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* [SPARK-10720] [SQL] [JAVA] Add a java wrapper to create a dataframe from a ↵Holden Karau2015-09-272-17/+56
| | | | | | | | | | local list of java beans Similar to SPARK-10630 it would be nice if Java users didn't have to parallelize there data explicitly (as Scala users already can skip). Issue came up in http://stackoverflow.com/questions/32613413/apache-spark-machine-learning-cant-get-estimator-example-to-work Author: Holden Karau <holden@pigscanfly.ca> Closes #8879 from holdenk/SPARK-10720-add-a-java-wrapper-to-create-a-dataframe-from-a-local-list-of-java-beans.
* [SPARK-10741] [SQL] Hive Query Having/OrderBy against Parquet table is not ↵Wenchen Fan2015-09-276-27/+44
| | | | | | | | | | | working https://issues.apache.org/jira/browse/SPARK-10741 I choose the second approach: do not change output exprIds when convert MetastoreRelation to LogicalRelation Author: Wenchen Fan <cloud0fan@163.com> Closes #8889 from cloud-fan/hot-bug.
* [SPARK-9852] Let reduce tasks fetch multiple map output partitionsMatei Zaharia2015-09-241-0/+6
| | | | | | | | | | | | | This makes two changes: - Allow reduce tasks to fetch multiple map output partitions -- this is a pretty small change to HashShuffleFetcher - Move shuffle locality computation out of DAGScheduler and into ShuffledRDD / MapOutputTracker; this was needed because the code in DAGScheduler wouldn't work for RDDs that fetch multiple map output partitions from each reduce task I also added an AdaptiveSchedulingSuite that creates RDDs depending on multiple map output partitions. Author: Matei Zaharia <matei@databricks.com> Closes #8844 from mateiz/spark-9852.
* [SPARK-10705] [SQL] Avoid using external rows in DataFrame.toJSONLiang-Chi Hsieh2015-09-243-85/+3
| | | | | | | | | | JIRA: https://issues.apache.org/jira/browse/SPARK-10705 As described in the JIRA ticket, `DataFrame.toJSON` uses `DataFrame.mapPartitions`, which converts internal rows to external rows. We should use `queryExecution.toRdd.mapPartitions` that directly uses internal rows for better performance. Author: Liang-Chi Hsieh <viirya@appier.com> Closes #8865 from viirya/df-tojson-internalrow.
* [SPARK-10765] [SQL] use new aggregate interface for hive UDAFWenchen Fan2015-09-243-2/+65
| | | | | | Author: Wenchen Fan <cloud0fan@163.com> Closes #8874 from cloud-fan/hive-agg.
* [SPARK-10474] [SQL] Aggregation fails to allocate memory for pointer array ↵Andrew Or2015-09-232-13/+4
| | | | | | | | | | | | | | (round 2) This patch reverts most of the changes in a previous fix #8827. The real cause of the issue is that in `TungstenAggregate`'s prepare method we only reserve 1 page, but later when we switch to sort-based aggregation we try to acquire 1 page AND a pointer array. The longer-term fix should be to reserve also the pointer array, but for now ***we will simply not track the pointer array***. (Note that elsewhere we already don't track the pointer array, e.g. [here](https://github.com/apache/spark/blob/a18208047f06a4244703c17023bb20cbe1f59d73/sql/core/src/main/java/org/apache/spark/sql/execution/UnsafeKVExternalSorter.java#L88)) Note: This patch reuses the unit test added in #8827 so it doesn't show up in the diff. Author: Andrew Or <andrew@databricks.com> Closes #8888 from andrewor14/dont-track-pointer-array.
* [SPARK-10731] [SQL] Delegate to Scala's DataFrame.take implementation in ↵Reynold Xin2015-09-232-10/+20
| | | | | | | | | | | | Python DataFrame. Python DataFrame.head/take now requires scanning all the partitions. This pull request changes them to delegate the actual implementation to Scala DataFrame (by calling DataFrame.take). This is more of a hack for fixing this issue in 1.5.1. A more proper fix is to change executeCollect and executeTake to return InternalRow rather than Row, and thus eliminate the extra round-trip conversion. Author: Reynold Xin <rxin@databricks.com> Closes #8876 from rxin/SPARK-10731.
* [SPARK-10403] Allow UnsafeRowSerializer to work with tungsten-sort ↵Josh Rosen2015-09-232-18/+27
| | | | | | | | | | ShuffleManager This patch attempts to fix an issue where Spark SQL's UnsafeRowSerializer was incompatible with the `tungsten-sort` ShuffleManager. Author: Josh Rosen <joshrosen@databricks.com> Closes #8873 from JoshRosen/SPARK-10403.
* [SPARK-10714] [SPARK-8632] [SPARK-10685] [SQL] Refactor Python UDF handlingReynold Xin2015-09-221-34/+46
| | | | | | | | | | | | | | | | This patch refactors Python UDF handling: 1. Extract the per-partition Python UDF calling logic from PythonRDD into a PythonRunner. PythonRunner itself expects iterator as input/output, and thus has no dependency on RDD. This way, we can use PythonRunner directly in a mapPartitions call, or in the future in an environment without RDDs. 2. Use PythonRunner in Spark SQL's BatchPythonEvaluation. 3. Updated BatchPythonEvaluation to only use its input once, rather than twice. This should fix Python UDF performance regression in Spark 1.5. There are a number of small cleanups I wanted to do when I looked at the code, but I kept most of those out so the diff looks small. This basically implements the approach in https://github.com/apache/spark/pull/8833, but with some code moving around so the correctness doesn't depend on the inner workings of Spark serialization and task execution. Author: Reynold Xin <rxin@databricks.com> Closes #8835 from rxin/python-iter-refactor.
* [SPARK-10737] [SQL] When using UnsafeRows, SortMergeJoin may return wrong ↵Yin Huai2015-09-223-5/+57
| | | | | | | | | | results https://issues.apache.org/jira/browse/SPARK-10737 Author: Yin Huai <yhuai@databricks.com> Closes #8854 from yhuai/SMJBug.
* [SPARK-10740] [SQL] handle nondeterministic expressions correctly for set ↵Wenchen Fan2015-09-221-0/+41
| | | | | | | | | | operations https://issues.apache.org/jira/browse/SPARK-10740 Author: Wenchen Fan <cloud0fan@163.com> Closes #8858 from cloud-fan/non-deter.
* [SQL] [MINOR] map -> foreach.Reynold Xin2015-09-221-3/+2
| | | | | | | | DataFrame.explain should use foreach to print the explain content. Author: Reynold Xin <rxin@databricks.com> Closes #8862 from rxin/map-foreach.
* [SPARK-10446][SQL] Support to specify join type when calling join with ↵Liang-Chi Hsieh2015-09-212-1/+34
| | | | | | | | | | | | usingColumns JIRA: https://issues.apache.org/jira/browse/SPARK-10446 Currently the method `join(right: DataFrame, usingColumns: Seq[String])` only supports inner join. It is more convenient to have it support other join types. Author: Liang-Chi Hsieh <viirya@appier.com> Closes #8600 from viirya/usingcolumns_df.
* [SPARK-10419] [SQL] Adding SQLServer support for datetimeoffset types to ↵Ewan Leith2015-09-212-0/+19
| | | | | | | | | | | | JdbcDialects Reading from Microsoft SQL Server over jdbc fails when the table contains datetimeoffset types. This patch registers a SQLServer JDBC Dialect that maps datetimeoffset to a String, as Microsoft suggest. Author: Ewan Leith <ewan.leith@realitymine.com> Closes #8575 from realitymine-coordinator/sqlserver.
* [SPARK-10495] [SQL] Read date values in JSON data stored by Spark 1.5.0.Yin Huai2015-09-213-2/+152
| | | | | | | | https://issues.apache.org/jira/browse/SPARK-10681 Author: Yin Huai <yhuai@databricks.com> Closes #8806 from yhuai/SPARK-10495.
* [SPARK-10630] [SQL] Add a createDataFrame API that takes in a java listHolden Karau2015-09-212-0/+24
| | | | | | | | It would be nice to support creating a DataFrame directly from a Java List of Row. Author: Holden Karau <holden@pigscanfly.ca> Closes #8779 from holdenk/SPARK-10630-create-DataFrame-from-Java-List.
* [SPARK-10710] Remove ability to disable spilling in core and SQLJosh Rosen2015-09-197-62/+19
| | | | | | | | | | It does not make much sense to set `spark.shuffle.spill` or `spark.sql.planner.externalSort` to false: I believe that these configurations were initially added as "escape hatches" to guard against bugs in the external operators, but these operators are now mature and well-tested. In addition, these configurations are not handled in a consistent way anymore: SQL's Tungsten codepath ignores these configurations and will continue to use spilling operators. Similarly, Spark Core's `tungsten-sort` shuffle manager does not respect `spark.shuffle.spill=false`. This pull request removes these configurations, adds warnings at the appropriate places, and deletes a large amount of code which was only used in code paths that did not support spilling. Author: Josh Rosen <joshrosen@databricks.com> Closes #8831 from JoshRosen/remove-ability-to-disable-spilling.
* [SPARK-10155] [SQL] Change SqlParser to object to avoid memory leakzsxwing2015-09-194-9/+9
| | | | | | | | | | Since `scala.util.parsing.combinator.Parsers` is thread-safe since Scala 2.10 (See [SI-4929](https://issues.scala-lang.org/browse/SI-4929)), we can change SqlParser to object to avoid memory leak. I didn't change other subclasses of `scala.util.parsing.combinator.Parsers` because there is only one instance in one SQLContext, which should not be an issue. Author: zsxwing <zsxwing@gmail.com> Closes #8357 from zsxwing/sql-memory-leak.
* [SPARK-10474] [SQL] Aggregation fails to allocate memory for pointer arrayAndrew Or2015-09-182-3/+54
| | | | | | | | | | | | | | | | When `TungstenAggregation` hits memory pressure, it switches from hash-based to sort-based aggregation in-place. However, in the process we try to allocate the pointer array for writing to the new `UnsafeExternalSorter` *before* actually freeing the memory from the hash map. This lead to the following exception: ``` java.io.IOException: Could not acquire 65536 bytes of memory at org.apache.spark.util.collection.unsafe.sort.UnsafeExternalSorter.initializeForWriting(UnsafeExternalSorter.java:169) at org.apache.spark.util.collection.unsafe.sort.UnsafeExternalSorter.spill(UnsafeExternalSorter.java:220) at org.apache.spark.sql.execution.UnsafeKVExternalSorter.<init>(UnsafeKVExternalSorter.java:126) at org.apache.spark.sql.execution.UnsafeFixedWidthAggregationMap.destructAndCreateExternalSorter(UnsafeFixedWidthAggregationMap.java:257) at org.apache.spark.sql.execution.aggregate.TungstenAggregationIterator.switchToSortBasedAggregation(TungstenAggregationIterator.scala:435) ``` Author: Andrew Or <andrew@databricks.com> Closes #8827 from andrewor14/allocate-pointer-array.
* [SPARK-10539] [SQL] Project should not be pushed down through Intersect or ↵Yijie Shen2015-09-181-0/+9
| | | | | | | | | | | | | | | Except #8742 Intersect and Except are both set operators and they use the all the columns to compare equality between rows. When pushing their Project parent down, the relations they based on would change, therefore not an equivalent transformation. JIRA: https://issues.apache.org/jira/browse/SPARK-10539 I added some comments based on the fix of https://github.com/apache/spark/pull/8742. Author: Yijie Shen <henry.yijieshen@gmail.com> Author: Yin Huai <yhuai@databricks.com> Closes #8823 from yhuai/fix_set_optimization.
* [SPARK-10451] [SQL] Prevent unnecessary serializations in ↵Yash Datta2015-09-181-14/+21
| | | | | | | | | | | | InMemoryColumnarTableScan Many of the fields in InMemoryColumnar scan and InMemoryRelation can be made transient. This reduces my 1000ms job to abt 700 ms . The task size reduces from 2.8 mb to ~1300kb Author: Yash Datta <Yash.Datta@guavus.com> Closes #8604 from saucam/serde.
* [SPARK-10639] [SQL] Need to convert UDAF's result from scala to sql typeYin Huai2015-09-173-9/+60
| | | | | | | | https://issues.apache.org/jira/browse/SPARK-10639 Author: Yin Huai <yhuai@databricks.com> Closes #8788 from yhuai/udafConversion.
* [SPARK-10459] [SQL] Do not need to have ConvertToSafe for PythonUDFLiang-Chi Hsieh2015-09-171-0/+4
| | | | | | | | | | | | JIRA: https://issues.apache.org/jira/browse/SPARK-10459 As mentioned in the JIRA, `PythonUDF` actually could process `UnsafeRow`. Specially, the rows in `childResults` in `BatchPythonEvaluation` will be projected to a `MutableRow`. So I think we can enable `canProcessUnsafeRows` for `BatchPythonEvaluation` and get rid of redundant `ConvertToSafe`. Author: Liang-Chi Hsieh <viirya@appier.com> Closes #8616 from viirya/pyudf-unsafe.
* [SPARK-10050] [SPARKR] Support collecting data of MapType in DataFrame.Sun Rui2015-09-161-0/+6
| | | | | | | | | 1. Support collecting data of MapType from DataFrame. 2. Support data of MapType in createDataFrame. Author: Sun Rui <rui.sun@intel.com> Closes #8711 from sun-rui/SPARK-10050.
* [SPARK-9078] [SQL] Allow jdbc dialects to override the query used to check ↵sureshthalamati2015-09-154-4/+41
| | | | | | | | | | | | the table. Current implementation uses query with a LIMIT clause to find if table already exists. This syntax works only in some database systems. This patch changes the default query to the one that is likely to work on most databases, and adds a new method to the JdbcDialect abstract class to allow dialects to override the default query. I looked at using the JDBC meta data calls, it turns out there is no common way to find the current schema, catalog..etc. There is a new method Connection.getSchema() , but that is available only starting jdk1.7 , and existing jdbc drivers may not have implemented it. Other option was to use jdbc escape syntax clause for LIMIT, not sure on how well this supported in all the databases also. After looking at all the jdbc metadata options my conclusion was most common way is to use the simple select query with 'where 1 =0' , and allow dialects to customize as needed Author: sureshthalamati <suresh.thalamati@gmail.com> Closes #8676 from sureshthalamati/table_exists_spark-9078.
* [SPARK-10613] [SPARK-10624] [SQL] Reduce LocalNode tests dependency on ↵Andrew Or2015-09-1517-636/+468
| | | | | | | | | | | | SQLContext Instead of relying on `DataFrames` to verify our answers, we can just use simple arrays. This significantly simplifies the test logic for `LocalNode`s and reduces a lot of code duplicated from `SparkPlanTest`. This also fixes an additional issue [SPARK-10624](https://issues.apache.org/jira/browse/SPARK-10624) where the output of `TakeOrderedAndProjectNode` is not actually ordered. Author: Andrew Or <andrew@databricks.com> Closes #8764 from andrewor14/sql-local-tests-cleanup.
* [SPARK-10381] Fix mixup of taskAttemptNumber & attemptId in ↵Josh Rosen2015-09-152-4/+3
| | | | | | | | | | | | | | OutputCommitCoordinator When speculative execution is enabled, consider a scenario where the authorized committer of a particular output partition fails during the OutputCommitter.commitTask() call. In this case, the OutputCommitCoordinator is supposed to release that committer's exclusive lock on committing once that task fails. However, due to a unit mismatch (we used task attempt number in one place and task attempt id in another) the lock will not be released, causing Spark to go into an infinite retry loop. This bug was masked by the fact that the OutputCommitCoordinator does not have enough end-to-end tests (the current tests use many mocks). Other factors contributing to this bug are the fact that we have many similarly-named identifiers that have different semantics but the same data types (e.g. attemptNumber and taskAttemptId, with inconsistent variable naming which makes them difficult to distinguish). This patch adds a regression test and fixes this bug by always using task attempt numbers throughout this code. Author: Josh Rosen <joshrosen@databricks.com> Closes #8544 from JoshRosen/SPARK-10381.
* [SPARK-10612] [SQL] Add prepare to LocalNode.Reynold Xin2015-09-151-0/+8
| | | | | | | | The idea is that we should separate the function call that does memory reservation (i.e. prepare) from the function call that consumes the input (e.g. open()), so all operators can be a chance to reserve memory before they are all consumed. Author: Reynold Xin <rxin@databricks.com> Closes #8761 from rxin/SPARK-10612.
* [SPARK-10548] [SPARK-10563] [SQL] Fix concurrent SQL executionsAndrew Or2015-09-151-0/+101
| | | | | | | | | | | | | | | | *Note: this is for master branch only.* The fix for branch-1.5 is at #8721. The query execution ID is currently passed from a thread to its children, which is not the intended behavior. This led to `IllegalArgumentException: spark.sql.execution.id is already set` when running queries in parallel, e.g.: ``` (1 to 100).par.foreach { _ => sc.parallelize(1 to 5).map { i => (i, i) }.toDF("a", "b").count() } ``` The cause is `SparkContext`'s local properties are inherited by default. This patch adds a way to exclude keys we don't want to be inherited, and makes SQL go through that code path. Author: Andrew Or <andrew@databricks.com> Closes #8710 from andrewor14/concurrent-sql-executions.
* [SPARK-10437] [SQL] Support aggregation expressions in Order ByLiang-Chi Hsieh2015-09-151-0/+20
| | | | | | | | | | JIRA: https://issues.apache.org/jira/browse/SPARK-10437 If an expression in `SortOrder` is a resolved one, such as `count(1)`, the corresponding rule in `Analyzer` to make it work in order by will not be applied. Author: Liang-Chi Hsieh <viirya@appier.com> Closes #8599 from viirya/orderby-agg.
* Revert "[SPARK-10300] [BUILD] [TESTS] Add support for test tags in ↵Marcelo Vanzin2015-09-151-0/+5
| | | | | | run-tests.py." This reverts commit 8abef21dac1a6538c4e4e0140323b83d804d602b.
* [SPARK-10300] [BUILD] [TESTS] Add support for test tags in run-tests.py.Marcelo Vanzin2015-09-151-5/+0
| | | | | | | | | | | | | | | This change does two things: - tag a few tests and adds the mechanism in the build to be able to disable those tags, both in maven and sbt, for both junit and scalatest suites. - add some logic to run-tests.py to disable some tags depending on what files have changed; that's used to disable expensive tests when a module hasn't explicitly been changed, to speed up testing for changes that don't directly affect those modules. Author: Marcelo Vanzin <vanzin@cloudera.com> Closes #8437 from vanzin/test-tags.
* Update version to 1.6.0-SNAPSHOT.Reynold Xin2015-09-151-1/+1
| | | | | | Author: Reynold Xin <rxin@databricks.com> Closes #8350 from rxin/1.6.
* [SPARK-9996] [SPARK-9997] [SQL] Add local expand and NestedLoopJoin operatorszsxwing2015-09-147-15/+574
| | | | | | | | This PR is in conflict with #8535 and #8573. Will update this one when they are merged. Author: zsxwing <zsxwing@gmail.com> Closes #8642 from zsxwing/expand-nest-join.
* [SPARK-6981] [SQL] Factor out SparkPlanner and QueryExecution from SQLContextEdoardo Vacchi2015-09-146-128/+195
| | | | | | | | | | Alternative to PR #6122; in this case the refactored out classes are replaced by inner classes with the same name for backwards binary compatibility * process in a lighter-weight, backwards-compatible way Author: Edoardo Vacchi <uncommonnonsense@gmail.com> Closes #6356 from evacchi/sqlctx-refactoring-lite.
* [SPARK-10330] Add Scalastyle rule to require use of SparkHadoopUtil ↵Josh Rosen2015-09-126-9/+29
| | | | | | | | | | JobContext methods This is a followup to #8499 which adds a Scalastyle rule to mandate the use of SparkHadoopUtil's JobContext accessor methods and fixes the existing violations. Author: Josh Rosen <joshrosen@databricks.com> Closes #8521 from JoshRosen/SPARK-10330-part2.
* [SPARK-6548] Adding stddev to DataFrame functionsJihongMa2015-09-127-10/+140
| | | | | | | | | | | Adding STDDEV support for DataFrame using 1-pass online /parallel algorithm to compute variance. Please review the code change. Author: JihongMa <linlin200605@gmail.com> Author: Jihong MA <linlin200605@gmail.com> Author: Jihong MA <jihongma@jihongs-mbp.usca.ibm.com> Author: Jihong MA <jihongma@Jihongs-MacBook-Pro.local> Closes #6297 from JihongMA/SPARK-SQL.
* [SPARK-10547] [TEST] Streamline / improve style of Java API testsSean Owen2015-09-125-48/+54
| | | | | | | | Fix a few Java API test style issues: unused generic types, exceptions, wrong assert argument order Author: Sean Owen <sowen@cloudera.com> Closes #8706 from srowen/SPARK-10547.
* [SPARK-9990] [SQL] Local hash join follow-upsAndrew Or2015-09-114-5/+125
| | | | | | | | | 1. Hide `LocalNodeIterator` behind the `LocalNode#asIterator` method 2. Add tests for this Author: Andrew Or <andrew@databricks.com> Closes #8708 from andrewor14/local-hash-join-follow-up.
* [SPARK-9992] [SPARK-9994] [SPARK-9998] [SQL] Implement the local TopK, ↵zsxwing2015-09-118-1/+353
| | | | | | | | | | sample and intersect operators This PR is in conflict with #8535. I will update this one when #8535 gets merged. Author: zsxwing <zsxwing@gmail.com> Closes #8573 from zsxwing/more-local-operators.
* [SPARK-10472] [SQL] Fixes DataType.typeName for UDTCheng Lian2015-09-111-0/+6
| | | | | | | | Before this fix, `MyDenseVectorUDT.typeName` gives `mydensevecto`, which is not desirable. Author: Cheng Lian <lian@databricks.com> Closes #8640 from liancheng/spark-10472/udt-type-name.
* [SPARK-10443] [SQL] Refactor SortMergeOuterJoin to reduce duplicationAndrew Or2015-09-101-61/+77
| | | | | | | | `LeftOutputIterator` and `RightOutputIterator` are symmetrically identical and can share a lot of code. If someone makes a change in one but forgets to do the same thing in the other we'll end up with inconsistent behavior. This patch also adds inline comments to clarify the intention of the code. Author: Andrew Or <andrew@databricks.com> Closes #8596 from andrewor14/smoj-cleanup.
* [SPARK-10049] [SPARKR] Support collecting data of ArraryType in DataFrame.Sun Rui2015-09-101-4/+10
| | | | | | | | | | | | | | this PR : 1. Enhance reflection in RBackend. Automatically matching a Java array to Scala Seq when finding methods. Util functions like seq(), listToSeq() in R side can be removed, as they will conflict with the Serde logic that transferrs a Scala seq to R side. 2. Enhance the SerDe to support transferring a Scala seq to R side. Data of ArrayType in DataFrame after collection is observed to be of Scala Seq type. 3. Support ArrayType in createDataFrame(). Author: Sun Rui <rui.sun@intel.com> Closes #8458 from sun-rui/SPARK-10049.
* [SPARK-9990] [SQL] Create local hash join operatorzsxwing2015-09-1016-24/+455
| | | | | | | | | | | This PR includes the following changes: - Add SQLConf to LocalNode - Add HashJoinNode - Add ConvertToUnsafeNode and ConvertToSafeNode.scala to test unsafe hash join. Author: zsxwing <zsxwing@gmail.com> Closes #8535 from zsxwing/SPARK-9990.
* [SPARK-10466] [SQL] UnsafeRow SerDe exception with data spillCheng Hao2015-09-102-5/+61
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | Data Spill with UnsafeRow causes assert failure. ``` java.lang.AssertionError: assertion failed at scala.Predef$.assert(Predef.scala:165) at org.apache.spark.sql.execution.UnsafeRowSerializerInstance$$anon$2.writeKey(UnsafeRowSerializer.scala:75) at org.apache.spark.storage.DiskBlockObjectWriter.write(DiskBlockObjectWriter.scala:180) at org.apache.spark.util.collection.ExternalSorter$$anonfun$writePartitionedFile$2$$anonfun$apply$1.apply(ExternalSorter.scala:688) at org.apache.spark.util.collection.ExternalSorter$$anonfun$writePartitionedFile$2$$anonfun$apply$1.apply(ExternalSorter.scala:687) at scala.collection.Iterator$class.foreach(Iterator.scala:727) at scala.collection.AbstractIterator.foreach(Iterator.scala:1157) at org.apache.spark.util.collection.ExternalSorter$$anonfun$writePartitionedFile$2.apply(ExternalSorter.scala:687) at org.apache.spark.util.collection.ExternalSorter$$anonfun$writePartitionedFile$2.apply(ExternalSorter.scala:683) at scala.collection.Iterator$class.foreach(Iterator.scala:727) at scala.collection.AbstractIterator.foreach(Iterator.scala:1157) at org.apache.spark.util.collection.ExternalSorter.writePartitionedFile(ExternalSorter.scala:683) at org.apache.spark.shuffle.sort.SortShuffleWriter.write(SortShuffleWriter.scala:80) at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:73) at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:41) at org.apache.spark.scheduler.Task.run(Task.scala:88) at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:214) ``` To reproduce that with code (thanks andrewor14): ```scala bin/spark-shell --master local --conf spark.shuffle.memoryFraction=0.005 --conf spark.shuffle.sort.bypassMergeThreshold=0 sc.parallelize(1 to 2 * 1000 * 1000, 10) .map { i => (i, i) }.toDF("a", "b").groupBy("b").avg().count() ``` Author: Cheng Hao <hao.cheng@intel.com> Closes #8635 from chenghao-intel/unsafe_spill.
* [SPARK-10301] [SPARK-10428] [SQL] Addresses comments of PR #8583 and #8509 ↵Cheng Lian2015-09-104-45/+522
| | | | | | | | for master Author: Cheng Lian <lian@databricks.com> Closes #8670 from liancheng/spark-10301/address-pr-comments.
* [SPARK-9730] [SQL] Add Full Outer Join support for SortMergeJoinLiang-Chi Hsieh2015-09-094-34/+248
| | | | | | | | | | | | | | | This PR is based on #8383 , thanks to viirya JIRA: https://issues.apache.org/jira/browse/SPARK-9730 This patch adds the Full Outer Join support for SortMergeJoin. A new class SortMergeFullJoinScanner is added to scan rows from left and right iterators. FullOuterIterator is simply a wrapper of type RowIterator to consume joined rows from SortMergeFullJoinScanner. Closes #8383 Author: Liang-Chi Hsieh <viirya@appier.com> Author: Davies Liu <davies@databricks.com> Closes #8579 from davies/smj_fullouter.
* [SPARK-10227] fatal warnings with sbt on Scala 2.11Luc Bourlier2015-09-091-5/+5
| | | | | | | | | | | The bulk of the changes are on `transient` annotation on class parameter. Often the compiler doesn't generate a field for this parameters, so the the transient annotation would be unnecessary. But if the class parameter are used in methods, then fields are created. So it is safer to keep the annotations. The remainder are some potential bugs, and deprecated syntax. Author: Luc Bourlier <luc.bourlier@typesafe.com> Closes #8433 from skyluc/issue/sbt-2.11.
* [HOTFIX] Fix build break caused by #8494Michael Armbrust2015-09-081-2/+2
| | | | | | Author: Michael Armbrust <michael@databricks.com> Closes #8659 from marmbrus/testBuildBreak.
* [SPARK-10327] [SQL] Cache Table is not working while subquery has alias in ↵Cheng Hao2015-09-081-0/+16
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | its project list ```scala import org.apache.spark.sql.hive.execution.HiveTableScan sql("select key, value, key + 1 from src").registerTempTable("abc") cacheTable("abc") val sparkPlan = sql( """select a.key, b.key, c.key from |abc a join abc b on a.key=b.key |join abc c on a.key=c.key""".stripMargin).queryExecution.sparkPlan assert(sparkPlan.collect { case e: InMemoryColumnarTableScan => e }.size === 3) // failed assert(sparkPlan.collect { case e: HiveTableScan => e }.size === 0) // failed ``` The actual plan is: ``` == Parsed Logical Plan == 'Project [unresolvedalias('a.key),unresolvedalias('b.key),unresolvedalias('c.key)] 'Join Inner, Some(('a.key = 'c.key)) 'Join Inner, Some(('a.key = 'b.key)) 'UnresolvedRelation [abc], Some(a) 'UnresolvedRelation [abc], Some(b) 'UnresolvedRelation [abc], Some(c) == Analyzed Logical Plan == key: int, key: int, key: int Project [key#14,key#61,key#66] Join Inner, Some((key#14 = key#66)) Join Inner, Some((key#14 = key#61)) Subquery a Subquery abc Project [key#14,value#15,(key#14 + 1) AS _c2#16] MetastoreRelation default, src, None Subquery b Subquery abc Project [key#61,value#62,(key#61 + 1) AS _c2#58] MetastoreRelation default, src, None Subquery c Subquery abc Project [key#66,value#67,(key#66 + 1) AS _c2#63] MetastoreRelation default, src, None == Optimized Logical Plan == Project [key#14,key#61,key#66] Join Inner, Some((key#14 = key#66)) Project [key#14,key#61] Join Inner, Some((key#14 = key#61)) Project [key#14] InMemoryRelation [key#14,value#15,_c2#16], true, 10000, StorageLevel(true, true, false, true, 1), (Project [key#14,value#15,(key#14 + 1) AS _c2#16]), Some(abc) Project [key#61] MetastoreRelation default, src, None Project [key#66] MetastoreRelation default, src, None == Physical Plan == TungstenProject [key#14,key#61,key#66] BroadcastHashJoin [key#14], [key#66], BuildRight TungstenProject [key#14,key#61] BroadcastHashJoin [key#14], [key#61], BuildRight ConvertToUnsafe InMemoryColumnarTableScan [key#14], (InMemoryRelation [key#14,value#15,_c2#16], true, 10000, StorageLevel(true, true, false, true, 1), (Project [key#14,value#15,(key#14 + 1) AS _c2#16]), Some(abc)) ConvertToUnsafe HiveTableScan [key#61], (MetastoreRelation default, src, None) ConvertToUnsafe HiveTableScan [key#66], (MetastoreRelation default, src, None) ``` Author: Cheng Hao <hao.cheng@intel.com> Closes #8494 from chenghao-intel/weird_cache.
generated by cgit v1.2.3 (git 2.39.1) at 2024-09-16 14:02:29 +0000