Given that a lot of users are trying to use hive 0.13 in spark, and the incompatibility between hive-0.12 and hive-0.13 on the API level I want to propose following approach, which has no or minimum impact on existing hive-0.12 support, but be able to jumpstart the development of hive-0.13 and future version support.
Approach: Introduce “hive-version” property, and manipulate pom.xml files to support different hive version at compiling time through shim layer, e.g., hive-0.12.0 and hive-0.13.1. More specifically,
1. For each different hive version, there is a very light layer of shim code to handle API differences, sitting in sql/hive/hive-version, e.g., sql/hive/v0.12.0 or sql/hive/v0.13.1
2. Add a new profile hive-default active by default, which picks up all existing configuration and hive-0.12.0 shim (v0.12.0) if no hive.version is specified.
3. If user specifies different version (currently only 0.13.1 by -Dhive.version = 0.13.1), hive-versions profile will be activated, which pick up hive-version specific shim layer and configuration, mainly the hive jars and hive-version shim, e.g., v0.13.1.
4. With this approach, nothing is changed with current hive-0.12 support.
No change by default: sbt/sbt -Phive
For example: sbt/sbt -Phive -Pyarn -Phadoop-2.4 -Dhadoop.version=2.4.0 assembly
To enable hive-0.13: sbt/sbt -Dhive.version=0.13.1
For example: sbt/sbt -Dhive.version=0.13.1 -Pyarn -Phadoop-2.4 -Dhadoop.version=2.4.0 assembly
Note that in hive-0.13, hive-thriftserver is not enabled, which should be fixed by other Jira, and we don’t need -Phive with -Dhive.version in building (probably we should use -Phive -Dhive.version=xxx instead after thrift server is also supported in hive-0.13.1).
Author: Zhan Zhang <zhazhan@gmail.com>
Author: zhzhan <zhazhan@gmail.com>
Author: Patrick Wendell <pwendell@gmail.com>
Closes#2241 from zhzhan/spark-2706 and squashes the following commits:
3ece905 [Zhan Zhang] minor fix
410b668 [Zhan Zhang] solve review comments
cbb4691 [Zhan Zhang] change run-test for new options
0d4d2ed [Zhan Zhang] rebase
497b0f4 [Zhan Zhang] Merge branch 'master' of https://github.com/apache/spark
8fad1cf [Zhan Zhang] change the pom file and make hive-0.13.1 as the default
ab028d1 [Zhan Zhang] rebase
4a2e36d [Zhan Zhang] Merge branch 'master' of https://github.com/apache/spark
4cb1b93 [zhzhan] Merge pull request #1 from pwendell/pr-2241
b0478c0 [Patrick Wendell] Changes to simplify the build of SPARK-2706
2b50502 [Zhan Zhang] rebase
a72c0d4 [Zhan Zhang] Merge branch 'master' of https://github.com/apache/spark
cb22863 [Zhan Zhang] correct the typo
20f6cf7 [Zhan Zhang] solve compatability issue
f7912a9 [Zhan Zhang] rebase and solve review feedback
301eb4a [Zhan Zhang] Merge branch 'master' of https://github.com/apache/spark
10c3565 [Zhan Zhang] address review comments
6bc9204 [Zhan Zhang] rebase and remove temparory repo
d3aa3f2 [Zhan Zhang] Merge branch 'master' into spark-2706
cedcc6f [Zhan Zhang] Merge branch 'master' of https://github.com/apache/spark
3ced0d7 [Zhan Zhang] rebase
d9b981d [Zhan Zhang] rebase and fix error due to rollback
adf4924 [Zhan Zhang] Merge branch 'master' of https://github.com/apache/spark
3dd50e8 [Zhan Zhang] solve conflicts and remove unnecessary implicts
d10bf00 [Zhan Zhang] Merge branch 'master' of https://github.com/apache/spark
dc7bdb3 [Zhan Zhang] solve conflicts
7e0cc36 [Zhan Zhang] Merge branch 'master' of https://github.com/apache/spark
d7c3e1e [Zhan Zhang] Merge branch 'master' into spark-2706
68deb11 [Zhan Zhang] Merge branch 'master' of https://github.com/apache/spark
d48bd18 [Zhan Zhang] address review comments
3ee3b2b [Zhan Zhang] Merge branch 'master' of https://github.com/apache/spark
57ea52e [Zhan Zhang] Merge branch 'master' into spark-2706
2b0d513 [Zhan Zhang] Merge branch 'master' of https://github.com/apache/spark
9412d24 [Zhan Zhang] address review comments
f4af934 [Zhan Zhang] rebase
1ccd7cc [Zhan Zhang] Merge branch 'master' of https://github.com/apache/spark
128b60b [Zhan Zhang] ignore 0.12.0 test cases for the time being
af9feb9 [Zhan Zhang] Merge branch 'master' of https://github.com/apache/spark
5f5619f [Zhan Zhang] restructure the directory and different hive version support
05d3683 [Zhan Zhang] solve conflicts
e4c1982 [Zhan Zhang] Merge branch 'master' of https://github.com/apache/spark
94b4fdc [Zhan Zhang] Spark-2706: hive-0.13.1 support on spark
87ebf3b [Zhan Zhang] Merge branch 'master' into spark-2706
921e914 [Zhan Zhang] Merge branch 'master' of https://github.com/apache/spark
f896b2a [Zhan Zhang] Merge branch 'master' into spark-2706
789ea21 [Zhan Zhang] Merge branch 'master' of https://github.com/apache/spark
cb53a2c [Zhan Zhang] Merge branch 'master' of https://github.com/apache/spark
f6a8a40 [Zhan Zhang] revert
ba14f28 [Zhan Zhang] test
dbedff3 [Zhan Zhang] Merge remote-tracking branch 'upstream/master'
70964fe [Zhan Zhang] revert
fe0f379 [Zhan Zhang] Merge branch 'master' of https://github.com/zhzhan/spark
70ffd93 [Zhan Zhang] revert
42585ec [Zhan Zhang] test
7d5fce2 [Zhan Zhang] test
redundant methods for broadcast in ```TableReader```
Author: wangfei <wangfei1@huawei.com>
Closes#2862 from scwf/TableReader and squashes the following commits:
414cc24 [wangfei] unnecessary methods for broadcast
SparkSql crashes on selecting tables using custom serde.
Example:
----------------
CREATE EXTERNAL TABLE table_name PARTITIONED BY ( a int) ROW FORMAT 'SERDE "org.apache.hadoop.hive.serde2.thrift.ThriftDeserializer" with serdeproperties("serialization.format"="org.apache.thrift.protocol.TBinaryProtocol","serialization.class"="ser_class") STORED AS SEQUENCEFILE;
The following exception is seen on running a query like 'select * from table_name limit 1':
ERROR CliDriver: org.apache.hadoop.hive.serde2.SerDeException: java.lang.NullPointerException
at org.apache.hadoop.hive.serde2.thrift.ThriftDeserializer.initialize(ThriftDeserializer.java:68)
at org.apache.hadoop.hive.ql.plan.TableDesc.getDeserializer(TableDesc.java:80)
at org.apache.spark.sql.hive.execution.HiveTableScan.addColumnMetadataToConf(HiveTableScan.scala:86)
at org.apache.spark.sql.hive.execution.HiveTableScan.<init>(HiveTableScan.scala:100)
at org.apache.spark.sql.hive.HiveStrategies$HiveTableScans$$anonfun$14.apply(HiveStrategies.scala:188)
at org.apache.spark.sql.hive.HiveStrategies$HiveTableScans$$anonfun$14.apply(HiveStrategies.scala:188)
at org.apache.spark.sql.SQLContext$SparkPlanner.pruneFilterProject(SQLContext.scala:364)
at org.apache.spark.sql.hive.HiveStrategies$HiveTableScans$.apply(HiveStrategies.scala:184)
at org.apache.spark.sql.catalyst.planning.QueryPlanner$$anonfun$1.apply(QueryPlanner.scala:58)
at org.apache.spark.sql.catalyst.planning.QueryPlanner$$anonfun$1.apply(QueryPlanner.scala:58)
at scala.collection.Iterator$$anon$13.hasNext(Iterator.scala:371)
at org.apache.spark.sql.catalyst.planning.QueryPlanner.apply(QueryPlanner.scala:59)
at org.apache.spark.sql.catalyst.planning.QueryPlanner.planLater(QueryPlanner.scala:54)
at org.apache.spark.sql.execution.SparkStrategies$BasicOperators$.apply(SparkStrategies.scala:280)
at org.apache.spark.sql.catalyst.planning.QueryPlanner$$anonfun$1.apply(QueryPlanner.scala:58)
at org.apache.spark.sql.catalyst.planning.QueryPlanner$$anonfun$1.apply(QueryPlanner.scala:58)
at scala.collection.Iterator$$anon$13.hasNext(Iterator.scala:371)
at org.apache.spark.sql.catalyst.planning.QueryPlanner.apply(QueryPlanner.scala:59)
at org.apache.spark.sql.SQLContext$QueryExecution.sparkPlan$lzycompute(SQLContext.scala:402)
at org.apache.spark.sql.SQLContext$QueryExecution.sparkPlan(SQLContext.scala:400)
at org.apache.spark.sql.SQLContext$QueryExecution.executedPlan$lzycompute(SQLContext.scala:406)
at org.apache.spark.sql.SQLContext$QueryExecution.executedPlan(SQLContext.scala:406)
at org.apache.spark.sql.hive.HiveContext$QueryExecution.stringResult(HiveContext.scala:406)
at org.apache.spark.sql.hive.thriftserver.SparkSQLDriver.run(SparkSQLDriver.scala:59)
at org.apache.spark.sql.hive.thriftserver.SparkSQLCLIDriver.processCmd(SparkSQLCLIDriver.scala:291)
at org.apache.hadoop.hive.cli.CliDriver.processLine(CliDriver.java:413)
at org.apache.spark.sql.hive.thriftserver.SparkSQLCLIDriver$.main(SparkSQLCLIDriver.scala:226)
at org.apache.spark.sql.hive.thriftserver.SparkSQLCLIDriver.main(SparkSQLCLIDriver.scala)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(Unknown Source)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(Unknown Source)
at java.lang.reflect.Method.invoke(Unknown Source)
at org.apache.spark.deploy.SparkSubmit$.launch(SparkSubmit.scala:328)
at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:75)
at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)
Caused by: java.lang.NullPointerException
Author: chirag <chirag.aggarwal@guavus.com>
Closes#2674 from chiragaggarwal/branch-1.1 and squashes the following commits:
370c31b [chirag] SPARK-3807: Add a test case to validate the fix.
1f26805 [chirag] SPARK-3807: SparkSql does not work for tables created using custom serde (Incorporated Review Comments)
ba4bc0c [chirag] SPARK-3807: SparkSql does not work for tables created using custom serde
5c73b72 [chirag] SPARK-3807: SparkSql does not work for tables created using custom serde
(cherry picked from commit 925e22d313)
Signed-off-by: Michael Armbrust <michael@databricks.com>
Author: Venkata Ramana G <ramana.gollamudihuawei.com>
Author: Venkata Ramana Gollamudi <ramana.gollamudi@huawei.com>
Closes#2713 from gvramana/remove_unnecessary_columns and squashes the following commits:
b7ba768 [Venkata Ramana Gollamudi] Added comment and checkstyle fix
6a93459 [Venkata Ramana Gollamudi] cloned hiveconf for each TableScanOperators so that only required columns are added
There are lots of temporal files created by TestHive under the /tmp by default, which may cause potential performance issue for testing. This PR will automatically delete them after test exit.
Author: Cheng Hao <hao.cheng@intel.com>
Closes#2393 from chenghao-intel/delete_temp_on_exit and squashes the following commits:
3a6511f [Cheng Hao] Remove the temp dir after text exit
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
The queries like SELECT a.key FROM (SELECT key FROM src) \`a\` does not work as backticks in subquery aliases are not handled properly. This PR fixes that.
Author : ravipesala ravindra.pesalahuawei.com
Author: ravipesala <ravindra.pesala@huawei.com>
Closes#2737 from ravipesala/SPARK-3834 and squashes the following commits:
0e0ab98 [ravipesala] Fixing issue in backtick handling for subquery aliases
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
Author: Vida Ha <vida@databricks.com>
Closes#2621 from vidaha/vida/SPARK-3752 and squashes the following commits:
d7fdbbc [Vida Ha] Add tests for different UDF's
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.
Builds all wrappers at first according to object inspector types to avoid per row costs.
Author: Cheng Lian <lian.cs.zju@gmail.com>
Closes#2592 from liancheng/hive-value-wrapper and squashes the following commits:
9696559 [Cheng Lian] Passes all tests
4998666 [Cheng Lian] Prevents per row dynamic dispatching and pattern matching when inserting Hive values
Includes partition keys into account when applying `PreInsertionCasts` rule.
Author: Cheng Lian <lian.cs.zju@gmail.com>
Closes#2672 from liancheng/fix-pre-insert-casts and squashes the following commits:
def1a1a [Cheng Lian] Makes PreInsertionCasts handle partitions properly
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
Do not use TestSQLContext in JavaHiveQLSuite, that may lead to two SparkContexts in one jvm and enable JavaHiveQLSuite
Author: scwf <wangfei1@huawei.com>
Closes#2652 from scwf/fix-JavaHiveQLSuite and squashes the following commits:
be35c91 [scwf] enable JavaHiveQLSuite
It should just use `maxResults` there.
Author: Liang-Chi Hsieh <viirya@gmail.com>
Closes#2654 from viirya/trivial_fix and squashes the following commits:
1362289 [Liang-Chi Hsieh] Trivial fix to make codes more readable.
This is a follow up of #2226 and #2616 to fix Jenkins master SBT build failures for lower Hadoop versions (1.0.x and 2.0.x).
The root cause is the semantics difference of `FileSystem.globStatus()` between different versions of Hadoop, as illustrated by the following test code:
```scala
object GlobExperiments extends App {
val conf = new Configuration()
val fs = FileSystem.getLocal(conf)
fs.globStatus(new Path("/tmp/wh/*/*/*")).foreach { status =>
println(status.getPath)
}
}
```
Target directory structure:
```
/tmp/wh
├── dir0
│ ├── dir1
│ │ └── level2
│ └── level1
└── level0
```
Hadoop 2.4.1 result:
```
file:/tmp/wh/dir0/dir1/level2
```
Hadoop 1.0.4 resuet:
```
file:/tmp/wh/dir0/dir1/level2
file:/tmp/wh/dir0/level1
file:/tmp/wh/level0
```
In #2226 and #2616, we call `FileOutputCommitter.commitJob()` at the end of the job, and the `_SUCCESS` mark file is written. When working with lower Hadoop versions, due to the `globStatus()` semantics issue, `_SUCCESS` is included as a separate partition data file by `Hive.loadDynamicPartitions()`, and fails partition spec checking. The fix introduced in this PR is kind of a hack: when inserting data with dynamic partitioning, we intentionally avoid writing the `_SUCCESS` marker to workaround this issue.
Hive doesn't suffer this issue because `FileSinkOperator` doesn't call `FileOutputCommitter.commitJob()`, instead, it calls `Utilities.mvFileToFinalPath()` to cleanup the output directory and then loads it into Hive warehouse by with `loadDynamicPartitions()`/`loadPartition()`/`loadTable()`. This approach is better because it handles failed job and speculative tasks properly. We should add this step to `InsertIntoHiveTable` in another PR.
Author: Cheng Lian <lian.cs.zju@gmail.com>
Closes#2663 from liancheng/dp-hadoop-1-fix and squashes the following commits:
0177dae [Cheng Lian] Fixes dynamic partitioning support for lower Hadoop versions
_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.
PR #2226 was reverted because it broke Jenkins builds for unknown reason. This debugging PR aims to fix the Jenkins build.
This PR also fixes two bugs:
1. Compression configurations in `InsertIntoHiveTable` are disabled by mistake
The `FileSinkDesc` object passed to the writer container doesn't have compression related configurations. These configurations are not taken care of until `saveAsHiveFile` is called. This PR moves compression code forward, right after instantiation of the `FileSinkDesc` object.
1. `PreInsertionCasts` doesn't take table partitions into account
In `castChildOutput`, `table.attributes` only contains non-partition columns, thus for partitioned table `childOutputDataTypes` never equals to `tableOutputDataTypes`. This results funny analyzed plan like this:
```
== Analyzed Logical Plan ==
InsertIntoTable Map(partcol1 -> None, partcol2 -> None), false
MetastoreRelation default, dynamic_part_table, None
Project [c_0#1164,c_1#1165,c_2#1166]
Project [c_0#1164,c_1#1165,c_2#1166]
Project [c_0#1164,c_1#1165,c_2#1166]
... (repeats 99 times) ...
Project [c_0#1164,c_1#1165,c_2#1166]
Project [c_0#1164,c_1#1165,c_2#1166]
Project [1 AS c_0#1164,1 AS c_1#1165,1 AS c_2#1166]
Filter (key#1170 = 150)
MetastoreRelation default, src, None
```
Awful though this logical plan looks, it's harmless because all projects will be eliminated by optimizer. Guess that's why this issue hasn't been caught before.
Author: Cheng Lian <lian.cs.zju@gmail.com>
Author: baishuo(白硕) <vc_java@hotmail.com>
Author: baishuo <vc_java@hotmail.com>
Closes#2616 from liancheng/dp-fix and squashes the following commits:
21935b6 [Cheng Lian] Adds back deleted trailing space
f471c4b [Cheng Lian] PreInsertionCasts should take table partitions into account
a132c80 [Cheng Lian] Fixes output compression
9c6eb2d [Cheng Lian] Adds tests to verify dynamic partitioning folder layout
0eed349 [Cheng Lian] Addresses @yhuai's comments
26632c3 [Cheng Lian] Adds more tests
9227181 [Cheng Lian] Minor refactoring
c47470e [Cheng Lian] Refactors InsertIntoHiveTable to a Command
6fb16d7 [Cheng Lian] Fixes typo in test name, regenerated golden answer files
d53daa5 [Cheng Lian] Refactors dynamic partitioning support
b821611 [baishuo] pass check style
997c990 [baishuo] use HiveConf.DEFAULTPARTITIONNAME to replace hive.exec.default.partition.name
761ecf2 [baishuo] modify according micheal's advice
207c6ac [baishuo] modify for some bad indentation
caea6fb [baishuo] modify code to pass scala style checks
b660e74 [baishuo] delete a empty else branch
cd822f0 [baishuo] do a little modify
8e7268c [baishuo] update file after test
3f91665 [baishuo(白硕)] Update Cast.scala
8ad173c [baishuo(白硕)] Update InsertIntoHiveTable.scala
051ba91 [baishuo(白硕)] Update Cast.scala
d452eb3 [baishuo(白硕)] Update HiveQuerySuite.scala
37c603b [baishuo(白硕)] Update InsertIntoHiveTable.scala
98cfb1f [baishuo(白硕)] Update HiveCompatibilitySuite.scala
6af73f4 [baishuo(白硕)] Update InsertIntoHiveTable.scala
adf02f1 [baishuo(白硕)] Update InsertIntoHiveTable.scala
1867e23 [baishuo(白硕)] Update SparkHadoopWriter.scala
6bb5880 [baishuo(白硕)] Update HiveQl.scala
Implemented UDAF Hive aggregates by adding wrapper to Spark Hive.
Author: ravipesala <ravindra.pesala@huawei.com>
Closes#2620 from ravipesala/SPARK-2693 and squashes the following commits:
a8df326 [ravipesala] Removed resolver from constructor arguments
caf25c6 [ravipesala] Fixed style issues
5786200 [ravipesala] Supported for UDAF Hive Aggregates like PERCENTILE
Created separate parser for hql. It preparses the commands like cache,uncache,add jar etc.. and then parses with HiveQl
Author: ravipesala <ravindra.pesala@huawei.com>
Closes#2590 from ravipesala/SPARK-3654 and squashes the following commits:
bbca7dd [ravipesala] Fixed code as per admin comments.
ae9290a [ravipesala] Fixed style issues as per Admin comments
898ed81 [ravipesala] Removed spaces
fb24edf [ravipesala] Updated the code as per admin comments
8947d37 [ravipesala] Removed duplicate code
ba26cd1 [ravipesala] Created seperate parser for hql.It pre parses the commands like cache,uncache,add jar etc.. and then parses with HiveQl
With the old ordering it was possible for commands in the HiveDriver to NPE due to the lack of configuration in the threadlocal session state.
Author: Michael Armbrust <michael@databricks.com>
Closes#2635 from marmbrus/initOrder and squashes the following commits:
9749850 [Michael Armbrust] Initilize session state before creating CommandProcessor
This change avoids a NPE during context initialization when settings are present.
Author: Michael Armbrust <michael@databricks.com>
Closes#2583 from marmbrus/configNPE and squashes the following commits:
da2ec57 [Michael Armbrust] Do all hive session state initilialization in lazy val
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
add case for VoidObjectInspector in ```inspectorToDataType```
Author: scwf <wangfei1@huawei.com>
Closes#2552 from scwf/inspectorToDataType and squashes the following commits:
453d892 [scwf] add case for VoidObjectInspector
The below query gives error
sql("SELECT k FROM (SELECT \`key\` AS \`k\` FROM src) a")
It gives error because the aliases are not cleaned so it could not be resolved in further processing.
Author: ravipesala <ravindra.pesala@huawei.com>
Closes#2594 from ravipesala/SPARK-3708 and squashes the following commits:
d55db54 [ravipesala] Fixed SPARK-3708 (Backticks aren't handled correctly is aliases)
Author: Michael Armbrust <michael@databricks.com>
Closes#2598 from marmbrus/hiveClientLock and squashes the following commits:
ca89fe8 [Michael Armbrust] Lock hive client when creating tables
MD5 of query strings in `createQueryTest` calls are used to generate golden files, leaving trailing spaces there can be really dangerous. Got bitten by this while working on #2616: my "smart" IDE automatically removed a trailing space and makes Jenkins fail.
(Really should add "no trailing space" to our coding style guidelines!)
Author: Cheng Lian <lian.cs.zju@gmail.com>
Closes#2619 from liancheng/kill-trailing-space and squashes the following commits:
034f119 [Cheng Lian] Kill dangerous trailing space in query string
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
Typing of UDFs should be lazy as it is often not valid to call `dataType` on an expression until after all of its children are `resolved`.
Author: Michael Armbrust <michael@databricks.com>
Closes#2525 from marmbrus/concatBug and squashes the following commits:
5b8efe7 [Michael Armbrust] fix bug with eager typing of udfs
This is a bug in JDK6: http://bugs.java.com/bugdatabase/view_bug.do?bug_id=4428022
this is because jdk get different result to operate ```double```,
```System.out.println(1/500d)``` in different jdk get different result
jdk 1.6.0(_31) ---- 0.0020
jdk 1.7.0(_05) ---- 0.002
this leads to HiveQuerySuite failed when generate golden answer in jdk 1.7 and run tests in jdk 1.6, result did not match
Author: w00228970 <wangfei1@huawei.com>
Closes#2517 from scwf/HiveQuerySuite and squashes the following commits:
0cb5e8d [w00228970] delete golden answer of division-0 and timestamp cast #1
1df3964 [w00228970] Jdk version leads to different query output for Double, this make HiveQuerySuite failed
Author: Daoyuan Wang <daoyuan.wang@intel.com>
Closes#2396 from adrian-wang/selectnull and squashes the following commits:
2458229 [Daoyuan Wang] rebase solution
Since we have moved to `ConventionHelper`, it is quite easy to avoid call `javaClassToDataType` in hive simple udf. This will solve SPARK-3582.
Author: Daoyuan Wang <daoyuan.wang@intel.com>
Closes#2506 from adrian-wang/spark3582 and squashes the following commits:
450c28e [Daoyuan Wang] not limit argument type for hive simple udf
this patch fixes timestamp smaller than 0 and cast int as timestamp
select cast(1000 as timestamp) from src limit 1;
should return 1970-01-01 00:00:01, but we now take it as 1000 seconds.
also, current implementation has bug when the time is before 1970-01-01 00:00:00.
rxin marmbrus chenghao-intel
Author: Daoyuan Wang <daoyuan.wang@intel.com>
Closes#2458 from adrian-wang/timestamp and squashes the following commits:
4274b1d [Daoyuan Wang] set test not related to timezone
1234f66 [Daoyuan Wang] fix timestamp smaller than 0 and cast int as timestamp
**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 is just another solution to SPARK-3485, in addition to PR #2355
In this patch, we will use ConventionHelper and FunctionRegistry to invoke a simple udf evaluation, which rely more on hive, but much cleaner and safer.
We can discuss which one is better.
Author: Daoyuan Wang <daoyuan.wang@intel.com>
Closes#2407 from adrian-wang/simpleudf and squashes the following commits:
15762d2 [Daoyuan Wang] add posmod test which would fail the test but now ok
0d69eb4 [Daoyuan Wang] another way to pass to hive simple udf
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 ...
When do the query like:
```
select datediff(cast(value as timestamp), cast('2002-03-21 00:00:00' as timestamp)) from src;
```
SparkSQL will raise exception:
```
[info] scala.MatchError: TimestampType (of class org.apache.spark.sql.catalyst.types.TimestampType$)
[info] at org.apache.spark.sql.catalyst.expressions.Cast.castToTimestamp(Cast.scala:77)
[info] at org.apache.spark.sql.catalyst.expressions.Cast.cast$lzycompute(Cast.scala:251)
[info] at org.apache.spark.sql.catalyst.expressions.Cast.cast(Cast.scala:247)
[info] at org.apache.spark.sql.catalyst.expressions.Cast.eval(Cast.scala:263)
[info] at org.apache.spark.sql.catalyst.optimizer.ConstantFolding$$anonfun$apply$5$$anonfun$applyOrElse$2.applyOrElse(Optimizer.scala:217)
[info] at org.apache.spark.sql.catalyst.optimizer.ConstantFolding$$anonfun$apply$5$$anonfun$applyOrElse$2.applyOrElse(Optimizer.scala:210)
[info] at org.apache.spark.sql.catalyst.trees.TreeNode.transformDown(TreeNode.scala:144)
[info] at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$4$$anonfun$apply$2.apply(TreeNode.scala:180)
[info] at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:244)
[info] at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:244)
```
Author: Cheng Hao <hao.cheng@intel.com>
Closes#2368 from chenghao-intel/cast_exception and squashes the following commits:
5c9c3a5 [Cheng Hao] make more clear code
49dfc50 [Cheng Hao] Add no-op for Cast and revert the position of SimplifyCasts
b804abd [Cheng Hao] Add unit test to show the failure in identical data type casting
330a5c8 [Cheng Hao] Update Code based on comments
b834ed4 [Cheng Hao] Fix bug of HiveSimpleUDF with unnecessary type cast which cause exception in constant folding
Throwing an error in the constructor makes it possible to run queries, even when there is no actual ambiguity. Remove this check in favor of throwing an error in analysis when they query is actually is ambiguous.
Also took the opportunity to add test cases that would have caught a subtle bug in my first attempt at fixing this and refactor some other test code.
Author: Michael Armbrust <michael@databricks.com>
Closes#2209 from marmbrus/sameNameStruct and squashes the following commits:
729cca4 [Michael Armbrust] Better tests.
a003aeb [Michael Armbrust] Remove error (it'll be caught in analysis).
SPARK-3039: Adds the maven property "avro.mapred.classifier" to build spark-assembly with avro-mapred with support for the new Hadoop API. Sets this property to hadoop2 for Hadoop 2 profiles.
I am not very familiar with maven, nor do I know whether this potentially breaks something in the hive part of spark. There might be a more elegant way of doing this.
Author: Bertrand Bossy <bertrandbossy@gmail.com>
Closes#1945 from bbossy/SPARK-3039 and squashes the following commits:
c32ce59 [Bertrand Bossy] SPARK-3039: Allow spark to be built using avro-mapred for hadoop2
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 is a follow up of #2352. Now we can finally remove the evil "MINOR HACK", which covered up the eldest bug in the history of Spark SQL (see details [here](https://github.com/apache/spark/pull/2352#issuecomment-55440621)).
Author: Cheng Lian <lian.cs.zju@gmail.com>
Closes#2377 from liancheng/remove-evil-minor-hack and squashes the following commits:
0869c78 [Cheng Lian] Removes the evil MINOR HACK
Please refer to the JIRA ticket for details.
**NOTE** We should check all test suites that do similar initialization-like side effects in their constructors. This PR only fixes `ParquetMetastoreSuite` because it breaks our Jenkins Maven build.
Author: Cheng Lian <lian.cs.zju@gmail.com>
Closes#2375 from liancheng/say-no-to-constructor and squashes the following commits:
0ceb75b [Cheng Lian] Moves test suite setup code to beforeAll rather than in constructor
Logically, we should remove the Hive Table/Database first and then reset the Hive configuration, repoint to the new data warehouse directory etc.
Otherwise it raised exceptions like "Database doesn't not exists: default" in the local testing.
Author: Cheng Hao <hao.cheng@intel.com>
Closes#2352 from chenghao-intel/test_hive and squashes the following commits:
74fd76b [Cheng Hao] eliminate the error log
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.
In order to read from partitioned Avro files we need to also set the `SERDEPROPERTIES` since `TBLPROPERTIES` are not passed to the initialization. This PR simply adds a test to make sure we don't break this workaround.
Author: Michael Armbrust <michael@databricks.com>
Closes#2340 from marmbrus/avroPartitioned and squashes the following commits:
6b969d6 [Michael Armbrust] fix style
fea2124 [Michael Armbrust] Add test case with workaround for reading partitioned avro files.
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
Current implementation will ignore else val type.
Author: Daoyuan Wang <daoyuan.wang@intel.com>
Closes#2245 from adrian-wang/casewhenbug and squashes the following commits:
3332f6e [Daoyuan Wang] remove wrong comment
83b536c [Daoyuan Wang] a comment to trigger retest
d7315b3 [Daoyuan Wang] code improve
eed35fc [Daoyuan Wang] bug in casewhen resolve
This fixes some possible spurious test failures in `HiveQuerySuite` by comparing sets of key-value pairs as sets, rather than as lists.
Author: William Benton <willb@redhat.com>
Author: Aaron Davidson <aaron@databricks.com>
Closes#2220 from willb/spark-3329 and squashes the following commits:
3b3e205 [William Benton] Collapse collectResults case match in HiveQuerySuite
6525d8e [William Benton] Handle cases where SET returns Rows of (single) strings
cf11b0e [Aaron Davidson] Fix flakey HiveQuerySuite test
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
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
Adds logical and physical command classes for the "add jar" command.
Note that this PR conflicts with and should be merged after #2215.
Author: Cheng Lian <lian.cs.zju@gmail.com>
Closes#2242 from liancheng/add-jar and squashes the following commits:
e43a2f1 [Cheng Lian] Updates AddJar according to conventions introduced in #2215
b99107f [Cheng Lian] Added test case for ADD JAR command
095b2c7 [Cheng Lian] Also forward ADD JAR command to Hive
9be031b [Cheng Lian] Trims Jar path string
8195056 [Cheng Lian] Added support for the "add jar" command
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"
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
":" is not allowed to appear in a file name of Windows system. If file name contains ":", this file can't be checked out in a Windows system and developers using Windows must be careful to not commit the deletion of such files, Which is very inconvenient.
Author: qiping.lqp <qiping.lqp@alibaba-inc.com>
Closes#2191 from chouqin/querytest and squashes the following commits:
0e943a1 [qiping.lqp] rename golden file
60a863f [qiping.lqp] TestcaseName in createQueryTest should not contain ":"
`HiveCompatibilitySuite` already turns on in-memory columnar caching, it would be good to also enable compression to improve test coverage.
Author: Cheng Lian <lian.cs.zju@gmail.com>
Closes#2190 from liancheng/compression-on and squashes the following commits:
88b536c [Cheng Lian] Code cleanup, narrowed field visibility
d13efd2 [Cheng Lian] Turns on in-memory columnar compression in HiveCompatibilitySuite
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
When run the udf_unix_timestamp of org.apache.spark.sql.hive.execution.HiveCompatibilitySuite testcase
with not "America/Los_Angeles" TimeZone throws error. [https://issues.apache.org/jira/browse/SPARK-3065]
add locale setting on beforeAll and afterAll method to fix the bug of HiveCompatibilitySuite testcase
Author: luogankun <luogankun@gmail.com>
Closes#1968 from luogankun/SPARK-3065 and squashes the following commits:
c167832 [luogankun] [SPARK-3065][SQL] Add Locale setting to HiveCompatibilitySuite
0a25e3a [luogankun] [SPARK-3065][SQL] Add Locale setting to HiveCompatibilitySuite
Currently we do `relation.hiveQlTable.getDataLocation.getPath`, which returns the path-part of the URI (e.g., "s3n://my-bucket/my-path" => "/my-path"). We should do `relation.hiveQlTable.getDataLocation.toString` instead, as a URI's toString returns a faithful representation of the full URI, which can later be passed into a Hadoop Path.
Author: Aaron Davidson <aaron@databricks.com>
Closes#2150 from aarondav/parquet-location and squashes the following commits:
459f72c [Aaron Davidson] [SQL] [SPARK-3236] Reading Parquet tables from Metastore mangles location
According to the text message, both relations should be tested. So add the missing condition.
Author: viirya <viirya@gmail.com>
Closes#2159 from viirya/fix_test and squashes the following commits:
b1c0f52 [viirya] add missing condition.
JIRA issue: [SPARK-3118] https://issues.apache.org/jira/browse/SPARK-3118
eg:
> SHOW TBLPROPERTIES test;
SHOW TBLPROPERTIES test;
numPartitions 0
numFiles 1
transient_lastDdlTime 1407923642
numRows 0
totalSize 82
rawDataSize 0
eg:
> SHOW COLUMNS in test;
SHOW COLUMNS in test;
OK
Time taken: 0.304 seconds
id
stid
bo
Author: u0jing <u9jing@gmail.com>
Closes#2034 from u0jing/spark-3118 and squashes the following commits:
b231d87 [u0jing] add golden answer files
35f4885 [u0jing] add 'show columns' and 'show tblproperties' support
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.
We can simple treat cross join as inner join without join conditions.
Author: Daoyuan Wang <daoyuan.wang@intel.com>
Author: adrian-wang <daoyuanwong@gmail.com>
Closes#2124 from adrian-wang/crossjoin and squashes the following commits:
8c9b7c5 [Daoyuan Wang] add a test
7d47bbb [adrian-wang] add cross join support for hql
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
Seems we missed `transient` for the `functionRegistry` in `HiveContext`.
cc: marmbrus
Author: Yin Huai <huaiyin.thu@gmail.com>
Closes#2074 from yhuai/makeFunctionRegistryTransient and squashes the following commits:
6534e7d [Yin Huai] Make functionRegistry transient.
...al job conf
Author: Alex Liu <alex_liu68@yahoo.com>
Closes#1927 from alexliu68/SPARK-SQL-2846 and squashes the following commits:
e4bdc4c [Alex Liu] SPARK-SQL-2846 add configureInputJobPropertiesForStorageHandler to initial job conf
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.
A small change - we should just add this dependency. It doesn't have any recursive deps and it's needed for reading have parquet tables.
Author: Patrick Wendell <pwendell@gmail.com>
Closes#2009 from pwendell/parquet and squashes the following commits:
e411f9f [Patrick Wendell] SPARk-309: Include parquet hive serde by default in build
Author: Michael Armbrust <michael@databricks.com>
Closes#1915 from marmbrus/arrayUDF and squashes the following commits:
a1c503d [Michael Armbrust] Support for udfs that take complex types
In spark sql component, the "show create table" syntax had been disabled.
We thought it is a useful funciton to describe a hive table.
Author: tianyi <tianyi@asiainfo-linkage.com>
Author: tianyi <tianyi@asiainfo.com>
Author: tianyi <tianyi.asiainfo@gmail.com>
Closes#1760 from tianyi/spark-2817 and squashes the following commits:
7d28b15 [tianyi] [SPARK-2817] fix too short prefix problem
cbffe8b [tianyi] [SPARK-2817] fix the case problem
565ec14 [tianyi] [SPARK-2817] fix the case problem
60d48a9 [tianyi] [SPARK-2817] use system temporary folder instead of temporary files in the source tree, and also clean some empty line
dbe1031 [tianyi] [SPARK-2817] move some code out of function rewritePaths, as it may be called multiple times
9b2ba11 [tianyi] [SPARK-2817] fix the line length problem
9f97586 [tianyi] [SPARK-2817] remove test.tmp.dir from pom.xml
bfc2999 [tianyi] [SPARK-2817] add "File.separator" support, create a "testTmpDir" outside the rewritePaths
bde800a [tianyi] [SPARK-2817] add "${system:test.tmp.dir}" support add "last_modified_by" to nonDeterministicLineIndicators in HiveComparisonTest
bb82726 [tianyi] [SPARK-2817] remove test which requires a system from the whitelist.
bbf6b42 [tianyi] [SPARK-2817] add a systemProperties named "test.tmp.dir" to pass the test which contains "${system:test.tmp.dir}"
a337bd6 [tianyi] [SPARK-2817] add "show create table" support
a03db77 [tianyi] [SPARK-2817] add "show create table" support
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
I should use `EliminateAnalysisOperators` in `analyze` instead of manually pattern matching.
Author: Yin Huai <huaiyin.thu@gmail.com>
Closes#1881 from yhuai/useEliminateAnalysisOperators and squashes the following commits:
f3e1e7f [Yin Huai] Use EliminateAnalysisOperators.
JIRA: https://issues.apache.org/jira/browse/SPARK-2888
Author: Yin Huai <huai@cse.ohio-state.edu>
Closes#1817 from yhuai/fixAddColumnMetadataToConf and squashes the following commits:
fba728c [Yin Huai] Fix addColumnMetadataToConf.
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.
Minor refactoring to allow resolution either using a nodes input or output.
Author: Michael Armbrust <michael@databricks.com>
Closes#1795 from marmbrus/ordering and squashes the following commits:
237f580 [Michael Armbrust] style
74d833b [Michael Armbrust] newline
705d963 [Michael Armbrust] Add a rule for resolving ORDER BY expressions that reference attributes not present in the SELECT clause.
82cabda [Michael Armbrust] Generalize attribute resolution.
Author: Michael Armbrust <michael@databricks.com>
Closes#1785 from marmbrus/caseNull and squashes the following commits:
126006d [Michael Armbrust] better error message
2fe357f [Michael Armbrust] Fix coercion of CASE WHEN.
JIRA: https://issues.apache.org/jira/browse/SPARK-2783
Author: Yin Huai <huai@cse.ohio-state.edu>
Closes#1741 from yhuai/analyzeTable and squashes the following commits:
7bb5f02 [Yin Huai] Use sql instead of hql.
4d09325 [Yin Huai] Merge remote-tracking branch 'upstream/master' into analyzeTable
e3ebcd4 [Yin Huai] Renaming.
c170f4e [Yin Huai] Do not use getContentSummary.
62393b6 [Yin Huai] Merge remote-tracking branch 'upstream/master' into analyzeTable
db233a6 [Yin Huai] Trying to debug jenkins...
fee84f0 [Yin Huai] Merge remote-tracking branch 'upstream/master' into analyzeTable
f0501f3 [Yin Huai] Fix compilation error.
24ad391 [Yin Huai] Merge remote-tracking branch 'upstream/master' into analyzeTable
8918140 [Yin Huai] Wording.
23df227 [Yin Huai] Add a simple analyze method to get the size of a table and update the "totalSize" property of this table in the Hive metastore.
JIRA issue: [SPARK-2814](https://issues.apache.org/jira/browse/SPARK-2814)
Author: Cheng Lian <lian.cs.zju@gmail.com>
Closes#1753 from liancheng/spark-2814 and squashes the following commits:
c74a3b2 [Cheng Lian] Fixed SPARK-2814
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
Author: Michael Armbrust <michael@databricks.com>
Closes#1742 from marmbrus/asserts and squashes the following commits:
5182d54 [Michael Armbrust] Remove assertions that throw when users try unsupported Hive commands.
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
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.
Author: Cheng Hao <hao.cheng@intel.com>
Closes#1686 from chenghao-intel/spark_sql_cli and squashes the following commits:
eb664cc [Cheng Hao] Output detailed failure message in console
93b0382 [Cheng Hao] Fix Bug of no output in cli if exception thrown internally
This PR tries to resolve the broken Jenkins maven test issue introduced by #1439. Now, we create a single query test to run both the setup work and the test query.
Author: Yin Huai <huai@cse.ohio-state.edu>
Closes#1669 from yhuai/SPARK-2523-fixTest and squashes the following commits:
358af1a [Yin Huai] Make partition_based_table_scan_with_different_serde run atomically.
LocalHiveContext is redundant with HiveContext. The only difference is it creates `./metastore` instead of `./metastore_db`.
Author: Michael Armbrust <michael@databricks.com>
Closes#1641 from marmbrus/localHiveContext and squashes the following commits:
e5ec497 [Michael Armbrust] Add deprecation version
626e056 [Michael Armbrust] Don't remove from imports yet
905cc5f [Michael Armbrust] Merge remote-tracking branch 'apache/master' into localHiveContext
1c2727e [Michael Armbrust] Deprecate LocalHiveContext
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
Author: Michael Armbrust <michael@databricks.com>
Closes#1650 from marmbrus/dropCached and squashes the following commits:
e6ab80b [Michael Armbrust] Support if exists.
83426c6 [Michael Armbrust] Remove tables from cache when DROP TABLE is run.
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`.
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.
For queries like `... HAVING COUNT(*) > 9` the expression is always resolved since it contains no attributes. This was causing us to avoid doing the Having clause aggregation rewrite.
Author: Michael Armbrust <michael@databricks.com>
Closes#1640 from marmbrus/havingNoRef and squashes the following commits:
92d3901 [Michael Armbrust] Don't check resolved for having filters.
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.
1. there's no `hook_context.q` but a `hook_context_cs.q` in query folder
2. there's no `compute_stats_table.q` in query folder
3. there's no `having1.q` in query folder
4. `udf_E` and `udf_PI` appear twice in white list
Author: Daoyuan <daoyuan.wang@intel.com>
Closes#1634 from adrian-wang/testcases and squashes the following commits:
d7482ce [Daoyuan] change some test lists
Author: Yadong Qi <qiyadong2010@gmail.com>
Closes#1629 from watermen/bug-fix2 and squashes the following commits:
59b7237 [Yadong Qi] Update HiveQl.scala
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
In HiveTableScan.scala, ObjectInspector was created for all of the partition based records, which probably causes ClassCastException if the object inspector is not identical among table & partitions.
This is the follow up with:
https://github.com/apache/spark/pull/1408https://github.com/apache/spark/pull/1390
I've run a micro benchmark in my local with 15000000 records totally, and got the result as below:
With This Patch | Partition-Based Table | Non-Partition-Based Table
------------ | ------------- | -------------
No | 1927 ms | 1885 ms
Yes | 1541 ms | 1524 ms
It showed this patch will also improve the performance.
PS: the benchmark code is also attached. (thanks liancheng )
```
package org.apache.spark.sql.hive
import org.apache.spark.SparkContext
import org.apache.spark.SparkConf
import org.apache.spark.sql._
object HiveTableScanPrepare extends App {
case class Record(key: String, value: String)
val sparkContext = new SparkContext(
new SparkConf()
.setMaster("local")
.setAppName(getClass.getSimpleName.stripSuffix("$")))
val hiveContext = new LocalHiveContext(sparkContext)
val rdd = sparkContext.parallelize((1 to 3000000).map(i => Record(s"$i", s"val_$i")))
import hiveContext._
hql("SHOW TABLES")
hql("DROP TABLE if exists part_scan_test")
hql("DROP TABLE if exists scan_test")
hql("DROP TABLE if exists records")
rdd.registerAsTable("records")
hql("""CREATE TABLE part_scan_test (key STRING, value STRING) PARTITIONED BY (part1 string, part2 STRING)
| ROW FORMAT SERDE
| 'org.apache.hadoop.hive.serde2.columnar.LazyBinaryColumnarSerDe'
| STORED AS RCFILE
""".stripMargin)
hql("""CREATE TABLE scan_test (key STRING, value STRING)
| ROW FORMAT SERDE
| 'org.apache.hadoop.hive.serde2.columnar.LazyBinaryColumnarSerDe'
| STORED AS RCFILE
""".stripMargin)
for (part1 <- 2000 until 2001) {
for (part2 <- 1 to 5) {
hql(s"""from records
| insert into table part_scan_test PARTITION (part1='$part1', part2='2010-01-$part2')
| select key, value
""".stripMargin)
hql(s"""from records
| insert into table scan_test select key, value
""".stripMargin)
}
}
}
object HiveTableScanTest extends App {
val sparkContext = new SparkContext(
new SparkConf()
.setMaster("local")
.setAppName(getClass.getSimpleName.stripSuffix("$")))
val hiveContext = new LocalHiveContext(sparkContext)
import hiveContext._
hql("SHOW TABLES")
val part_scan_test = hql("select key, value from part_scan_test")
val scan_test = hql("select key, value from scan_test")
val r_part_scan_test = (0 to 5).map(i => benchmark(part_scan_test))
val r_scan_test = (0 to 5).map(i => benchmark(scan_test))
println("Scanning Partition-Based Table")
r_part_scan_test.foreach(printResult)
println("Scanning Non-Partition-Based Table")
r_scan_test.foreach(printResult)
def printResult(result: (Long, Long)) {
println(s"Duration: ${result._1} ms Result: ${result._2}")
}
def benchmark(srdd: SchemaRDD) = {
val begin = System.currentTimeMillis()
val result = srdd.count()
val end = System.currentTimeMillis()
((end - begin), result)
}
}
```
Author: Cheng Hao <hao.cheng@intel.com>
Closes#1439 from chenghao-intel/hadoop_table_scan and squashes the following commits:
888968f [Cheng Hao] Fix issues in code style
27540ba [Cheng Hao] Fix the TableScan Bug while partition serde differs
40a24a7 [Cheng Hao] Add Unit Test
(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
Author: Michael Armbrust <michael@databricks.com>
Closes#1557 from marmbrus/fixDivision and squashes the following commits:
b85077f [Michael Armbrust] Fix unit tests.
af98f29 [Michael Armbrust] Change DIV to long type
0c29ae8 [Michael Armbrust] Fix division semantics for hive
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"
I think it's better to defined hiveQlTable as a val
Author: baishuo(白硕) <vc_java@hotmail.com>
Closes#1569 from baishuo/patch-1 and squashes the following commits:
dc2f895 [baishuo(白硕)] Update HiveMetastoreCatalog.scala
a7b32a2 [baishuo(白硕)] Update HiveMetastoreCatalog.scala
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
Hive Supports the operator "<=>", which returns same result with EQUAL(=) operator for non-null operands, but returns TRUE if both are NULL, FALSE if one of the them is NULL.
Author: Cheng Hao <hao.cheng@intel.com>
Closes#1570 from chenghao-intel/equalns and squashes the following commits:
8d6c789 [Cheng Hao] Remove the test case orc_predicate_pushdown
5b2ca88 [Cheng Hao] Add cases into whitelist
8e66cdd [Cheng Hao] Rename the EqualNSTo ==> EqualNullSafe
7af4b0b [Cheng Hao] Add EqualNS & Unit Tests
Author: Michael Armbrust <michael@databricks.com>
Closes#1556 from marmbrus/fixBooleanEqualsOne and squashes the following commits:
ad8edd4 [Michael Armbrust] Add rule for true = 1 and false = 0.
Author: witgo <witgo@qq.com>
Closes#1403 from witgo/hive_compatibility and squashes the following commits:
4e5ecdb [witgo] The default does not run hive compatibility tests
Instead of shipping just the name and then looking up the info on the workers, we now ship the whole classname. Also, I refactored the file as it was getting pretty large to move out the type conversion code to its own file.
Author: Michael Armbrust <michael@databricks.com>
Closes#1552 from marmbrus/fixTempUdfs and squashes the following commits:
b695904 [Michael Armbrust] Make add jar execute with Hive. Ship the whole function class name since sometimes we cannot lookup temporary functions on the workers.
This change adds an analyzer rule to
1. find expressions in `HAVING` clause filters that depend on unresolved attributes,
2. push these expressions down to the underlying aggregates, and then
3. project them away above the filter.
It also enables the `HAVING` queries in the Hive compatibility suite.
Author: William Benton <willb@redhat.com>
Closes#1497 from willb/spark-2226 and squashes the following commits:
92c9a93 [William Benton] Removed unnecessary import
f1d4f34 [William Benton] Cleanups missed in prior commit
0e1624f [William Benton] Incorporated suggestions from @marmbrus; thanks!
541d4ee [William Benton] Cleanups from review
5a12647 [William Benton] Explanatory comments and stylistic cleanups.
c7f2b2c [William Benton] Whitelist HAVING queries.
29a26e3 [William Benton] Added rule to handle unresolved attributes in HAVING clauses (SPARK-2226)
Currently, the "==" in HiveQL expression will cause exception thrown, this patch will fix it.
Author: Cheng Hao <hao.cheng@intel.com>
Closes#1522 from chenghao-intel/equal and squashes the following commits:
f62a0ff [Cheng Hao] Add == Support for HiveQl
Result may not be returned in the expected order, so relax that constraint.
Author: Aaron Davidson <aaron@databricks.com>
Closes#1514 from aarondav/flakey and squashes the following commits:
e5af823 [Aaron Davidson] Fix flakey HiveQuerySuite test
Author: Cheng Hao <hao.cheng@intel.com>
Closes#1436 from chenghao-intel/unwrapdata and squashes the following commits:
34cc21a [Cheng Hao] update the table scan accodringly since the unwrapData function changed
afc39da [Cheng Hao] Polish the code
39d6475 [Cheng Hao] Add HiveDecimal & HiveVarchar support in unwrap data
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.
This replaces the Hive UDF for SUBSTR(ING) with an implementation in Catalyst
and adds tests to verify correct operation.
Author: William Benton <willb@redhat.com>
Closes#1359 from willb/internalSqlSubstring and squashes the following commits:
ccedc47 [William Benton] Fixed too-long line.
a30a037 [William Benton] replace view bounds with implicit parameters
ec35c80 [William Benton] Adds fixes from review:
4f3bfdb [William Benton] Added internal implementation of SQL SUBSTR()
Author: Michael Armbrust <michael@databricks.com>
Closes#1396 from marmbrus/moreTests and squashes the following commits:
6660b60 [Michael Armbrust] Blacklist a test that requires DFS command.
8b6001c [Michael Armbrust] Add golden files.
ccd8f97 [Michael Armbrust] Whitelist more tests.
Author: Michael Armbrust <michael@databricks.com>
Closes#1411 from marmbrus/nestedRepeated and squashes the following commits:
044fa09 [Michael Armbrust] Fix parsing of repeated, nested data access.
This fix obtains a comparable performance boost as [PR #1390](https://github.com/apache/spark/pull/1390) by moving an array update and deserializer initialization out of a potentially very long loop. Suggested by yhuai. The below results are updated for this fix.
## Benchmarks
Generated a local text file with 10M rows of simple key-value pairs. The data is loaded as a table through Hive. Results are obtained on my local machine using hive/console.
Without the fix:
Type | Non-partitioned | Partitioned (1 part)
------------ | ------------ | -------------
First run | 9.52s end-to-end (1.64s Spark job) | 36.6s (28.3s)
Stablized runs | 1.21s (1.18s) | 27.6s (27.5s)
With this fix:
Type | Non-partitioned | Partitioned (1 part)
------------ | ------------ | -------------
First run | 9.57s (1.46s) | 11.0s (1.69s)
Stablized runs | 1.13s (1.10s) | 1.23s (1.19s)
Author: Zongheng Yang <zongheng.y@gmail.com>
Closes#1408 from concretevitamin/slow-read-2 and squashes the following commits:
d86e437 [Zongheng Yang] Move update & initialization out of potentially long loop.
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.
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.
Author: Michael Armbrust <michael@databricks.com>
Closes#1305 from marmbrus/usePrunerPartitions and squashes the following commits:
744aa20 [Michael Armbrust] Use getAllPartitionsForPruner instead of getPartitions, which avoids retrieving auth data
`PruningSuite` is executed first of Hive tests unfortunately, `TestHive.reset()` breaks the test environment.
To prevent this, we must run a query before calling reset the first time.
Author: Takuya UESHIN <ueshin@happy-camper.st>
Closes#1268 from ueshin/issues/SPARK-2328 and squashes the following commits:
043ceac [Takuya UESHIN] Add execution of `SHOW TABLES` before `TestHive.reset()`.
JIRA issue: [SPARK-2283](https://issues.apache.org/jira/browse/SPARK-2283)
If `PruningSuite` is run right after `HiveCompatibilitySuite`, the first test case fails because `srcpart` table is cached in-memory by `HiveCompatibilitySuite`, but column pruning is not implemented for `InMemoryColumnarTableScan` operator yet.
Author: Cheng Lian <lian.cs.zju@gmail.com>
Closes#1221 from liancheng/spark-2283 and squashes the following commits:
dc0b663 [Cheng Lian] SPARK-2283: reset test environment before running PruningSuite
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.
The `BigDecimal` branch in `unwrap` matches to `scala.math.BigDecimal` rather than `java.math.BigDecimal`.
Author: Cheng Lian <lian.cs.zju@gmail.com>
Closes#1199 from liancheng/javaBigDecimal and squashes the following commits:
e9bb481 [Cheng Lian] Should match java.math.BigDecimal when wnrapping Hive output
JIRA issue: [SPARK-2263](https://issues.apache.org/jira/browse/SPARK-2263)
Map objects were not converted to Hive types before inserting into Hive tables.
Author: Cheng Lian <lian.cs.zju@gmail.com>
Closes#1205 from liancheng/spark-2263 and squashes the following commits:
c7a4373 [Cheng Lian] Addressed @concretevitamin's comment
784940b [Cheng Lian] SARPK-2263: support inserting MAP<K, V> to Hive tables
Note that nothing gets printed to the console because we don't properly maintain session state right now.
I will have a followup PR that fixes it.
Author: Reynold Xin <rxin@apache.org>
Closes#1167 from rxin/commands and squashes the following commits:
56f04f8 [Reynold Xin] [SPARK-2227] Support dfs command in SQL.
The single file was getting very long (500+ loc).
Author: Reynold Xin <rxin@apache.org>
Closes#1166 from rxin/hiveOperators and squashes the following commits:
5b43068 [Reynold Xin] [SQL] Break hiveOperators.scala into multiple files.
Note that this is simply mimicing lookupRelation(). I do not have a concrete notion of why this solution is necessarily right-er than SessionState.get, but SessionState.get is returning null, which is bad.
Author: Aaron Davidson <aaron@databricks.com>
Closes#1148 from aarondav/createtable and squashes the following commits:
37c3e7c [Aaron Davidson] [SQL] Use hive.SessionState, not the thread local SessionState
Author: Reynold Xin <rxin@apache.org>
Closes#1162 from rxin/script and squashes the following commits:
2c836b9 [Reynold Xin] Move ScriptTransformation into the appropriate place.
@willb
Author: Reynold Xin <rxin@apache.org>
Closes#1161 from rxin/having-filter and squashes the following commits:
fa8359a [Reynold Xin] [SPARK-2225] Turn HAVING without GROUP BY into WHERE.
This PR extends Spark's HiveQL support to handle HAVING clauses in aggregations. The HAVING test from the Hive compatibility suite doesn't appear to be runnable from within Spark, so I added a simple comparable test to `HiveQuerySuite`.
Author: William Benton <willb@redhat.com>
Closes#1136 from willb/SPARK-2180 and squashes the following commits:
3bbaf26 [William Benton] Added casts to HAVING expressions
83f1340 [William Benton] scalastyle fixes
18387f1 [William Benton] Add test for HAVING without GROUP BY
b880bef [William Benton] Added semantic error for HAVING without GROUP BY
942428e [William Benton] Added test coverage for SPARK-2180.
56084cc [William Benton] Add support for HAVING clauses in Hive queries.
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.
```
explain select cast(cast(key=0 as boolean) as boolean) aaa from src
```
should be
```
[Physical execution plan:]
[Project [(key#10:0 = 0) AS aaa#7]]
[ HiveTableScan [key#10], (MetastoreRelation default, src, None), None]
```
However, it is currently
```
[Physical execution plan:]
[Project [NOT((key#10=0) = 0) AS aaa#7]]
[ HiveTableScan [key#10], (MetastoreRelation default, src, None), None]
```
Author: Reynold Xin <rxin@apache.org>
Closes#1144 from rxin/booleancast and squashes the following commits:
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: Michael Armbrust <michael@databricks.com>
Closes#1130 from marmbrus/noFunctional and squashes the following commits:
ccdb68c [Michael Armbrust] Remove functional programming and Array allocations from fast path in InsertIntoHiveTable.
Author: Michael Armbrust <michael@databricks.com>
Closes#1129 from marmbrus/doubleCreateAs and squashes the following commits:
9c6d9e4 [Michael Armbrust] Fix typo.
5128fe2 [Michael Armbrust] Make sure InsertIntoHiveTable doesn't execute each time you ask for its result.
@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.
JIRA ticket: https://issues.apache.org/jira/browse/SPARK-2053
This PR adds support for two types of CASE statements present in Hive. The first type is of the form `CASE WHEN a THEN b [WHEN c THEN d]* [ELSE e] END`, with the semantics like a chain of if statements. The second type is of the form `CASE a WHEN b THEN c [WHEN d THEN e]* [ELSE f] END`, with the semantics like a switch statement on key `a`. Both forms are implemented in `CaseWhen`.
[This link](https://cwiki.apache.org/confluence/display/Hive/LanguageManual+UDF#LanguageManualUDF-ConditionalFunctions) contains more detailed descriptions on their semantics.
Notes / Open issues:
* Please check if any implicit contracts / invariants are broken in the implementations (especially for the operators). I am not very familiar with them and I currently find them tricky to spot.
* We should decide whether or not a non-boolean condition is allowed in a branch of `CaseWhen`. Hive throws a `SemanticException` for this situation and I think it'd be good to mimic it -- the question is where in the whole Spark SQL pipeline should we signal an exception for such a query.
Author: Zongheng Yang <zongheng.y@gmail.com>
Closes#1055 from concretevitamin/caseWhen and squashes the following commits:
4226eb9 [Zongheng Yang] Comment.
79d26fc [Zongheng Yang] Merge branch 'master' into caseWhen
caf9383 [Zongheng Yang] Update a FIXME.
9d26ab8 [Zongheng Yang] Add @transient marker.
788a0d9 [Zongheng Yang] Implement CastNulls, which fixes udf_case and udf_when.
7ef284f [Zongheng Yang] Refactors: remove redundant passes, improve toString, mark transient.
f47ae7b [Zongheng Yang] Modify queries in tests to have shorter golden files.
1c1fbfc [Zongheng Yang] Cleanups per review comments.
7d2b7e2 [Zongheng Yang] Translate CaseKeyWhen to CaseWhen at parsing time.
47d406a [Zongheng Yang] Do toArray once and lazily outside of eval().
bb3d109 [Zongheng Yang] Update scaladoc of a method.
aea3195 [Zongheng Yang] Fix bug that branchesArr is not used; remove unused import.
96870a8 [Zongheng Yang] Turn off scalastyle for some comments.
7392f3a [Zongheng Yang] Minor cleanup.
2cf08bb [Zongheng Yang] Merge branch 'master' into caseWhen
9f84b40 [Zongheng Yang] Add golden outputs from Hive.
db51a85 [Zongheng Yang] Add allCondBooleans check; uncomment tests.
3f9ef0a [Zongheng Yang] Cleanups and bug fixes (mainly in eval() and resolved).
be54bc8 [Zongheng Yang] Rewrite eval() to a low-level implementation. Separate two CASE stmts.
f2bcb9d [Zongheng Yang] WIP
5906f75 [Zongheng Yang] WIP
efd019b [Zongheng Yang] eval() and toString() bug fixes.
7d81e95 [Zongheng Yang] Clean up resolved.
a31d782 [Zongheng Yang] Finish up Case.
