By @egraldlo.
Author: egraldlo <egraldlo@gmail.com>
Author: Michael Armbrust <michael@databricks.com>
Closes#1033 from marmbrus/pr/978 and squashes the following commits:
e228c5e [Michael Armbrust] Remove "test".
762aeaf [Michael Armbrust] Remove unneeded rule. More descriptive name for test table.
d414cd7 [egraldlo] fommatting issues
1153f75 [egraldlo] do best to avoid overflowing in function avg().
As the rule described in https://cwiki.apache.org/confluence/display/Hive/OuterJoinBehavior, we can optimize the SQL Join by pushing down the Join predicate and Where predicate.
Author: Cheng Hao <hao.cheng@intel.com>
Closes#1015 from chenghao-intel/join_predicate_push_down and squashes the following commits:
10feff9 [Cheng Hao] fix bug of changing the join type in PredicatePushDownThroughJoin
44c6700 [Cheng Hao] Add logical to support pushdown the join filter
0bce426 [Cheng Hao] Pushdown the join filter & predicate for outer join
The package is `org.apache.spark.sql.hive.execution`, while the file was placed under `sql/hive/src/main/scala/org/apache/spark/sql/hive/`.
Author: Cheng Lian <lian.cs.zju@gmail.com>
Closes#1029 from liancheng/moveHiveOperators and squashes the following commits:
d632eb8 [Cheng Lian] Moved hiveOperators.scala to the right package folder
This PR (1) introduces a new class SQLConf that stores key-value properties for a SQLContext (2) clean up the semantics of various forms of SET commands.
The SQLConf class unlocks user-controllable optimization opportunities; for example, user can now override the number of partitions used during an Exchange. A SQLConf can be accessed and modified programmatically through its getters and setters. It can also be modified through SET commands executed by `sql()` or `hql()`. Note that users now have the ability to change a particular property for different queries inside the same Spark job, unlike settings configured in SparkConf.
For SET commands: "SET" will return all properties currently set in a SQLConf, "SET key" will return the key-value pair (if set) or an undefined message, and "SET key=value" will call the setter on SQLConf, and if a HiveContext is used, it will be executed in Hive as well.
Author: Zongheng Yang <zongheng.y@gmail.com>
Closes#956 from concretevitamin/sqlconf and squashes the following commits:
4968c11 [Zongheng Yang] Very minor cleanup.
d74dde5 [Zongheng Yang] Remove the redundant mkQueryExecution() method.
c129b86 [Zongheng Yang] Merge remote-tracking branch 'upstream/master' into sqlconf
26c40eb [Zongheng Yang] Make SQLConf a trait and have SQLContext mix it in.
dd19666 [Zongheng Yang] Update a comment.
baa5d29 [Zongheng Yang] Remove default param for shuffle partitions accessor.
5f7e6d8 [Zongheng Yang] Add default num partitions.
22d9ed7 [Zongheng Yang] Fix output() of Set physical. Add SQLConf param accessor method.
e9856c4 [Zongheng Yang] Use java.util.Collections.synchronizedMap on a Java HashMap.
88dd0c8 [Zongheng Yang] Remove redundant SET Keyword.
271f0b1 [Zongheng Yang] Minor change.
f8983d1 [Zongheng Yang] Minor changes per review comments.
1ce8a5e [Zongheng Yang] Invoke runSqlHive() in SQLConf#get for the HiveContext case.
b766af9 [Zongheng Yang] Remove a test.
d52e1bd [Zongheng Yang] De-hardcode number of shuffle partitions for BasicOperators (read from SQLConf).
555599c [Zongheng Yang] Bullet-proof (relatively) parsing SET per review comment.
c2067e8 [Zongheng Yang] Mark SQLContext transient and put it in a second param list.
2ea8cdc [Zongheng Yang] Wrap long line.
41d7f09 [Zongheng Yang] Fix imports.
13279e6 [Zongheng Yang] Refactor the logic of eagerly processing SET commands.
b14b83e [Zongheng Yang] In a HiveContext, make SQLConf a subset of HiveConf.
6983180 [Zongheng Yang] Move a SET test to SQLQuerySuite and make it complete.
5b67985 [Zongheng Yang] New line at EOF.
c651797 [Zongheng Yang] Add commands.scala.
efd82db [Zongheng Yang] Clean up semantics of several cases of SET.
c1017c2 [Zongheng Yang] WIP in changing SetCommand to take two Options (for different semantics of SETs).
0f00d86 [Zongheng Yang] Add a test for singleton set command in SQL.
41acd75 [Zongheng Yang] Add a test for hql() in HiveQuerySuite.
2276929 [Zongheng Yang] Fix default hive result for set commands in HiveComparisonTest.
3b0c71b [Zongheng Yang] Remove Parser for set commands. A few other fixes.
d0c4578 [Zongheng Yang] Tmux typo.
0ecea46 [Zongheng Yang] Changes for HiveQl and HiveContext.
ce22d80 [Zongheng Yang] Fix parsing issues.
cb722c1 [Zongheng Yang] Finish up SQLConf patch.
4ebf362 [Zongheng Yang] First cut at SQLConf inside SQLContext.
This PR attempts to resolve [SPARK-1704](https://issues.apache.org/jira/browse/SPARK-1704) by introducing a physical plan for EXPLAIN commands, which just prints out the debug string (containing various SparkSQL's plans) of the corresponding QueryExecution for the actual query.
Author: Zongheng Yang <zongheng.y@gmail.com>
Closes#1003 from concretevitamin/explain-cmd and squashes the following commits:
5b7911f [Zongheng Yang] Add a regression test.
1bfa379 [Zongheng Yang] Modify output().
719ada9 [Zongheng Yang] Override otherCopyArgs for ExplainCommandPhysical.
4318fd7 [Zongheng Yang] Make all output one Row.
439c6ab [Zongheng Yang] Minor cleanups.
408f574 [Zongheng Yang] SPARK-1704: Add CommandStrategy and ExplainCommandPhysical.
Just submit another solution for #395
Author: Daoyuan <daoyuan.wang@intel.com>
Author: Michael Armbrust <michael@databricks.com>
Author: Daoyuan Wang <daoyuan.wang@intel.com>
Closes#837 from adrian-wang/left-semi-join-support and squashes the following commits:
d39cd12 [Daoyuan Wang] Merge pull request #1 from marmbrus/pr/837
6713c09 [Michael Armbrust] Better debugging for failed query tests.
035b73e [Michael Armbrust] Add test for left semi that can't be done with a hash join.
5ec6fa4 [Michael Armbrust] Add left semi to SQL Parser.
4c726e5 [Daoyuan] improvement according to Michael
8d4a121 [Daoyuan] add golden files for leftsemijoin
83a3c8a [Daoyuan] scala style fix
14cff80 [Daoyuan] add support for left semi join
Basically there is a race condition (possibly a scala bug?) when these values are recomputed on all of the slaves that results in an incorrect projection being generated (possibly because the GUID uniqueness contract is broken?).
In general we should probably enforce that all expression planing occurs on the driver, as is now occurring here.
Author: Michael Armbrust <michael@databricks.com>
Closes#1004 from marmbrus/fixAggBug and squashes the following commits:
e0c116c [Michael Armbrust] Compute aggregate expression during planning instead of lazily on workers.
Followup: #989
Author: Michael Armbrust <michael@databricks.com>
Closes#994 from marmbrus/caseSensitiveFunctions2 and squashes the following commits:
9d9c8ed [Michael Armbrust] Fix DIV and BETWEEN.
Author: Michael Armbrust <michael@databricks.com>
Closes#989 from marmbrus/caseSensitiveFuncitons and squashes the following commits:
681de54 [Michael Armbrust] LIKE, RLIKE and IN in HQL should not be case sensitive.
Author: Michael Armbrust <michael@databricks.com>
Closes#985 from marmbrus/tableName and squashes the following commits:
3caaa27 [Michael Armbrust] Correctly analyze queries where columnName == tableName.
`CaseConversionExpression` should check if the evaluated value is `null`.
Author: Takuya UESHIN <ueshin@happy-camper.st>
Closes#982 from ueshin/issues/SPARK-2036 and squashes the following commits:
61e1c54 [Takuya UESHIN] Add check if the evaluated value is null.
Author: Takuya UESHIN <ueshin@happy-camper.st>
Closes#974 from ueshin/issues/SPARK-2029 and squashes the following commits:
e19e8f4 [Takuya UESHIN] Bump version number to 1.1.0-SNAPSHOT.
stop resetting spark.driver.port in unit tests (scala, java and python).
Author: Syed Hashmi <shashmi@cloudera.com>
Author: CodingCat <zhunansjtu@gmail.com>
Closes#943 from syedhashmi/master and squashes the following commits:
885f210 [Syed Hashmi] Removing unnecessary file (created by mergetool)
b8bd4b5 [Syed Hashmi] Merge remote-tracking branch 'upstream/master'
b895e59 [Syed Hashmi] Revert "[SPARK-1784] Add a new partitioner"
57b6587 [Syed Hashmi] Revert "[SPARK-1784] Add a balanced partitioner"
1574769 [Syed Hashmi] [SPARK-1942] Stop clearing spark.driver.port in unit tests
4354836 [Syed Hashmi] Revert "SPARK-1686: keep schedule() calling in the main thread"
fd36542 [Syed Hashmi] [SPARK-1784] Add a balanced partitioner
6668015 [CodingCat] SPARK-1686: keep schedule() calling in the main thread
4ca94cc [Syed Hashmi] [SPARK-1784] Add a new partitioner
This is a follow up of PR #758.
The `unwrapHiveData` function is now composed statically before actual rows are scanned according to the field object inspector to avoid dynamic dispatching cost.
According to the same micro benchmark used in PR #758, this simple change brings slight performance boost: 2.5% for CSV table and 1% for RCFile table.
```
Optimized version:
CSV: 6870 ms, RCFile: 5687 ms
CSV: 6832 ms, RCFile: 5800 ms
CSV: 6822 ms, RCFile: 5679 ms
CSV: 6704 ms, RCFile: 5758 ms
CSV: 6819 ms, RCFile: 5725 ms
Original version:
CSV: 7042 ms, RCFile: 5667 ms
CSV: 6883 ms, RCFile: 5703 ms
CSV: 7115 ms, RCFile: 5665 ms
CSV: 7020 ms, RCFile: 5981 ms
CSV: 6871 ms, RCFile: 5906 ms
```
Author: Cheng Lian <lian.cs.zju@gmail.com>
Closes#935 from liancheng/staticUnwrapping and squashes the following commits:
c49c70c [Cheng Lian] Avoid dynamic dispatching when unwrapping Hive data.
I don't know whether it's time to implement system function about string operation in spark sql now.
Author: egraldlo <egraldlo@gmail.com>
Closes#936 from egraldlo/stringoperator and squashes the following commits:
3c6c60a [egraldlo] Add UPPER, LOWER, MAX and MIN into hive parser
ea76d0a [egraldlo] modify the formatting issues
b49f25e [egraldlo] modify the formatting issues
1f0bbb5 [egraldlo] system function upper and lower supported
13d3267 [egraldlo] system function upper and lower supported
In cases like `Limit` and `TakeOrdered`, `executeCollect()` makes optimizations that `execute().collect()` will not.
Author: Cheng Lian <lian.cs.zju@gmail.com>
Closes#939 from liancheng/spark-1958 and squashes the following commits:
bdc4a14 [Cheng Lian] Copy rows to present immutable data to users
8250976 [Cheng Lian] Added return type explicitly for public API
192a25c [Cheng Lian] [SPARK-1958] Calling .collect() on a SchemaRDD should call executeCollect() on the underlying query plan.
Author: Michael Armbrust <michael@databricks.com>
Closes#913 from marmbrus/timestampMetastore and squashes the following commits:
8e0154f [Michael Armbrust] Add timestamp to hive metastore type parser.
Child of `SumDistinct` or `Average` should be widened to prevent overflows the same as `Sum`.
Author: Takuya UESHIN <ueshin@happy-camper.st>
Closes#902 from ueshin/issues/SPARK-1947 and squashes the following commits:
99c3dcb [Takuya UESHIN] Insert Cast for SumDistinct and Average.
JIRA issue: [SPARK-1959](https://issues.apache.org/jira/browse/SPARK-1959)
Author: Cheng Lian <lian.cs.zju@gmail.com>
Closes#909 from liancheng/spark-1959 and squashes the following commits:
306659c [Cheng Lian] [SPARK-1959] String "NULL" shouldn't be interpreted as null value
JIRA issue: [SPARK-1368](https://issues.apache.org/jira/browse/SPARK-1368)
This PR introduces two major updates:
- Replaced FP style code with `while` loop and reusable `GenericMutableRow` object in critical path of `HiveTableScan`.
- Using `ColumnProjectionUtils` to help optimizing RCFile and ORC column pruning.
My quick micro benchmark suggests these two optimizations made the optimized version 2x and 2.5x faster when scanning CSV table and RCFile table respectively:
```
Original:
[info] CSV: 27676 ms, RCFile: 26415 ms
[info] CSV: 27703 ms, RCFile: 26029 ms
[info] CSV: 27511 ms, RCFile: 25962 ms
Optimized:
[info] CSV: 13820 ms, RCFile: 10402 ms
[info] CSV: 14158 ms, RCFile: 10691 ms
[info] CSV: 13606 ms, RCFile: 10346 ms
```
The micro benchmark loads a 609MB CVS file (structurally similar to the `src` test table) into a normal Hive table with `LazySimpleSerDe` and a RCFile table, then scans these tables respectively.
Preparation code:
```scala
package org.apache.spark.examples.sql.hive
import org.apache.spark.sql.hive.LocalHiveContext
import org.apache.spark.{SparkConf, SparkContext}
object HiveTableScanPrepare extends App {
val sparkContext = new SparkContext(
new SparkConf()
.setMaster("local")
.setAppName(getClass.getSimpleName.stripSuffix("$")))
val hiveContext = new LocalHiveContext(sparkContext)
import hiveContext._
hql("drop table scan_csv")
hql("drop table scan_rcfile")
hql("""create table scan_csv (key int, value string)
| row format serde 'org.apache.hadoop.hive.serde2.lazy.LazySimpleSerDe'
| with serdeproperties ('field.delim'=',')
""".stripMargin)
hql(s"""load data local inpath "${args(0)}" into table scan_csv""")
hql("""create table scan_rcfile (key int, value string)
| row format serde 'org.apache.hadoop.hive.serde2.columnar.ColumnarSerDe'
|stored as
| inputformat 'org.apache.hadoop.hive.ql.io.RCFileInputFormat'
| outputformat 'org.apache.hadoop.hive.ql.io.RCFileOutputFormat'
""".stripMargin)
hql(
"""
|from scan_csv
|insert overwrite table scan_rcfile
|select scan_csv.key, scan_csv.value
""".stripMargin)
}
```
Benchmark code:
```scala
package org.apache.spark.examples.sql.hive
import org.apache.spark.sql.hive.LocalHiveContext
import org.apache.spark.{SparkConf, SparkContext}
object HiveTableScanBenchmark extends App {
val sparkContext = new SparkContext(
new SparkConf()
.setMaster("local")
.setAppName(getClass.getSimpleName.stripSuffix("$")))
val hiveContext = new LocalHiveContext(sparkContext)
import hiveContext._
val scanCsv = hql("select key from scan_csv")
val scanRcfile = hql("select key from scan_rcfile")
val csvDuration = benchmark(scanCsv.count())
val rcfileDuration = benchmark(scanRcfile.count())
println(s"CSV: $csvDuration ms, RCFile: $rcfileDuration ms")
def benchmark(f: => Unit) = {
val begin = System.currentTimeMillis()
f
val end = System.currentTimeMillis()
end - begin
}
}
```
@marmbrus Please help review, thanks!
Author: Cheng Lian <lian.cs.zju@gmail.com>
Closes#758 from liancheng/fastHiveTableScan and squashes the following commits:
4241a19 [Cheng Lian] Distinguishes sorted and possibly not sorted operations more accurately in HiveComparisonTest
cf640d8 [Cheng Lian] More HiveTableScan optimisations:
bf0e7dc [Cheng Lian] Added SortedOperation pattern to match *some* definitely sorted operations and avoid some sorting cost in HiveComparisonTest.
6d1c642 [Cheng Lian] Using ColumnProjectionUtils to optimise RCFile and ORC column pruning
eb62fd3 [Cheng Lian] [SPARK-1368] Optimized HiveTableScan
`ApproxCountDistinctMergeFunction` should return `Int` value because the `dataType` of `ApproxCountDistinct` is `IntegerType`.
Author: Takuya UESHIN <ueshin@happy-camper.st>
Closes#893 from ueshin/issues/SPARK-1938 and squashes the following commits:
3970e88 [Takuya UESHIN] Remove a superfluous line.
5ad7ec1 [Takuya UESHIN] Make dataType for each of CountDistinct, ApproxCountDistinctMerge and ApproxCountDistinct LongType.
cbe7c71 [Takuya UESHIN] Revert a change.
fc3ac0f [Takuya UESHIN] Fix evaluated value type of ApproxCountDistinctMergeFunction to Int.
Allow underscore in column name of a struct field https://issues.apache.org/jira/browse/SPARK-1922 .
Author: LY Lai <ly.lai@vpon.com>
Closes#873 from lyuanlai/master and squashes the following commits:
2253263 [LY Lai] Allow underscore in struct field column name
Average values are difference between the calculation is done partially or not partially.
Because `AverageFunction` (in not-partially calculation) counts even if the evaluated value is null.
Author: Takuya UESHIN <ueshin@happy-camper.st>
Closes#862 from ueshin/issues/SPARK-1915 and squashes the following commits:
b1ff3c0 [Takuya UESHIN] Modify AverageFunction not to count if the evaluated value is null.
Nullability of `Max`/`Min`/`First` should be `true` because they return `null` if there are no rows.
Author: Takuya UESHIN <ueshin@happy-camper.st>
Closes#881 from ueshin/issues/SPARK-1926 and squashes the following commits:
322610f [Takuya UESHIN] Fix nullability of Min/Max/First.
`CountFunction` should count up only if the child's evaluated value is not null.
Because it traverses to evaluate all child expressions, even if the child is null, it counts up if one of the all children is not null.
Author: Takuya UESHIN <ueshin@happy-camper.st>
Closes#861 from ueshin/issues/SPARK-1914 and squashes the following commits:
3b37315 [Takuya UESHIN] Merge branch 'master' into issues/SPARK-1914
2afa238 [Takuya UESHIN] Simplify CountFunction not to traverse to evaluate all child expressions.
```scala
rdd.aggregate(Sum('val))
```
is just shorthand for
```scala
rdd.groupBy()(Sum('val))
```
but seems be more natural than doing a groupBy with no grouping expressions when you really just want an aggregation over all rows.
Did not add a JavaSchemaRDD or Python API, as these seem to be lacking several other methods like groupBy() already -- leaving that cleanup for future patches.
Author: Aaron Davidson <aaron@databricks.com>
Closes#874 from aarondav/schemardd and squashes the following commits:
e9e68ee [Aaron Davidson] Add comment
db6afe2 [Aaron Davidson] Introduce SchemaRDD#aggregate() for simple aggregations
Minor cleanup following #841.
Author: Reynold Xin <rxin@apache.org>
Closes#868 from rxin/schema-count and squashes the following commits:
5442651 [Reynold Xin] SPARK-1822: Some minor cleanup work on SchemaRDD.count()
Author: Kan Zhang <kzhang@apache.org>
Closes#841 from kanzhang/SPARK-1822 and squashes the following commits:
2f8072a [Kan Zhang] [SPARK-1822] Minor style update
cf4baa4 [Kan Zhang] [SPARK-1822] Adding Scaladoc
e67c910 [Kan Zhang] [SPARK-1822] SchemaRDD.count() should use optimizer
JIRA issue: [SPARK-1913](https://issues.apache.org/jira/browse/SPARK-1913)
When scanning Parquet tables, attributes referenced only in predicates that are pushed down are not passed to the `ParquetTableScan` operator and causes exception.
Author: Cheng Lian <lian.cs.zju@gmail.com>
Closes#863 from liancheng/spark-1913 and squashes the following commits:
f976b73 [Cheng Lian] Addessed the readability issue commented by @rxin
f5b257d [Cheng Lian] Added back comments deleted by mistake
ae60ab3 [Cheng Lian] [SPARK-1913] Attributes referenced only in predicates pushed down should remain in ParquetTableScan operator
...ys.
When tables are equi-joined by multiple-keys `HashJoin` should be used, but `CartesianProduct` and then `Filter` are used.
The join keys are paired by `And` expression so we need to apply `splitConjunctivePredicates` to join condition while finding join keys.
Author: Takuya UESHIN <ueshin@happy-camper.st>
Closes#836 from ueshin/issues/SPARK-1889 and squashes the following commits:
fe1c387 [Takuya UESHIN] Apply splitConjunctivePredicates to join condition while finding join keys.
`lateral_view_outer` query sometimes returns a different set of 10 rows.
Author: Tathagata Das <tathagata.das1565@gmail.com>
Closes#838 from tdas/hive-test-fix2 and squashes the following commits:
9128a0d [Tathagata Das] Blacklisted flaky HiveCompatibility test.
Author: witgo <witgo@qq.com>
Closes#824 from witgo/SPARK-1875_commons-lang-2.6 and squashes the following commits:
ef7231d [witgo] review commit
ead3c3b [witgo] SPARK-1875:NoClassDefFoundError: StringUtils when building against Hadoop 1
Simple filter predicates such as LessThan, GreaterThan, etc., where one side is a literal and the other one a NamedExpression are now pushed down to the underlying ParquetTableScan. Here are some results for a microbenchmark with a simple schema of six fields of different types where most records failed the test:
| Uncompressed | Compressed
-------------| ------------- | -------------
File size | 10 GB | 2 GB
Speedup | 2 | 1.8
Since mileage may vary I added a new option to SparkConf:
`org.apache.spark.sql.parquet.filter.pushdown`
Default value would be `true` and setting it to `false` disables the pushdown. When most rows are expected to pass the filter or when there are few fields performance can be better when pushdown is disabled. The default should fit situations with a reasonable number of (possibly nested) fields where not too many records on average pass the filter.
Because of an issue with Parquet ([see here](https://github.com/Parquet/parquet-mr/issues/371])) currently only predicates on non-nullable attributes are pushed down. If one would know that for a given table no optional fields have missing values one could also allow overriding this.
Author: Andre Schumacher <andre.schumacher@iki.fi>
Closes#511 from AndreSchumacher/parquet_filter and squashes the following commits:
16bfe83 [Andre Schumacher] Removing leftovers from merge during rebase
7b304ca [Andre Schumacher] Fixing formatting
c36d5cb [Andre Schumacher] Scalastyle
3da98db [Andre Schumacher] Second round of review feedback
7a78265 [Andre Schumacher] Fixing broken formatting in ParquetFilter
a86553b [Andre Schumacher] First round of code review feedback
b0f7806 [Andre Schumacher] Optimizing imports in ParquetTestData
85fea2d [Andre Schumacher] Adding SparkConf setting to disable filter predicate pushdown
f0ad3cf [Andre Schumacher] Undoing changes not needed for this PR
210e9cb [Andre Schumacher] Adding disjunctive filter predicates
a93a588 [Andre Schumacher] Adding unit test for filtering
6d22666 [Andre Schumacher] Extending ParquetFilters
93e8192 [Andre Schumacher] First commit Parquet record filtering
Author: Michael Armbrust <michael@databricks.com>
Closes#804 from marmbrus/between and squashes the following commits:
ae24672 [Michael Armbrust] add golden answer.
d9997ef [Michael Armbrust] Implement between in hql.
9bd4433 [Michael Armbrust] Better error on parse failures.
This patch unify the foldable & nullable interface for Expression.
1) Deterministic-less UDF (like Rand()) can not be folded.
2) Short-circut will significantly improves the performance in Expression Evaluation, however, the stateful UDF should not be ignored in a short-circuit evaluation(e.g. in expression: col1 > 0 and row_sequence() < 1000, row_sequence() can not be ignored even if col1 > 0 is false)
I brought an concept of DeferredObject from Hive, which has 2 kinds of children classes (EagerResult / DeferredResult), the former requires triggering the evaluation before it's created, while the later trigger the evaluation when first called its get() method.
Author: Cheng Hao <hao.cheng@intel.com>
Closes#446 from chenghao-intel/expression_deferred_evaluation and squashes the following commits:
d2729de [Cheng Hao] Fix the codestyle issues
a08f09c [Cheng Hao] fix bug in or/and short-circuit evaluation
af2236b [Cheng Hao] revert the short-circuit expression evaluation for IF
b7861d2 [Cheng Hao] Add Support for Deferred Expression Evaluation
Author: Michael Armbrust <michael@databricks.com>
Closes#797 from marmbrus/smallInt and squashes the following commits:
2db9dae [Michael Armbrust] Fix tiny/small ints from HiveMetastore.
This patch replaces colon in several filenames with dash to make these filenames Windows compatible.
Author: Stevo Slavić <sslavic@gmail.com>
Author: Stevo Slavic <sslavic@gmail.com>
Closes#739 from sslavic/SPARK-1803 and squashes the following commits:
3ec66eb [Stevo Slavic] Removed extra empty line which was causing test to fail
b967cc3 [Stevo Slavić] Aligned tests and names of test resources
2b12776 [Stevo Slavić] Fixed a typo in file name
1c5dfff [Stevo Slavić] Replaced colon in file name with dash
8f5bf7f [Stevo Slavić] Replaced colon in file name with dash
c5b5083 [Stevo Slavić] Replaced colon in file name with dash
a49801f [Stevo Slavić] Replaced colon in file name with dash
401d99e [Stevo Slavić] Replaced colon in file name with dash
40a9621 [Stevo Slavić] Replaced colon in file name with dash
4774580 [Stevo Slavić] Replaced colon in file name with dash
004f8bb [Stevo Slavić] Replaced colon in file name with dash
d6a3e2c [Stevo Slavić] Replaced colon in file name with dash
b585126 [Stevo Slavić] Replaced colon in file name with dash
028e48a [Stevo Slavić] Replaced colon in file name with dash
ece0507 [Stevo Slavić] Replaced colon in file name with dash
84f5d2f [Stevo Slavić] Replaced colon in file name with dash
2fc7854 [Stevo Slavić] Replaced colon in file name with dash
9e1467d [Stevo Slavić] Replaced colon in file name with dash
`GetField.nullable` should be `true` not only when `field.nullable` is `true` but also when `child.nullable` is `true`.
Author: Takuya UESHIN <ueshin@happy-camper.st>
Closes#757 from ueshin/issues/SPARK-1819 and squashes the following commits:
8781a11 [Takuya UESHIN] Modify a test to use named parameters.
5bfc77d [Takuya UESHIN] Fix GetField.nullable.
...Scala collections.
When I execute `orderBy` or `limit` for `SchemaRDD` including `ArrayType` or `MapType`, `SparkSqlSerializer` throws the following exception:
```
com.esotericsoftware.kryo.KryoException: Class cannot be created (missing no-arg constructor): scala.collection.immutable.$colon$colon
```
or
```
com.esotericsoftware.kryo.KryoException: Class cannot be created (missing no-arg constructor): scala.collection.immutable.Vector
```
or
```
com.esotericsoftware.kryo.KryoException: Class cannot be created (missing no-arg constructor): scala.collection.immutable.HashMap$HashTrieMap
```
and so on.
This is because registrations of serializers for each concrete collections are missing in `SparkSqlSerializer`.
I believe it should use `AllScalaRegistrar`.
`AllScalaRegistrar` covers a lot of serializers for concrete classes of `Seq`, `Map` for `ArrayType`, `MapType`.
Author: Takuya UESHIN <ueshin@happy-camper.st>
Closes#790 from ueshin/issues/SPARK-1845 and squashes the following commits:
d1ed992 [Takuya UESHIN] Use AllScalaRegistrar for SparkSqlSerializer to register serializers of Scala collections.
Author: witgo <witgo@qq.com>
Closes#754 from witgo/commons-lang and squashes the following commits:
3ebab31 [witgo] merge master
f3b8fa2 [witgo] merge master
2083fae [witgo] repeat definition
5599cdb [witgo] multiple version of sbt dependency
c1b66a1 [witgo] fix different versions of commons-lang dependency
This is a few changes based on the original patch by @scrapcodes.
Author: Prashant Sharma <prashant.s@imaginea.com>
Author: Patrick Wendell <pwendell@gmail.com>
Closes#785 from pwendell/package-docs and squashes the following commits:
c32b731 [Patrick Wendell] Changes based on Prashant's patch
c0463d3 [Prashant Sharma] added eof new line
ce8bf73 [Prashant Sharma] Added eof new line to all files.
4c35f2e [Prashant Sharma] SPARK-1563 Add package-info.java and package.scala files for all packages that appear in docs
Author: wangfei <scnbwf@yeah.net>
Closes#765 from scwf/dslfix and squashes the following commits:
d2d1a9d [wangfei] Update package.scala
66ff53b [wangfei] fix the head notation of package object dsl
See https://issues.apache.org/jira/browse/SPARK-1828 for more information.
This is being submitted to Jenkin's for testing. The dependency won't fully
propagate in Maven central for a few more hours.
Author: Patrick Wendell <pwendell@gmail.com>
Closes#767 from pwendell/hive-shaded and squashes the following commits:
ea10ac5 [Patrick Wendell] SPARK-1828: Created forked version of hive-exec that doesn't bundle other dependencies
Add the implementation for ApproximateCountDistinct to SparkSql. We use the HyperLogLog algorithm implemented in stream-lib, and do the count in two phases: 1) counting the number of distinct elements in each partitions, and 2) merge the HyperLogLog results from different partitions.
A simple serializer and test cases are added as well.
Author: larvaboy <larvaboy@gmail.com>
Closes#737 from larvaboy/master and squashes the following commits:
bd8ef3f [larvaboy] Add support of user-provided standard deviation to ApproxCountDistinct.
9ba8360 [larvaboy] Fix alignment and null handling issues.
95b4067 [larvaboy] Add a test case for count distinct and approximate count distinct.
f57917d [larvaboy] Add the parser for the approximate count.
a2d5d10 [larvaboy] Add ApproximateCountDistinct aggregates and functions.
7ad273a [larvaboy] Add SparkSql serializer for HyperLogLog.
1d9aacf [larvaboy] Fix a minor typo in the toString method of the Count case class.
653542b [larvaboy] Fix a couple of minor typos.
Author: Michael Armbrust <michael@databricks.com>
Closes#761 from marmbrus/existingContext and squashes the following commits:
4651051 [Michael Armbrust] Make it possible to create Java/Python SQLContexts from an existing Scala SQLContext.
https://issues.apache.org/jira/browse/SPARK-1757
The first test succeeds, but the second test fails with exception:
```
[info] - save and load case class RDD with Nones as parquet *** FAILED *** (14 milliseconds)
[info] java.lang.RuntimeException: Unsupported datatype StructType(List())
[info] at scala.sys.package$.error(package.scala:27)
[info] at org.apache.spark.sql.parquet.ParquetTypesConverter$.fromDataType(ParquetRelation.scala:201)
[info] at org.apache.spark.sql.parquet.ParquetTypesConverter$$anonfun$1.apply(ParquetRelation.scala:235)
[info] at org.apache.spark.sql.parquet.ParquetTypesConverter$$anonfun$1.apply(ParquetRelation.scala:235)
[info] at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:244)
[info] at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:244)
[info] at scala.collection.immutable.List.foreach(List.scala:318)
[info] at scala.collection.TraversableLike$class.map(TraversableLike.scala:244)
[info] at scala.collection.AbstractTraversable.map(Traversable.scala:105)
[info] at org.apache.spark.sql.parquet.ParquetTypesConverter$.convertFromAttributes(ParquetRelation.scala:234)
[info] at org.apache.spark.sql.parquet.ParquetTypesConverter$.writeMetaData(ParquetRelation.scala:267)
[info] at org.apache.spark.sql.parquet.ParquetRelation$.createEmpty(ParquetRelation.scala:143)
[info] at org.apache.spark.sql.parquet.ParquetRelation$.create(ParquetRelation.scala:122)
[info] at org.apache.spark.sql.execution.SparkStrategies$ParquetOperations$.apply(SparkStrategies.scala:139)
[info] at org.apache.spark.sql.catalyst.planning.QueryPlanner$$anonfun$1.apply(QueryPlanner.scala:58)
[info] at org.apache.spark.sql.catalyst.planning.QueryPlanner$$anonfun$1.apply(QueryPlanner.scala:58)
[info] at scala.collection.Iterator$$anon$13.hasNext(Iterator.scala:371)
[info] at org.apache.spark.sql.catalyst.planning.QueryPlanner.apply(QueryPlanner.scala:59)
[info] at org.apache.spark.sql.SQLContext$QueryExecution.sparkPlan$lzycompute(SQLContext.scala:264)
[info] at org.apache.spark.sql.SQLContext$QueryExecution.sparkPlan(SQLContext.scala:264)
[info] at org.apache.spark.sql.SQLContext$QueryExecution.executedPlan$lzycompute(SQLContext.scala:265)
[info] at org.apache.spark.sql.SQLContext$QueryExecution.executedPlan(SQLContext.scala:265)
[info] at org.apache.spark.sql.SQLContext$QueryExecution.toRdd$lzycompute(SQLContext.scala:268)
[info] at org.apache.spark.sql.SQLContext$QueryExecution.toRdd(SQLContext.scala:268)
[info] at org.apache.spark.sql.SchemaRDDLike$class.saveAsParquetFile(SchemaRDDLike.scala:66)
[info] at org.apache.spark.sql.SchemaRDD.saveAsParquetFile(SchemaRDD.scala:98)
```
Author: Andrew Ash <andrew@andrewash.com>
Author: Michael Armbrust <michael@databricks.com>
Closes#690 from ash211/rdd-parquet-save and squashes the following commits:
747a0b9 [Andrew Ash] Merge pull request #1 from marmbrus/pr/690
54bd00e [Michael Armbrust] Need to put Option first since Option <: Seq.
8f3f281 [Andrew Ash] SPARK-1757 Add failing test for saving SparkSQL Schemas with Option[?] fields as parquet
I need this to be public for the implementation of SharkServer2. However, I think this functionality is generally useful and should be pretty stable.
Author: Michael Armbrust <michael@databricks.com>
Closes#750 from marmbrus/metastoreTypes and squashes the following commits:
f51b62e [Michael Armbrust] Make Hive Metastore conversion functions publicly visible.
