical plan classes for DDL/commands
74789c1 [Cheng Lian] Fixed failing test cases
0ad343a [Cheng Lian] Added physical plan for DDL and commands to ensure the "exactly once" semantics
Author: Michael Armbrust <michael@databricks.com>
Closes#1072 from marmbrus/cachedStars and squashes the following commits:
8757c8e [Michael Armbrust] Use planner for in-memory scans.
This has been messing up the SQL PySpark tests on Jenkins.
Author: Patrick Wendell <pwendell@gmail.com>
Closes#1054 from pwendell/pyspark and squashes the following commits:
1eb5487 [Patrick Wendell] False change
06f062d [Patrick Wendell] HOTFIX: PySpark tests should be order insensitive
Some improvement for PR #837, add another case to white list and use `filter` to build result iterator.
Author: Daoyuan <daoyuan.wang@intel.com>
Closes#1049 from adrian-wang/clean-LeftSemiJoinHash and squashes the following commits:
b314d5a [Daoyuan] change hashSet name
27579a9 [Daoyuan] add semijoin to white list and use filter to create new iterator in LeftSemiJoinBNL
Signed-off-by: Michael Armbrust <michael@databricks.com>
This PR implements `take()` on a `SchemaRDD` by inserting a logical limit that is followed by a `collect()`. This is also accompanied by adding a catalyst optimizer rule for collapsing adjacent limits. Doing so prevents an unnecessary shuffle that is sometimes triggered by `take()`.
Author: Sameer Agarwal <sameer@databricks.com>
Closes#1048 from sameeragarwal/master and squashes the following commits:
3eeb848 [Sameer Agarwal] Fixing Tests
1b76ff1 [Sameer Agarwal] Deprecating limit(limitExpr: Expression) in v1.1.0
b723ac4 [Sameer Agarwal] Added limit folding tests
a0ff7c4 [Sameer Agarwal] Adding catalyst rule to fold two consecutive limits
8d42d03 [Sameer Agarwal] Implement trigger() as limit() followed by collect()
JIRA issue: [SPARK-1968](https://issues.apache.org/jira/browse/SPARK-1968)
This PR added support for SQL/HiveQL command for caching/uncaching tables:
```
scala> sql("CACHE TABLE src")
...
res0: org.apache.spark.sql.SchemaRDD =
SchemaRDD[0] at RDD at SchemaRDD.scala:98
== Query Plan ==
CacheCommandPhysical src, true
scala> table("src")
...
res1: org.apache.spark.sql.SchemaRDD =
SchemaRDD[3] at RDD at SchemaRDD.scala:98
== Query Plan ==
InMemoryColumnarTableScan [key#0,value#1], (HiveTableScan [key#0,value#1], (MetastoreRelation default, src, None), None), false
scala> isCached("src")
res2: Boolean = true
scala> sql("CACHE TABLE src")
...
res3: org.apache.spark.sql.SchemaRDD =
SchemaRDD[4] at RDD at SchemaRDD.scala:98
== Query Plan ==
CacheCommandPhysical src, false
scala> table("src")
...
res4: org.apache.spark.sql.SchemaRDD =
SchemaRDD[11] at RDD at SchemaRDD.scala:98
== Query Plan ==
HiveTableScan [key#2,value#3], (MetastoreRelation default, src, None), None
scala> isCached("src")
res5: Boolean = false
```
Things also work for `hql`.
Author: Cheng Lian <lian.cs.zju@gmail.com>
Closes#1038 from liancheng/sqlCacheTable and squashes the following commits:
ecb7194 [Cheng Lian] Trimmed the SQL string before parsing special commands
6f4ce42 [Cheng Lian] Moved logical command classes to a separate file
3458a24 [Cheng Lian] Added comment for public API
f0ffacc [Cheng Lian] Added isCached() predicate
15ec6d2 [Cheng Lian] Added "(UN)CACHE TABLE" SQL/HiveQL statements
Thanks goes to @liancheng, who pointed out that `sql/test-only *.SQLConfSuite *.SQLQuerySuite` passed but `sql/test-only *.SQLQuerySuite *.SQLConfSuite` failed. The reason is that some tests use the same test keys and without clear()'ing, they get carried over to other tests. This hotfix simply adds some `clear()` calls.
This problem was not evident on Jenkins before probably because `parallelExecution` is not set to `false` for `sqlCoreSettings`.
Author: Zongheng Yang <zongheng.y@gmail.com>
Closes#1040 from concretevitamin/sqlconf-tests and squashes the following commits:
6d14ceb [Zongheng Yang] HOTFIX: clear() confs in SQLConf related unit tests.
By @egraldlo.
Author: egraldlo <egraldlo@gmail.com>
Author: Michael Armbrust <michael@databricks.com>
Closes#1033 from marmbrus/pr/978 and squashes the following commits:
e228c5e [Michael Armbrust] Remove "test".
762aeaf [Michael Armbrust] Remove unneeded rule. More descriptive name for test table.
d414cd7 [egraldlo] fommatting issues
1153f75 [egraldlo] do best to avoid overflowing in function avg().
This PR (1) introduces a new class SQLConf that stores key-value properties for a SQLContext (2) clean up the semantics of various forms of SET commands.
The SQLConf class unlocks user-controllable optimization opportunities; for example, user can now override the number of partitions used during an Exchange. A SQLConf can be accessed and modified programmatically through its getters and setters. It can also be modified through SET commands executed by `sql()` or `hql()`. Note that users now have the ability to change a particular property for different queries inside the same Spark job, unlike settings configured in SparkConf.
For SET commands: "SET" will return all properties currently set in a SQLConf, "SET key" will return the key-value pair (if set) or an undefined message, and "SET key=value" will call the setter on SQLConf, and if a HiveContext is used, it will be executed in Hive as well.
Author: Zongheng Yang <zongheng.y@gmail.com>
Closes#956 from concretevitamin/sqlconf and squashes the following commits:
4968c11 [Zongheng Yang] Very minor cleanup.
d74dde5 [Zongheng Yang] Remove the redundant mkQueryExecution() method.
c129b86 [Zongheng Yang] Merge remote-tracking branch 'upstream/master' into sqlconf
26c40eb [Zongheng Yang] Make SQLConf a trait and have SQLContext mix it in.
dd19666 [Zongheng Yang] Update a comment.
baa5d29 [Zongheng Yang] Remove default param for shuffle partitions accessor.
5f7e6d8 [Zongheng Yang] Add default num partitions.
22d9ed7 [Zongheng Yang] Fix output() of Set physical. Add SQLConf param accessor method.
e9856c4 [Zongheng Yang] Use java.util.Collections.synchronizedMap on a Java HashMap.
88dd0c8 [Zongheng Yang] Remove redundant SET Keyword.
271f0b1 [Zongheng Yang] Minor change.
f8983d1 [Zongheng Yang] Minor changes per review comments.
1ce8a5e [Zongheng Yang] Invoke runSqlHive() in SQLConf#get for the HiveContext case.
b766af9 [Zongheng Yang] Remove a test.
d52e1bd [Zongheng Yang] De-hardcode number of shuffle partitions for BasicOperators (read from SQLConf).
555599c [Zongheng Yang] Bullet-proof (relatively) parsing SET per review comment.
c2067e8 [Zongheng Yang] Mark SQLContext transient and put it in a second param list.
2ea8cdc [Zongheng Yang] Wrap long line.
41d7f09 [Zongheng Yang] Fix imports.
13279e6 [Zongheng Yang] Refactor the logic of eagerly processing SET commands.
b14b83e [Zongheng Yang] In a HiveContext, make SQLConf a subset of HiveConf.
6983180 [Zongheng Yang] Move a SET test to SQLQuerySuite and make it complete.
5b67985 [Zongheng Yang] New line at EOF.
c651797 [Zongheng Yang] Add commands.scala.
efd82db [Zongheng Yang] Clean up semantics of several cases of SET.
c1017c2 [Zongheng Yang] WIP in changing SetCommand to take two Options (for different semantics of SETs).
0f00d86 [Zongheng Yang] Add a test for singleton set command in SQL.
41acd75 [Zongheng Yang] Add a test for hql() in HiveQuerySuite.
2276929 [Zongheng Yang] Fix default hive result for set commands in HiveComparisonTest.
3b0c71b [Zongheng Yang] Remove Parser for set commands. A few other fixes.
d0c4578 [Zongheng Yang] Tmux typo.
0ecea46 [Zongheng Yang] Changes for HiveQl and HiveContext.
ce22d80 [Zongheng Yang] Fix parsing issues.
cb722c1 [Zongheng Yang] Finish up SQLConf patch.
4ebf362 [Zongheng Yang] First cut at SQLConf inside SQLContext.
This PR attempts to resolve [SPARK-1704](https://issues.apache.org/jira/browse/SPARK-1704) by introducing a physical plan for EXPLAIN commands, which just prints out the debug string (containing various SparkSQL's plans) of the corresponding QueryExecution for the actual query.
Author: Zongheng Yang <zongheng.y@gmail.com>
Closes#1003 from concretevitamin/explain-cmd and squashes the following commits:
5b7911f [Zongheng Yang] Add a regression test.
1bfa379 [Zongheng Yang] Modify output().
719ada9 [Zongheng Yang] Override otherCopyArgs for ExplainCommandPhysical.
4318fd7 [Zongheng Yang] Make all output one Row.
439c6ab [Zongheng Yang] Minor cleanups.
408f574 [Zongheng Yang] SPARK-1704: Add CommandStrategy and ExplainCommandPhysical.
Just submit another solution for #395
Author: Daoyuan <daoyuan.wang@intel.com>
Author: Michael Armbrust <michael@databricks.com>
Author: Daoyuan Wang <daoyuan.wang@intel.com>
Closes#837 from adrian-wang/left-semi-join-support and squashes the following commits:
d39cd12 [Daoyuan Wang] Merge pull request #1 from marmbrus/pr/837
6713c09 [Michael Armbrust] Better debugging for failed query tests.
035b73e [Michael Armbrust] Add test for left semi that can't be done with a hash join.
5ec6fa4 [Michael Armbrust] Add left semi to SQL Parser.
4c726e5 [Daoyuan] improvement according to Michael
8d4a121 [Daoyuan] add golden files for leftsemijoin
83a3c8a [Daoyuan] scala style fix
14cff80 [Daoyuan] add support for left semi join
Basically there is a race condition (possibly a scala bug?) when these values are recomputed on all of the slaves that results in an incorrect projection being generated (possibly because the GUID uniqueness contract is broken?).
In general we should probably enforce that all expression planing occurs on the driver, as is now occurring here.
Author: Michael Armbrust <michael@databricks.com>
Closes#1004 from marmbrus/fixAggBug and squashes the following commits:
e0c116c [Michael Armbrust] Compute aggregate expression during planning instead of lazily on workers.
Author: Michael Armbrust <michael@databricks.com>
Closes#985 from marmbrus/tableName and squashes the following commits:
3caaa27 [Michael Armbrust] Correctly analyze queries where columnName == tableName.
`CaseConversionExpression` should check if the evaluated value is `null`.
Author: Takuya UESHIN <ueshin@happy-camper.st>
Closes#982 from ueshin/issues/SPARK-2036 and squashes the following commits:
61e1c54 [Takuya UESHIN] Add check if the evaluated value is null.
Author: Takuya UESHIN <ueshin@happy-camper.st>
Closes#974 from ueshin/issues/SPARK-2029 and squashes the following commits:
e19e8f4 [Takuya UESHIN] Bump version number to 1.1.0-SNAPSHOT.
I don't know whether it's time to implement system function about string operation in spark sql now.
Author: egraldlo <egraldlo@gmail.com>
Closes#936 from egraldlo/stringoperator and squashes the following commits:
3c6c60a [egraldlo] Add UPPER, LOWER, MAX and MIN into hive parser
ea76d0a [egraldlo] modify the formatting issues
b49f25e [egraldlo] modify the formatting issues
1f0bbb5 [egraldlo] system function upper and lower supported
13d3267 [egraldlo] system function upper and lower supported
In cases like `Limit` and `TakeOrdered`, `executeCollect()` makes optimizations that `execute().collect()` will not.
Author: Cheng Lian <lian.cs.zju@gmail.com>
Closes#939 from liancheng/spark-1958 and squashes the following commits:
bdc4a14 [Cheng Lian] Copy rows to present immutable data to users
8250976 [Cheng Lian] Added return type explicitly for public API
192a25c [Cheng Lian] [SPARK-1958] Calling .collect() on a SchemaRDD should call executeCollect() on the underlying query plan.
JIRA issue: [SPARK-1368](https://issues.apache.org/jira/browse/SPARK-1368)
This PR introduces two major updates:
- Replaced FP style code with `while` loop and reusable `GenericMutableRow` object in critical path of `HiveTableScan`.
- Using `ColumnProjectionUtils` to help optimizing RCFile and ORC column pruning.
My quick micro benchmark suggests these two optimizations made the optimized version 2x and 2.5x faster when scanning CSV table and RCFile table respectively:
```
Original:
[info] CSV: 27676 ms, RCFile: 26415 ms
[info] CSV: 27703 ms, RCFile: 26029 ms
[info] CSV: 27511 ms, RCFile: 25962 ms
Optimized:
[info] CSV: 13820 ms, RCFile: 10402 ms
[info] CSV: 14158 ms, RCFile: 10691 ms
[info] CSV: 13606 ms, RCFile: 10346 ms
```
The micro benchmark loads a 609MB CVS file (structurally similar to the `src` test table) into a normal Hive table with `LazySimpleSerDe` and a RCFile table, then scans these tables respectively.
Preparation code:
```scala
package org.apache.spark.examples.sql.hive
import org.apache.spark.sql.hive.LocalHiveContext
import org.apache.spark.{SparkConf, SparkContext}
object HiveTableScanPrepare extends App {
val sparkContext = new SparkContext(
new SparkConf()
.setMaster("local")
.setAppName(getClass.getSimpleName.stripSuffix("$")))
val hiveContext = new LocalHiveContext(sparkContext)
import hiveContext._
hql("drop table scan_csv")
hql("drop table scan_rcfile")
hql("""create table scan_csv (key int, value string)
| row format serde 'org.apache.hadoop.hive.serde2.lazy.LazySimpleSerDe'
| with serdeproperties ('field.delim'=',')
""".stripMargin)
hql(s"""load data local inpath "${args(0)}" into table scan_csv""")
hql("""create table scan_rcfile (key int, value string)
| row format serde 'org.apache.hadoop.hive.serde2.columnar.ColumnarSerDe'
|stored as
| inputformat 'org.apache.hadoop.hive.ql.io.RCFileInputFormat'
| outputformat 'org.apache.hadoop.hive.ql.io.RCFileOutputFormat'
""".stripMargin)
hql(
"""
|from scan_csv
|insert overwrite table scan_rcfile
|select scan_csv.key, scan_csv.value
""".stripMargin)
}
```
Benchmark code:
```scala
package org.apache.spark.examples.sql.hive
import org.apache.spark.sql.hive.LocalHiveContext
import org.apache.spark.{SparkConf, SparkContext}
object HiveTableScanBenchmark extends App {
val sparkContext = new SparkContext(
new SparkConf()
.setMaster("local")
.setAppName(getClass.getSimpleName.stripSuffix("$")))
val hiveContext = new LocalHiveContext(sparkContext)
import hiveContext._
val scanCsv = hql("select key from scan_csv")
val scanRcfile = hql("select key from scan_rcfile")
val csvDuration = benchmark(scanCsv.count())
val rcfileDuration = benchmark(scanRcfile.count())
println(s"CSV: $csvDuration ms, RCFile: $rcfileDuration ms")
def benchmark(f: => Unit) = {
val begin = System.currentTimeMillis()
f
val end = System.currentTimeMillis()
end - begin
}
}
```
@marmbrus Please help review, thanks!
Author: Cheng Lian <lian.cs.zju@gmail.com>
Closes#758 from liancheng/fastHiveTableScan and squashes the following commits:
4241a19 [Cheng Lian] Distinguishes sorted and possibly not sorted operations more accurately in HiveComparisonTest
cf640d8 [Cheng Lian] More HiveTableScan optimisations:
bf0e7dc [Cheng Lian] Added SortedOperation pattern to match *some* definitely sorted operations and avoid some sorting cost in HiveComparisonTest.
6d1c642 [Cheng Lian] Using ColumnProjectionUtils to optimise RCFile and ORC column pruning
eb62fd3 [Cheng Lian] [SPARK-1368] Optimized HiveTableScan
Average values are difference between the calculation is done partially or not partially.
Because `AverageFunction` (in not-partially calculation) counts even if the evaluated value is null.
Author: Takuya UESHIN <ueshin@happy-camper.st>
Closes#862 from ueshin/issues/SPARK-1915 and squashes the following commits:
b1ff3c0 [Takuya UESHIN] Modify AverageFunction not to count if the evaluated value is null.
`CountFunction` should count up only if the child's evaluated value is not null.
Because it traverses to evaluate all child expressions, even if the child is null, it counts up if one of the all children is not null.
Author: Takuya UESHIN <ueshin@happy-camper.st>
Closes#861 from ueshin/issues/SPARK-1914 and squashes the following commits:
3b37315 [Takuya UESHIN] Merge branch 'master' into issues/SPARK-1914
2afa238 [Takuya UESHIN] Simplify CountFunction not to traverse to evaluate all child expressions.
```scala
rdd.aggregate(Sum('val))
```
is just shorthand for
```scala
rdd.groupBy()(Sum('val))
```
but seems be more natural than doing a groupBy with no grouping expressions when you really just want an aggregation over all rows.
Did not add a JavaSchemaRDD or Python API, as these seem to be lacking several other methods like groupBy() already -- leaving that cleanup for future patches.
Author: Aaron Davidson <aaron@databricks.com>
Closes#874 from aarondav/schemardd and squashes the following commits:
e9e68ee [Aaron Davidson] Add comment
db6afe2 [Aaron Davidson] Introduce SchemaRDD#aggregate() for simple aggregations
Minor cleanup following #841.
Author: Reynold Xin <rxin@apache.org>
Closes#868 from rxin/schema-count and squashes the following commits:
5442651 [Reynold Xin] SPARK-1822: Some minor cleanup work on SchemaRDD.count()
Author: Kan Zhang <kzhang@apache.org>
Closes#841 from kanzhang/SPARK-1822 and squashes the following commits:
2f8072a [Kan Zhang] [SPARK-1822] Minor style update
cf4baa4 [Kan Zhang] [SPARK-1822] Adding Scaladoc
e67c910 [Kan Zhang] [SPARK-1822] SchemaRDD.count() should use optimizer
JIRA issue: [SPARK-1913](https://issues.apache.org/jira/browse/SPARK-1913)
When scanning Parquet tables, attributes referenced only in predicates that are pushed down are not passed to the `ParquetTableScan` operator and causes exception.
Author: Cheng Lian <lian.cs.zju@gmail.com>
Closes#863 from liancheng/spark-1913 and squashes the following commits:
f976b73 [Cheng Lian] Addessed the readability issue commented by @rxin
f5b257d [Cheng Lian] Added back comments deleted by mistake
ae60ab3 [Cheng Lian] [SPARK-1913] Attributes referenced only in predicates pushed down should remain in ParquetTableScan operator
...ys.
When tables are equi-joined by multiple-keys `HashJoin` should be used, but `CartesianProduct` and then `Filter` are used.
The join keys are paired by `And` expression so we need to apply `splitConjunctivePredicates` to join condition while finding join keys.
Author: Takuya UESHIN <ueshin@happy-camper.st>
Closes#836 from ueshin/issues/SPARK-1889 and squashes the following commits:
fe1c387 [Takuya UESHIN] Apply splitConjunctivePredicates to join condition while finding join keys.
Simple filter predicates such as LessThan, GreaterThan, etc., where one side is a literal and the other one a NamedExpression are now pushed down to the underlying ParquetTableScan. Here are some results for a microbenchmark with a simple schema of six fields of different types where most records failed the test:
| Uncompressed | Compressed
-------------| ------------- | -------------
File size | 10 GB | 2 GB
Speedup | 2 | 1.8
Since mileage may vary I added a new option to SparkConf:
`org.apache.spark.sql.parquet.filter.pushdown`
Default value would be `true` and setting it to `false` disables the pushdown. When most rows are expected to pass the filter or when there are few fields performance can be better when pushdown is disabled. The default should fit situations with a reasonable number of (possibly nested) fields where not too many records on average pass the filter.
Because of an issue with Parquet ([see here](https://github.com/Parquet/parquet-mr/issues/371])) currently only predicates on non-nullable attributes are pushed down. If one would know that for a given table no optional fields have missing values one could also allow overriding this.
Author: Andre Schumacher <andre.schumacher@iki.fi>
Closes#511 from AndreSchumacher/parquet_filter and squashes the following commits:
16bfe83 [Andre Schumacher] Removing leftovers from merge during rebase
7b304ca [Andre Schumacher] Fixing formatting
c36d5cb [Andre Schumacher] Scalastyle
3da98db [Andre Schumacher] Second round of review feedback
7a78265 [Andre Schumacher] Fixing broken formatting in ParquetFilter
a86553b [Andre Schumacher] First round of code review feedback
b0f7806 [Andre Schumacher] Optimizing imports in ParquetTestData
85fea2d [Andre Schumacher] Adding SparkConf setting to disable filter predicate pushdown
f0ad3cf [Andre Schumacher] Undoing changes not needed for this PR
210e9cb [Andre Schumacher] Adding disjunctive filter predicates
a93a588 [Andre Schumacher] Adding unit test for filtering
6d22666 [Andre Schumacher] Extending ParquetFilters
93e8192 [Andre Schumacher] First commit Parquet record filtering
...Scala collections.
When I execute `orderBy` or `limit` for `SchemaRDD` including `ArrayType` or `MapType`, `SparkSqlSerializer` throws the following exception:
```
com.esotericsoftware.kryo.KryoException: Class cannot be created (missing no-arg constructor): scala.collection.immutable.$colon$colon
```
or
```
com.esotericsoftware.kryo.KryoException: Class cannot be created (missing no-arg constructor): scala.collection.immutable.Vector
```
or
```
com.esotericsoftware.kryo.KryoException: Class cannot be created (missing no-arg constructor): scala.collection.immutable.HashMap$HashTrieMap
```
and so on.
This is because registrations of serializers for each concrete collections are missing in `SparkSqlSerializer`.
I believe it should use `AllScalaRegistrar`.
`AllScalaRegistrar` covers a lot of serializers for concrete classes of `Seq`, `Map` for `ArrayType`, `MapType`.
Author: Takuya UESHIN <ueshin@happy-camper.st>
Closes#790 from ueshin/issues/SPARK-1845 and squashes the following commits:
d1ed992 [Takuya UESHIN] Use AllScalaRegistrar for SparkSqlSerializer to register serializers of Scala collections.
Add the implementation for ApproximateCountDistinct to SparkSql. We use the HyperLogLog algorithm implemented in stream-lib, and do the count in two phases: 1) counting the number of distinct elements in each partitions, and 2) merge the HyperLogLog results from different partitions.
A simple serializer and test cases are added as well.
Author: larvaboy <larvaboy@gmail.com>
Closes#737 from larvaboy/master and squashes the following commits:
bd8ef3f [larvaboy] Add support of user-provided standard deviation to ApproxCountDistinct.
9ba8360 [larvaboy] Fix alignment and null handling issues.
95b4067 [larvaboy] Add a test case for count distinct and approximate count distinct.
f57917d [larvaboy] Add the parser for the approximate count.
a2d5d10 [larvaboy] Add ApproximateCountDistinct aggregates and functions.
7ad273a [larvaboy] Add SparkSql serializer for HyperLogLog.
1d9aacf [larvaboy] Fix a minor typo in the toString method of the Count case class.
653542b [larvaboy] Fix a couple of minor typos.
Author: Michael Armbrust <michael@databricks.com>
Closes#761 from marmbrus/existingContext and squashes the following commits:
4651051 [Michael Armbrust] Make it possible to create Java/Python SQLContexts from an existing Scala SQLContext.
https://issues.apache.org/jira/browse/SPARK-1757
The first test succeeds, but the second test fails with exception:
```
[info] - save and load case class RDD with Nones as parquet *** FAILED *** (14 milliseconds)
[info] java.lang.RuntimeException: Unsupported datatype StructType(List())
[info] at scala.sys.package$.error(package.scala:27)
[info] at org.apache.spark.sql.parquet.ParquetTypesConverter$.fromDataType(ParquetRelation.scala:201)
[info] at org.apache.spark.sql.parquet.ParquetTypesConverter$$anonfun$1.apply(ParquetRelation.scala:235)
[info] at org.apache.spark.sql.parquet.ParquetTypesConverter$$anonfun$1.apply(ParquetRelation.scala:235)
[info] at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:244)
[info] at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:244)
[info] at scala.collection.immutable.List.foreach(List.scala:318)
[info] at scala.collection.TraversableLike$class.map(TraversableLike.scala:244)
[info] at scala.collection.AbstractTraversable.map(Traversable.scala:105)
[info] at org.apache.spark.sql.parquet.ParquetTypesConverter$.convertFromAttributes(ParquetRelation.scala:234)
[info] at org.apache.spark.sql.parquet.ParquetTypesConverter$.writeMetaData(ParquetRelation.scala:267)
[info] at org.apache.spark.sql.parquet.ParquetRelation$.createEmpty(ParquetRelation.scala:143)
[info] at org.apache.spark.sql.parquet.ParquetRelation$.create(ParquetRelation.scala:122)
[info] at org.apache.spark.sql.execution.SparkStrategies$ParquetOperations$.apply(SparkStrategies.scala:139)
[info] at org.apache.spark.sql.catalyst.planning.QueryPlanner$$anonfun$1.apply(QueryPlanner.scala:58)
[info] at org.apache.spark.sql.catalyst.planning.QueryPlanner$$anonfun$1.apply(QueryPlanner.scala:58)
[info] at scala.collection.Iterator$$anon$13.hasNext(Iterator.scala:371)
[info] at org.apache.spark.sql.catalyst.planning.QueryPlanner.apply(QueryPlanner.scala:59)
[info] at org.apache.spark.sql.SQLContext$QueryExecution.sparkPlan$lzycompute(SQLContext.scala:264)
[info] at org.apache.spark.sql.SQLContext$QueryExecution.sparkPlan(SQLContext.scala:264)
[info] at org.apache.spark.sql.SQLContext$QueryExecution.executedPlan$lzycompute(SQLContext.scala:265)
[info] at org.apache.spark.sql.SQLContext$QueryExecution.executedPlan(SQLContext.scala:265)
[info] at org.apache.spark.sql.SQLContext$QueryExecution.toRdd$lzycompute(SQLContext.scala:268)
[info] at org.apache.spark.sql.SQLContext$QueryExecution.toRdd(SQLContext.scala:268)
[info] at org.apache.spark.sql.SchemaRDDLike$class.saveAsParquetFile(SchemaRDDLike.scala:66)
[info] at org.apache.spark.sql.SchemaRDD.saveAsParquetFile(SchemaRDD.scala:98)
```
Author: Andrew Ash <andrew@andrewash.com>
Author: Michael Armbrust <michael@databricks.com>
Closes#690 from ash211/rdd-parquet-save and squashes the following commits:
747a0b9 [Andrew Ash] Merge pull request #1 from marmbrus/pr/690
54bd00e [Michael Armbrust] Need to put Option first since Option <: Seq.
8f3f281 [Andrew Ash] SPARK-1757 Add failing test for saving SparkSQL Schemas with Option[?] fields as parquet
Three issues related to temp files that tests generate – these should be touched up for hygiene but are not urgent.
Modules have a log4j.properties which directs the unit-test.log output file to a directory like `[module]/target/unit-test.log`. But this ends up creating `[module]/[module]/target/unit-test.log` instead of former.
The `work/` directory is not deleted by "mvn clean", in the parent and in modules. Neither is the `checkpoint/` directory created under the various external modules.
Many tests create a temp directory, which is not usually deleted. This can be largely resolved by calling `deleteOnExit()` at creation and trying to call `Utils.deleteRecursively` consistently to clean up, sometimes in an `@After` method.
_If anyone seconds the motion, I can create a more significant change that introduces a new test trait along the lines of `LocalSparkContext`, which provides management of temp directories for subclasses to take advantage of._
Author: Sean Owen <sowen@cloudera.com>
Closes#732 from srowen/SPARK-1798 and squashes the following commits:
5af578e [Sean Owen] Try to consistently delete test temp dirs and files, and set deleteOnExit() for each
b21b356 [Sean Owen] Remove work/ and checkpoint/ dirs with mvn clean
bdd0f41 [Sean Owen] Remove duplicate module dir in log4j.properties output path for tests
This pull request contains a rebased patch from @heathermiller (https://github.com/heathermiller/spark/pull/1) to add ClassTags on Serializer and types that depend on it (Broadcast and AccumulableCollection). Putting these in the public API signatures now will allow us to use Scala Pickling for serialization down the line without breaking binary compatibility.
One question remaining is whether we also want them on Accumulator -- Accumulator is passed as part of a bigger Task or TaskResult object via the closure serializer so it doesn't seem super useful to add the ClassTag there. Broadcast and AccumulableCollection in contrast were being serialized directly.
CC @rxin, @pwendell, @heathermiller
Author: Matei Zaharia <matei@databricks.com>
Closes#700 from mateiz/spark-1708 and squashes the following commits:
1a3d8b0 [Matei Zaharia] Use fake ClassTag in Java
3b449ed [Matei Zaharia] test fix
2209a27 [Matei Zaharia] Code style fixes
9d48830 [Matei Zaharia] Add a ClassTag on Serializer and things that depend on it
Add `limit` transformation to `SchemaRDD`.
Author: Takuya UESHIN <ueshin@happy-camper.st>
Closes#711 from ueshin/issues/SPARK-1778 and squashes the following commits:
33169df [Takuya UESHIN] Add 'limit' transformation to SchemaRDD.
* Add native min/max (was using hive before).
* Handle nulls correctly in Avg and Sum.
Author: Michael Armbrust <michael@databricks.com>
Closes#683 from marmbrus/aggFixes and squashes the following commits:
64fe30b [Michael Armbrust] Improve SparkSQL Aggregates * Add native min/max (was using hive before). * Handle nulls correctly in Avg and Sum.
... that do not change schema
Author: Kan Zhang <kzhang@apache.org>
Closes#448 from kanzhang/SPARK-1460 and squashes the following commits:
111e388 [Kan Zhang] silence MiMa errors in EdgeRDD and VertexRDD
91dc787 [Kan Zhang] Taking into account newly added Ordering param
79ed52a [Kan Zhang] [SPARK-1460] Returning SchemaRDD on Set operations that do not change schema
I also removed a println that I bumped into.
Author: Michael Armbrust <michael@databricks.com>
Closes#658 from marmbrus/nullPrimitives and squashes the following commits:
a3ec4f3 [Michael Armbrust] Remove println.
695606b [Michael Armbrust] Support for null primatives from using scala and java reflection.
In-memory compression is now configurable in `SparkConf` by the `spark.sql.inMemoryCompression.enabled` property, and is disabled by default.
To help code review, the bug fix is in [the first commit](d537a367ed), compression configuration is in [the second one](4ce09aa8aa).
Author: Cheng Lian <lian.cs.zju@gmail.com>
Closes#608 from liancheng/spark-1678 and squashes the following commits:
66c3a8d [Cheng Lian] Renamed in-memory compression configuration key
f8fb3a0 [Cheng Lian] Added assertion for testing .hasNext of various decoder
4ce09aa [Cheng Lian] Made in-memory compression configurable via SparkConf
d537a36 [Cheng Lian] Fixed SPARK-1678
Modify spelling errors
Author: ArcherShao <ArcherShao@users.noreply.github.com>
Closes#619 from ArcherShao/patch-1 and squashes the following commits:
2957195 [ArcherShao] Update SchemaRDD.scala
This will be helpful for [SPARK-1495](https://issues.apache.org/jira/browse/SPARK-1495) and other cases where we want to have custom hash join implementations but don't want to repeat the logic for finding the join keys.
Author: Michael Armbrust <michael@databricks.com>
Closes#418 from marmbrus/hashFilter and squashes the following commits:
d5cc79b [Michael Armbrust] Address @rxin 's comments.
366b6d9 [Michael Armbrust] style fixes
14560eb [Michael Armbrust] Generalize pattern for planning hash joins.
f4809c1 [Michael Armbrust] Move common functions to PredicateHelper.
Unfortunately, this is not exhaustive - particularly hive tests still fail due to path issues.
Author: Mridul Muralidharan <mridulm80@apache.org>
This patch had conflicts when merged, resolved by
Committer: Matei Zaharia <matei@databricks.com>
Closes#505 from mridulm/windows_fixes and squashes the following commits:
ef12283 [Mridul Muralidharan] Move to org.apache.commons.lang3 for StringEscapeUtils. Earlier version was buggy appparently
cdae406 [Mridul Muralidharan] Remove leaked changes from > 2G fix branch
3267f4b [Mridul Muralidharan] Fix build failures
35b277a [Mridul Muralidharan] Fix Scalastyle failures
bc69d14 [Mridul Muralidharan] Change from hardcoded path separator
10c4d78 [Mridul Muralidharan] Use explicit encoding while using getBytes
1337abd [Mridul Muralidharan] fix classpath while running in windows
Author: Michael Armbrust <michael@databricks.com>
Closes#518 from marmbrus/parseArrayIndex and squashes the following commits:
afd2d6b [Michael Armbrust] 100 chars
c3d6026 [Michael Armbrust] Add support for parsing indexing into arrays in SQL.
copying form previous pull request https://github.com/apache/spark/pull/462
Its probably better to let the underlying language implementation take care of the default . This was easier to do with python as the default value for seed in random and numpy random is None.
In Scala/Java side it might mean propagating an Option or null(oh no!) down the chain until where the Random is constructed. But, looks like the convention in some other methods was to use System.nanoTime. So, followed that convention.
Conflict with overloaded method in sql.SchemaRDD.sample which also defines default params.
sample(fraction, withReplacement=false, seed=math.random)
Scala does not allow more than one overloaded to have default params. I believe the author intended to override the RDD.sample method and not overload it. So, changed it.
If backward compatible is important, 3 new method can be introduced (without default params) like this
sample(fraction)
sample(fraction, withReplacement)
sample(fraction, withReplacement, seed)
Added some tests for the scala RDD takeSample method.
Author: Arun Ramakrishnan <smartnut007@gmail.com>
This patch had conflicts when merged, resolved by
Committer: Matei Zaharia <matei@databricks.com>
Closes#477 from smartnut007/master and squashes the following commits:
07bb06e [Arun Ramakrishnan] SPARK-1438 fixing more space formatting issues
b9ebfe2 [Arun Ramakrishnan] SPARK-1438 removing redundant import of random in python rddsampler
8d05b1a [Arun Ramakrishnan] SPARK-1438 RDD . Replace System.nanoTime with a Random generated number. python: use a separate instance of Random instead of seeding language api global Random instance.
69619c6 [Arun Ramakrishnan] SPARK-1438 fix spacing issue
0c247db [Arun Ramakrishnan] SPARK-1438 RDD language apis to support optional seed in RDD methods sample/takeSample
Author: Michael Armbrust <michael@databricks.com>
Closes#489 from marmbrus/sqlDocFixes and squashes the following commits:
acee4f3 [Michael Armbrust] Fix visibility / annotation of Spark SQL APIs
I think I hit a class loading issue when running JavaSparkSQL example using spark-submit in local mode.
Author: Kan Zhang <kzhang@apache.org>
Closes#484 from kanzhang/SPARK-1570 and squashes the following commits:
feaaeba [Kan Zhang] [SPARK-1570] Fix classloading in JavaSQLContext.applySchema
... so that we don't follow an unspoken set of forbidden rules for adding **@AlphaComponent**, **@DeveloperApi**, and **@Experimental** annotations in the code.
In addition, this PR
(1) removes unnecessary `:: * ::` tags,
(2) adds missing `:: * ::` tags, and
(3) removes annotations for internal APIs.
Author: Andrew Or <andrewor14@gmail.com>
Closes#470 from andrewor14/annotations-fix and squashes the following commits:
92a7f42 [Andrew Or] Document + fix annotation usages
Author: Cheng Lian <lian.cs.zju@gmail.com>
Closes#432 from liancheng/reuseRow and squashes the following commits:
9e6d083 [Cheng Lian] Simplified code with BufferedIterator
52acec9 [Cheng Lian] Reuses Row object in ExistingRdd.productToRowRdd()
This makes it possible to create tables and insert into them using the DSL and SQL for the scala and java apis.
Author: Michael Armbrust <michael@databricks.com>
Closes#354 from marmbrus/insertIntoTable and squashes the following commits:
6c6f227 [Michael Armbrust] Create random temporary files in python parquet unit tests.
f5e6d5c [Michael Armbrust] Merge remote-tracking branch 'origin/master' into insertIntoTable
765c506 [Michael Armbrust] Add to JavaAPI.
77b512c [Michael Armbrust] typos.
5c3ef95 [Michael Armbrust] use names for boolean args.
882afdf [Michael Armbrust] Change createTableAs to saveAsTable. Clean up api annotations.
d07d94b [Michael Armbrust] Add tests, support for creating parquet files and hive tables.
fa3fe81 [Michael Armbrust] Make insertInto available on JavaSchemaRDD as well. Add createTableAs function.
An initial API that exposes SparkSQL functionality in PySpark. A PythonRDD composed of dictionaries, with string keys and primitive values (boolean, float, int, long, string) can be converted into a SchemaRDD that supports sql queries.
```
from pyspark.context import SQLContext
sqlCtx = SQLContext(sc)
rdd = sc.parallelize([{"field1" : 1, "field2" : "row1"}, {"field1" : 2, "field2": "row2"}, {"field1" : 3, "field2": "row3"}])
srdd = sqlCtx.applySchema(rdd)
sqlCtx.registerRDDAsTable(srdd, "table1")
srdd2 = sqlCtx.sql("SELECT field1 AS f1, field2 as f2 from table1")
srdd2.collect()
```
The last line yields ```[{"f1" : 1, "f2" : "row1"}, {"f1" : 2, "f2": "row2"}, {"f1" : 3, "f2": "row3"}]```
Author: Ahir Reddy <ahirreddy@gmail.com>
Author: Michael Armbrust <michael@databricks.com>
Closes#363 from ahirreddy/pysql and squashes the following commits:
0294497 [Ahir Reddy] Updated log4j properties to supress Hive Warns
307d6e0 [Ahir Reddy] Style fix
6f7b8f6 [Ahir Reddy] Temporary fix MIMA checker. Since we now assemble Spark jar with Hive, we don't want to check the interfaces of all of our hive dependencies
3ef074a [Ahir Reddy] Updated documentation because classes moved to sql.py
29245bf [Ahir Reddy] Cache underlying SchemaRDD instead of generating and caching PythonRDD
f2312c7 [Ahir Reddy] Moved everything into sql.py
a19afe4 [Ahir Reddy] Doc fixes
6d658ba [Ahir Reddy] Remove the metastore directory created by the HiveContext tests in SparkSQL
521ff6d [Ahir Reddy] Trying to get spark to build with hive
ab95eba [Ahir Reddy] Set SPARK_HIVE=true on jenkins
ded03e7 [Ahir Reddy] Added doc test for HiveContext
22de1d4 [Ahir Reddy] Fixed maven pyrolite dependency
e4da06c [Ahir Reddy] Display message if hive is not built into spark
227a0be [Michael Armbrust] Update API links. Fix Hive example.
58e2aa9 [Michael Armbrust] Build Docs for pyspark SQL Api. Minor fixes.
4285340 [Michael Armbrust] Fix building of Hive API Docs.
38a92b0 [Michael Armbrust] Add note to future non-python developers about python docs.
337b201 [Ahir Reddy] Changed com.clearspring.analytics stream version from 2.4.0 to 2.5.1 to match SBT build, and added pyrolite to maven build
40491c9 [Ahir Reddy] PR Changes + Method Visibility
1836944 [Michael Armbrust] Fix comments.
e00980f [Michael Armbrust] First draft of python sql programming guide.
b0192d3 [Ahir Reddy] Added Long, Double and Boolean as usable types + unit test
f98a422 [Ahir Reddy] HiveContexts
79621cf [Ahir Reddy] cleaning up cruft
b406ba0 [Ahir Reddy] doctest formatting
20936a5 [Ahir Reddy] Added tests and documentation
e4d21b4 [Ahir Reddy] Added pyrolite dependency
79f739d [Ahir Reddy] added more tests
7515ba0 [Ahir Reddy] added more tests :)
d26ec5e [Ahir Reddy] added test
e9f5b8d [Ahir Reddy] adding tests
906d180 [Ahir Reddy] added todo explaining cost of creating Row object in python
251f99d [Ahir Reddy] for now only allow dictionaries as input
09b9980 [Ahir Reddy] made jrdd explicitly lazy
c608947 [Ahir Reddy] SchemaRDD now has all RDD operations
725c91e [Ahir Reddy] awesome row objects
55d1c76 [Ahir Reddy] return row objects
4fe1319 [Ahir Reddy] output dictionaries correctly
be079de [Ahir Reddy] returning dictionaries works
cd5f79f [Ahir Reddy] Switched to using Scala SQLContext
e948bd9 [Ahir Reddy] yippie
4886052 [Ahir Reddy] even better
c0fb1c6 [Ahir Reddy] more working
043ca85 [Ahir Reddy] working
5496f9f [Ahir Reddy] doesn't crash
b8b904b [Ahir Reddy] Added schema rdd class
67ba875 [Ahir Reddy] java to python, and python to java
bcc0f23 [Ahir Reddy] Java to python
ab6025d [Ahir Reddy] compiling
Fixed several bugs of in-memory columnar storage to make `HiveInMemoryCompatibilitySuite` pass.
@rxin @marmbrus It is reasonable to include `HiveInMemoryCompatibilitySuite` in this PR, but I didn't, since it significantly increases test execution time. What do you think?
**UPDATE** `HiveCompatibilitySuite` has been made to cache tables in memory. `HiveInMemoryCompatibilitySuite` was removed.
Author: Cheng Lian <lian.cs.zju@gmail.com>
Author: Michael Armbrust <michael@databricks.com>
Closes#374 from liancheng/inMemBugFix and squashes the following commits:
6ad6d9b [Cheng Lian] Merged HiveCompatibilitySuite and HiveInMemoryCompatibilitySuite
5bdbfe7 [Cheng Lian] Revert 882c538 & 8426ddc, which introduced regression
882c538 [Cheng Lian] Remove attributes field from InMemoryColumnarTableScan
32cc9ce [Cheng Lian] Code style cleanup
99382bf [Cheng Lian] Enable compression by default
4390bcc [Cheng Lian] Report error for any Throwable in HiveComparisonTest
d1df4fd [Michael Armbrust] Remove test tables that might always get created anyway?
ab9e807 [Michael Armbrust] Fix the logged console version of failed test cases to use the new syntax.
1965123 [Michael Armbrust] Don't use coalesce for gathering all data to a single partition, as it does not work correctly with mutable rows.
e36cdd0 [Michael Armbrust] Spelling.
2d0e168 [Michael Armbrust] Run Hive tests in-memory too.
6360723 [Cheng Lian] Made PreInsertionCasts support SparkLogicalPlan and InMemoryColumnarTableScan
c9b0f6f [Cheng Lian] Let InsertIntoTable support InMemoryColumnarTableScan
9c8fc40 [Cheng Lian] Disable compression by default
e619995 [Cheng Lian] Bug fix: incorrect byte order in CompressionScheme.columnHeaderSize
8426ddc [Cheng Lian] Bug fix: InMemoryColumnarTableScan should cache columns specified by the attributes argument
036cd09 [Cheng Lian] Clean up unused imports
44591a5 [Cheng Lian] Bug fix: NullableColumnAccessor.hasNext must take nulls into account
052bf41 [Cheng Lian] Bug fix: should only gather compressibility info for non-null values
95b3301 [Cheng Lian] Fixed bugs in IntegralDelta
The Spark codebase is a bit fast-and-loose when accessing classloaders and this has caused a few bugs to surface in master.
This patch defines some utility methods for accessing classloaders. This makes the intention when accessing a classloader much more explicit in the code and fixes a few cases where the wrong one was chosen.
case (a) -> We want the classloader that loaded Spark
case (b) -> We want the context class loader, or if not present, we want (a)
This patch provides a better fix for SPARK-1403 (https://issues.apache.org/jira/browse/SPARK-1403) than the current work around, which it reverts. It also fixes a previously unreported bug that the `./spark-submit` script did not work for running with `local` master. It didn't work because the executor classloader did not properly delegate to the context class loader (if it is defined) and in local mode the context class loader is set by the `./spark-submit` script. A unit test is added for that case.
Author: Patrick Wendell <pwendell@gmail.com>
Closes#398 from pwendell/class-loaders and squashes the following commits:
b4a1a58 [Patrick Wendell] Minor clean up
14f1272 [Patrick Wendell] SPARK-1480: Clean up use of classloaders
stack these together in a commit else they show up chunk by chunk in different commits.
Author: Sandeep <sandeep@techaddict.me>
Closes#380 from techaddict/white_space and squashes the following commits:
b58f294 [Sandeep] Remove Unnecessary Whitespace's
Author: witgo <witgo@qq.com>
Closes#325 from witgo/SPARK-1413 and squashes the following commits:
e57cd8e [witgo] use scala reflection to access and call the SLF4JBridgeHandler methods
45c8f40 [witgo] Merge branch 'master' of https://github.com/apache/spark into SPARK-1413
5e35d87 [witgo] Merge branch 'master' of https://github.com/apache/spark into SPARK-1413
0d5f819 [witgo] review commit
45e5b70 [witgo] Merge branch 'master' of https://github.com/apache/spark into SPARK-1413
fa69dcf [witgo] Merge branch 'master' into SPARK-1413
3c98dc4 [witgo] Merge branch 'master' into SPARK-1413
38160cb [witgo] Merge branch 'master' of https://github.com/apache/spark into SPARK-1413
ba09bcd [witgo] remove set the parquet log level
a63d574 [witgo] Merge branch 'master' of https://github.com/apache/spark into SPARK-1413
5231ecd [witgo] Merge branch 'master' of https://github.com/apache/spark into SPARK-1413
3feb635 [witgo] parquet logger use parent handler
fa00d5d [witgo] Merge branch 'master' of https://github.com/apache/spark into SPARK-1413
8bb6ffd [witgo] enableLogForwarding note fix
edd9630 [witgo] move to
f447f50 [witgo] merging master
5ad52bd [witgo] Merge branch 'master' of https://github.com/apache/spark into SPARK-1413
76670c1 [witgo] review commit
70f3c64 [witgo] Fix SPARK-1413
This patch marks some existing classes as private[spark] and adds two types of API annotations:
- `EXPERIMENTAL API` = experimental user-facing module
- `DEVELOPER API - UNSTABLE` = developer-facing API that might change
There is some discussion of the different mechanisms for doing this here:
https://issues.apache.org/jira/browse/SPARK-1081
I was pretty aggressive with marking things private. Keep in mind that if we want to open something up in the future we can, but we can never reduce visibility.
A few notes here:
- In the past we've been inconsistent with the visiblity of the X-RDD classes. This patch marks them private whenever there is an existing function in RDD that can directly creat them (e.g. CoalescedRDD and rdd.coalesce()). One trade-off here is users can't subclass them.
- Noted that compression and serialization formats don't have to be wire compatible across versions.
- Compression codecs and serialization formats are semi-private as users typically don't instantiate them directly.
- Metrics sources are made private - user only interacts with them through Spark's reflection
Author: Patrick Wendell <pwendell@gmail.com>
Author: Andrew Or <andrewor14@gmail.com>
Closes#274 from pwendell/private-apis and squashes the following commits:
44179e4 [Patrick Wendell] Merge remote-tracking branch 'apache-github/master' into private-apis
042c803 [Patrick Wendell] spark.annotations -> spark.annotation
bfe7b52 [Patrick Wendell] Adding experimental for approximate counts
8d0c873 [Patrick Wendell] Warning in SparkEnv
99b223a [Patrick Wendell] Cleaning up annotations
e849f64 [Patrick Wendell] Merge pull request #2 from andrewor14/annotations
982a473 [Andrew Or] Generalize jQuery matching for non Spark-core API docs
a01c076 [Patrick Wendell] Merge pull request #1 from andrewor14/annotations
c1bcb41 [Andrew Or] DeveloperAPI -> DeveloperApi
0d48908 [Andrew Or] Comments and new lines (minor)
f3954e0 [Andrew Or] Add identifier tags in comments to work around scaladocs bug
99192ef [Andrew Or] Dynamically add badges based on annotations
824011b [Andrew Or] Add support for injecting arbitrary JavaScript to API docs
037755c [Patrick Wendell] Some changes after working with andrew or
f7d124f [Patrick Wendell] Small fixes
c318b24 [Patrick Wendell] Use CSS styles
e4c76b9 [Patrick Wendell] Logging
f390b13 [Patrick Wendell] Better visibility for workaround constructors
d6b0afd [Patrick Wendell] Small chang to existing constructor
403ba52 [Patrick Wendell] Style fix
870a7ba [Patrick Wendell] Work around for SI-8479
7fb13b2 [Patrick Wendell] Changes to UnionRDD and EmptyRDD
4a9e90c [Patrick Wendell] EXPERIMENTAL API --> EXPERIMENTAL
c581dce [Patrick Wendell] Changes after building against Shark.
8452309 [Patrick Wendell] Style fixes
1ed27d2 [Patrick Wendell] Formatting and coloring of badges
cd7a465 [Patrick Wendell] Code review feedback
2f706f1 [Patrick Wendell] Don't use floats
542a736 [Patrick Wendell] Small fixes
cf23ec6 [Patrick Wendell] Marking GraphX as alpha
d86818e [Patrick Wendell] Another naming change
5a76ed6 [Patrick Wendell] More visiblity clean-up
42c1f09 [Patrick Wendell] Using better labels
9d48cbf [Patrick Wendell] Initial pass
JIRA issue: [SPARK-1402](https://issues.apache.org/jira/browse/SPARK-1402)
This PR provides 3 more compression schemes for Spark SQL in-memory columnar storage:
* `BooleanBitSet`
* `IntDelta`
* `LongDelta`
Now there are 6 compression schemes in total, including the no-op `PassThrough` scheme.
Also fixed a bug in PR #286: not all compression schemes are added as available schemes when accessing an in-memory column, and when a column is compressed with an unrecognised scheme, `ColumnAccessor` throws exception.
Author: Cheng Lian <lian.cs.zju@gmail.com>
Closes#330 from liancheng/moreCompressionSchemes and squashes the following commits:
1d037b8 [Cheng Lian] Fixed SPARK-1436: in-memory column byte buffer must be able to be accessed multiple times
d7c0e8f [Cheng Lian] Added test suite for IntegralDelta (IntDelta & LongDelta)
3c1ad7a [Cheng Lian] Added test suite for BooleanBitSet, refactored other test suites
44fe4b2 [Cheng Lian] Refactored CompressionScheme, added 3 more compression schemes.
Author: Reynold Xin <rxin@apache.org>
Closes#348 from rxin/aggregate and squashes the following commits:
f4bc36f [Reynold Xin] Rename execution/aggregates.scala Aggregate.scala, and added a bunch of private[this] to variables.
Also used this opportunity to add a bunch of override's and made some members private.
Author: Reynold Xin <rxin@apache.org>
Closes#340 from rxin/eval and squashes the following commits:
a7c7ca7 [Reynold Xin] Fixed conflicts in merge.
9069de6 [Reynold Xin] Merge branch 'master' into eval
3ccc313 [Reynold Xin] Merge branch 'master' into eval
1a47e10 [Reynold Xin] Renamed apply to eval for generators and added a bunch of override's.
ea061de [Reynold Xin] Rename Expression.apply to eval for better readability.
Author: Michael Armbrust <michael@databricks.com>
Closes#343 from marmbrus/toStringFix and squashes the following commits:
37198fe [Michael Armbrust] Fix toString for SchemaRDD NativeCommands.
Given:
```scala
case class Data(a: Int, b: Int)
val rdd =
sparkContext
.parallelize(1 to 200)
.flatMap(_ => (1 to 50000).map(i => Data(i % 100, i)))
rdd.registerAsTable("data")
cacheTable("data")
```
Before:
```
SELECT COUNT(*) FROM data:[10000000]
16795.567ms
SELECT a, SUM(b) FROM data GROUP BY a
7536.436ms
SELECT SUM(b) FROM data
10954.1ms
```
After:
```
SELECT COUNT(*) FROM data:[10000000]
1372.175ms
SELECT a, SUM(b) FROM data GROUP BY a
2070.446ms
SELECT SUM(b) FROM data
958.969ms
```
Author: Michael Armbrust <michael@databricks.com>
Closes#295 from marmbrus/hashAgg and squashes the following commits:
ec63575 [Michael Armbrust] Add comment.
d0495a9 [Michael Armbrust] Use scaladoc instead.
b4a6887 [Michael Armbrust] Address review comments.
a2d90ba [Michael Armbrust] Capture child output statically to avoid issues with generators and serialization.
7c13112 [Michael Armbrust] Rewrite Aggregate operator to stream input and use projections. Remove unused local RDD functions implicits.
5096f99 [Michael Armbrust] Make HiveUDAF fields transient since object inspectors are not serializable.
6a4b671 [Michael Armbrust] Add option to avoid binding operators expressions automatically.
92cca08 [Michael Armbrust] Always include serialization debug info when running tests.
1279df2 [Michael Armbrust] Increase default number of partitions.
Use Java 6's recommended equivalent of Java 7's Logger.getGlobal() to retain Java 6 compatibility. See PR #195
Author: Sean Owen <sowen@cloudera.com>
Closes#334 from srowen/FixPR195ForJava6 and squashes the following commits:
f92fbd3 [Sean Owen] Use Java 6's recommended equivalent of Java 7's Logger.getGlobal() to retain Java 6 compatibility
Author: Michael Armbrust <michael@databricks.com>
Closes#315 from marmbrus/minorFixes and squashes the following commits:
b23a15d [Michael Armbrust] fix scaladoc
11062ac [Michael Armbrust] Fix registering "SELECT *" queries as tables and caching them. As some tests for this and self-joins.
3997dc9 [Michael Armbrust] Move Row extractor to catalyst.
208bf5e [Michael Armbrust] More idiomatic naming of DSL functions. * subquery => as * for join condition => on, i.e., `r.join(s, condition = 'a == 'b)` =>`r.join(s, on = 'a == 'b)`
87211ce [Michael Armbrust] Correctly handle self joins of in-memory cached tables.
69e195e [Michael Armbrust] Change != to !== in the DSL since != will always translate to != on Any.
01f2dd5 [Michael Armbrust] Correctly assign aliases to tables in SqlParser.
The JavaAPI and the Parquet improvements PRs didn't conflict, but broke the build.
Author: Michael Armbrust <michael@databricks.com>
Closes#316 from marmbrus/hotFixJavaApi and squashes the following commits:
0b84c2d [Michael Armbrust] Fix compilation of Spark SQL Java API.
This PR includes:
1) Add new data type Timestamp
2) Add more data type casting base on Hive's Rule
3) Fix bug missing data type in both parsers (HiveQl & SQLParser).
Author: Cheng Hao <hao.cheng@intel.com>
Closes#275 from chenghao-intel/timestamp and squashes the following commits:
df709e5 [Cheng Hao] Move orc_ends_with_nulls to blacklist
24b04b0 [Cheng Hao] Put 3 cases into the black lists(describe_pretty,describe_syntax,lateral_view_outer)
fc512c2 [Cheng Hao] remove the unnecessary data type equality check in data casting
d0d1919 [Cheng Hao] Add more data type for scala reflection
3259808 [Cheng Hao] Add the new Golden files
3823b97 [Cheng Hao] Update the UnitTest cases & add timestamp type for HiveQL
54a0489 [Cheng Hao] fix bug mapping to 0 (which is supposed to be null) when NumberFormatException occurs
9cb505c [Cheng Hao] Fix issues according to PR comments
e529168 [Cheng Hao] Fix bug of converting from String
6fc8100 [Cheng Hao] Update Unit Test & CodeStyle
8a1d4d6 [Cheng Hao] Add DataType for SqlParser
ce4385e [Cheng Hao] Add TimestampType Support
A few improvements to the Parquet support for SQL queries:
- Instead of files a ParquetRelation is now backed by a directory, which simplifies importing data from other
sources
- InsertIntoParquetTable operation now supports switching between overwriting or appending (at least in
HiveQL)
- tests now use the new API
- Parquet logging can be set to WARNING level (Default)
- Default compression for Parquet files (GZIP, as in parquet-mr)
Author: Andre Schumacher <andre.schumacher@iki.fi>
Closes#195 from AndreSchumacher/spark_parquet_improvements and squashes the following commits:
54df314 [Andre Schumacher] SPARK-1383 [SQL] Improvements to ParquetRelation
Author: Michael Armbrust <michael@databricks.com>
Closes#293 from marmbrus/reflectTypes and squashes the following commits:
f54e8e8 [Michael Armbrust] Improve datatype and test coverage for ScalaReflection schema inference.
1. Renamed StopAfter to Limit to be more consistent with naming in other relational databases.
2. Renamed TopK to TakeOrdered to be more consistent with Spark RDD API.
3. Avoid breaking lineage in Limit.
4. Added a bunch of override's to execution/basicOperators.scala.
@marmbrus @liancheng
Author: Reynold Xin <rxin@apache.org>
Author: Michael Armbrust <michael@databricks.com>
Closes#233 from rxin/limit and squashes the following commits:
13eb12a [Reynold Xin] Merge pull request #1 from marmbrus/limit
92b9727 [Michael Armbrust] More hacks to make Maps serialize with Kryo.
4fc8b4e [Reynold Xin] Merge branch 'master' of github.com:apache/spark into limit
87b7d37 [Reynold Xin] Use the proper serializer in limit.
9b79246 [Reynold Xin] Updated doc for Limit.
47d3327 [Reynold Xin] Copy tuples in Limit before shuffle.
231af3a [Reynold Xin] Limit/TakeOrdered: 1. Renamed StopAfter to Limit to be more consistent with naming in other relational databases. 2. Renamed TopK to TakeOrdered to be more consistent with Spark RDD API. 3. Avoid breaking lineage in Limit. 4. Added a bunch of override's to execution/basicOperators.scala.
JIRA issue: [SPARK-1373](https://issues.apache.org/jira/browse/SPARK-1373)
(Although tagged as WIP, this PR is structurally complete. The only things left unimplemented are 3 more compression algorithms: `BooleanBitSet`, `IntDelta` and `LongDelta`, which are trivial to add later in this or another separate PR.)
This PR contains compression support for Spark SQL in-memory columnar storage. Main interfaces include:
* `CompressionScheme`
Each `CompressionScheme` represents a concrete compression algorithm, which basically consists of an `Encoder` for compression and a `Decoder` for decompression. Algorithms implemented include:
* `RunLengthEncoding`
* `DictionaryEncoding`
Algorithms to be implemented include:
* `BooleanBitSet`
* `IntDelta`
* `LongDelta`
* `CompressibleColumnBuilder`
A stackable `ColumnBuilder` trait used to build byte buffers for compressible columns. A best `CompressionScheme` that exhibits lowest compression ratio is chosen for each column according to statistical information gathered while elements are appended into the `ColumnBuilder`. However, if no `CompressionScheme` can achieve a compression ratio better than 80%, no compression will be done for this column to save CPU time.
Memory layout of the final byte buffer is showed below:
```
.--------------------------- Column type ID (4 bytes)
| .----------------------- Null count N (4 bytes)
| | .------------------- Null positions (4 x N bytes, empty if null count is zero)
| | | .------------- Compression scheme ID (4 bytes)
| | | | .--------- Compressed non-null elements
V V V V V
+---+---+-----+---+---------+
| | | ... | | ... ... |
+---+---+-----+---+---------+
\-----------/ \-----------/
header body
```
* `CompressibleColumnAccessor`
A stackable `ColumnAccessor` trait used to iterate (possibly) compressed data column.
* `ColumnStats`
Used to collect statistical information while loading data into in-memory columnar table. Optimizations like partition pruning rely on this information.
Strictly speaking, `ColumnStats` related code is not part of the compression support. It's contained in this PR to ensure and validate the row-based API design (which is used to avoid boxing/unboxing cost whenever possible).
A major refactoring change since PR #205 is:
* Refactored all getter/setter methods for primitive types in various places into `ColumnType` classes to remove duplicated code.
Author: Cheng Lian <lian.cs.zju@gmail.com>
Closes#285 from liancheng/memColumnarCompression and squashes the following commits:
ed71bbd [Cheng Lian] Addressed all PR comments by @marmbrus
d3a4fa9 [Cheng Lian] Removed Ordering[T] in ColumnStats for better performance
5034453 [Cheng Lian] Bug fix, more tests, and more refactoring
c298b76 [Cheng Lian] Test suites refactored
2780d6a [Cheng Lian] [WIP] in-memory columnar compression support
211331c [Cheng Lian] WIP: in-memory columnar compression support
85cc59b [Cheng Lian] Refactored ColumnAccessors & ColumnBuilders to remove duplicate code
This doesn't yet support different databases in Hive (though you can probably workaround this by calling `USE <dbname>`). However, given the time constraints for 1.0 I think its probably worth including this now and extending the functionality in the next release.
Author: Michael Armbrust <michael@databricks.com>
Closes#282 from marmbrus/cacheTables and squashes the following commits:
83785db [Michael Armbrust] Support for caching and uncaching tables in a SQLContext.
Before we were materializing everything in memory. This also uses the projection interface so will be easier to plug in code gen (its ported from that branch).
@rxin @liancheng
Author: Michael Armbrust <michael@databricks.com>
Closes#250 from marmbrus/hashJoin and squashes the following commits:
1ad873e [Michael Armbrust] Change hasNext logic back to the correct version.
8e6f2a2 [Michael Armbrust] Review comments.
1e9fb63 [Michael Armbrust] style
bc0cb84 [Michael Armbrust] Rewrite join implementation to allow streaming of one relation.
Author: Prashant Sharma <prashant.s@imaginea.com>
Closes#261 from ScrapCodes/comment-style-check2 and squashes the following commits:
6cde61e [Prashant Sharma] comment style space before ending */ check.
Fix attribute unresolved when query with table name as a qualifier in SQLContext with SimplCatelog, details please see [SPARK-1354](https://issues.apache.org/jira/browse/SPARK-1354?jql=project%20%3D%20SPARK).
Author: jerryshao <saisai.shao@intel.com>
Closes#272 from jerryshao/qualifier-fix and squashes the following commits:
7950170 [jerryshao] Add tableName as a qualifier for SimpleCatelogy
@AndreSchumacher, please take a look.
https://spark-project.atlassian.net/browse/SPARK-1354
Author: Michael Armbrust <michael@databricks.com>
Closes#269 from marmbrus/parquetJoin and squashes the following commits:
4081e77 [Michael Armbrust] Create new instances of Parquet relation when multiple copies are in a single plan.
...sql pom files
Author: Thomas Graves <tgraves@apache.org>
Closes#263 from tgravescs/SPARK-1345 and squashes the following commits:
b43a2a0 [Thomas Graves] SPARK-1345 adding missing dependency on avro for hadoop 0.23 to the new sql pom files
Author: Michael Armbrust <michael@databricks.com>
Closes#243 from marmbrus/mapSer and squashes the following commits:
54045f7 [Michael Armbrust] Add a custom serializer for maps since they do not have a no-arg constructor.
According to discussions in comments of PR #208, this PR unifies package definition format in Spark SQL.
Some broken links in ScalaDoc and typos detected along the way are also fixed.
Author: Cheng Lian <lian.cs.zju@gmail.com>
Closes#225 from liancheng/packageDefinition and squashes the following commits:
75c47b3 [Cheng Lian] Fixed file line length
4f87968 [Cheng Lian] Unified package definition format in Spark SQL
This removes duplicated logic, dead code and casting when planning parquet table scans and hive table scans.
Other changes:
- Fix tests now that we are doing a better job of column pruning (i.e., since pruning predicates are applied before we even start scanning tuples, columns required by these predicates do not need to be included in the output of the scan unless they are also included in the final output of this logical plan fragment).
- Add rule to simplify trivial filters. This was required to avoid `WHERE false` from getting pushed into table scans, since `HiveTableScan` (reasonably) refuses to apply partition pruning predicates to non-partitioned tables.
Author: Michael Armbrust <michael@databricks.com>
Closes#213 from marmbrus/strategyCleanup and squashes the following commits:
48ce403 [Michael Armbrust] Move one more bit of parquet stuff into the core SQLContext.
834ce08 [Michael Armbrust] Address comments.
0f2c6f5 [Michael Armbrust] Unify the logic for column pruning, projection, and filtering of table scans for both Hive and Parquet relations. Fix tests now that we are doing a better job of column pruning.
Author: Prashant Sharma <prashant.s@imaginea.com>
Closes#125 from ScrapCodes/rat-integration and squashes the following commits:
64f7c7d [Prashant Sharma] added license headers.
fcf28b1 [Prashant Sharma] Review feedback.
c0648db [Prashant Sharma] SPARK-1144 Added license and RAT to check licenses.
This PR addresses various coding style issues in Spark SQL, including but not limited to those mentioned by @mateiz in PR #146.
As this PR affects lots of source files and may cause potential conflicts, it would be better to merge this as soon as possible *after* PR #205 (In-memory columnar representation for Spark SQL) is merged.
Author: Cheng Lian <lian.cs.zju@gmail.com>
Closes#208 from liancheng/fixCodingStyle and squashes the following commits:
fc2b528 [Cheng Lian] Merge branch 'master' into fixCodingStyle
b531273 [Cheng Lian] Fixed coding style issues in sql/hive
0b56f77 [Cheng Lian] Fixed coding style issues in sql/core
fae7b02 [Cheng Lian] Addressed styling issues mentioned by @marmbrus
9265366 [Cheng Lian] Fixed coding style issues in sql/core
3dcbbbd [Cheng Lian] Fixed relative package imports for package catalyst
This PR is rebased from the Catalyst repository, and contains the first version of in-memory columnar representation for Spark SQL. Compression support is not included yet and will be added later in a separate PR.
Author: Cheng Lian <lian@databricks.com>
Author: Cheng Lian <lian.cs.zju@gmail.com>
Closes#205 from liancheng/memColumnarSupport and squashes the following commits:
99dba41 [Cheng Lian] Restricted new objects/classes to `private[sql]'
0892ad8 [Cheng Lian] Addressed ScalaStyle issues
af1ad5e [Cheng Lian] Fixed some minor issues introduced during rebasing
0dbf2fb [Cheng Lian] Make necessary renaming due to rebase
a162d4d [Cheng Lian] Removed the unnecessary InMemoryColumnarRelation class
9bcae4b [Cheng Lian] Added Apache license
220ee1e [Cheng Lian] Added table scan operator for in-memory columnar support.
c701c7a [Cheng Lian] Using SparkSqlSerializer for generic object SerDe causes error, made a workaround
ed8608e [Cheng Lian] Added implicit conversion from DataType to ColumnType
b8a645a [Cheng Lian] Replaced KryoSerializer with an updated SparkSqlSerializer
b6c0a49 [Cheng Lian] Minor test suite refactoring
214be73 [Cheng Lian] Refactored BINARY and GENERIC to reduce duplicate code
da2f4d5 [Cheng Lian] Added Apache license
dbf7a38 [Cheng Lian] Added ColumnAccessor and test suite, refactored ColumnBuilder
c01a177 [Cheng Lian] Added column builder classes and test suite
f18ddc6 [Cheng Lian] Added ColumnTypes and test suite
2d09066 [Cheng Lian] Added KryoSerializer
34f3c19 [Cheng Lian] Added TypeTag field to all NativeTypes
acc5c48 [Cheng Lian] Added Hive test files to .gitignore
This is a bit of a hack that allows all variations of a keyword, but it still seems to produce valid error messages and such.
Author: Matei Zaharia <matei@databricks.com>
Closes#193 from mateiz/case-insensitive-sql and squashes the following commits:
0ee4ace [Matei Zaharia] Removed unnecessary `+ ""`
e3ed773 [Matei Zaharia] Make SQL keywords case-insensitive
Sorry! I added this test at the last minute and failed to run it in maven as well.
Note that, this will probably not be sufficient to actually fix the maven jenkins build, as that does not use the dev/run-tests scripts. We will need to configure it to also run dev/download-hive-tests.sh. The other option would be to check in the tests as I suggested in the original PR. (I can do this if we agree its the right thing to do).
Long term it would probably be a good idea to also have maven run some sort of test env setup script so that we can decouple the test environment from the jenkins configuration.
Author: Michael Armbrust <michael@databricks.com>
Closes#191 from marmbrus/fixMaven and squashes the following commits:
3366e37 [Michael Armbrust] Fix maven jenkins: Add explicit init for required tables in SQLQuerySuite
This pull request adds support to Spark for working with structured data using a simple SQL dialect, HiveQL and a Scala Query DSL.
*This is being contributed as a new __alpha component__ to Spark and does not modify Spark core or other components.*
The code is broken into three primary components:
- Catalyst (sql/catalyst) - An implementation-agnostic framework for manipulating trees of relational operators and expressions.
- Execution (sql/core) - A query planner / execution engine for translating Catalyst’s logical query plans into Spark RDDs. This component also includes a new public interface, SqlContext, that allows users to execute SQL or structured scala queries against existing RDDs and Parquet files.
- Hive Metastore Support (sql/hive) - An extension of SqlContext called HiveContext that allows users to write queries using a subset of HiveQL and access data from a Hive Metastore using Hive SerDes. There are also wrappers that allows users to run queries that include Hive UDFs, UDAFs, and UDTFs.
A more complete design of this new component can be found in [the associated JIRA](https://spark-project.atlassian.net/browse/SPARK-1251).
[An updated version of the Spark documentation, including API Docs for all three sub-components,](http://people.apache.org/~pwendell/catalyst-docs/sql-programming-guide.html) is also available for review.
With this PR comes support for inferring the schema of existing RDDs that contain case classes. Using this information, developers can now express structured queries that are automatically compiled into RDD operations.
```scala
// Define the schema using a case class.
case class Person(name: String, age: Int)
val people: RDD[Person] =
sc.textFile("people.txt").map(_.split(",")).map(p => Person(p(0), p(1).toInt))
// The following is the same as 'SELECT name FROM people WHERE age >= 10 && age <= 19'
val teenagers = people.where('age >= 10).where('age <= 19).select('name).toRdd
```
RDDs can also be registered as Tables, allowing SQL queries to be written over them.
```scala
people.registerAsTable("people")
val teenagers = sql("SELECT name FROM people WHERE age >= 10 && age <= 19")
```
The results of queries are themselves RDDs and support standard RDD operations:
```scala
teenagers.map(t => "Name: " + t(0)).collect().foreach(println)
```
Finally, with the optional Hive support, users can read and write data located in existing Apache Hive deployments using HiveQL.
```scala
sql("CREATE TABLE IF NOT EXISTS src (key INT, value STRING)")
sql("LOAD DATA LOCAL INPATH 'src/main/resources/kv1.txt' INTO TABLE src")
// Queries are expressed in HiveQL
sql("SELECT key, value FROM src").collect().foreach(println)
```
## Relationship to Shark
Unlike Shark, Spark SQL does not act as a drop in replacement for Hive or the HiveServer. Instead this new feature is intended to make it easier for Spark developers to run queries over structured data, using either SQL or the query DSL. After this sub-project graduates from Alpha status it will likely become a new optimizer/backend for the Shark project.
Author: Michael Armbrust <michael@databricks.com>
Author: Yin Huai <huaiyin.thu@gmail.com>
Author: Reynold Xin <rxin@apache.org>
Author: Lian, Cheng <rhythm.mail@gmail.com>
Author: Andre Schumacher <andre.schumacher@iki.fi>
Author: Yin Huai <huai@cse.ohio-state.edu>
Author: Timothy Chen <tnachen@gmail.com>
Author: Cheng Lian <lian.cs.zju@gmail.com>
Author: Timothy Chen <tnachen@apache.org>
Author: Henry Cook <henry.m.cook+github@gmail.com>
Author: Mark Hamstra <markhamstra@gmail.com>
Closes#146 from marmbrus/catalyst and squashes the following commits:
458bd1b [Michael Armbrust] Update people.txt
0d638c3 [Michael Armbrust] Typo fix from @ash211.
bdab185 [Michael Armbrust] Address another round of comments: * Doc examples can now copy/paste into spark-shell. * SQLContext is serializable * Minor parser bugs fixed * Self-joins of RDDs now handled correctly. * Removed deprecated examples * Removed deprecated parquet docs * Made more of the API private * Copied all the DSLQuery tests and rewrote them as SQLQueryTests
778299a [Michael Armbrust] Fix some old links to spark-project.org
fead0b6 [Michael Armbrust] Create a new RDD type, SchemaRDD, that is now the return type for all SQL operations. This improves the old API by reducing the number of implicits that are required, and avoids throwing away schema information when returning an RDD to the user. This change also makes it slightly less verbose to run language integrated queries.
fee847b [Michael Armbrust] Merge remote-tracking branch 'origin/master' into catalyst, integrating changes to serialization for ShuffledRDD.
48a99bc [Michael Armbrust] Address first round of feedback.
461581c [Michael Armbrust] Blacklist test that depends on JVM specific rounding behaviour
adcf1a4 [Henry Cook] Update sql-programming-guide.md
9dffbfa [Michael Armbrust] Style fixes. Add downloading of test cases to jenkins.
6978dd8 [Michael Armbrust] update docs, add apache license
1d0eb63 [Michael Armbrust] update changes with spark core
e5e1d6b [Michael Armbrust] Remove travis configuration.
c2efad6 [Michael Armbrust] First draft of SQL documentation.
013f62a [Michael Armbrust] Fix documentation / code style.
c01470f [Michael Armbrust] Clean up example
2f22454 [Michael Armbrust] WIP: Parquet example.
ce8073b [Michael Armbrust] clean up implicits.
f7d992d [Michael Armbrust] Naming / spelling.
9eb0294 [Michael Armbrust] Bring expressions implicits into SqlContext.
d2d9678 [Michael Armbrust] Make sure hive isn't in the assembly jar. Create a separate, optional Hive assembly that is used when present.
8b35e0a [Michael Armbrust] address feedback, work on DSL
5d71074 [Michael Armbrust] Merge pull request #62 from AndreSchumacher/parquet_file_fixes
f93aa39 [Andre Schumacher] Better handling of path names in ParquetRelation
1a4bbd9 [Michael Armbrust] Merge pull request #60 from marmbrus/maven
3386e4f [Michael Armbrust] Merge pull request #58 from AndreSchumacher/parquet_fixes
3447c3e [Michael Armbrust] Don't override the metastore / warehouse in non-local/test hive context.
7233a74 [Michael Armbrust] initial support for maven builds
f0ba39e [Michael Armbrust] Merge remote-tracking branch 'origin/master' into maven
7386a9f [Michael Armbrust] Initial example programs using spark sql.
aeaef54 [Andre Schumacher] Removing unnecessary Row copying and reverting some changes to MutableRow
7ca4b4e [Andre Schumacher] Improving checks in Parquet tests
5bacdc0 [Andre Schumacher] Moving towards mutable rows inside ParquetRowSupport
54637ec [Andre Schumacher] First part of second round of code review feedback
c2a658d [Michael Armbrust] Merge pull request #55 from marmbrus/mutableRows
ba28849 [Michael Armbrust] code review comments.
d994333 [Michael Armbrust] Remove copies before shuffle, this required changing the default shuffle serialization.
9049cf0 [Michael Armbrust] Extend MutablePair interface to support easy syntax for in-place updates. Also add a constructor so that it can be serialized out-of-the-box.
959bdf0 [Michael Armbrust] Don't silently swallow all KryoExceptions, only the one that indicates the end of a stream.
d371393 [Michael Armbrust] Add a framework for dealing with mutable rows to reduce the number of object allocations that occur in the critical path.
c9f8fb3 [Michael Armbrust] Merge pull request #53 from AndreSchumacher/parquet_support
3c3f962 [Michael Armbrust] Fix a bug due to array reuse. This will need to be revisited after we merge the mutable row PR.
7d0f13e [Michael Armbrust] Update parquet support with master.
9d419a6 [Michael Armbrust] Merge remote-tracking branch 'catalyst/catalystIntegration' into parquet_support
0040ae6 [Andre Schumacher] Feedback from code review
1ce01c7 [Michael Armbrust] Merge pull request #56 from liancheng/unapplySeqForRow
70e489d [Cheng Lian] Fixed a spelling typo
6d315bb [Cheng Lian] Added Row.unapplySeq to extract fields from a Row object.
8d5da5e [Michael Armbrust] modify compute-classpath.sh to include datanucleus jars explicitly
99e61fb [Michael Armbrust] Merge pull request #51 from marmbrus/expressionEval
7b9d142 [Michael Armbrust] Update travis to increase permgen size.
da9afbd [Michael Armbrust] Add byte wrappers for hive UDFS.
6fdefe6 [Michael Armbrust] Port sbt improvements from master.
296fe50 [Michael Armbrust] Address review feedback.
d7fbc3a [Michael Armbrust] Several performance enhancements and simplifications of the expression evaluation framework.
3bda72d [Andre Schumacher] Adding license banner to new files
3ac9eb0 [Andre Schumacher] Rebasing to new main branch
c863bed [Andre Schumacher] Codestyle checks
61e3bfb [Andre Schumacher] Adding WriteToFile operator and rewriting ParquetQuerySuite
3321195 [Andre Schumacher] Fixing one import in ParquetQueryTests.scala
3a0a552 [Andre Schumacher] Reorganizing Parquet table operations
18fdc44 [Andre Schumacher] Reworking Parquet metadata in relation and adding CREATE TABLE AS for Parquet tables
75262ee [Andre Schumacher] Integrating operations on Parquet files into SharkStrategies
f347273 [Andre Schumacher] Adding ParquetMetaData extraction, fixing schema projection
6a6bf98 [Andre Schumacher] Added column projections to ParquetTableScan
0f17d7b [Andre Schumacher] Rewriting ParquetRelation tests with RowWriteSupport
a11e364 [Andre Schumacher] Adding Parquet RowWriteSupport
6ad05b3 [Andre Schumacher] Moving ParquetRelation to spark.sql core
eb0e521 [Andre Schumacher] Fixing package names and other problems that came up after the rebase
99a9209 [Andre Schumacher] Expanding ParquetQueryTests to cover all primitive types
b33e47e [Andre Schumacher] First commit of Parquet import of primitive column types
c334386 [Michael Armbrust] Initial support for generating schema's based on case classes.
608a29e [Michael Armbrust] Add hive as a repl dependency
7413ac2 [Michael Armbrust] make test downloading quieter.
4d57d0e [Michael Armbrust] Fix test execution on travis.
5f2963c [Michael Armbrust] naming and continuous compilation fixes.
f5e7492 [Michael Armbrust] Add Apache license. Make naming more consistent.
3ac9416 [Michael Armbrust] Merge support for working with schema-ed RDDs using catalyst in as a spark subproject.
2225431 [Michael Armbrust] Merge pull request #48 from marmbrus/minorFixes
d393d2a [Michael Armbrust] Review Comments: Add comment to map that adds a sub query.
24eaa79 [Michael Armbrust] fix > 100 chars
6e04e5b [Michael Armbrust] Add insertIntoTable to the DSL.
df88f01 [Michael Armbrust] add a simple test for aggregation
18a861b [Michael Armbrust] Correctly convert nested products into nested rows when turning scala data into catalyst data.
b922511 [Michael Armbrust] Fix insertion of nested types into hive tables.
5fe7de4 [Michael Armbrust] Move table creation out of rule into a separate function.
a430895 [Michael Armbrust] Planning for logical Repartition operators.
532dd37 [Michael Armbrust] Allow the local warehouse path to be specified.
4905b2b [Michael Armbrust] Add more efficient TopK that avoids global sort for logical Sort => StopAfter.
8c01c24 [Michael Armbrust] Move definition of Row out of execution to top level sql package.
c9116a6 [Michael Armbrust] Add combiner to avoid NPE when spark performs external aggregation.
29effad [Michael Armbrust] Include alias in attributes that are produced by overridden tables.
9990ec7 [Michael Armbrust] Merge pull request #28 from liancheng/columnPruning
f22df3a [Michael Armbrust] Merge pull request #37 from yhuai/SerDe
cf4db59 [Lian, Cheng] Added golden answers for PruningSuite
54f165b [Lian, Cheng] Fixed spelling typo in two golden answer file names
2682f72 [Lian, Cheng] Merge remote-tracking branch 'origin/master' into columnPruning
c5a4fab [Lian, Cheng] Merge branch 'master' into columnPruning
f670c8c [Yin Huai] Throw a NotImplementedError for not supported clauses in a CTAS query.
128a9f8 [Yin Huai] Minor changes.
017872c [Yin Huai] Remove stats20 from whitelist.
a1a4776 [Yin Huai] Update comments.
feb022c [Yin Huai] Partitioning key should be case insensitive.
555fb1d [Yin Huai] Correctly set the extension for a text file.
d00260b [Yin Huai] Strips backticks from partition keys.
334aace [Yin Huai] New golden files.
a40d6d6 [Yin Huai] Loading the static partition specified in a INSERT INTO/OVERWRITE query.
428aff5 [Yin Huai] Distinguish `INSERT INTO` and `INSERT OVERWRITE`.
eea75c5 [Yin Huai] Correctly set codec.
45ffb86 [Yin Huai] Merge remote-tracking branch 'upstream/master' into SerDeNew
e089627 [Yin Huai] Code style.
563bb22 [Yin Huai] Set compression info in FileSinkDesc.
35c9a8a [Michael Armbrust] Merge pull request #46 from marmbrus/reviewFeedback
bdab5ed [Yin Huai] Add a TODO for loading data into partitioned tables.
5495fab [Yin Huai] Remove cloneRecords which is no longer needed.
1596e1b [Yin Huai] Cleanup imports to make IntelliJ happy.
3bb272d [Michael Armbrust] move org.apache.spark.sql package.scala to the correct location.
8506c17 [Michael Armbrust] Address review feedback.
3cb4f2e [Michael Armbrust] Merge pull request #45 from tnachen/master
9ad474d [Michael Armbrust] Merge pull request #44 from marmbrus/sampling
566fd66 [Timothy Chen] Whitelist tests and add support for Binary type
69adf72 [Yin Huai] Set cloneRecords to false.
a9c3188 [Timothy Chen] Fix udaf struct return
346f828 [Yin Huai] Move SharkHadoopWriter to the correct location.
59e37a3 [Yin Huai] Merge remote-tracking branch 'upstream/master' into SerDeNew
ed3a1d1 [Yin Huai] Load data directly into Hive.
7f206b5 [Michael Armbrust] Add support for hive TABLESAMPLE PERCENT.
b6de691 [Michael Armbrust] Merge pull request #43 from liancheng/fixMakefile
1f6260d [Lian, Cheng] Fixed package name and test suite name in Makefile
5ae010f [Michael Armbrust] Merge pull request #42 from markhamstra/non-ascii
678341a [Mark Hamstra] Replaced non-ascii text
887f928 [Yin Huai] Merge remote-tracking branch 'upstream/master' into SerDeNew
1f7d00a [Reynold Xin] Merge pull request #41 from marmbrus/splitComponents
7588a57 [Michael Armbrust] Break into 3 major components and move everything into the org.apache.spark.sql package.
bc9a12c [Michael Armbrust] Move hive test files.
5720d2b [Lian, Cheng] Fixed comment typo
f0c3742 [Lian, Cheng] Refactored PhysicalOperation
f235914 [Lian, Cheng] Test case udf_regex and udf_like need BooleanWritable registered
cf691df [Lian, Cheng] Added the PhysicalOperation to generalize ColumnPrunings
2407a21 [Lian, Cheng] Added optimized logical plan to debugging output
a7ad058 [Michael Armbrust] Merge pull request #40 from marmbrus/includeGoldens
9329820 [Michael Armbrust] add golden answer files to repository
dce0593 [Michael Armbrust] move golden answer to the source code directory.
964368f [Michael Armbrust] Merge pull request #39 from marmbrus/lateralView
7785ee6 [Michael Armbrust] Tighten visibility based on comments.
341116c [Michael Armbrust] address comments.
0e6c1d7 [Reynold Xin] Merge pull request #38 from yhuai/parseDBNameInCTAS
2897deb [Michael Armbrust] fix scaladoc
7123225 [Yin Huai] Correctly parse the db name and table name in INSERT queries.
b376d15 [Michael Armbrust] fix newlines at EOF
5cc367c [Michael Armbrust] use berkeley instead of cloudbees
ff5ea3f [Michael Armbrust] new golden
db92adc [Michael Armbrust] more tests passing. clean up logging.
740febb [Michael Armbrust] Tests for tgfs.
0ce61b0 [Michael Armbrust] Docs for GenericHiveUdtf.
ba8897f [Michael Armbrust] Merge remote-tracking branch 'yin/parseDBNameInCTAS' into lateralView
dd00b7e [Michael Armbrust] initial implementation of generators.
ea76cf9 [Michael Armbrust] Add NoRelation to planner.
bea4b7f [Michael Armbrust] Add SumDistinct.
016b489 [Michael Armbrust] fix typo.
acb9566 [Michael Armbrust] Correctly type attributes of CTAS.
8841eb8 [Michael Armbrust] Rename Transform -> ScriptTransformation.
02ff8e4 [Yin Huai] Correctly parse the db name and table name in a CTAS query.
5e4d9b4 [Michael Armbrust] Merge pull request #35 from marmbrus/smallFixes
5479066 [Reynold Xin] Merge pull request #36 from marmbrus/partialAgg
8017afb [Michael Armbrust] fix copy paste error.
dc6353b [Michael Armbrust] turn off deprecation
cab1a84 [Michael Armbrust] Fix PartialAggregate inheritance.
883006d [Michael Armbrust] improve tests.
32b615b [Michael Armbrust] add override to asPartial.
e1999f9 [Yin Huai] Use Deserializer and Serializer instead of AbstractSerDe.
f94345c [Michael Armbrust] fix doc link
d8cb805 [Michael Armbrust] Implement partial aggregation.
ccdb07a [Michael Armbrust] Fix bug where averages of strings are turned into sums of strings. Remove a blank line.
b4be6a5 [Michael Armbrust] better logging when applying rules.
67128b8 [Reynold Xin] Merge pull request #30 from marmbrus/complex
cb57459 [Michael Armbrust] blacklist machine specific test.
2f27604 [Michael Armbrust] Address comments / style errors.
389525d [Michael Armbrust] update golden, blacklist mr.
e3c10bd [Michael Armbrust] update whitelist.
44d343c [Michael Armbrust] Merge remote-tracking branch 'databricks/master' into complex
42ec4af [Michael Armbrust] improve complex type support in hive udfs/udafs.
ab5bff3 [Michael Armbrust] Support for get item of map types.
1679554 [Michael Armbrust] add toString for if and IS NOT NULL.
ab9a131 [Michael Armbrust] when UDFs fail they should return null.
25288d0 [Michael Armbrust] Implement [] for arrays and maps.
e7933e9 [Michael Armbrust] fix casting bug when working with fractional expressions.
010accb [Michael Armbrust] add tinyint to metastore type parser.
7a0f543 [Michael Armbrust] Avoid propagating types from unresolved nodes.
ac9d7de [Michael Armbrust] Resolve *s in Transform clauses.
692a477 [Michael Armbrust] Support for wrapping arrays to be written into hive tables.
92e4158 [Reynold Xin] Merge pull request #32 from marmbrus/tooManyProjects
9c06778 [Michael Armbrust] fix serialization issues, add JavaStringObjectInspector.
72a003d [Michael Armbrust] revert regex change
7661b6c [Michael Armbrust] blacklist machines specific tests
aa430e7 [Michael Armbrust] Update .travis.yml
e4def6b [Michael Armbrust] set dataType for HiveGenericUdfs.
5e54aa6 [Michael Armbrust] quotes for struct field names.
bbec500 [Michael Armbrust] update test coverage, new golden
3734a94 [Michael Armbrust] only quote string types.
3f9e519 [Michael Armbrust] use names w/ boolean args
5b3d2c8 [Michael Armbrust] implement distinct.
5b33216 [Michael Armbrust] work on decimal support.
2c6deb3 [Michael Armbrust] improve printing compatibility.
35a70fb [Michael Armbrust] multi-letter field names.
a9388fb [Michael Armbrust] printing for map types.
c3feda7 [Michael Armbrust] use toArray.
c654f19 [Michael Armbrust] Support for list and maps in hive table scan.
cf8d992 [Michael Armbrust] Use built in functions for creating temp directory.
1579eec [Michael Armbrust] Only cast unresolved inserts.
6420c7c [Michael Armbrust] Memoize the ordinal in the GetField expression.
da7ae9d [Michael Armbrust] Add boolean writable that was breaking udf_regexp test. Not sure how this was passing before...
6709441 [Michael Armbrust] Evaluation for accessing nested fields.
dc6463a [Michael Armbrust] Support for resolving access to nested fields using "." notation.
d670e41 [Michael Armbrust] Print nested fields like hive does.
efa7217 [Michael Armbrust] Support for reading structs in HiveTableScan.
9c22b4e [Michael Armbrust] Support for parsing nested types.
82163e3 [Michael Armbrust] special case handling of partitionKeys when casting insert into tables
ea6f37f [Michael Armbrust] fix style.
7845364 [Michael Armbrust] deactivate concurrent test.
b649c20 [Michael Armbrust] fix test logging / caching.
1590568 [Michael Armbrust] add log4j.properties
19bfd74 [Michael Armbrust] store hive output in circular buffer
dfb67aa [Michael Armbrust] add test case
cb775ac [Michael Armbrust] get rid of SharkContext singleton
2de89d0 [Michael Armbrust] Merge pull request #13 from tnachen/master
63003e9 [Michael Armbrust] Fix spacing.
41b41f3 [Michael Armbrust] Only cast unresolved inserts.
6eb5960 [Michael Armbrust] Merge remote-tracking branch 'databricks/master' into udafs
5b7afd8 [Michael Armbrust] Merge pull request #10 from yhuai/exchangeOperator
b1151a8 [Timothy Chen] Fix load data regex
8e0931f [Michael Armbrust] Cast to avoid using deprecated hive API.
e079f2b [Timothy Chen] Add GenericUDAF wrapper and HiveUDAFFunction
45b334b [Yin Huai] fix comments
235cbb4 [Yin Huai] Merge remote-tracking branch 'upstream/master' into exchangeOperator
fc67b50 [Yin Huai] Check for a Sort operator with the global flag set instead of an Exchange operator with a RangePartitioning.
6015f93 [Michael Armbrust] Merge pull request #29 from rxin/style
271e483 [Michael Armbrust] Update build status icon.
d3a3d48 [Michael Armbrust] add testing to travis
807b2d7 [Michael Armbrust] check style and publish docs with travis
d20b565 [Michael Armbrust] fix if style
bce024d [Michael Armbrust] Merge remote-tracking branch 'databricks/master' into style Disable if brace checking as it errors in single line functional cases unlike the style guide.
d91e276 [Michael Armbrust] Remove dependence on HIVE_HOME for running tests. This was done by moving all the hive query test (from branch-0.12) and data files into src/test/hive. These are used by default when HIVE_HOME is not set.
f47c2f6 [Yin Huai] set outputPartitioning in BroadcastNestedLoopJoin
41bbee6 [Yin Huai] Merge remote-tracking branch 'upstream/master' into exchangeOperator
7e24436 [Reynold Xin] Removed dependency on JDK 7 (nio.file).
5c1e600 [Reynold Xin] Added hash code implementation for AttributeReference
7213a2c [Reynold Xin] style fix for Hive.scala.
08e4d05 [Reynold Xin] First round of style cleanup.
605255e [Reynold Xin] Added scalastyle checker.
61e729c [Lian, Cheng] Added ColumnPrunings strategy and test cases
2486fb7 [Lian, Cheng] Fixed spelling
8ee41be [Lian, Cheng] Minor refactoring
ebb56fa [Michael Armbrust] add travis config
4c89d6e [Reynold Xin] Merge pull request #27 from marmbrus/moreTests
d4f539a [Michael Armbrust] blacklist mr and user specific tests.
677eb07 [Michael Armbrust] Update test whitelist.
5dab0bc [Michael Armbrust] Merge pull request #26 from liancheng/serdeAndPartitionPruning
c263c84 [Michael Armbrust] Only push predicates into partitioned table scans.
ab77882 [Michael Armbrust] upgrade spark to RC5.
c98ede5 [Lian, Cheng] Response to comments from @marmbrus
83d4520 [Yin Huai] marmbrus's comments
70994a3 [Lian, Cheng] Revert unnecessary Scaladoc changes
9ebff47 [Yin Huai] remove unnecessary .toSeq
e811d1a [Yin Huai] markhamstra's comments
4802f69 [Yin Huai] The outputPartitioning of a UnaryNode inherits its child's outputPartitioning by default. Also, update the logic in AddExchange to avoid unnecessary shuffling operations.
040fbdf [Yin Huai] AddExchange is the only place to add Exchange operators.
9fb357a [Yin Huai] use getSpecifiedDistribution to create Distribution. ClusteredDistribution and OrderedDistribution do not take Nil as inptu expressions.
e9347fc [Michael Armbrust] Remove broken scaladoc links.
99c6707 [Michael Armbrust] upgrade spark
57799ad [Lian, Cheng] Added special treat for HiveVarchar in InsertIntoHiveTable
cb49af0 [Lian, Cheng] Fixed Scaladoc links
4e5e4d4 [Lian, Cheng] Added PreInsertionCasts to do necessary casting before insertion
111ffdc [Lian, Cheng] More comments and minor reformatting
9e0d840 [Lian, Cheng] Added partition pruning optimization
761bbb8 [Lian, Cheng] Generalized BindReferences to run against any query plan
04eb5da [Yin Huai] Merge remote-tracking branch 'upstream/master' into exchangeOperator
9dd3b26 [Michael Armbrust] Fix scaladoc.
6f44cac [Lian, Cheng] Made TableReader & HadoopTableReader private to catalyst
7c92a41 [Lian, Cheng] Added Hive SerDe support
ce5fdd6 [Yin Huai] Merge remote-tracking branch 'upstream/master' into exchangeOperator
2957f31 [Yin Huai] addressed comments on PR
907db68 [Michael Armbrust] Space after while.
04573a0 [Reynold Xin] Merge pull request #24 from marmbrus/binaryCasts
4e50679 [Reynold Xin] Merge pull request #25 from marmbrus/rowOrderingWhile
5bc1dc2 [Yin Huai] Merge remote-tracking branch 'upstream/master' into exchangeOperator
be1fff7 [Michael Armbrust] Replace foreach with while in RowOrdering. Fixes#23
fd084a4 [Michael Armbrust] implement casts binary <=> string.
0b31176 [Michael Armbrust] Merge pull request #22 from rxin/type
548e479 [Yin Huai] merge master into exchangeOperator and fix code style
5b11db0 [Reynold Xin] Added Void to Boolean type widening.
9e3d989 [Reynold Xin] Made HiveTypeCoercion.WidenTypes more clear.
9bb1979 [Reynold Xin] Merge pull request #19 from marmbrus/variadicUnion
a2beb38 [Michael Armbrust] Merge pull request #21 from liancheng/fixIssue20
b20a4d4 [Lian, Cheng] Fix issue #20
6d6cb58 [Michael Armbrust] add source links that point to github to the scala doc.
4285962 [Michael Armbrust] Remove temporary test cases
167162f [Michael Armbrust] more merge errors, cleanup.
e170ccf [Michael Armbrust] Improve documentation and remove some spurious changes that were introduced by the merge.
6377d0b [Michael Armbrust] Drop empty files, fix if ().
c0b0e60 [Michael Armbrust] cleanup broken doc links.
330a88b [Michael Armbrust] Fix bugs in AddExchange.
4f345f2 [Michael Armbrust] Remove SortKey, use RowOrdering.
043e296 [Michael Armbrust] Make physical union nodes variadic.
ece15e1 [Michael Armbrust] update unit tests
5c89d2e [Michael Armbrust] Merge remote-tracking branch 'databricks/master' into exchangeOperator Fix deprecated use of combineValuesByKey. Get rid of test where the answer is dependent on the plan execution width.
9804eb5 [Michael Armbrust] upgrade spark
053a371 [Michael Armbrust] Merge pull request #15 from marmbrus/orderedRow
5ab18be [Michael Armbrust] Merge remote-tracking branch 'databricks/master' into orderedRow
ca2ff68 [Michael Armbrust] Merge pull request #17 from marmbrus/unionTypes
bf9161c [Michael Armbrust] Merge pull request #18 from marmbrus/noSparkAgg
563053f [Michael Armbrust] Address @rxin's comments.
6537c66 [Michael Armbrust] Address @rxin's comments.
2a76fc6 [Michael Armbrust] add notes from @rxin.
685bfa1 [Michael Armbrust] fix spelling
69ed98f [Michael Armbrust] Output a single row for empty Aggregations with no grouping expressions.
7859a86 [Michael Armbrust] Remove SparkAggregate. Its kinda broken and breaks RDD lineage.
fc22e01 [Michael Armbrust] whitelist newly passing union test.
3f547b8 [Michael Armbrust] Add support for widening types in unions.
53b95f8 [Michael Armbrust] coercion should not occur until children are resolved.
b892e32 [Michael Armbrust] Union is not resolved until the types match up.
95ab382 [Michael Armbrust] Use resolved instead of custom function. This is better because some nodes override the notion of resolved.
81a109d [Michael Armbrust] fix link.
f143f61 [Michael Armbrust] Implement sampling. Fixes a flaky test where the JVM notices that RAND as a Comparison method "violates its general contract!"
6cd442b [Michael Armbrust] Use numPartitions variable, fix grammar.
c800798 [Michael Armbrust] Add build status icon.
0cf5a75 [Michael Armbrust] Merge pull request #16 from marmbrus/filterPushDown
05d3a0d [Michael Armbrust] Refactor to avoid serializing ordering details with every row.
f2fdd77 [Michael Armbrust] fix required distribtion for aggregate.
658866e [Michael Armbrust] Pull back in changes made by @yhuai eliminating CoGroupedLocallyRDD.scala
583a337 [Michael Armbrust] break apart distribution and partitioning.
e8d41a9 [Michael Armbrust] Merge remote-tracking branch 'yin/exchangeOperator' into exchangeOperator
0ff8be7 [Michael Armbrust] Cleanup spurious changes and fix doc links.
73c70de [Yin Huai] add a first set of unit tests for data properties.
fbfa437 [Michael Armbrust] Merge remote-tracking branch 'databricks/master' into filterPushDown Minor doc improvements.
2b9d80f [Yin Huai] initial commit of adding exchange operators to physical plans.
fcbc03b [Michael Armbrust] Fix if ().
7b9080c [Michael Armbrust] Create OrderedRow class to allow ordering to be used by multiple operators.
b4adb0f [Michael Armbrust] Merge pull request #14 from marmbrus/castingAndTypes
b2a1ec5 [Michael Armbrust] add comment on how using numeric implicitly complicates spark serialization.
e286d20 [Michael Armbrust] address code review comments.
80d0681 [Michael Armbrust] fix scaladoc links.
de0c248 [Michael Armbrust] Print the executed plan in SharkQuery toString.
3413e61 [Michael Armbrust] Add mapChildren and withNewChildren methods to TreeNode.
404d552 [Michael Armbrust] Better exception when unbound attributes make it to evaluation.
fb84ae4 [Michael Armbrust] Refactor DataProperty into Distribution.
2abb0bc [Michael Armbrust] better debug messages, use exists.
098dfc4 [Michael Armbrust] Implement Long sorting again.
60f3a9a [Michael Armbrust] More aggregate functions out of the aggregate class to make things more readable.
a1ef62e [Michael Armbrust] Print the executed plan in SharkQuery toString.
dfce426 [Michael Armbrust] Add mapChildren and withNewChildren methods to TreeNode.
037a2ed [Michael Armbrust] Better exception when unbound attributes make it to evaluation.
ec90620 [Michael Armbrust] Support for Sets as arguments to TreeNode classes.
b21f803 [Michael Armbrust] Merge pull request #11 from marmbrus/goldenGen
83adb9d [Yin Huai] add DataProperty
5a26292 [Michael Armbrust] Rules to bring casting more inline with Hive semantics.
f0e0161 [Michael Armbrust] Move numeric types into DataTypes simplifying evaluator. This can probably also be use for codegen...
6d2924d [Michael Armbrust] add support for If. Not integrated in HiveQL yet.
ccc4dbf [Michael Armbrust] Add optimization rule to simplify casts.
058ec15 [Michael Armbrust] handle more writeables.
ffa9f25 [Michael Armbrust] blacklist some more MR tests.
aa2239c [Michael Armbrust] filter test lines containing Owner:
f71a325 [Michael Armbrust] Update golden jar.
a3003ae [Michael Armbrust] Update makefile to use better sharding support.
568d150 [Michael Armbrust] Updates to white/blacklist.
8351f25 [Michael Armbrust] Add an ignored test to remind us we don't do empty aggregations right.
c4104ec [Michael Armbrust] Numerous improvements to testing infrastructure. See comments for details.
09c6300 [Michael Armbrust] Add nullability information to StructFields.
5460b2d [Michael Armbrust] load srcpart by default.
3695141 [Michael Armbrust] Lots of parser improvements.
965ac9a [Michael Armbrust] Add expressions that allow access into complex types.
3ba53c9 [Michael Armbrust] Output type suffixes on AttributeReferences.
8777489 [Michael Armbrust] Initial support for operators that allow the user to specify partitioning.
e57f97a [Michael Armbrust] more decimal/null support.
e1440ed [Michael Armbrust] Initial support for function specific type conversions.
1814ed3 [Michael Armbrust] use childrenResolved function.
f2ec57e [Michael Armbrust] Begin supporting decimal.
6924e6e [Michael Armbrust] Handle NullTypes when resolving HiveUDFs
7fcfa8a [Michael Armbrust] Initial support for parsing unspecified partition parameters.
d0124f3 [Michael Armbrust] Correctly type null literals.
b65626e [Michael Armbrust] Initial support for parsing BigDecimal.
a90efda [Michael Armbrust] utility function for outputing string stacktraces.
7102f33 [Michael Armbrust] methods with side-effects should use ().
3ccaef7 [Michael Armbrust] add renaming TODO.
bc282c7 [Michael Armbrust] fix bug in getNodeNumbered
c8e89d5 [Michael Armbrust] memoize inputSet calculation.
6aefa46 [Michael Armbrust] Skip folding literals.
a72e540 [Michael Armbrust] Add IN operator.
04f885b [Michael Armbrust] literals are only non-nullable if they are not null.
35d2948 [Michael Armbrust] correctly order partition and normal attributes in hive relation output.
12fd52d [Michael Armbrust] support for sorting longs.
0606520 [Michael Armbrust] drop old comment.
859200a [Michael Armbrust] support for reading more types from the metastore.
1fedd18 [Michael Armbrust] coercion from null to numeric types
71e902d [Michael Armbrust] fix test cases.
cc06b6c [Michael Armbrust] Merge remote-tracking branch 'databricks/master' into interviewAnswer
8a8b521 [Reynold Xin] Merge pull request #8 from marmbrus/testImprovment
86355a6 [Michael Armbrust] throw error if there are unexpected join clauses.
c5842d2 [Michael Armbrust] don't throw an error when a select clause outputs multiple copies of the same attribute.
0e975ea [Michael Armbrust] parse bucket sampling as percentage sampling
a92919d [Michael Armbrust] add alter view as to native commands
f58d5a5 [Michael Armbrust] support for parsing SELECT DISTINCT
f0faa26 [Michael Armbrust] add sample and distinct operators.
ef7b943 [Michael Armbrust] add metastore support for float
e9f4588 [Michael Armbrust] fix > 100 char.
755b229 [Michael Armbrust] blacklist some ddl tests.
9ae740a [Michael Armbrust] blacklist more tests that require MR.
4cfc11a [Michael Armbrust] more test coverage.
0d9d56a [Michael Armbrust] add more native commands to parser
78d730d [Michael Armbrust] Load src test table on RESET.
8364ec2 [Michael Armbrust] whitelist all possible partition values.
b01468d [Michael Armbrust] support path rewrites when the query begins with a comment.
4c6b454 [Michael Armbrust] add option for recomputing the cached golden answer when tests fail.
4c5fb0f [Michael Armbrust] makefile target for building new whitelist.
4b6fed8 [Michael Armbrust] support for parsing both DESTINATION and INSERT_INTO.
516481c [Michael Armbrust] Ignore requests to explain native commands.
68aa2e6 [Michael Armbrust] Stronger type for Token extractor.
ca4ea26 [Michael Armbrust] Support for parsing UDF(*).
1aafea3 [Michael Armbrust] Configure partition whitelist in TestShark reset.
9627616 [Michael Armbrust] Use current database as default database.
9b02b44 [Michael Armbrust] Fix spelling error. Add failFast mode.
6f64cee [Michael Armbrust] don't line wrap string literal
eafaeed [Michael Armbrust] add type documentation
f54c94c [Michael Armbrust] make golden answers file a test dependency
5362365 [Michael Armbrust] push conditions into join
0d2388b [Michael Armbrust] Point at databricks hosted scaladoc.
73b29cd [Michael Armbrust] fix bad casting
9aa06c5 [Michael Armbrust] Merge pull request #7 from marmbrus/docFixes
7eff191 [Michael Armbrust] link all the expression names.
83227e4 [Michael Armbrust] fix scaladoc list syntax, add docs for some rules
9de6b74 [Michael Armbrust] fix language feature and deprecation warnings.
0b1960a [Michael Armbrust] Fix broken scala doc links / warnings.
b1acb36 [Michael Armbrust] Merge pull request #3 from yhuai/evalauteLiteralsInExpressions
01c00c2 [Michael Armbrust] new golden
5c14857 [Yin Huai] Merge remote-tracking branch 'upstream/master' into evalauteLiteralsInExpressions
b749b51 [Michael Armbrust] Merge pull request #5 from marmbrus/testCaching
66adceb [Michael Armbrust] Merge pull request #6 from marmbrus/joinWork
1a393da [Yin Huai] folded -> foldable
1e964ea [Yin Huai] update
a43d41c [Michael Armbrust] more tests passing!
8ca38d0 [Michael Armbrust] begin support for varchar / binary types.
ab8bbd1 [Michael Armbrust] parsing % operator
c16c8b5 [Michael Armbrust] case insensitive checking for hooks in tests.
3a90a5f [Michael Armbrust] simpler output when running a single test from the commandline.
5332fee [Yin Huai] Merge remote-tracking branch 'upstream/master' into evalauteLiteralsInExpressions
367fb9e [Yin Huai] update
0cd5cc6 [Michael Armbrust] add BIGINT cast parsing
61b266f [Michael Armbrust] comment for eliminate subqueries.
d72a5a2 [Michael Armbrust] add long to literal factory object.
b3bd15f [Michael Armbrust] blacklist more mr requiring tests.
e06fd38 [Michael Armbrust] black list map reduce tests.
8e7ce30 [Michael Armbrust] blacklist some env specific tests.
6250cbd [Michael Armbrust] Do not exit on test failure
b22b220 [Michael Armbrust] also look for cached hive test answers on the classpath.
b6e4899 [Yin Huai] formatting
e75c90d [Reynold Xin] Merge pull request #4 from marmbrus/hive12
5fabbec [Michael Armbrust] ignore partitioned scan test. scan seems to be working but there is some error about the table already existing?
9e190f5 [Michael Armbrust] drop unneeded ()
68b58c1 [Michael Armbrust] drop a few more tests.
b0aa400 [Michael Armbrust] update whitelist.
c99012c [Michael Armbrust] skip tests with hooks
db00ebf [Michael Armbrust] more types for hive udfs
dbc3678 [Michael Armbrust] update ghpages repo
138f53d [Yin Huai] addressed comments and added a space after a space after the defining keyword of every control structure.
6f954ee [Michael Armbrust] export the hadoop classpath when starting sbt, required to invoke hive during tests.
46bf41b [Michael Armbrust] add a makefile for priming the test answer cache in parallel. usage: "make -j 8 -i"
8d47ed4 [Yin Huai] comment
2795f05 [Yin Huai] comment
e003728 [Yin Huai] move OptimizerSuite to the package of catalyst.optimizer
2941d3a [Yin Huai] Merge remote-tracking branch 'upstream/master' into evalauteLiteralsInExpressions
0bd1688 [Yin Huai] update
6a7bd75 [Michael Armbrust] fix partition column delimiter configuration.
e942da1 [Michael Armbrust] Begin upgrade to Hive 0.12.0.
b8cd7e3 [Michael Armbrust] Merge pull request #7 from rxin/moreclean
52864da [Reynold Xin] Added executeCollect method to SharkPlan.
f0e1cbf [Reynold Xin] Added resolved lazy val to LogicalPlan.
b367e36 [Reynold Xin] Replaced the use of ??? with UnsupportedOperationException.
38124bd [Yin Huai] formatting
2924468 [Yin Huai] add two tests for testing pre-order and post-order tree traversal, respectively
555d839 [Reynold Xin] More cleaning ...
d48d0e1 [Reynold Xin] Code review feedback.
aa2e694 [Yin Huai] Merge remote-tracking branch 'upstream/master' into evalauteLiteralsInExpressions
5c421ac [Reynold Xin] Imported SharkEnv, SharkContext, and HadoopTableReader to remove Shark dependency.
479e055 [Reynold Xin] A set of minor changes, including: - import order - limit some lines to 100 character wide - inline code comment - more scaladocs - minor spacing (i.e. add a space after if)
da16e45 [Reynold Xin] Merge pull request #3 from rxin/packagename
e36caf5 [Reynold Xin] Renamed Rule.name to Rule.ruleName since name is used too frequently in the code base and is shadowed often by local scope.
72426ed [Reynold Xin] Rename shark2 package to execution.
0892153 [Reynold Xin] Merge pull request #2 from rxin/packagename
e58304a [Reynold Xin] Merge pull request #1 from rxin/gitignore
3f9fee1 [Michael Armbrust] rewrite push filter through join optimization.
c6527f5 [Reynold Xin] Moved the test src files into the catalyst directory.
c9777d8 [Reynold Xin] Put all source files in a catalyst directory.
019ea74 [Reynold Xin] Updated .gitignore to include IntelliJ files.
80ca4be [Timothy Chen] Address comments
0079392 [Michael Armbrust] support for multiple insert commands in a single query
75b5a01 [Michael Armbrust] remove space.
4283400 [Timothy Chen] Add limited predicate push down
e547e50 [Michael Armbrust] implement First.
e77c9b6 [Michael Armbrust] more work on unique join.
c795e06 [Michael Armbrust] improve star expansion
a26494e [Michael Armbrust] allow aliases to have qualifiers
d078333 [Michael Armbrust] remove extra space
a75c023 [Michael Armbrust] implement Coalesce
3a018b6 [Michael Armbrust] fix up docs.
ab6f67d [Michael Armbrust] import the string "null" as actual null.
5377c04 [Michael Armbrust] don't call dataType until checking if children are resolved.
191ce3e [Michael Armbrust] analyze rewrite test query.
60b1526 [Michael Armbrust] don't call dataType until checking if children are resolved.
2ab5a32 [Michael Armbrust] stop using uberjar as it has its own set of issues.
e42f75a [Michael Armbrust] Merge remote-tracking branch 'origin/master' into HEAD
c086a35 [Michael Armbrust] docs, spacing
c4060e4 [Michael Armbrust] cleanup
3b85462 [Michael Armbrust] more tests passing
bcfc8c5 [Michael Armbrust] start supporting partition attributes when inserting data.
c944a95 [Michael Armbrust] First aggregate expression.
1e28311 [Michael Armbrust] make tests execute in alpha order again
a287481 [Michael Armbrust] spelling
8492548 [Michael Armbrust] beginning of UNIQUEJOIN parsing.
a6ab6c7 [Michael Armbrust] add !=
4529594 [Michael Armbrust] draft of coalesce
70f253f [Michael Armbrust] more tests passing!
7349e7b [Michael Armbrust] initial support for test thrift table
d3c9305 [Michael Armbrust] fix > 100 char line
93b64b0 [Michael Armbrust] load test tables that are args to "DESCRIBE"
06b2aba [Michael Armbrust] don't be case sensitive when fixing load paths
6355d0e [Michael Armbrust] match actual return type of count with expected
cda43ab [Michael Armbrust] don't throw an exception when one of the join tables is empty.
fd4b096 [Michael Armbrust] fix casing of null strings as well.
4632695 [Michael Armbrust] support for megastore bigint
67b88cf [Michael Armbrust] more verbose debugging of evaluation return types
c680e0d [Michael Armbrust] Failed string => number conversion should return null.
2326be1 [Michael Armbrust] make getClauses case insensitive.
dac2786 [Michael Armbrust] correctly handle null values when going from string to numeric types.
045ac4b [Yin Huai] Merge remote-tracking branch 'upstream/master' into evalauteLiteralsInExpressions
fb5ddfd [Michael Armbrust] move ViewExamples to examples/
83833e8 [Michael Armbrust] more tests passing!
47c98d6 [Michael Armbrust] add query tests for like and hash.
1724c16 [Michael Armbrust] clear lines that contain last updated times.
cfd6bbc [Michael Armbrust] Quick skipping of tests that we can't even parse.
9b2642b [Michael Armbrust] make the blacklist support regexes
1d50af6 [Michael Armbrust] more datatypes, fix nonserializable instance variables in udfs
910e33e [Michael Armbrust] basic support for building an assembly jar.
d55bb52 [Michael Armbrust] add local warehouse/metastore to gitignore.
495d9dc [Michael Armbrust] Add an expression for when we decide to support LIKE natively instead of using the HIVE udf.
65f4e69 [Michael Armbrust] remove incorrect comments
0831a3c [Michael Armbrust] support for parsing some operator udfs.
6c27aa7 [Michael Armbrust] more cast parsing.
43db061 [Michael Armbrust] significant generalization of hive udf functionality.
3fe24ec [Michael Armbrust] better implementation of 3vl in Evaluate, fix some > 100 char lines.
e5690a6 [Michael Armbrust] add BinaryType
adab892 [Michael Armbrust] Clear out functions that are created during tests when reset is called.
d408021 [Michael Armbrust] support for printing out arrays in the output in the same form as hive (e.g., [e1, e1]).
8d5f504 [Michael Armbrust] Example of schema RDD using scala's dynamic trait, resulting in a more standard ORM style of usage.
21f0d91 [Michael Armbrust] Simple example of schemaRdd with scala filter function.
0daaa0e [Michael Armbrust] Promote booleans that appear in comparisons.
2b70abf [Michael Armbrust] true and false literals.
ef8b0a5 [Michael Armbrust] more tests.
14d070f [Michael Armbrust] add support for correctly extracting partition keys.
0afbe73 [Yin Huai] Merge remote-tracking branch 'upstream/master' into evalauteLiteralsInExpressions
69a0bd4 [Michael Armbrust] promote strings in predicates with number too.
3946e31 [Michael Armbrust] don't build strings unless assertion fails.
90c453d [Michael Armbrust] more tests passing!
6e6417a [Michael Armbrust] correct handling of nulls in boolean logic and sorting.
8000504 [Michael Armbrust] Improve type coercion.
9087152 [Michael Armbrust] fix toString of Not.
58b111c [Michael Armbrust] fix bad scaladoc tag.
d5c05c6 [Michael Armbrust] For now, ignore the big data benchmark tests when the data isn't there.
ac6376d [Michael Armbrust] Split out general shark query execution driver from test harness.
1d0ae1e [Michael Armbrust] Switch from IndexSeq[Any] to Row interface that will allow us unboxed access to primitive types.
d873b2b [Yin Huai] Remove numbers associated with test cases.
8545675 [Yin Huai] Merge remote-tracking branch 'upstream/master' into evalauteLiteralsInExpressions
b34a9eb [Michael Armbrust] Merge branch 'master' into filterPushDown
d1e7b8e [Michael Armbrust] Update README.md
c8b1553 [Michael Armbrust] Update README.md
9307ef9 [Michael Armbrust] update list of passing tests.
934c18c [Michael Armbrust] Filter out non-deterministic lines when comparing test answers.
a045c9c [Michael Armbrust] SparkAggregate doesn't actually support sum right now.
ae0024a [Yin Huai] update
cf80545 [Yin Huai] Merge remote-tracking branch 'origin/evalauteLiteralsInExpressions' into evalauteLiteralsInExpressions
21976ae [Yin Huai] update
b4999fe [Yin Huai] Merge remote-tracking branch 'upstream/filterPushDown' into evalauteLiteralsInExpressions
dedbf0c [Yin Huai] support Boolean literals
eaac9e2 [Yin Huai] explain the limitation of the current EvaluateLiterals
37817b5 [Yin Huai] add a comment to EvaluateLiterals.
468667f [Yin Huai] First draft of literal evaluation in the optimization phase. TreeNode has been extended to support transform in the post order. So, for an expression, we can evaluate literal from the leaf nodes of this expression tree. For an attribute reference in the expression node, we just leave it as is.
b1d1843 [Michael Armbrust] more work on big data benchmark tests.
cc9a957 [Michael Armbrust] support for creating test tables outside of TestShark
7d7fa9f [Michael Armbrust] support for create table as
5f54f03 [Michael Armbrust] parsing for ASC
d42b725 [Michael Armbrust] Sum of strings requires cast
34b30fa [Michael Armbrust] not all attributes need to be bound (e.g. output attributes that are contained in non-leaf operators.)
81659cb [Michael Armbrust] implement transform operator.
5cd76d6 [Michael Armbrust] break up the file based test case code for reuse
1031b65 [Michael Armbrust] support for case insensitive resolution.
320df04 [Michael Armbrust] add snapshot repo for databricks (has shark/spark snapshots)
b6f083e [Michael Armbrust] support for publishing scala doc to github from sbt
d9d18b4 [Michael Armbrust] debug logging implicit.
669089c [Yin Huai] support Boolean literals
ef3321e [Yin Huai] explain the limitation of the current EvaluateLiterals
73a05fd [Yin Huai] add a comment to EvaluateLiterals.
191eb7d [Yin Huai] First draft of literal evaluation in the optimization phase. TreeNode has been extended to support transform in the post order. So, for an expression, we can evaluate literal from the leaf nodes of this expression tree. For an attribute reference in the expression node, we just leave it as is.
80039cc [Yin Huai] Merge pull request #1 from yhuai/master
cbe1ca1 [Yin Huai] add explicit result type to the overloaded sideBySide
5c518e4 [Michael Armbrust] fix bug in test.
b50dd0e [Michael Armbrust] fix return type of overloaded method
05679b7 [Michael Armbrust] download assembly jar for easy compiling during interview.
8c60cc0 [Michael Armbrust] Update README.md
03b9526 [Michael Armbrust] First draft of optimizer tests.
f392755 [Michael Armbrust] Add flatMap to TreeNode
6cbe8d1 [Michael Armbrust] fix bug in side by side, add support for working with unsplit strings
15a53fc [Michael Armbrust] more generic sum calculation and better binding of grouping expressions.
06749d0 [Michael Armbrust] add expression enumerations for query plan operators and recursive version of transform expression.
4b0a888 [Michael Armbrust] implement string comparison and more casts.
356b321 [Michael Armbrust] Update README.md
3776395 [Michael Armbrust] Update README.md
304d17d [Michael Armbrust] Create README.md
b7d8be0 [Michael Armbrust] more tests passing.
b82481f [Michael Armbrust] add todo comment.
02e6dee [Michael Armbrust] add another test that breaks the harness to the blacklist.
cc5efe3 [Michael Armbrust] First draft of broadcast nested loop join with full outer support.
c43a259 [Michael Armbrust] comments
15ff448 [Michael Armbrust] better error message when a dsl test throws an exception
76ec650 [Michael Armbrust] fix join conditions
e10df99 [Michael Armbrust] Create new expr ids for local relations that exist more than once in a query plan.
91573a4 [Michael Armbrust] initial type promotion
e2ef4a5 [Michael Armbrust] logging
e43dc1e [Michael Armbrust] add string => int cast evaluation
f1f7e96 [Michael Armbrust] fix incorrect generation of join keys
2b27230 [Michael Armbrust] add depth based subtree access
0f6279f [Michael Armbrust] broken tests.
389bc0b [Michael Armbrust] support for partitioned columns in output.
12584f4 [Michael Armbrust] better errors for missing clauses. support for matching multiple clauses with the same name.
b67a225 [Michael Armbrust] better errors when types don't match up.
9e74808 [Michael Armbrust] add children resolved.
6d03ce9 [Michael Armbrust] defaults for unresolved relation
2469b00 [Michael Armbrust] skip nodes with unresolved children when doing coersions
be5ae2c [Michael Armbrust] better resolution logging
cb7b5af [Michael Armbrust] views example
420e05b [Michael Armbrust] more tests passing!
6916c63 [Michael Armbrust] Reading from partitioned hive tables.
a1245f9 [Michael Armbrust] more tests passing
956e760 [Michael Armbrust] extended explain
5f14c35 [Michael Armbrust] more test tables supported
175c43e [Michael Armbrust] better errors for parse exceptions
480ade5 [Michael Armbrust] don't use partial cached results.
8a9d21c [Michael Armbrust] fix evaluation
7aee69c [Michael Armbrust] parsing for joins, boolean logic
7fcf480 [Michael Armbrust] test for and logic
3ea9b00 [Michael Armbrust] don't use simpleString if there are no new lines.
6902490 [Michael Armbrust] fix boolean logic evaluation
4d5eba7 [Michael Armbrust] add more dsl for expression arithmetic and boolean logic
8b2a2ee [Michael Armbrust] more tests passing!
ad1f3b4 [Michael Armbrust] toString for null literals
a5c0a1b [Michael Armbrust] more test harness improvements: * regex whitelist * side by side answer comparison (still needs formatting work)
60ec19d [Michael Armbrust] initial support for udfs
c45b440 [Michael Armbrust] support for is (not) null and boolean logic
7f4a1dc [Michael Armbrust] add NoRelation logical operator
72e183b [Michael Armbrust] support for null values in tree node args.
ad596d2 [Michael Armbrust] add sc to Union's otherCopyArgs
e5c9d1a [Michael Armbrust] use nonEmpty
dcc4fe1 [Michael Armbrust] support for src1 test table.
c78b587 [Michael Armbrust] casting.
75c3f3f [Michael Armbrust] add support for logging with scalalogging.
da2c011 [Michael Armbrust] make it more obvious when results are being truncated.
96b73ba [Michael Armbrust] more docs in TestShark
18524fd [Michael Armbrust] add method to SharkSqlQuery for directly executing the same query on hive.
e6d063b [Michael Armbrust] more join tests.
664c1c3 [Michael Armbrust] make parsing of function names case insensitive.
0967d4e [Michael Armbrust] fix hardcoded path to hiveDevHome.
1a6db68 [Michael Armbrust] spelling
7638cb4 [Michael Armbrust] simple join execution with dsl tests. no hive tests yes.
859d4c9 [Michael Armbrust] better argString printing of nested trees.
fc53615 [Michael Armbrust] add same instance comparisons for tree nodes.
a026e6b [Michael Armbrust] move out hive specific operators
fff4d1c [Michael Armbrust] add simple query execution debugging
e2120ab [Michael Armbrust] sorting for strings
da06eb6 [Michael Armbrust] Parsing for sortby and joins
9eb5c5e [Michael Armbrust] override equality in Attribute references to compare exprId.
8eb2460 [Michael Armbrust] add system property to override whitelist.
88124bb [Michael Armbrust] make strategy evaluation lazy.
74a3a21 [Michael Armbrust] implement outputSet
d25b171 [Michael Armbrust] Add AND and OR expressions
67f0a4a [Michael Armbrust] dsl improvements: string to attribute, subquery, unionAll
12acf0a [Michael Armbrust] add .DS_Store for macs
f7da6ce [Michael Armbrust] add agg with grouping expr in select test
36805b3 [Michael Armbrust] pull out and improve aggregation
75613e1 [Michael Armbrust] better evaluations failure messages.
4789a35 [Michael Armbrust] weaken type since its hard to create pure references.
e89dd36 [Michael Armbrust] no newline for online trees
d0590d4 [Michael Armbrust] include stack trace for catalyst failures.
081c0d9 [Michael Armbrust] more generic computation of agg functions.
31af3a0 [Michael Armbrust] fail when clauses are unhandeled in the parser
ecd45b2 [Michael Armbrust] Add more passing tests.
97d5419 [Michael Armbrust] fix alignment.
565cc13 [Michael Armbrust] make the canary query optional.
a95e65c [Michael Armbrust] support for resolving qualified attribute references.
e1dfa0c [Michael Armbrust] better error reporting for comparison tests when hive works but catalyst fails.
4640a0b [Michael Armbrust] handle test tables when database is specified.
bef12e3 [Michael Armbrust] Add Subquery node and trivial optimizer to remove it after analysis.
fec5158 [Michael Armbrust] add hive / idea files to .gitignore
3f97ffe [Michael Armbrust] Rename Hive => HiveQl
656b836 [Michael Armbrust] Support for parsing select clause aliases.
3ca7414 [Michael Armbrust] StopAfter needs otherCopyArgs.
3ffde66 [Michael Armbrust] When the child of an alias is unresolved it should return an unresolved attribute instead of throwing an exception.
8cbef8a [Michael Armbrust] spelling
aa8c37c [Michael Armbrust] Better toString for SortOrder
1bb8b45 [Michael Armbrust] fix error message for UnresolvedExceptions
a2e0327 [Michael Armbrust] add a bunch of tests.
4a3e1ea [Michael Armbrust] docs and use shark for data loading.
339bb8f [Michael Armbrust] better docs, Not support
1d7b2d9 [Michael Armbrust] Add NaN conversions.
46a2534 [Michael Armbrust] only run canary query on failure.
8996066 [Michael Armbrust] remove protected from makeCopy
53bcf41 [Michael Armbrust] testing improvements: * reset hive vars * delete indexes and tables * delete database * reset to use default database * record tests that pass
04a372a [Michael Armbrust] add a flag for running all tests.
3b2235b [Michael Armbrust] More general implementation of arithmetic.
edd7795 [Michael Armbrust] More testing improvements: * Check that results match for native commands * Ensure explain commands can be planned * Cache hive "golden" results
da6c577 [Michael Armbrust] add string <==> file utility functions.
3adf5ca [Michael Armbrust] Initial support for groupBy and count.
7bcd8a4 [Michael Armbrust] Improvements to comparison tests: * Sort answer when query doesn't contain an order by. * Display null values the same as Hive. * Print full query results in easy to read format when they differ.
a52e7c9 [Michael Armbrust] Transform children that are present in sequences of the product.
d66ba7e [Michael Armbrust] drop printlns.
88f2efd [Michael Armbrust] Add sum / count distinct expressions.
05adedc [Michael Armbrust] rewrite relative paths when loading data in TestShark
07784b3 [Michael Armbrust] add support for rewriting paths and running 'set' commands.
b8a9910 [Michael Armbrust] quote tests passing.
8e5e267 [Michael Armbrust] handle aliased select expressions.
4286a96 [Michael Armbrust] drop debugging println
ac34aeb [Michael Armbrust] proof of concept for hive ast transformations.
2238b00 [Michael Armbrust] better error when makeCopy functions fails due to incorrect arguments
ff1eab8 [Michael Armbrust] start trying to make insert into hive table more general.
74a6337 [Michael Armbrust] use fastEquals when doing transformations.
1184a23 [Michael Armbrust] add native test for escapes.
b972b18 [Michael Armbrust] create BaseRelation class
fa6bce9 [Michael Armbrust] implement union
6391a87 [Michael Armbrust] count aggregate.
d47c317 [Michael Armbrust] add unary minus, more tests passing.
c7114e4 [Michael Armbrust] first draft of star expansion.
044c43d [Michael Armbrust] better support for numeric literal parsing.
1d0f072 [Michael Armbrust] use native drop table as it doesn't appear to fail when the "table" is actually a view.
61503c5 [Michael Armbrust] add cached toRdd
2036883 [Michael Armbrust] skip explain queries when testing.
ebac4b1 [Michael Armbrust] fix bug in sort reference calculation
ca0dee0 [Michael Armbrust] docs.
1ee0471 [Michael Armbrust] string literal parsing.
357278b [Michael Armbrust] add limit support
9b3e479 [Michael Armbrust] creation of string literals.
02efa30 [Michael Armbrust] alias evaluation
cb68b33 [Michael Armbrust] parsing for random sample in hive ql.
126dd36 [Michael Armbrust] include query plans in failure output
bb59ae9 [Michael Armbrust] doc fixes
7e68286 [Michael Armbrust] fix confusing naming
768bb25 [Michael Armbrust] handle errors in shark query toString
829c3ce [Michael Armbrust] Auto loading of test data on demand. Add reset method to test shark. Make test shark a singleton to avoid weirdness with the hive megastore.
ad02e41 [Michael Armbrust] comment jdo dependency
7bc89fe [Michael Armbrust] add collect to TreeNode.
438cf74 [Michael Armbrust] create explicit treeString function in addition to toString override. docs.
09679ee [Michael Armbrust] fix bug in TreeNode foreach
2930b27 [Michael Armbrust] more specific name for del query tests.
8842549 [Michael Armbrust] docs.
da81f81 [Michael Armbrust] Implementation and tests for simple AVG query in Hive SQL.
a8969b9 [Michael Armbrust] Factor out hive query comparison test framework.
1a7efb0 [Michael Armbrust] specialize spark aggregate for global aggregations.
a36dd9a [Michael Armbrust] evaluation for other > data types.
cae729b [Michael Armbrust] remove unnecessary lazy vals.
d8e12af [Michael Armbrust] docs
3a60d67 [Michael Armbrust] implement average, placeholder for count
f05c106 [Michael Armbrust] checkAnswer handles single row results.
2730534 [Michael Armbrust] implement inputSet
a9aa79d [Michael Armbrust] debugging for sort exec
8bec3c9 [Michael Armbrust] better tree makeCopy when there are two constructors.
554b4b2 [Michael Armbrust] BoundAttribute pretty printing.
754f5fa [Michael Armbrust] dsl for setting nullability
a206d7a [Michael Armbrust] clean up query tests.
84ad6ef [Michael Armbrust] better sort implementation and tests.
de24923 [Michael Armbrust] add double type.
9611a2c [Michael Armbrust] literal creation for doubles.
7358313 [Michael Armbrust] sort order returns child type.
b544715 [Michael Armbrust] implement eval for rand, and > for doubles
7013bad [Michael Armbrust] asc, desc should work for expressions and unresolved attributes (symbols)
1c1a35e [Michael Armbrust] add simple Rand expression.
3ca51de [Michael Armbrust] add orderBy to dsl
7ae41ab [Michael Armbrust] more literal implicit conversions
b18b675 [Michael Armbrust] First cut at native query tests for shark.
d392e29 [Michael Armbrust] add toRdd implicit conversion for logical plans in TestShark.
5eac895 [Michael Armbrust] better error when descending is specified.
2b16f86 [Michael Armbrust] add todo
e527bb8 [Michael Armbrust] remove arguments to binary predicate constructor as they seem to break serialization
9dde3c8 [Michael Armbrust] add project and filter operations.
ad9037b [Michael Armbrust] Add support for local relations.
6227143 [Michael Armbrust] evaluation of Equals.
7526290 [Michael Armbrust] BoundReference should also be an Attribute.
bd33e26 [Michael Armbrust] more documentation
5de0ea3 [Michael Armbrust] Move all shark specific into a separate package. Lots of documentation improvements.
0ae292b [Michael Armbrust] implement calculation of sort expressions.
9fd5011 [Michael Armbrust] First cut at expression evaluation.
6259e3a [Michael Armbrust] cleanup
787e5a2 [Michael Armbrust] use fastEquals
f90da36 [Michael Armbrust] better printing of optimization exceptions
b05dd67 [Michael Armbrust] Application of rules to fixed point.
bb2e0db [Michael Armbrust] pretty print for literals.
1ec3287 [Michael Armbrust] Add extractor for IntegerLiterals.
d3a3687 [Michael Armbrust] add fastEquals
2b4935b [Michael Armbrust] set sbt.version explicitly
46dfd7f [Michael Armbrust] first cut at checking answer for HiveCompatability tests.
c79f2fd [Michael Armbrust] insert operator should return an empty rdd.
14c22ec [Michael Armbrust] implement sorting when the sort expression is the first attribute of the input.
ae7b4c3 [Michael Armbrust] remove implicit dependencies. now compiles without copying things into lib/ manually.
84082f9 [Michael Armbrust] add sbt binaries and scripts
15371a8 [Michael Armbrust] First draft of simple Hive DDL parser.
063bf44 [Michael Armbrust] Periods should end all comments.
e1f7f4c [Michael Armbrust] Remove "NativePlaceholder" hack.
ed3633e [Michael Armbrust] start consolidating Hive/Shark specific code. first hive compatibility test case passing!
b34a770 [Michael Armbrust] Add data sink strategy, make strategy application a little more robust.
e7174ec [Michael Armbrust] fix schema, add docs, make helper method protected.
26f410a [Michael Armbrust] physical traits should extend PhysicalPlan.
dc72469 [Michael Armbrust] beginning of hive compatibility testing framework.
0763490 [Michael Armbrust] support for hive native command pass-through.
d8a924f [Michael Armbrust] scaladoc
29a7163 [Michael Armbrust] Insert into hive table physical operator.
633cebc [Michael Armbrust] better error message when there is no appropriate planning strategy.
59ac444 [Michael Armbrust] add unary expression
3aa1b28 [Michael Armbrust] support for table names in the form 'database.tableName'
665f7d0 [Michael Armbrust] add logical nodes for hive data sinks.
64d2923 [Michael Armbrust] Add classes for representing sorts.
f72b7ce [Michael Armbrust] first trivial end to end query execution.
5c7d244 [Michael Armbrust] first draft of references implementation.
7bff274 [Michael Armbrust] point at new shark.
c7cd57f [Michael Armbrust] docs for util function.
910811c [Michael Armbrust] check each item of the sequence
ef21a0b [Michael Armbrust] line up comments.
4b765d5 [Michael Armbrust] docs, drop println
6f9bafd [Michael Armbrust] empty output for unresolved relation to avoid exception in resolution.
a703c49 [Michael Armbrust] this order works better until fixed point is implemented.
ec1d7c0 [Michael Armbrust] Simple attribute resolution.
069df02 [Michael Armbrust] parsing binary predicates
a1cf754 [Michael Armbrust] add joins and equality.
3f5bc98 [Michael Armbrust] add optiq to sbt.
54f3460 [Michael Armbrust] initial optiq parsing.
d9161ce [Michael Armbrust] add join operator
1e423eb [Michael Armbrust] placeholders in LogicalPlan, docs
24ef6fb [Michael Armbrust] toString for alias.
ae7d776 [Michael Armbrust] add nullability changing function
d49dc02 [Michael Armbrust] scaladoc for named exprs
7c45dd7 [Michael Armbrust] pretty printing of trees.
78e34bf [Michael Armbrust] simple git ignore.
7ba19be [Michael Armbrust] First draft of interface to hive metastore.
7e7acf0 [Michael Armbrust] physical placeholder.
1c11136 [Michael Armbrust] first draft of error handling / plans for debugging.
3766a41 [Michael Armbrust] rearrange utility functions.
7fb3d5e [Michael Armbrust] docs and equality improvements.
45da47b [Michael Armbrust] flesh out plans and expressions a little. first cut at named expressions.
002d4d4 [Michael Armbrust] default to no alias.
be25003 [Michael Armbrust] add repl initialization to sbt.
0608a00 [Michael Armbrust] tighten public interface
a1a8b38 [Michael Armbrust] test that ids don't change for no-op transforms.
daa71ca [Michael Armbrust] foreach, maps, and scaladoc
6a158cb [Michael Armbrust] simple transform working.
db0299f [Michael Armbrust] basic analysis of relations minus transform function.
f74c4ee [Michael Armbrust] parsing a simple query.
08e4f57 [Michael Armbrust] upgrade scala include shark.
d3c6404 [Michael Armbrust] initial commit
