add regression test for doubly nested data #1

marmbrus · 2014-09-05T02:04:42Z

No description provided.

See compiled doc at http://people.apache.org/~rxin/tmp/openstack-swift/_site/storage-openstack-swift.html This is based on apache#1010. Closes apache#1010. Author: Reynold Xin <[email protected]> Author: Gil Vernik <[email protected]> Closes apache#2298 from rxin/openstack-swift and squashes the following commits: ff4e394 [Reynold Xin] Two minor comments from Patrick. 279f6de [Reynold Xin] core-sites -> core-site dfb8fea [Reynold Xin] Updated based on Gil's suggestion. 846f5cb [Reynold Xin] Added a link from overview page. 0447c9f [Reynold Xin] Removed sample code. e9c3761 [Reynold Xin] Merge pull request apache#1010 from gilv/master 9233fef [Gil Vernik] Fixed typos 6994827 [Gil Vernik] Merge pull request #1 from rxin/openstack ac0679e [Reynold Xin] Fixed an unclosed tr. 47ce99d [Reynold Xin] Merge branch 'master' into openstack cca7192 [Gil Vernik] Removed white spases from pom.xml 99f095d [Reynold Xin] Pending openstack changes. eb22295 [Reynold Xin] Merge pull request apache#1010 from gilv/master 39a9737 [Gil Vernik] Spark integration with Openstack Swift c977658 [Gil Vernik] Merge branch 'master' of https://github.com/gilv/spark 2aba763 [Gil Vernik] Fix to docs/openstack-integration.md 9b625b5 [Gil Vernik] Merge branch 'master' of https://github.com/gilv/spark eff538d [Gil Vernik] SPARK-938 - Openstack Swift object storage support ce483d7 [Gil Vernik] SPARK-938 - Openstack Swift object storage support b6c37ef [Gil Vernik] Openstack Swift support

Testing arguments to `sbt` need to be passed as an array, not a single, long string. Fixes a bug introduced in apache#2420. Author: Nicholas Chammas <[email protected]> Closes apache#2437 from nchammas/selective-testing and squashes the following commits: a9f9c1c [Nicholas Chammas] fix printing of sbt test arguments cf57cbf [Nicholas Chammas] fix sbt test arguments e33b978 [Nicholas Chammas] Merge pull request #2 from apache/master 0b47ca4 [Nicholas Chammas] Merge branch 'master' of github.com:nchammas/spark 8051486 [Nicholas Chammas] Merge pull request #1 from apache/master 03180a4 [Nicholas Chammas] Merge branch 'master' of github.com:nchammas/spark d4c5f43 [Nicholas Chammas] Merge pull request #6 from apache/master

VertexRDD.apply had a bug where it ignored the merge function for duplicate vertices and instead used whichever vertex attribute occurred first. This commit fixes the bug by passing the merge function through to ShippableVertexPartition.apply, which merges any duplicates using the merge function and then fills in missing vertices using the specified default vertex attribute. This commit also adds a unit test for VertexRDD.apply. Author: Larry Xiao <[email protected]> Author: Blie Arkansol <[email protected]> Author: Ankur Dave <[email protected]> Closes apache#1903 from larryxiao/2062 and squashes the following commits: 625aa9d [Blie Arkansol] Merge pull request #1 from ankurdave/SPARK-2062 476770b [Ankur Dave] ShippableVertexPartition.initFrom: Don't run mergeFunc on default values 614059f [Larry Xiao] doc update: note about the default null value vertices construction dfdb3c9 [Larry Xiao] minor fix 1c70366 [Larry Xiao] scalastyle check: wrap line, parameter list indent 4 spaces e4ca697 [Larry Xiao] [TEST] VertexRDD.apply mergeFunc 6a35ea8 [Larry Xiao] [TEST] VertexRDD.apply mergeFunc 4fbc29c [Blie Arkansol] undo unnecessary change efae765 [Larry Xiao] fix mistakes: should be able to call with or without mergeFunc b2422f9 [Larry Xiao] Merge branch '2062' of github.com:larryxiao/spark into 2062 52dc7f7 [Larry Xiao] pass mergeFunc to VertexPartitionBase, where merge is handled 581e9ee [Larry Xiao] TODO: VertexRDDSuite 20d80a3 [Larry Xiao] [SPARK-2062][GraphX] VertexRDD.apply does not use the mergeFunc

…/1.7 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 <[email protected]> Closes apache#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

@yhuai

a new PR base on new master. changes are the same as apache#1919 Author: baishuo(白硕) <[email protected]> Author: baishuo <[email protected]> Author: Cheng Lian <[email protected]> Closes apache#2226 from baishuo/patch-3007 and squashes the following commits: e69ce88 [Cheng Lian] Adds tests to verify dynamic partitioning folder layout b20a3dc [Cheng Lian] Addresses @yhuai's comments 096bbbc [baishuo(白硕)] Merge pull request #1 from liancheng/refactor-dp 1093c20 [Cheng Lian] Adds more tests 5004542 [Cheng Lian] Minor refactoring fae9eff [Cheng Lian] Refactors InsertIntoHiveTable to a Command 528e84c [Cheng Lian] Fixes typo in test name, regenerated golden answer files c464b26 [Cheng Lian] Refactors dynamic partitioning support 5033928 [baishuo] pass check style 2201c75 [baishuo] use HiveConf.DEFAULTPARTITIONNAME to replace hive.exec.default.partition.name b47c9bf [baishuo] modify according micheal's advice c3ab36d [baishuo] modify for some bad indentation 7ce2d9f [baishuo] modify code to pass scala style checks 37c1c43 [baishuo] delete a empty else branch 66e33fc [baishuo] do a little modify 88d0110 [baishuo] update file after test a3961d9 [baishuo(白硕)] Update Cast.scala f7467d0 [baishuo(白硕)] Update InsertIntoHiveTable.scala c1a59dd [baishuo(白硕)] Update Cast.scala 0e18496 [baishuo(白硕)] Update HiveQuerySuite.scala 60f70aa [baishuo(白硕)] Update InsertIntoHiveTable.scala 0a50db9 [baishuo(白硕)] Update HiveCompatibilitySuite.scala 491c7d0 [baishuo(白硕)] Update InsertIntoHiveTable.scala a2374a8 [baishuo(白硕)] Update InsertIntoHiveTable.scala 701a814 [baishuo(白硕)] Update SparkHadoopWriter.scala dc24c41 [baishuo(白硕)] Update HiveQl.scala

…link to HistoryPage's page #1 There is a Spark logo on the header of HistoryPage. We can have too many HistoryPages if we run 20+ applications. So I think, it's useful if the logo is as a link to the HistoryPage's page number 1. Author: Kousuke Saruta <[email protected]> Closes apache#2690 from sarutak/SPARK-3829 and squashes the following commits: 908c109 [Kousuke Saruta] Removed extra space. 00bfbd7 [Kousuke Saruta] Merge branch 'master' of git://git.apache.org/spark into SPARK-3829 dd87480 [Kousuke Saruta] Made header Spark log image as a link to History Server's top page.

@giwa

This patch brings Python API for Streaming. This patch is based on work from @giwa Author: giwa <[email protected]> Author: Ken Takagiwa <[email protected]> Author: Davies Liu <[email protected]> Author: Ken Takagiwa <[email protected]> Author: Tathagata Das <[email protected]> Author: Ken <[email protected]> Author: Ken Takagiwa <[email protected]> Author: Matthew Farrellee <[email protected]> Closes apache#2538 from davies/streaming and squashes the following commits: 64561e4 [Davies Liu] fix tests 331ecce [Davies Liu] fix example 3e2492b [Davies Liu] change updateStateByKey() to easy API 182be73 [Davies Liu] Merge branch 'master' of github.com:apache/spark into streaming 02d0575 [Davies Liu] add wrapper for foreachRDD() bebeb4a [Davies Liu] address all comments 6db00da [Davies Liu] Merge branch 'master' of github.com:apache/spark into streaming 8380064 [Davies Liu] Merge branch 'master' of github.com:apache/spark into streaming 52c535b [Davies Liu] remove fix for sum() e108ec1 [Davies Liu] address comments 37fe06f [Davies Liu] use random port for callback server d05871e [Davies Liu] remove reuse of PythonRDD be5e5ff [Davies Liu] merge branch of env, make tests stable. 8071541 [Davies Liu] Merge branch 'env' into streaming c7bbbce [Davies Liu] fix sphinx docs 6bb9d91 [Davies Liu] Merge branch 'master' of github.com:apache/spark into streaming 4d0ea8b [Davies Liu] clear reference of SparkEnv after stop 54bd92b [Davies Liu] improve tests c2b31cb [Davies Liu] Merge branch 'master' of github.com:apache/spark into streaming 7a88f9f [Davies Liu] rollback RDD.setContext(), use textFileStream() to test checkpointing bd8a4c2 [Davies Liu] fix scala style 7797c70 [Davies Liu] refactor ff88bec [Davies Liu] rename RDDFunction to TransformFunction d328aca [Davies Liu] fix serializer in queueStream 6f0da2f [Davies Liu] recover from checkpoint fa7261b [Davies Liu] refactor a13ff34 [Davies Liu] address comments 8466916 [Davies Liu] support checkpoint 9a16bd1 [Davies Liu] change number of partitions during tests b98d63f [Davies Liu] change private[spark] to private[python] eed6e2a [Davies Liu] rollback not needed changes e00136b [Davies Liu] address comments 069a94c [Davies Liu] fix the number of partitions during window() 338580a [Davies Liu] change _first(), _take(), _collect() as private API 19797f9 [Davies Liu] clean up 6ebceca [Davies Liu] add more tests c40c52d [Davies Liu] change first(), take(n) to has the same behavior as RDD 98ac6c2 [Davies Liu] support ssc.transform() b983f0f [Davies Liu] address comments 847f9b9 [Davies Liu] add more docs, add first(), take() e059ca2 [Davies Liu] move check of window into Python fce0ef5 [Davies Liu] rafactor of foreachRDD() 7001b51 [Davies Liu] refactor of queueStream() 26ea396 [Davies Liu] refactor 74df565 [Davies Liu] fix print and docs b32774c [Davies Liu] move java_import into streaming 604323f [Davies Liu] enable streaming tests c499ba0 [Davies Liu] remove Time and Duration 3f0fb4b [Davies Liu] refactor fix tests c28f520 [Davies Liu] support updateStateByKey d357b70 [Davies Liu] support windowed dstream bd13026 [Davies Liu] fix examples eec401e [Davies Liu] refactor, combine TransformedRDD, fix reuse PythonRDD, fix union 9a57685 [Davies Liu] fix python style bd27874 [Davies Liu] fix scala style 7339be0 [Davies Liu] delete tests 7f53086 [Davies Liu] support transform(), refactor and cleanup df098fc [Davies Liu] Merge branch 'master' into giwa 550dfd9 [giwa] WIP fixing 1.1 merge 5cdb6fa [giwa] changed for SCCallSiteSync e685853 [giwa] meged with rebased 1.1 branch 2d32a74 [giwa] added some StreamingContextTestSuite 4a59e1e [giwa] WIP:added more test for StreamingContext 8ffdbf1 [giwa] added atexit to handle callback server d5f5fcb [giwa] added comment for StreamingContext.sparkContext 63c881a [giwa] added StreamingContext.sparkContext d39f102 [giwa] added StreamingContext.remember d542743 [giwa] clean up code 2fdf0de [Matthew Farrellee] Fix scalastyle errors c0a06bc [giwa] delete not implemented functions f385976 [giwa] delete inproper comments b0f2015 [giwa] added comment in dstream._test_output bebb3f3 [giwa] remove the last brank line fbed8da [giwa] revert pom.xml 8ed93af [giwa] fixed explanaiton 066ba90 [giwa] revert pom.xml fa4af88 [giwa] remove duplicated import 6ae3caa [giwa] revert pom.xml 7dc7391 [giwa] fixed typo 62dc7a3 [giwa] clean up exmples f04882c [giwa] clen up examples b171ec3 [giwa] fixed pep8 violation f198d14 [giwa] clean up code 3166d31 [giwa] clean up c00e091 [giwa] change test case not to use awaitTermination e80647e [giwa] adopted the latest compression way of python command 58e41ff [giwa] merge with master 455e5af [giwa] removed wasted print in DStream af336b7 [giwa] add comments ddd4ee1 [giwa] added TODO coments 99ce042 [giwa] added saveAsTextFiles and saveAsPickledFiles 2a06cdb [giwa] remove waste duplicated code c5ecfc1 [giwa] basic function test cases are passed 8dcda84 [giwa] all tests are passed if numSlice is 2 and the numver of each input is over 4 795b2cd [giwa] broke something 1e126bf [giwa] WIP: solved partitioned and None is not recognized f67cf57 [giwa] added mapValues and flatMapVaules WIP for glom and mapPartitions test 953deb0 [giwa] edited the comment to add more precise description af610d3 [giwa] removed unnesessary changes c1d546e [giwa] fixed PEP-008 violation 99410be [giwa] delete waste file b3b0362 [giwa] added basic operation test cases 9cde7c9 [giwa] WIP added test case bd3ba53 [giwa] WIP 5c04a5f [giwa] WIP: added PythonTestInputStream 019ef38 [giwa] WIP 1934726 [giwa] update comment 376e3ac [giwa] WIP 932372a [giwa] clean up dstream.py 0b09cff [giwa] added stop in StreamingContext 92e333e [giwa] implemented reduce and count function in Dstream 1b83354 [giwa] Removed the waste line 88f7506 [Ken Takagiwa] Kill py4j callback server properly 54b5358 [Ken Takagiwa] tried to restart callback server 4f07163 [Tathagata Das] Implemented DStream.foreachRDD in the Python API using Py4J callback server. fe02547 [Ken Takagiwa] remove waste file 2ad7bd3 [Ken Takagiwa] clean up codes 6197a11 [Ken Takagiwa] clean up code eb4bf48 [Ken Takagiwa] fix map function 98c2a00 [Ken Takagiwa] added count operation but this implementation need double check 58591d2 [Ken Takagiwa] reduceByKey is working 0df7111 [Ken Takagiwa] delete old file f485b1d [Ken Takagiwa] fied input of socketTextDStream dd6de81 [Ken Takagiwa] initial commit for socketTextStream 247fd74 [Ken Takagiwa] modified the code base on comment in tdas#10 4bcb318 [Ken Takagiwa] implementing transform function in Python 38adf95 [Ken Takagiwa] added reducedByKey not working yet 66fcfff [Ken Takagiwa] modify dstream.py to fix indent error 41886c2 [Ken Takagiwa] comment PythonDStream.PairwiseDStream 0b99bec [Ken] initial commit for pySparkStreaming c214199 [giwa] added testcase for combineByKey 5625bdc [giwa] added gorupByKey testcase 10ab87b [giwa] added sparkContext as input parameter in StreamingContext 10b5b04 [giwa] removed wasted print in DStream e54f986 [giwa] add comments 16aa64f [giwa] added TODO coments 74535d4 [giwa] added saveAsTextFiles and saveAsPickledFiles f76c182 [giwa] remove waste duplicated code 18c8723 [giwa] modified streaming test case to add coment 13fb44c [giwa] basic function test cases are passed 3000b2b [giwa] all tests are passed if numSlice is 2 and the numver of each input is over 4 ff14070 [giwa] broke something bcdec33 [giwa] WIP: solved partitioned and None is not recognized 270a9e1 [giwa] added mapValues and flatMapVaules WIP for glom and mapPartitions test bb10956 [giwa] edited the comment to add more precise description 253a863 [giwa] removed unnesessary changes 3d37822 [giwa] fixed PEP-008 violation f21cab3 [giwa] delete waste file 878bad7 [giwa] added basic operation test cases ce2acd2 [giwa] WIP added test case 9ad6855 [giwa] WIP 1df77f5 [giwa] WIP: added PythonTestInputStream 1523b66 [giwa] WIP 8a0fbbc [giwa] update comment fe648e3 [giwa] WIP 29c2bc5 [giwa] initial commit for testcase 4d40d63 [giwa] clean up dstream.py c462bb3 [giwa] added stop in StreamingContext d2c01ba [giwa] clean up examples 3c45cd2 [giwa] implemented reduce and count function in Dstream b349649 [giwa] Removed the waste line 3b498e1 [Ken Takagiwa] Kill py4j callback server properly 84a9668 [Ken Takagiwa] tried to restart callback server 9ab8952 [Tathagata Das] Added extra line. 05e991b [Tathagata Das] Added missing file b1d2a30 [Tathagata Das] Implemented DStream.foreachRDD in the Python API using Py4J callback server. 678e854 [Ken Takagiwa] remove waste file 0a8bbbb [Ken Takagiwa] clean up codes bab31c1 [Ken Takagiwa] clean up code 72b9738 [Ken Takagiwa] fix map function d3ee86a [Ken Takagiwa] added count operation but this implementation need double check 15feea9 [Ken Takagiwa] edit python sparkstreaming example 6f98e50 [Ken Takagiwa] reduceByKey is working c455c8d [Ken Takagiwa] added reducedByKey not working yet dc6995d [Ken Takagiwa] delete old file b31446a [Ken Takagiwa] fixed typo of network_workdcount.py ccfd214 [Ken Takagiwa] added doctest for pyspark.streaming.duration 0d1b954 [Ken Takagiwa] fied input of socketTextDStream f746109 [Ken Takagiwa] initial commit for socketTextStream bb7ccf3 [Ken Takagiwa] remove unused import in python 224fc5e [Ken Takagiwa] add empty line d2099d8 [Ken Takagiwa] sorted the import following Spark coding convention 5bac7ec [Ken Takagiwa] revert streaming/pom.xml e1df940 [Ken Takagiwa] revert pom.xml 494cae5 [Ken Takagiwa] remove not implemented DStream functions in python 17a74c6 [Ken Takagiwa] modified the code base on comment in tdas#10 1a0f065 [Ken Takagiwa] implementing transform function in Python d7b4d6f [Ken Takagiwa] added reducedByKey not working yet 87438e2 [Ken Takagiwa] modify dstream.py to fix indent error b406252 [Ken Takagiwa] comment PythonDStream.PairwiseDStream 454981d [Ken] initial commit for pySparkStreaming 150b94c [giwa] added some StreamingContextTestSuite f7bc8f9 [giwa] WIP:added more test for StreamingContext ee50c5a [giwa] added atexit to handle callback server fdc9125 [giwa] added comment for StreamingContext.sparkContext f5bfb70 [giwa] added StreamingContext.sparkContext da09768 [giwa] added StreamingContext.remember d68b568 [giwa] clean up code 4afa390 [giwa] clean up code 1fd6bc7 [Ken Takagiwa] Merge pull request #2 from mattf/giwa-master d9d59fe [Matthew Farrellee] Fix scalastyle errors 67473a9 [giwa] delete not implemented functions c97377c [giwa] delete inproper comments 2ea769e [giwa] added comment in dstream._test_output 3b27bd4 [giwa] remove the last brank line acfcaeb [giwa] revert pom.xml 93f7637 [giwa] fixed explanaiton 50fd6f9 [giwa] revert pom.xml 4f82c89 [giwa] remove duplicated import 9d1de23 [giwa] revert pom.xml 7339df2 [giwa] fixed typo 9c85e48 [giwa] clean up exmples 24f95db [giwa] clen up examples 0d30109 [giwa] fixed pep8 violation b7dab85 [giwa] improve test case 583e66d [giwa] move tests for streaming inside streaming directory 1d84142 [giwa] remove unimplement test f0ea311 [giwa] clean up code 171edeb [giwa] clean up 4dedd2d [giwa] change test case not to use awaitTermination 268a6a5 [giwa] Changed awaitTermination not to call awaitTermincation in Scala. Just use time.sleep instread 09a28bf [giwa] improve testcases 58150f5 [giwa] Changed the test case to focus the test operation 199e37f [giwa] adopted the latest compression way of python command 185fdbf [giwa] merge with master f1798c4 [giwa] merge with master e70f706 [giwa] added testcase for combineByKey e162822 [giwa] added gorupByKey testcase 97742fe [giwa] added sparkContext as input parameter in StreamingContext 14d4c0e [giwa] removed wasted print in DStream 6d8190a [giwa] add comments 4aa99e4 [giwa] added TODO coments e9fab72 [giwa] added saveAsTextFiles and saveAsPickledFiles 94f2b65 [giwa] remove waste duplicated code 580fbc2 [giwa] modified streaming test case to add coment 99e4bb3 [giwa] basic function test cases are passed 7051a84 [giwa] all tests are passed if numSlice is 2 and the numver of each input is over 4 35933e1 [giwa] broke something 9767712 [giwa] WIP: solved partitioned and None is not recognized 4f2d7e6 [giwa] added mapValues and flatMapVaules WIP for glom and mapPartitions test 33c0f94 [giwa] edited the comment to add more precise description 774f18d [giwa] removed unnesessary changes 3a671cc [giwa] remove export PYSPARK_PYTHON in spark submit 8efa266 [giwa] fixed PEP-008 violation fa75d71 [giwa] delete waste file 7f96294 [giwa] added basic operation test cases 3dda31a [giwa] WIP added test case 1f68b78 [giwa] WIP c05922c [giwa] WIP: added PythonTestInputStream 1fd12ae [giwa] WIP c880a33 [giwa] update comment 5d22c92 [giwa] WIP ea4b06b [giwa] initial commit for testcase 5a9b525 [giwa] clean up dstream.py 79c5809 [giwa] added stop in StreamingContext 189dcea [giwa] clean up examples b8d7d24 [giwa] implemented reduce and count function in Dstream b6468e6 [giwa] Removed the waste line b47b5fd [Ken Takagiwa] Kill py4j callback server properly 19ddcdd [Ken Takagiwa] tried to restart callback server c9fc124 [Tathagata Das] Added extra line. 4caae3f [Tathagata Das] Added missing file 4eff053 [Tathagata Das] Implemented DStream.foreachRDD in the Python API using Py4J callback server. 5e822d4 [Ken Takagiwa] remove waste file aeaf8a5 [Ken Takagiwa] clean up codes 9fa249b [Ken Takagiwa] clean up code 05459c6 [Ken Takagiwa] fix map function a9f4ecb [Ken Takagiwa] added count operation but this implementation need double check d1ee6ca [Ken Takagiwa] edit python sparkstreaming example 0b8b7d0 [Ken Takagiwa] reduceByKey is working d25d5cf [Ken Takagiwa] added reducedByKey not working yet 7f7c5d1 [Ken Takagiwa] delete old file 967dc26 [Ken Takagiwa] fixed typo of network_workdcount.py 57fb740 [Ken Takagiwa] added doctest for pyspark.streaming.duration 4b69fb1 [Ken Takagiwa] fied input of socketTextDStream 02f618a [Ken Takagiwa] initial commit for socketTextStream 4ce4058 [Ken Takagiwa] remove unused import in python 856d98e [Ken Takagiwa] add empty line 490e338 [Ken Takagiwa] sorted the import following Spark coding convention 5594bd4 [Ken Takagiwa] revert pom.xml 2adca84 [Ken Takagiwa] remove not implemented DStream functions in python e551e13 [Ken Takagiwa] add coment for hack why PYSPARK_PYTHON is needed in spark-submit 3758175 [Ken Takagiwa] add coment for hack why PYSPARK_PYTHON is needed in spark-submit c5518b4 [Ken Takagiwa] modified the code base on comment in tdas#10 dcf243f [Ken Takagiwa] implementing transform function in Python 9af03f4 [Ken Takagiwa] added reducedByKey not working yet 6e0d9c7 [Ken Takagiwa] modify dstream.py to fix indent error e497b9b [Ken Takagiwa] comment PythonDStream.PairwiseDStream 5c3a683 [Ken] initial commit for pySparkStreaming 665bfdb [giwa] added testcase for combineByKey a3d2379 [giwa] added gorupByKey testcase 636090a [giwa] added sparkContext as input parameter in StreamingContext e7ebb08 [giwa] removed wasted print in DStream d8b593b [giwa] add comments ea9c873 [giwa] added TODO coments 89ae38a [giwa] added saveAsTextFiles and saveAsPickledFiles e3033fc [giwa] remove waste duplicated code a14c7e1 [giwa] modified streaming test case to add coment 536def4 [giwa] basic function test cases are passed 2112638 [giwa] all tests are passed if numSlice is 2 and the numver of each input is over 4 080541a [giwa] broke something 0704b86 [giwa] WIP: solved partitioned and None is not recognized 90a6484 [giwa] added mapValues and flatMapVaules WIP for glom and mapPartitions test a65f302 [giwa] edited the comment to add more precise description bdde697 [giwa] removed unnesessary changes e8c7bfc [giwa] remove export PYSPARK_PYTHON in spark submit 3334169 [giwa] fixed PEP-008 violation db0a303 [giwa] delete waste file 2cfd3a0 [giwa] added basic operation test cases 90ae568 [giwa] WIP added test case a120d07 [giwa] WIP f671cdb [giwa] WIP: added PythonTestInputStream 56fae45 [giwa] WIP e35e101 [giwa] Merge branch 'master' into testcase ba5112d [giwa] update comment 28aa56d [giwa] WIP fb08559 [giwa] initial commit for testcase a613b85 [giwa] clean up dstream.py c40c0ef [giwa] added stop in StreamingContext 31e4260 [giwa] clean up examples d2127d6 [giwa] implemented reduce and count function in Dstream 48f7746 [giwa] Removed the waste line 0f83eaa [Ken Takagiwa] delete py4j 0.8.1 1679808 [Ken Takagiwa] Kill py4j callback server properly f96cd4e [Ken Takagiwa] tried to restart callback server fe86198 [Ken Takagiwa] add py4j 0.8.2.1 but server is not launched 1064fe0 [Ken Takagiwa] Merge branch 'master' of https://github.com/giwa/spark 28c6620 [Ken Takagiwa] Implemented DStream.foreachRDD in the Python API using Py4J callback server 85b0fe1 [Ken Takagiwa] Merge pull request #1 from tdas/python-foreach 54e2e8c [Tathagata Das] Added extra line. e185338 [Tathagata Das] Added missing file a778d4b [Tathagata Das] Implemented DStream.foreachRDD in the Python API using Py4J callback server. cc2092b [Ken Takagiwa] remove waste file d042ac6 [Ken Takagiwa] clean up codes 84a021f [Ken Takagiwa] clean up code bd20e17 [Ken Takagiwa] fix map function d01a125 [Ken Takagiwa] added count operation but this implementation need double check 7d05109 [Ken Takagiwa] merge with remote branch ae464e0 [Ken Takagiwa] edit python sparkstreaming example 04af046 [Ken Takagiwa] reduceByKey is working 3b6d7b0 [Ken Takagiwa] implementing transform function in Python 571d52d [Ken Takagiwa] added reducedByKey not working yet 5720979 [Ken Takagiwa] delete old file e604fcb [Ken Takagiwa] fixed typo of network_workdcount.py 4b7c08b [Ken Takagiwa] Merge branch 'master' of https://github.com/giwa/spark ce7d426 [Ken Takagiwa] added doctest for pyspark.streaming.duration a8c9fd5 [Ken Takagiwa] fixed for socketTextStream a61fa9e [Ken Takagiwa] fied input of socketTextDStream 1e84f41 [Ken Takagiwa] initial commit for socketTextStream 6d012f7 [Ken Takagiwa] remove unused import in python 25d30d5 [Ken Takagiwa] add empty line 6e0a64a [Ken Takagiwa] sorted the import following Spark coding convention fa4a7fc [Ken Takagiwa] revert streaming/pom.xml 8f8202b [Ken Takagiwa] revert streaming pom.xml c9d79dd [Ken Takagiwa] revert pom.xml 57e3e52 [Ken Takagiwa] remove not implemented DStream functions in python 0a516f5 [Ken Takagiwa] add coment for hack why PYSPARK_PYTHON is needed in spark-submit a7a0b5c [Ken Takagiwa] add coment for hack why PYSPARK_PYTHON is needed in spark-submit 72bfc66 [Ken Takagiwa] modified the code base on comment in tdas#10 69e9cd3 [Ken Takagiwa] implementing transform function in Python 94a0787 [Ken Takagiwa] added reducedByKey not working yet 88068cf [Ken Takagiwa] modify dstream.py to fix indent error 1367be5 [Ken Takagiwa] comment PythonDStream.PairwiseDStream eb2b3ba [Ken] Merge remote-tracking branch 'upstream/master' d8e51f9 [Ken] initial commit for pySparkStreaming

…ion sometimes JobProgressPage could not show Fair Scheduler Pools section sometimes. SparkContext starts webui and then postEnvironmentUpdate. Sometimes JobProgressPage is accessed between webui starting and postEnvironmentUpdate, then the lazy val isFairScheduler will be false. The Fair Scheduler Pools section will not display any more. Author: yantangzhai <[email protected]> Author: YanTangZhai <[email protected]> Closes apache#1966 from YanTangZhai/SPARK-3067 and squashes the following commits: d4323f8 [yantangzhai] update [SPARK-3067] JobProgressPage could not show Fair Scheduler Pools section sometimes 8a00106 [YanTangZhai] Merge pull request #6 from apache/master b6391cc [yantangzhai] revert [SPARK-3067] JobProgressPage could not show Fair Scheduler Pools section sometimes d2226cd [yantangzhai] [SPARK-3067] JobProgressPage could not show Fair Scheduler Pools section sometimes cbcba66 [YanTangZhai] Merge pull request #3 from apache/master aac7f7b [yantangzhai] [SPARK-3067] JobProgressPage could not show Fair Scheduler Pools section sometimes cdef539 [YanTangZhai] Merge pull request #1 from apache/master

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 <[email protected]> Author: zhzhan <[email protected]> Author: Patrick Wendell <[email protected]> Closes apache#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

This adds a Streaming KMeans algorithm to MLlib. It uses an update rule that generalizes the mini-batch KMeans update to incorporate a decay factor, which allows past data to be forgotten. The decay factor can be specified explicitly, or via a more intuitive "fractional decay" setting, in units of either data points or batches. The PR includes: - StreamingKMeans algorithm with decay factor settings - Usage example - Additions to documentation clustering page - Unit tests of basic behavior and decay behaviors tdas mengxr rezazadeh Author: freeman <[email protected]> Author: Jeremy Freeman <[email protected]> Author: Xiangrui Meng <[email protected]> Closes apache#2942 from freeman-lab/streaming-kmeans and squashes the following commits: b2e5b4a [freeman] Fixes to docs / examples 078617c [Jeremy Freeman] Merge pull request #1 from mengxr/SPARK-3254 2e682c0 [Xiangrui Meng] take discount on previous weights; use BLAS; detect dying clusters 0411bf5 [freeman] Change decay parameterization 9f7aea9 [freeman] Style fixes 374a706 [freeman] Formatting ad9bdc2 [freeman] Use labeled points and predictOnValues in examples 77dbd3f [freeman] Make initialization check an assertion 9cfc301 [freeman] Make random seed an argument 44050a9 [freeman] Simpler constructor c7050d5 [freeman] Fix spacing 2899623 [freeman] Use pattern matching for clarity a4a316b [freeman] Use collect 1472ec5 [freeman] Doc formatting ea22ec8 [freeman] Fix imports 2086bdc [freeman] Log cluster center updates ea9877c [freeman] More documentation 9facbe3 [freeman] Bug fix 5db7074 [freeman] Example usage for StreamingKMeans f33684b [freeman] Add explanation and example to docs b5b5f8d [freeman] Add better documentation a0fd790 [freeman] Merge remote-tracking branch 'upstream/master' into streaming-kmeans 9fd9c15 [freeman] Merge remote-tracking branch 'upstream/master' into streaming-kmeans b93350f [freeman] Streaming KMeans with decay

@mateiz

The additions add the abstract BinaryFileInputFormat and BinaryRecordReader classes for reading in data as a byte stream and converting it to another format using the ```def parseByteArray(inArray: Array[Byte]): T``` function. As a trivial example ```ByteInputFormat``` and ```ByteRecordReader``` are included which just return the Array[Byte] from a given file. Finally a RDD for ```BinaryFileInputFormat``` (to allow for easier partitioning changes as was done for WholeFileInput) was added and the appropriate byteFiles to the ```SparkContext``` so the functions can be easily used by others. A common use case might be to read in a folder ``` sc.byteFiles("s3://mydrive/tif/*.tif").map(rawData => ReadTiffFromByteArray(rawData)) ``` Author: Kevin Mader <[email protected]> Author: Kevin Mader <[email protected]> Closes apache#1658 from kmader/master and squashes the following commits: 3c49a30 [Kevin Mader] fixing wholetextfileinput to it has the same setMinPartitions function as in BinaryData files 359a096 [Kevin Mader] making the final corrections suggested by @mateiz and renaming a few functions to make their usage clearer 6379be4 [Kevin Mader] reorganizing code 7b9d181 [Kevin Mader] removing developer API, cleaning up imports 8ac288b [Kevin Mader] fixed a single slightly over 100 character line 92bda0d [Kevin Mader] added new tests, renamed files, fixed several of the javaapi functions, formatted code more nicely a32fef7 [Kevin Mader] removed unneeded classes added DeveloperApi note to portabledatastreams since the implementation might change 49174d9 [Kevin Mader] removed unneeded classes added DeveloperApi note to portabledatastreams since the implementation might change c27a8f1 [Kevin Mader] jenkins crashed before running anything last time, so making minor change b348ce1 [Kevin Mader] fixed order in check (prefix only appears on jenkins not when I run unit tests locally) 0588737 [Kevin Mader] filename check in "binary file input as byte array" test now ignores prefixes and suffixes which might get added by Hadoop 4163e38 [Kevin Mader] fixing line length and output from FSDataInputStream to DataInputStream to minimize sensitivity to Hadoop API changes 19812a8 [Kevin Mader] Fixed the serialization issue with PortableDataStream since neither CombineFileSplit nor TaskAttemptContext implement the Serializable interface, by using ByteArrays for storing both and then recreating the objects from these bytearrays as needed. 238c83c [Kevin Mader] fixed several scala-style issues, changed structure of binaryFiles, removed excessive classes added new tests. The caching tests still have a serialization issue, but that should be easily fixed as well. 932a206 [Kevin Mader] Update RawFileInput.scala a01c9cf [Kevin Mader] Update RawFileInput.scala 441f79a [Kevin Mader] fixed a few small comments and dependency 12e7be1 [Kevin Mader] removing imglib from maven (definitely not ready yet) 5deb79e [Kevin Mader] added new portabledatastream to code so that it can be serialized correctly f032bc0 [Kevin Mader] fixed bug in path name, renamed tests bc5c0b9 [Kevin Mader] made minor stylistic adjustments from mateiz df8e528 [Kevin Mader] fixed line lengths and changed java test 9a313d5 [Kevin Mader] making classes that needn't be public private, adding automatic file closure, adding new tests edf5829 [Kevin Mader] fixing line lengths, adding new lines f4841dc [Kevin Mader] un-optimizing imports, silly intellij eacfaa6 [Kevin Mader] Added FixedLengthBinaryInputFormat and RecordReader from freeman-lab and added them to both the JavaSparkContext and the SparkContext as fixedLengthBinaryFile 1622935 [Kevin Mader] changing the line lengths to make jenkins happy 1cfa38a [Kevin Mader] added apache headers, added datainputstream directly as an output option for more complicated readers (HDF5 perhaps), and renamed several of the functions and files to be more consistent. Also added parallel functions to the java api 84035f1 [Kevin Mader] adding binary and byte file support spark 81c5f12 [Kevin Mader] Merge pull request #1 from apache/master

Add `metadata: Metadata` to `StructField` to store extra information of columns. `Metadata` is a simple wrapper over `Map[String, Any]` with value types restricted to Boolean, Long, Double, String, Metadata, and arrays of those types. SerDe is via JSON. Metadata is preserved through simple operations like `SELECT`. marmbrus liancheng Author: Xiangrui Meng <[email protected]> Author: Michael Armbrust <[email protected]> Closes apache#2701 from mengxr/structfield-metadata and squashes the following commits: dedda56 [Xiangrui Meng] merge remote 5ef930a [Xiangrui Meng] Merge remote-tracking branch 'apache/master' into structfield-metadata c35203f [Xiangrui Meng] Merge pull request #1 from marmbrus/pr/2701 886b85c [Michael Armbrust] Expose Metadata and MetadataBuilder through the public scala and java packages. 589f314 [Xiangrui Meng] Merge remote-tracking branch 'apache/master' into structfield-metadata 1e2abcf [Xiangrui Meng] change default value of metadata to None in python 611d3c2 [Xiangrui Meng] move metadata from Expr to NamedExpr ddfcfad [Xiangrui Meng] Merge remote-tracking branch 'apache/master' into structfield-metadata a438440 [Xiangrui Meng] Merge remote-tracking branch 'apache/master' into structfield-metadata 4266f4d [Xiangrui Meng] add StructField.toString back for backward compatibility 3f49aab [Xiangrui Meng] remove StructField.toString 24a9f80 [Xiangrui Meng] Merge remote-tracking branch 'apache/master' into structfield-metadata 473a7c5 [Xiangrui Meng] merge master c9d7301 [Xiangrui Meng] organize imports 1fcbf13 [Xiangrui Meng] change metadata type in StructField for Scala/Java 60cc131 [Xiangrui Meng] add doc and header 60614c7 [Xiangrui Meng] add metadata e42c452 [Xiangrui Meng] merge master 93518fb [Xiangrui Meng] support metadata in python 905bb89 [Xiangrui Meng] java conversions 618e349 [Xiangrui Meng] make tests work in scala 61b8e0f [Xiangrui Meng] merge master 7e5a322 [Xiangrui Meng] do not output metadata in StructField.toString c41a664 [Xiangrui Meng] merge master d8af0ed [Xiangrui Meng] move tests to SQLQuerySuite 67fdebb [Xiangrui Meng] add test on join d65072e [Xiangrui Meng] remove Map.empty 367d237 [Xiangrui Meng] add test c194d5e [Xiangrui Meng] add metadata field to StructField and Attribute

In RDDSampler, it try use numpy to gain better performance for possion(), but the number of call of random() is only (1+faction) * N in the pure python implementation of possion(), so there is no much performance gain from numpy. numpy is not a dependent of pyspark, so it maybe introduce some problem, such as there is no numpy installed in slaves, but only installed master, as reported in SPARK-927. It also complicate the code a lot, so we may should remove numpy from RDDSampler. I also did some benchmark to verify that: ``` >>> from pyspark.mllib.random import RandomRDDs >>> rdd = RandomRDDs.uniformRDD(sc, 1 << 20, 1).cache() >>> rdd.count() # cache it >>> rdd.sample(True, 0.9).count() # measure this line ``` the results: |withReplacement | random | numpy.random | ------- | ------------ | ------- |True | 1.5 s| 1.4 s| |False| 0.6 s | 0.8 s| closes apache#2313 Note: this patch including some commits that not mirrored to github, it will be OK after it catches up. Author: Davies Liu <[email protected]> Author: Xiangrui Meng <[email protected]> Closes apache#3351 from davies/numpy and squashes the following commits: 5c438d7 [Davies Liu] fix comment c5b9252 [Davies Liu] Merge pull request #1 from mengxr/SPARK-4477 98eb31b [Xiangrui Meng] make poisson sampling slightly faster ee17d78 [Davies Liu] remove = for float 13f7b05 [Davies Liu] Merge branch 'master' of http://git-wip-us.apache.org/repos/asf/spark into numpy f583023 [Davies Liu] fix tests 51649f5 [Davies Liu] remove numpy in RDDSampler 78bf997 [Davies Liu] fix tests, do not use numpy in randomSplit, no performance gain f5fdf63 [Davies Liu] fix bug with int in weights 4dfa2cd [Davies Liu] refactor f866bcf [Davies Liu] remove unneeded change c7a2007 [Davies Liu] switch to python implementation 95a48ac [Davies Liu] Merge branch 'master' of github.com:apache/spark into randomSplit 0d9b256 [Davies Liu] refactor 1715ee3 [Davies Liu] address comments 41fce54 [Davies Liu] randomSplit()

…if sql has null val jsc = new org.apache.spark.api.java.JavaSparkContext(sc) val jhc = new org.apache.spark.sql.hive.api.java.JavaHiveContext(jsc) val nrdd = jhc.hql("select null from spark_test.for_test") println(nrdd.schema) Then the error is thrown as follows: scala.MatchError: NullType (of class org.apache.spark.sql.catalyst.types.NullType$) at org.apache.spark.sql.types.util.DataTypeConversions$.asJavaDataType(DataTypeConversions.scala:43) Author: YanTangZhai <[email protected]> Author: yantangzhai <[email protected]> Author: Michael Armbrust <[email protected]> Closes apache#3538 from YanTangZhai/MatchNullType and squashes the following commits: e052dff [yantangzhai] [SPARK-4676] [SQL] JavaSchemaRDD.schema may throw NullType MatchError if sql has null 4b4bb34 [yantangzhai] [SPARK-4676] [SQL] JavaSchemaRDD.schema may throw NullType MatchError if sql has null 896c7b7 [yantangzhai] fix NullType MatchError in JavaSchemaRDD when sql has null 6e643f8 [YanTangZhai] Merge pull request #11 from apache/master e249846 [YanTangZhai] Merge pull request #10 from apache/master d26d982 [YanTangZhai] Merge pull request #9 from apache/master 76d4027 [YanTangZhai] Merge pull request #8 from apache/master 03b62b0 [YanTangZhai] Merge pull request #7 from apache/master 8a00106 [YanTangZhai] Merge pull request #6 from apache/master cbcba66 [YanTangZhai] Merge pull request #3 from apache/master cdef539 [YanTangZhai] Merge pull request #1 from apache/master

…the lineage The related JIRA is https://issues.apache.org/jira/browse/SPARK-4672 Iterative GraphX applications always have long lineage, while checkpoint() on EdgeRDD and VertexRDD themselves cannot shorten the lineage. In contrast, if we perform checkpoint() on their ParitionsRDD, the long lineage can be cut off. Moreover, the existing operations such as cache() in this code is performed on the PartitionsRDD, so checkpoint() should do the same way. More details and explanation can be found in the JIRA. Author: JerryLead <[email protected]> Author: Lijie Xu <[email protected]> Closes apache#3549 from JerryLead/my_graphX_checkpoint and squashes the following commits: d1aa8d8 [JerryLead] Perform checkpoint() on PartitionsRDD not VertexRDD and EdgeRDD themselves ff08ed4 [JerryLead] Merge branch 'master' of https://github.com/apache/spark c0169da [JerryLead] Merge branch 'master' of https://github.com/apache/spark 52799e3 [Lijie Xu] Merge pull request #1 from apache/master

…erflow error The related JIRA is https://issues.apache.org/jira/browse/SPARK-4672 In a nutshell, if `val partitionsRDD` in EdgeRDDImpl and VertexRDDImpl are non-transient, the serialization chain can become very long in iterative algorithms and finally lead to the StackOverflow error. More details and explanation can be found in the JIRA. Author: JerryLead <[email protected]> Author: Lijie Xu <[email protected]> Closes apache#3544 from JerryLead/my_graphX and squashes the following commits: 628f33c [JerryLead] set PartitionsRDD to be transient in EdgeRDDImpl and VertexRDDImpl c0169da [JerryLead] Merge branch 'master' of https://github.com/apache/spark 52799e3 [Lijie Xu] Merge pull request #1 from apache/master

…ation chain The related JIRA is https://issues.apache.org/jira/browse/SPARK-4672 The f closure of `PartitionsRDD(ZippedPartitionsRDD2)` contains a `$outer` that references EdgeRDD/VertexRDD, which causes task's serialization chain become very long in iterative GraphX applications. As a result, StackOverflow error will occur. If we set "f = null" in `clearDependencies()`, checkpoint() can cut off the long serialization chain. More details and explanation can be found in the JIRA. Author: JerryLead <[email protected]> Author: Lijie Xu <[email protected]> Closes apache#3545 from JerryLead/my_core and squashes the following commits: f7faea5 [JerryLead] checkpoint() should clear the f to avoid StackOverflow error c0169da [JerryLead] Merge branch 'master' of https://github.com/apache/spark 52799e3 [Lijie Xu] Merge pull request #1 from apache/master

…ins an empty AttributeSet() references The sql "select * from spark_test::for_test where abs(20141202) is not null" has predicates=List(IS NOT NULL HiveSimpleUdf#org.apache.hadoop.hive.ql.udf.UDFAbs(20141202)) and partitionKeyIds=AttributeSet(). PruningPredicates is List(IS NOT NULL HiveSimpleUdf#org.apache.hadoop.hive.ql.udf.UDFAbs(20141202)). Then the exception "java.lang.IllegalArgumentException: requirement failed: Partition pruning predicates only supported for partitioned tables." is thrown. The sql "select * from spark_test::for_test_partitioned_table where abs(20141202) is not null and type_id=11 and platform = 3" with partitioned key insert_date has predicates=List(IS NOT NULL HiveSimpleUdf#org.apache.hadoop.hive.ql.udf.UDFAbs(20141202), (type_id#12 = 11), (platform#8 = 3)) and partitionKeyIds=AttributeSet(insert_date#24). PruningPredicates is List(IS NOT NULL HiveSimpleUdf#org.apache.hadoop.hive.ql.udf.UDFAbs(20141202)). Author: YanTangZhai <[email protected]> Author: yantangzhai <[email protected]> Closes apache#3556 from YanTangZhai/SPARK-4693 and squashes the following commits: 620ebe3 [yantangzhai] [SPARK-4693] [SQL] PruningPredicates may be wrong if predicates contains an empty AttributeSet() references 37cfdf5 [yantangzhai] [SPARK-4693] [SQL] PruningPredicates may be wrong if predicates contains an empty AttributeSet() references 70a3544 [yantangzhai] [SPARK-4693] [SQL] PruningPredicates may be wrong if predicates contains an empty AttributeSet() references efa9b03 [YanTangZhai] Update HiveQuerySuite.scala 72accf1 [YanTangZhai] Update HiveQuerySuite.scala e572b9a [YanTangZhai] Update HiveStrategies.scala 6e643f8 [YanTangZhai] Merge pull request #11 from apache/master e249846 [YanTangZhai] Merge pull request #10 from apache/master d26d982 [YanTangZhai] Merge pull request #9 from apache/master 76d4027 [YanTangZhai] Merge pull request #8 from apache/master 03b62b0 [YanTangZhai] Merge pull request #7 from apache/master 8a00106 [YanTangZhai] Merge pull request #6 from apache/master cbcba66 [YanTangZhai] Merge pull request #3 from apache/master cdef539 [YanTangZhai] Merge pull request #1 from apache/master

…askTracker to reduce the chance of the communicating problem Using AkkaUtils.askWithReply in MapOutputTracker.askTracker to reduce the chance of the communicating problem Author: YanTangZhai <[email protected]> Author: yantangzhai <[email protected]> Closes apache#3785 from YanTangZhai/SPARK-4946 and squashes the following commits: 9ca6541 [yantangzhai] [SPARK-4946] [CORE] Using AkkaUtils.askWithReply in MapOutputTracker.askTracker to reduce the chance of the communicating problem e4c2c0a [YanTangZhai] Merge pull request #15 from apache/master 718afeb [YanTangZhai] Merge pull request #12 from apache/master 6e643f8 [YanTangZhai] Merge pull request #11 from apache/master e249846 [YanTangZhai] Merge pull request #10 from apache/master d26d982 [YanTangZhai] Merge pull request #9 from apache/master 76d4027 [YanTangZhai] Merge pull request #8 from apache/master 03b62b0 [YanTangZhai] Merge pull request #7 from apache/master 8a00106 [YanTangZhai] Merge pull request #6 from apache/master cbcba66 [YanTangZhai] Merge pull request #3 from apache/master cdef539 [YanTangZhai] Merge pull request #1 from apache/master

Addition of a very limited number of local matrix manipulation and generation methods that would be helpful in the further development for algorithms on top of BlockMatrix (SPARK-3974), such as Randomized SVD, and Multi Model Training (SPARK-1486). The proposed methods for addition are: For `Matrix` - map: maps the values in the matrix with a given function. Produces a new matrix. - update: the values in the matrix are updated with a given function. Occurs in place. Factory methods for `DenseMatrix`: - *zeros: Generate a matrix consisting of zeros - *ones: Generate a matrix consisting of ones - *eye: Generate an identity matrix - *rand: Generate a matrix consisting of i.i.d. uniform random numbers - *randn: Generate a matrix consisting of i.i.d. gaussian random numbers - *diag: Generate a diagonal matrix from a supplied vector *These methods already exist in the factory methods for `Matrices`, however for cases where we require a `DenseMatrix`, you constantly have to add `.asInstanceOf[DenseMatrix]` everywhere, which makes the code "dirtier". I propose moving these functions to factory methods for `DenseMatrix` where the putput will be a `DenseMatrix` and the factory methods for `Matrices` will call these functions directly and output a generic `Matrix`. Factory methods for `SparseMatrix`: - speye: Identity matrix in sparse format. Saves a ton of memory when dimensions are large, especially in Multi Model Training, where each row requires being multiplied by a scalar. - sprand: Generate a sparse matrix with a given density consisting of i.i.d. uniform random numbers. - sprandn: Generate a sparse matrix with a given density consisting of i.i.d. gaussian random numbers. - diag: Generate a diagonal matrix from a supplied vector, but is memory efficient, because it just stores the diagonal. Again, very helpful in Multi Model Training. Factory methods for `Matrices`: - Include all the factory methods given above, but return a generic `Matrix` rather than `SparseMatrix` or `DenseMatrix`. - horzCat: Horizontally concatenate matrices to form one larger matrix. Very useful in both Multi Model Training, and for the repartitioning of BlockMatrix. - vertCat: Vertically concatenate matrices to form one larger matrix. Very useful for the repartitioning of BlockMatrix. The names for these methods were selected from MATLAB Author: Burak Yavuz <[email protected]> Author: Xiangrui Meng <[email protected]> Closes apache#3319 from brkyvz/SPARK-4409 and squashes the following commits: b0354f6 [Burak Yavuz] [SPARK-4409] Incorporated mengxr's code 04c4829 [Burak Yavuz] Merge pull request #1 from mengxr/SPARK-4409 80cfa29 [Xiangrui Meng] minor changes ecc937a [Xiangrui Meng] update sprand 4e95e24 [Xiangrui Meng] simplify fromCOO implementation 10a63a6 [Burak Yavuz] [SPARK-4409] Fourth pass of code review f62d6c7 [Burak Yavuz] [SPARK-4409] Modified genRandMatrix 3971c93 [Burak Yavuz] [SPARK-4409] Third pass of code review 75239f8 [Burak Yavuz] [SPARK-4409] Second pass of code review e4bd0c0 [Burak Yavuz] [SPARK-4409] Modified horzcat and vertcat 65c562e [Burak Yavuz] [SPARK-4409] Hopefully fixed Java Test d8be7bc [Burak Yavuz] [SPARK-4409] Organized imports 065b531 [Burak Yavuz] [SPARK-4409] First pass after code review a8120d2 [Burak Yavuz] [SPARK-4409] Finished updates to API according to SPARK-4614 f798c82 [Burak Yavuz] [SPARK-4409] Updated API according to SPARK-4614 c75f3cd [Burak Yavuz] [SPARK-4409] Added JavaAPI Tests, and fixed a couple of bugs d662f9d [Burak Yavuz] [SPARK-4409] Modified according to remote repo 83dfe37 [Burak Yavuz] [SPARK-4409] Scalastyle error fixed a14c0da [Burak Yavuz] [SPARK-4409] Initial commit to add methods

Implementation of Expectation-Maximization for Gaussian Mixture Models. This is my maiden contribution to Apache Spark, so I apologize now if I have done anything incorrectly; having said that, this work is my own, and I offer it to the project under the project's open source license. Author: Travis Galoppo <[email protected]> Author: Travis Galoppo <[email protected]> Author: tgaloppo <[email protected]> Author: FlytxtRnD <[email protected]> Closes apache#3022 from tgaloppo/master and squashes the following commits: aaa8f25 [Travis Galoppo] MLUtils: changed privacy of EPSILON from [util] to [mllib] 709e4bf [Travis Galoppo] fixed usage line to include optional maxIterations parameter acf1fba [Travis Galoppo] Fixed parameter comment in GaussianMixtureModel Made maximum iterations an optional parameter to DenseGmmEM 9b2fc2a [Travis Galoppo] Style improvements Changed ExpectationSum to a private class b97fe00 [Travis Galoppo] Minor fixes and tweaks. 1de73f3 [Travis Galoppo] Removed redundant array from array creation 578c2d1 [Travis Galoppo] Removed unused import 227ad66 [Travis Galoppo] Moved prediction methods into model class. 308c8ad [Travis Galoppo] Numerous changes to improve code cff73e0 [Travis Galoppo] Replaced accumulators with RDD.aggregate 20ebca1 [Travis Galoppo] Removed unusued code 42b2142 [Travis Galoppo] Added functionality to allow setting of GMM starting point. Added two cluster test to testing suite. 8b633f3 [Travis Galoppo] Style issue 9be2534 [Travis Galoppo] Style issue d695034 [Travis Galoppo] Fixed style issues c3b8ce0 [Travis Galoppo] Merge branch 'master' of https://github.com/tgaloppo/spark Adds predict() method 2df336b [Travis Galoppo] Fixed style issue b99ecc4 [tgaloppo] Merge pull request #1 from FlytxtRnD/predictBranch f407b4c [FlytxtRnD] Added predict() to return the cluster labels and membership values 97044cf [Travis Galoppo] Fixed style issues dc9c742 [Travis Galoppo] Moved MultivariateGaussian utility class e7d413b [Travis Galoppo] Moved multivariate Gaussian utility class to mllib/stat/impl Improved comments 9770261 [Travis Galoppo] Corrected a variety of style and naming issues. 8aaa17d [Travis Galoppo] Added additional train() method to companion object for cluster count and tolerance parameters. 676e523 [Travis Galoppo] Fixed to no longer ignore delta value provided on command line e6ea805 [Travis Galoppo] Merged with master branch; update test suite with latest context changes. Improved cluster initialization strategy. 86fb382 [Travis Galoppo] Merge remote-tracking branch 'upstream/master' 719d8cc [Travis Galoppo] Added scala test suite with basic test c1a8e16 [Travis Galoppo] Made GaussianMixtureModel class serializable Modified sum function for better performance 5c96c57 [Travis Galoppo] Merge remote-tracking branch 'upstream/master' c15405c [Travis Galoppo] SPARK-4156

Support ! boolean logic operator like NOT in sql as follows select * from for_test where !(col1 > col2) Author: YanTangZhai <[email protected]> Author: Michael Armbrust <[email protected]> Closes apache#3555 from YanTangZhai/SPARK-4692 and squashes the following commits: 1a9f605 [YanTangZhai] Update HiveQuerySuite.scala 7c03c68 [YanTangZhai] Merge pull request apache#23 from apache/master 992046e [YanTangZhai] Update HiveQuerySuite.scala ea618f4 [YanTangZhai] Update HiveQuerySuite.scala 192411d [YanTangZhai] Merge pull request #17 from YanTangZhai/master e4c2c0a [YanTangZhai] Merge pull request #15 from apache/master 1e1ebb4 [YanTangZhai] Update HiveQuerySuite.scala efc4210 [YanTangZhai] Update HiveQuerySuite.scala bd2c444 [YanTangZhai] Update HiveQuerySuite.scala 1893956 [YanTangZhai] Merge pull request #14 from marmbrus/pr/3555 59e4de9 [Michael Armbrust] make hive test 718afeb [YanTangZhai] Merge pull request #12 from apache/master 950b21e [YanTangZhai] Update HiveQuerySuite.scala 74175b4 [YanTangZhai] Update HiveQuerySuite.scala 92242c7 [YanTangZhai] Update HiveQl.scala 6e643f8 [YanTangZhai] Merge pull request #11 from apache/master e249846 [YanTangZhai] Merge pull request #10 from apache/master d26d982 [YanTangZhai] Merge pull request #9 from apache/master 76d4027 [YanTangZhai] Merge pull request #8 from apache/master 03b62b0 [YanTangZhai] Merge pull request #7 from apache/master 8a00106 [YanTangZhai] Merge pull request #6 from apache/master cbcba66 [YanTangZhai] Merge pull request #3 from apache/master cdef539 [YanTangZhai] Merge pull request #1 from apache/master

This implements the functionality for SPARK-4749 and provides units tests in Scala and PySpark Author: nate.crosswhite <[email protected]> Author: nxwhite-str <[email protected]> Author: Xiangrui Meng <[email protected]> Closes apache#3610 from nxwhite-str/master and squashes the following commits: a2ebbd3 [nxwhite-str] Merge pull request #1 from mengxr/SPARK-4749-kmeans-seed 7668124 [Xiangrui Meng] minor updates f8d5928 [nate.crosswhite] Addressing PR issues 277d367 [nate.crosswhite] Merge remote-tracking branch 'upstream/master' 9156a57 [nate.crosswhite] Merge remote-tracking branch 'upstream/master' 5d087b4 [nate.crosswhite] Adding KMeans train with seed and Scala unit test 616d111 [nate.crosswhite] Merge remote-tracking branch 'upstream/master' 35c1884 [nate.crosswhite] Add kmeans initial seed to pyspark API

…l adjacent violators algorithm This PR introduces an API for Isotonic regression and one algorithm implementing it, Pool adjacent violators. The Isotonic regression problem is sufficiently described in [Floudas, Pardalos, Encyclopedia of Optimization](http://books.google.co.uk/books?id=gtoTkL7heS0C&pg=RA2-PA87&lpg=RA2-PA87&dq=pooled+adjacent+violators+code&source=bl&ots=ZzQbZXVJnn&sig=reH_hBV6yIb9BeZNTF9092vD8PY&hl=en&sa=X&ei=WmF2VLiOIZLO7Qa-t4Bo&ved=0CD8Q6AEwBA#v=onepage&q&f=false), [Wikipedia](http://en.wikipedia.org/wiki/Isotonic_regression) or [Stat Wiki](http://stat.wikia.com/wiki/Isotonic_regression). Pool adjacent violators was introduced by M. Ayer et al. in 1955. A history and development of isotonic regression algorithms is in [Leeuw, Hornik, Mair, Isotone Optimization in R: Pool-Adjacent-Violators Algorithm (PAVA) and Active Set Methods](http://www.jstatsoft.org/v32/i05/paper) and list of available algorithms including their complexity is listed in [Stout, Fastest Isotonic Regression Algorithms](http://web.eecs.umich.edu/~qstout/IsoRegAlg_140812.pdf). An approach to parallelize the computation of PAV was presented in [Kearsley, Tapia, Trosset, An Approach to Parallelizing Isotonic Regression](http://softlib.rice.edu/pub/CRPC-TRs/reports/CRPC-TR96640.pdf). The implemented Pool adjacent violators algorithm is based on [Floudas, Pardalos, Encyclopedia of Optimization](http://books.google.co.uk/books?id=gtoTkL7heS0C&pg=RA2-PA87&lpg=RA2-PA87&dq=pooled+adjacent+violators+code&source=bl&ots=ZzQbZXVJnn&sig=reH_hBV6yIb9BeZNTF9092vD8PY&hl=en&sa=X&ei=WmF2VLiOIZLO7Qa-t4Bo&ved=0CD8Q6AEwBA#v=onepage&q&f=false) (Chapter Isotonic regression problems, p. 86) and [Leeuw, Hornik, Mair, Isotone Optimization in R: Pool-Adjacent-Violators Algorithm (PAVA) and Active Set Methods](http://www.jstatsoft.org/v32/i05/paper), also nicely formulated in [Tibshirani, Hoefling, Tibshirani, Nearly-Isotonic Regression](http://www.stat.cmu.edu/~ryantibs/papers/neariso.pdf). Implementation itself inspired by R implementations [Klaus, Strimmer, 2008, fdrtool: Estimation of (Local) False Discovery Rates and Higher Criticism](http://cran.r-project.org/web/packages/fdrtool/index.html) and [R Development Core Team, stats, 2009](https://github.com/lgautier/R-3-0-branch-alt/blob/master/src/library/stats/R/isoreg.R). I ran tests with both these libraries and confirmed they yield the same results. More R implementations referenced in aforementioned [Leeuw, Hornik, Mair, Isotone Optimization in R: Pool-Adjacent-Violators Algorithm (PAVA) and Active Set Methods](http://www.jstatsoft.org/v32/i05/paper). The implementation is also inspired and cross checked with other implementations: [Ted Harding, 2007](https://stat.ethz.ch/pipermail/r-help/2007-March/127981.html), [scikit-learn](https://github.com/scikit-learn/scikit-learn/blob/master/sklearn/_isotonic.pyx), [Andrew Tulloch, 2014, Julia](https://github.com/ajtulloch/Isotonic.jl/blob/master/src/pooled_pava.jl), [Andrew Tulloch, 2014, c++](https://gist.github.com/ajtulloch/9499872), described in [Andrew Tulloch, Speeding up isotonic regression in scikit-learn by 5,000x](http://tullo.ch/articles/speeding-up-isotonic-regression/), [Fabian Pedregosa, 2012](https://gist.github.com/fabianp/3081831), [Sreangsu Acharyya. libpav](https://bitbucket.org/sreangsu/libpav/src/f744bc1b0fea257f0cacaead1c922eab201ba91b/src/pav.h?at=default) and [Gustav Larsson](https://gist.github.com/gustavla/9499068). Author: martinzapletal <[email protected]> Author: Xiangrui Meng <[email protected]> Author: Martin Zapletal <[email protected]> Closes apache#3519 from zapletal-martin/SPARK-3278 and squashes the following commits: 5a54ea4 [Martin Zapletal] Merge pull request #2 from mengxr/isotonic-fix-java 37ba24e [Xiangrui Meng] fix java tests e3c0e44 [martinzapletal] Merge remote-tracking branch 'origin/SPARK-3278' into SPARK-3278 d8feb82 [martinzapletal] Merge remote-tracking branch 'upstream/master' into SPARK-3278 ded071c [Martin Zapletal] Merge pull request #1 from mengxr/SPARK-3278 4dfe136 [Xiangrui Meng] add cache back 0b35c15 [Xiangrui Meng] compress pools and update tests 35d044e [Xiangrui Meng] update paraPAVA 077606b [Xiangrui Meng] minor 05422a8 [Xiangrui Meng] add unit test for model construction 5925113 [Xiangrui Meng] Merge remote-tracking branch 'zapletal-martin/SPARK-3278' into SPARK-3278 80c6681 [Xiangrui Meng] update IRModel 3da56e5 [martinzapletal] SPARK-3278 fixed indentation error 75eac55 [martinzapletal] Merge remote-tracking branch 'upstream/master' into SPARK-3278 88eb4e2 [martinzapletal] SPARK-3278 changes after PR comments apache#3519. Isotonic parameter removed from algorithm, defined behaviour for multiple data points with the same feature value, added tests to verify it e60a34f [martinzapletal] SPARK-3278 changes after PR comments apache#3519. Styling and comment fixes. d93c8f9 [martinzapletal] SPARK-3278 changes after PR comments apache#3519. Change to IsotonicRegression api. Isotonic parameter now follows api of other mllib algorithms 1fff77d [martinzapletal] SPARK-3278 changes after PR comments apache#3519. Java api changes, test refactoring, comments and citations, isotonic regression model validations, linear interpolation for predictions 12151e6 [martinzapletal] Merge remote-tracking branch 'upstream/master' into SPARK-3278 7aca4cc [martinzapletal] SPARK-3278 comment spelling 9ae9d53 [martinzapletal] SPARK-3278 changes after PR feedback apache#3519. Binary search used for isotonic regression model predictions fad4bf9 [martinzapletal] SPARK-3278 changes after PR comments apache#3519 ce0e30c [martinzapletal] SPARK-3278 readability refactoring f90c8c7 [martinzapletal] Merge remote-tracking branch 'upstream/master' into SPARK-3278 0d14bd3 [martinzapletal] SPARK-3278 changed Java api to match Scala api's (Double, Double, Double) 3c2954b [martinzapletal] SPARK-3278 Isotonic regression java api 45aa7e8 [martinzapletal] SPARK-3278 Isotonic regression java api e9b3323 [martinzapletal] Merge branch 'SPARK-3278-weightedLabeledPoint' into SPARK-3278 823d803 [martinzapletal] Merge remote-tracking branch 'upstream/master' into SPARK-3278 941fd1f [martinzapletal] SPARK-3278 Isotonic regression java api a24e29f [martinzapletal] SPARK-3278 refactored weightedlabeledpoint to (double, double, double) and updated api deb0f17 [martinzapletal] SPARK-3278 refactored weightedlabeledpoint to (double, double, double) and updated api 8cefd18 [martinzapletal] Merge remote-tracking branch 'upstream/master' into SPARK-3278-weightedLabeledPoint cab5a46 [martinzapletal] SPARK-3278 PR 3519 refactoring WeightedLabeledPoint to tuple as per comments b8b1620 [martinzapletal] Removed WeightedLabeledPoint. Replaced by tuple of doubles 34760d5 [martinzapletal] Removed WeightedLabeledPoint. Replaced by tuple of doubles 089bf86 [martinzapletal] Removed MonotonicityConstraint, Isotonic and Antitonic constraints. Replced by simple boolean c06f88c [martinzapletal] Merge remote-tracking branch 'upstream/master' into SPARK-3278 6046550 [martinzapletal] SPARK-3278 scalastyle errors resolved 8f5daf9 [martinzapletal] SPARK-3278 added comments and cleaned up api to consistently handle weights 629a1ce [martinzapletal] SPARK-3278 added isotonic regression for weighted data. Added tests for Java api 05d9048 [martinzapletal] SPARK-3278 isotonic regression refactoring and api changes 961aa05 [martinzapletal] Merge remote-tracking branch 'upstream/master' into SPARK-3278 3de71d0 [martinzapletal] SPARK-3278 added initial version of Isotonic regression algorithm including proposed API

…pattern mining in MLlib Apriori is the classic algorithm for frequent item set mining in a transactional data set. It will be useful if Apriori algorithm is added to MLLib in Spark. This PR add an implementation for it. There is a point I am not sure wether it is most efficient. In order to filter out the eligible frequent item set, currently I am using a cartesian operation on two RDDs to calculate the degree of support of each item set, not sure wether it is better to use broadcast variable to achieve the same. I will add an example to use this algorithm if requires Author: Jacky Li <[email protected]> Author: Jacky Li <[email protected]> Author: Xiangrui Meng <[email protected]> Closes apache#2847 from jackylk/apriori and squashes the following commits: bee3093 [Jacky Li] Merge pull request #1 from mengxr/SPARK-4001 7e69725 [Xiangrui Meng] simplify FPTree and update FPGrowth ec21f7d [Jacky Li] fix scalastyle 93f3280 [Jacky Li] create FPTree class d110ab2 [Jacky Li] change test case to use MLlibTestSparkContext a6c5081 [Jacky Li] Add Parallel FPGrowth algorithm eb3e4ca [Jacky Li] add FPGrowth 03df2b6 [Jacky Li] refactory according to comments 7b77ad7 [Jacky Li] fix scalastyle check f68a0bd [Jacky Li] add 2 apriori implemenation and fp-growth implementation 889b33f [Jacky Li] modify per scalastyle check da2cba7 [Jacky Li] adding apriori algorithm for frequent item set mining in Spark

Modifying Vector, DenseVector, and SparseVector to implement argmax functionality. This work is to set the stage for changes to be done in Spark-7423. Author: George Dittmar <[email protected]> Author: George <[email protected]> Author: dittmarg <[email protected]> Author: Xiangrui Meng <[email protected]> Closes apache#6112 from GeorgeDittmar/SPARK-7422 and squashes the following commits: 3e0a939 [George Dittmar] Merge pull request #1 from mengxr/SPARK-7422 127dec5 [Xiangrui Meng] update argmax impl 2ea6a55 [George Dittmar] Added MimaExcludes for Vectors.argmax 98058f4 [George Dittmar] Merge branch 'master' of github.com:apache/spark into SPARK-7422 5fd9380 [George Dittmar] fixing style check error 42341fb [George Dittmar] refactoring arg max check to better handle zero values b22af46 [George Dittmar] Fixing spaces between commas in unit test f2eba2f [George Dittmar] Cleaning up unit tests to be fewer lines aa330e3 [George Dittmar] Fixing some last if else spacing issues ac53c55 [George Dittmar] changing dense vector argmax unit test to be one line call vs 2 d5b5423 [George Dittmar] Fixing code style and updating if logic on when to check for zero values ee1a85a [George Dittmar] Cleaning up unit tests a bit and modifying a few cases 3ee8711 [George Dittmar] Fixing corner case issue with zeros in the active values of the sparse vector. Updated unit tests b1f059f [George Dittmar] Added comment before we start arg max calculation. Updated unit tests to cover corner cases f21dcce [George Dittmar] commit af17981 [dittmarg] Initial work fixing bug that was made clear in pr eeda560 [George] Fixing SparseVector argmax function to ignore zero values while doing the calculation. 4526acc [George] Merge branch 'master' of github.com:apache/spark into SPARK-7422 df9538a [George] Added argmax to sparse vector and added unit test 3cffed4 [George] Adding unit tests for argmax functions for Dense and Sparse vectors 04677af [George] initial work on adding argmax to Vector and SparseVector

…" into true or false directly SQL ``` select key from src where 3 in (4, 5); ``` Before ``` == Optimized Logical Plan == Project [key#12] Filter 3 INSET (5,4) MetastoreRelation default, src, None ``` After ``` == Optimized Logical Plan == LocalRelation [key#228], [] ``` Author: Zhongshuai Pei <[email protected]> Author: DoingDone9 <[email protected]> Closes apache#5972 from DoingDone9/InToFalse and squashes the following commits: 4c722a2 [Zhongshuai Pei] Update predicates.scala abe2bbb [Zhongshuai Pei] Update Optimizer.scala fa461a5 [Zhongshuai Pei] Update Optimizer.scala e34c28a [Zhongshuai Pei] Update predicates.scala 24739bd [Zhongshuai Pei] Update ConstantFoldingSuite.scala f4dbf50 [Zhongshuai Pei] Update ConstantFoldingSuite.scala 35ceb7a [Zhongshuai Pei] Update Optimizer.scala 36c194e [Zhongshuai Pei] Update Optimizer.scala 2e8f6ca [Zhongshuai Pei] Update Optimizer.scala 14952e2 [Zhongshuai Pei] Merge pull request #13 from apache/master f03fe7f [Zhongshuai Pei] Merge pull request #12 from apache/master f12fa50 [Zhongshuai Pei] Merge pull request #10 from apache/master f61210c [Zhongshuai Pei] Merge pull request #9 from apache/master 34b1a9a [Zhongshuai Pei] Merge pull request #8 from apache/master 802261c [DoingDone9] Merge pull request #7 from apache/master d00303b [DoingDone9] Merge pull request #6 from apache/master 98b134f [DoingDone9] Merge pull request #5 from apache/master 161cae3 [DoingDone9] Merge pull request #4 from apache/master c87e8b6 [DoingDone9] Merge pull request #3 from apache/master cb1852d [DoingDone9] Merge pull request #2 from apache/master c3f046f [DoingDone9] Merge pull request #1 from apache/master (cherry picked from commit 4b5e1fe) Signed-off-by: Michael Armbrust <[email protected]>

…cala and pySpark Author: Joshi <[email protected]> Author: Rekha Joshi <[email protected]> Closes apache#5989 from rekhajoshm/fix/SPARK-7435 and squashes the following commits: cfc9e02 [Joshi] Spark-7435[R]: updated patch for review comments 62becc1 [Joshi] SPARK-7435: Update to DataFrame e3677c9 [Rekha Joshi] Merge pull request #1 from apache/master (cherry picked from commit b94a933) Signed-off-by: Shivaram Venkataraman <[email protected]>

…at has space in its path escape spaces in the arguments. Author: Masayoshi TSUZUKI <[email protected]> Author: Kousuke Saruta <[email protected]> Closes apache#5447 from tsudukim/feature/SPARK-6568-2 and squashes the following commits: 3f9a188 [Masayoshi TSUZUKI] modified some errors. ed46047 [Masayoshi TSUZUKI] avoid scalastyle errors. 1784239 [Masayoshi TSUZUKI] removed Utils.formatPath. e03f289 [Masayoshi TSUZUKI] removed testWindows from Utils.resolveURI and Utils.resolveURIs. replaced SystemUtils.IS_OS_WINDOWS to Utils.isWindows. removed Utils.formatPath from PythonRunner.scala. 84c33d0 [Masayoshi TSUZUKI] - use resolveURI in nonLocalPaths - run tests for Windows path only on Windows 016128d [Masayoshi TSUZUKI] fixed to use File.toURI() 2c62e3b [Masayoshi TSUZUKI] Merge pull request #1 from sarutak/SPARK-6568-2 7019a8a [Masayoshi TSUZUKI] Merge branch 'master' of https://github.com/apache/spark into feature/SPARK-6568-2 45946ee [Kousuke Saruta] Merge branch 'master' of git://git.apache.org/spark into SPARK-6568-2 10f1c73 [Kousuke Saruta] Added a comment 93c3c40 [Kousuke Saruta] Merge branch 'classpath-handling-fix' of github.com:sarutak/spark into SPARK-6568-2 649da82 [Kousuke Saruta] Fix classpath handling c7ba6a7 [Masayoshi TSUZUKI] [SPARK-6568] spark-shell.cmd --jars option does not accept the jar that has space in its path (cherry picked from commit 50c7270) Signed-off-by: Sean Owen <[email protected]>

Fix for incorrect memory in Spark UI as per SPARK-5768 Author: Joshi <[email protected]> Author: Rekha Joshi <[email protected]> Closes apache#6972 from rekhajoshm/SPARK-5768 and squashes the following commits: b678a91 [Joshi] Fix for incorrect memory in Spark UI 2fe53d9 [Joshi] Fix for incorrect memory in Spark UI eb823b8 [Joshi] SPARK-5768: Fix for incorrect memory in Spark UI 0be142d [Rekha Joshi] Merge pull request #3 from apache/master 106fd8e [Rekha Joshi] Merge pull request #2 from apache/master e3677c9 [Rekha Joshi] Merge pull request #1 from apache/master (cherry picked from commit 085a721) Signed-off-by: Kousuke Saruta <[email protected]>

This makes sure attempts are listed in the order they were executed, and that the app's state matches the state of the most current attempt. Author: Joshi <[email protected]> Author: Rekha Joshi <[email protected]> Closes apache#7253 from rekhajoshm/SPARK-8593 and squashes the following commits: 874dd80 [Joshi] History Server: updated order for multiple attempts(logcleaner) 716e0b1 [Joshi] History Server: updated order for multiple attempts(descending start time works everytime) 548c753 [Joshi] History Server: updated order for multiple attempts(descending start time works everytime) 83306a8 [Joshi] History Server: updated order for multiple attempts(descending start time) b0fc922 [Joshi] History Server: updated order for multiple attempts(updated comment) cc0fda7 [Joshi] History Server: updated order for multiple attempts(updated test) 304cb0b [Joshi] History Server: updated order for multiple attempts(reverted HistoryPage) 85024e8 [Joshi] History Server: updated order for multiple attempts a41ac4b [Joshi] History Server: updated order for multiple attempts ab65fa1 [Joshi] History Server: some attempt completed to work with showIncomplete 0be142d [Rekha Joshi] Merge pull request #3 from apache/master 106fd8e [Rekha Joshi] Merge pull request #2 from apache/master e3677c9 [Rekha Joshi] Merge pull request #1 from apache/master (cherry picked from commit 42d8a01) Signed-off-by: Sean Owen <[email protected]>

…ected databases Continuation of work by zhangjiajin Closes apache#7412 Author: zhangjiajin <[email protected]> Author: Feynman Liang <[email protected]> Author: zhang jiajin <[email protected]> Closes apache#7783 from feynmanliang/SPARK-8998-improve-distributed and squashes the following commits: a61943d [Feynman Liang] Collect small patterns to local 4ddf479 [Feynman Liang] Parallelize freqItemCounts ad23aa9 [zhang jiajin] Merge pull request #1 from feynmanliang/SPARK-8998-collectBeforeLocal 87fa021 [Feynman Liang] Improve extend prefix readability c2caa5c [Feynman Liang] Readability improvements and comments 1235cfc [Feynman Liang] Use Iterable[Array[_]] over Array[Array[_]] for database da0091b [Feynman Liang] Use lists for prefixes to reuse data cb2a4fc [Feynman Liang] Inline code for readability 01c9ae9 [Feynman Liang] Add getters 6e149fa [Feynman Liang] Fix splitPrefixSuffixPairs 64271b3 [zhangjiajin] Modified codes according to comments. d2250b7 [zhangjiajin] remove minPatternsBeforeLocalProcessing, add maxSuffixesBeforeLocalProcessing. b07e20c [zhangjiajin] Merge branch 'master' of https://github.com/apache/spark into CollectEnoughPrefixes 095aa3a [zhangjiajin] Modified the code according to the review comments. baa2885 [zhangjiajin] Modified the code according to the review comments. 6560c69 [zhangjiajin] Add feature: Collect enough frequent prefixes before projection in PrefixeSpan a8fde87 [zhangjiajin] Merge branch 'master' of https://github.com/apache/spark 4dd1c8a [zhangjiajin] initialize file before rebase. 078d410 [zhangjiajin] fix a scala style error. 22b0ef4 [zhangjiajin] Add feature: Collect enough frequent prefixes before projection in PrefixSpan. ca9c4c8 [zhangjiajin] Modified the code according to the review comments. 574e56c [zhangjiajin] Add new object LocalPrefixSpan, and do some optimization. ba5df34 [zhangjiajin] Fix a Scala style error. 4c60fb3 [zhangjiajin] Fix some Scala style errors. 1dd33ad [zhangjiajin] Modified the code according to the review comments. 89bc368 [zhangjiajin] Fixed a Scala style error. a2eb14c [zhang jiajin] Delete PrefixspanSuite.scala 951fd42 [zhang jiajin] Delete Prefixspan.scala 575995f [zhangjiajin] Modified the code according to the review comments. 91fd7e6 [zhangjiajin] Add new algorithm PrefixSpan and test file.

This PR is based on apache#4229, thanks prabeesh. Closes apache#4229 Author: Prabeesh K <[email protected]> Author: zsxwing <[email protected]> Author: prabs <[email protected]> Author: Prabeesh K <[email protected]> Closes apache#7833 from zsxwing/pr4229 and squashes the following commits: 9570bec [zsxwing] Fix the variable name and check null in finally 4a9c79e [zsxwing] Fix pom.xml indentation abf5f18 [zsxwing] Merge branch 'master' into pr4229 935615c [zsxwing] Fix the flaky MQTT tests 47278c5 [zsxwing] Include the project class files 478f844 [zsxwing] Add unpack 5f8a1d4 [zsxwing] Make the maven build generate the test jar for Python MQTT tests 734db99 [zsxwing] Merge branch 'master' into pr4229 126608a [Prabeesh K] address the comments b90b709 [Prabeesh K] Merge pull request #1 from zsxwing/pr4229 d07f454 [zsxwing] Register StreamingListerner before starting StreamingContext; Revert unncessary changes; fix the python unit test a6747cb [Prabeesh K] wait for starting the receiver before publishing data 87fc677 [Prabeesh K] address the comments: 97244ec [zsxwing] Make sbt build the assembly test jar for streaming mqtt 80474d1 [Prabeesh K] fix 1f0cfe9 [Prabeesh K] python style fix e1ee016 [Prabeesh K] scala style fix a5a8f9f [Prabeesh K] added Python test 9767d82 [Prabeesh K] implemented Python-friendly class a11968b [Prabeesh K] fixed python style 795ec27 [Prabeesh K] address comments ee387ae [Prabeesh K] Fix assembly jar location of mqtt-assembly 3f4df12 [Prabeesh K] updated version b34c3c1 [prabs] adress comments 3aa7fff [prabs] Added Python streaming mqtt word count example b7d42ff [prabs] Mqtt streaming support in Python

This PR is based on apache#4229, thanks prabeesh. Closes apache#4229 Author: Prabeesh K <[email protected]> Author: zsxwing <[email protected]> Author: prabs <[email protected]> Author: Prabeesh K <[email protected]> Closes apache#7833 from zsxwing/pr4229 and squashes the following commits: 9570bec [zsxwing] Fix the variable name and check null in finally 4a9c79e [zsxwing] Fix pom.xml indentation abf5f18 [zsxwing] Merge branch 'master' into pr4229 935615c [zsxwing] Fix the flaky MQTT tests 47278c5 [zsxwing] Include the project class files 478f844 [zsxwing] Add unpack 5f8a1d4 [zsxwing] Make the maven build generate the test jar for Python MQTT tests 734db99 [zsxwing] Merge branch 'master' into pr4229 126608a [Prabeesh K] address the comments b90b709 [Prabeesh K] Merge pull request #1 from zsxwing/pr4229 d07f454 [zsxwing] Register StreamingListerner before starting StreamingContext; Revert unncessary changes; fix the python unit test a6747cb [Prabeesh K] wait for starting the receiver before publishing data 87fc677 [Prabeesh K] address the comments: 97244ec [zsxwing] Make sbt build the assembly test jar for streaming mqtt 80474d1 [Prabeesh K] fix 1f0cfe9 [Prabeesh K] python style fix e1ee016 [Prabeesh K] scala style fix a5a8f9f [Prabeesh K] added Python test 9767d82 [Prabeesh K] implemented Python-friendly class a11968b [Prabeesh K] fixed python style 795ec27 [Prabeesh K] address comments ee387ae [Prabeesh K] Fix assembly jar location of mqtt-assembly 3f4df12 [Prabeesh K] updated version b34c3c1 [prabs] adress comments 3aa7fff [prabs] Added Python streaming mqtt word count example b7d42ff [prabs] Mqtt streaming support in Python (cherry picked from commit 853809e) Signed-off-by: Tathagata Das <[email protected]>

## What changes were proposed in this pull request? This patch introduces SQLQueryTestSuite, a basic framework for end-to-end SQL test cases defined in spark/sql/core/src/test/resources/sql-tests. This is a more standard way to test SQL queries end-to-end in different open source database systems, because it is more manageable to work with files. This is inspired by HiveCompatibilitySuite, but simplified for general Spark SQL tests. Once this is merged, I can work towards porting SQLQuerySuite over, and eventually also move the existing HiveCompatibilitySuite to use this framework. Unlike HiveCompatibilitySuite, SQLQueryTestSuite compares both the output schema and the output data (in string form). When there is a mismatch, the error message looks like the following: ``` [info] - blacklist.sql !!! IGNORED !!! [info] - number-format.sql *** FAILED *** (2 seconds, 405 milliseconds) [info] Expected "...147483648 -214748364[8]", but got "...147483648 -214748364[9]" Result should match for query #1 (SQLQueryTestSuite.scala:171) [info] org.scalatest.exceptions.TestFailedException: [info] at org.scalatest.Assertions$class.newAssertionFailedException(Assertions.scala:495) [info] at org.scalatest.FunSuite.newAssertionFailedException(FunSuite.scala:1555) [info] at org.scalatest.Assertions$class.assertResult(Assertions.scala:1171) ``` ## How was this patch tested? This is a test infrastructure change. Author: petermaxlee <[email protected]> Closes apache#14472 from petermaxlee/SPARK-16866.

## What changes were proposed in this pull request? This patch introduces SQLQueryTestSuite, a basic framework for end-to-end SQL test cases defined in spark/sql/core/src/test/resources/sql-tests. This is a more standard way to test SQL queries end-to-end in different open source database systems, because it is more manageable to work with files. This is inspired by HiveCompatibilitySuite, but simplified for general Spark SQL tests. Once this is merged, I can work towards porting SQLQuerySuite over, and eventually also move the existing HiveCompatibilitySuite to use this framework. Unlike HiveCompatibilitySuite, SQLQueryTestSuite compares both the output schema and the output data (in string form). When there is a mismatch, the error message looks like the following: ``` [info] - blacklist.sql !!! IGNORED !!! [info] - number-format.sql *** FAILED *** (2 seconds, 405 milliseconds) [info] Expected "...147483648 -214748364[8]", but got "...147483648 -214748364[9]" Result should match for query #1 (SQLQueryTestSuite.scala:171) [info] org.scalatest.exceptions.TestFailedException: [info] at org.scalatest.Assertions$class.newAssertionFailedException(Assertions.scala:495) [info] at org.scalatest.FunSuite.newAssertionFailedException(FunSuite.scala:1555) [info] at org.scalatest.Assertions$class.assertResult(Assertions.scala:1171) ``` ## How was this patch tested? This is a test infrastructure change. Author: petermaxlee <[email protected]> Closes apache#14472 from petermaxlee/SPARK-16866. (cherry picked from commit b9f8a11) Signed-off-by: Wenchen Fan <[email protected]>

## What changes were proposed in this pull request? There were two related fixes regarding `from_json`, `get_json_object` and `json_tuple` ([Fix #1](apache@c8803c0), [Fix #2](apache@86174ea)), but they weren't comprehensive it seems. I wanted to extend those fixes to all the parsers, and add tests for each case. ## How was this patch tested? Regression tests Author: Burak Yavuz <[email protected]> Closes apache#20302 from brkyvz/json-invfix.

## What changes were proposed in this pull request? Solved two bugs to enable stream-stream self joins. ### Incorrect analysis due to missing MultiInstanceRelation trait Streaming leaf nodes did not extend MultiInstanceRelation, which is necessary for the catalyst analyzer to convert the self-join logical plan DAG into a tree (by creating new instances of the leaf relations). This was causing the error `Failure when resolving conflicting references in Join:` (see JIRA for details). ### Incorrect attribute rewrite when splicing batch plans in MicroBatchExecution When splicing the source's batch plan into the streaming plan (by replacing the StreamingExecutionPlan), we were rewriting the attribute reference in the streaming plan with the new attribute references from the batch plan. This was incorrectly handling the scenario when multiple StreamingExecutionRelation point to the same source, and therefore eventually point to the same batch plan returned by the source. Here is an example query, and its corresponding plan transformations. ``` val df = input.toDF val join = df.select('value % 5 as "key", 'value).join( df.select('value % 5 as "key", 'value), "key") ``` Streaming logical plan before splicing the batch plan ``` Project [key#6, value#1, value#12] +- Join Inner, (key#6 = key#9) :- Project [(value#1 % 5) AS key#6, value#1] : +- StreamingExecutionRelation Memory[#1], value#1 +- Project [(value#12 % 5) AS key#9, value#12] +- StreamingExecutionRelation Memory[#1], value#12 // two different leaves pointing to same source ``` Batch logical plan after splicing the batch plan and before rewriting ``` Project [key#6, value#1, value#12] +- Join Inner, (key#6 = key#9) :- Project [(value#1 % 5) AS key#6, value#1] : +- LocalRelation [value#66] // replaces StreamingExecutionRelation Memory[#1], value#1 +- Project [(value#12 % 5) AS key#9, value#12] +- LocalRelation [value#66] // replaces StreamingExecutionRelation Memory[#1], value#12 ``` Batch logical plan after rewriting the attributes. Specifically, for spliced, the new output attributes (value#66) replace the earlier output attributes (value#12, and value#1, one for each StreamingExecutionRelation). ``` Project [key#6, value#66, value#66] // both value#1 and value#12 replaces by value#66 +- Join Inner, (key#6 = key#9) :- Project [(value#66 % 5) AS key#6, value#66] : +- LocalRelation [value#66] +- Project [(value#66 % 5) AS key#9, value#66] +- LocalRelation [value#66] ``` This causes the optimizer to eliminate value#66 from one side of the join. ``` Project [key#6, value#66, value#66] +- Join Inner, (key#6 = key#9) :- Project [(value#66 % 5) AS key#6, value#66] : +- LocalRelation [value#66] +- Project [(value#66 % 5) AS key#9] // this does not generate value, incorrect join results +- LocalRelation [value#66] ``` **Solution**: Instead of rewriting attributes, use a Project to introduce aliases between the output attribute references and the new reference generated by the spliced plans. The analyzer and optimizer will take care of the rest. ``` Project [key#6, value#1, value#12] +- Join Inner, (key#6 = key#9) :- Project [(value#1 % 5) AS key#6, value#1] : +- Project [value#66 AS value#1] // solution: project with aliases : +- LocalRelation [value#66] +- Project [(value#12 % 5) AS key#9, value#12] +- Project [value#66 AS value#12] // solution: project with aliases +- LocalRelation [value#66] ``` ## How was this patch tested? New unit test Author: Tathagata Das <[email protected]> Closes apache#20598 from tdas/SPARK-23406.

## What changes were proposed in this pull request? There were two related fixes regarding `from_json`, `get_json_object` and `json_tuple` ([Fix #1](apache@c8803c0), [Fix #2](apache@86174ea)), but they weren't comprehensive it seems. I wanted to extend those fixes to all the parsers, and add tests for each case. ## How was this patch tested? Regression tests Author: Burak Yavuz <[email protected]> Closes apache#20302 from brkyvz/json-invfix. (cherry picked from commit e01919e) Signed-off-by: hyukjinkwon <[email protected]>

This is a backport of apache#20598. ## What changes were proposed in this pull request? Solved two bugs to enable stream-stream self joins. ### Incorrect analysis due to missing MultiInstanceRelation trait Streaming leaf nodes did not extend MultiInstanceRelation, which is necessary for the catalyst analyzer to convert the self-join logical plan DAG into a tree (by creating new instances of the leaf relations). This was causing the error `Failure when resolving conflicting references in Join:` (see JIRA for details). ### Incorrect attribute rewrite when splicing batch plans in MicroBatchExecution When splicing the source's batch plan into the streaming plan (by replacing the StreamingExecutionPlan), we were rewriting the attribute reference in the streaming plan with the new attribute references from the batch plan. This was incorrectly handling the scenario when multiple StreamingExecutionRelation point to the same source, and therefore eventually point to the same batch plan returned by the source. Here is an example query, and its corresponding plan transformations. ``` val df = input.toDF val join = df.select('value % 5 as "key", 'value).join( df.select('value % 5 as "key", 'value), "key") ``` Streaming logical plan before splicing the batch plan ``` Project [key#6, value#1, value#12] +- Join Inner, (key#6 = key#9) :- Project [(value#1 % 5) AS key#6, value#1] : +- StreamingExecutionRelation Memory[#1], value#1 +- Project [(value#12 % 5) AS key#9, value#12] +- StreamingExecutionRelation Memory[#1], value#12 // two different leaves pointing to same source ``` Batch logical plan after splicing the batch plan and before rewriting ``` Project [key#6, value#1, value#12] +- Join Inner, (key#6 = key#9) :- Project [(value#1 % 5) AS key#6, value#1] : +- LocalRelation [value#66] // replaces StreamingExecutionRelation Memory[#1], value#1 +- Project [(value#12 % 5) AS key#9, value#12] +- LocalRelation [value#66] // replaces StreamingExecutionRelation Memory[#1], value#12 ``` Batch logical plan after rewriting the attributes. Specifically, for spliced, the new output attributes (value#66) replace the earlier output attributes (value#12, and value#1, one for each StreamingExecutionRelation). ``` Project [key#6, value#66, value#66] // both value#1 and value#12 replaces by value#66 +- Join Inner, (key#6 = key#9) :- Project [(value#66 % 5) AS key#6, value#66] : +- LocalRelation [value#66] +- Project [(value#66 % 5) AS key#9, value#66] +- LocalRelation [value#66] ``` This causes the optimizer to eliminate value#66 from one side of the join. ``` Project [key#6, value#66, value#66] +- Join Inner, (key#6 = key#9) :- Project [(value#66 % 5) AS key#6, value#66] : +- LocalRelation [value#66] +- Project [(value#66 % 5) AS key#9] // this does not generate value, incorrect join results +- LocalRelation [value#66] ``` **Solution**: Instead of rewriting attributes, use a Project to introduce aliases between the output attribute references and the new reference generated by the spliced plans. The analyzer and optimizer will take care of the rest. ``` Project [key#6, value#1, value#12] +- Join Inner, (key#6 = key#9) :- Project [(value#1 % 5) AS key#6, value#1] : +- Project [value#66 AS value#1] // solution: project with aliases : +- LocalRelation [value#66] +- Project [(value#12 % 5) AS key#9, value#12] +- Project [value#66 AS value#12] // solution: project with aliases +- LocalRelation [value#66] ``` ## How was this patch tested? New unit test Author: Tathagata Das <[email protected]> Closes apache#20765 from tdas/SPARK-23406-2.3.

…te temporary path in local staging directory ## What changes were proposed in this pull request? Th environment of my cluster as follows: ``` OS:Linux version 2.6.32-220.7.1.el6.x86_64 (mockbuildc6b18n3.bsys.dev.centos.org) (gcc version 4.4.6 20110731 (Red Hat 4.4.6-3) (GCC) ) #1 SMP Wed Mar 7 00:52:02 GMT 2012 Hadoop: 2.7.2 Spark: 2.3.0 or 3.0.0(master branch) Hive: 1.2.1 ``` My spark run on deploy mode yarn-client. If I execute the SQL `insert overwrite local directory '/home/test/call_center/' select * from call_center`, a HiveException will appear as follows: `Caused by: org.apache.hadoop.hive.ql.metadata.HiveException: java.io.IOException: Mkdirs failed to create file:/home/xitong/hive/stagingdir_hive_2019-02-19_17-31-00_678_1816816774691551856-1/-ext-10000/_temporary/0/_temporary/attempt_20190219173233_0002_m_000000_3 (exists=false, cwd=file:/data10/yarn/nm-local-dir/usercache/xitong/appcache/application_1543893582405_6126857/container_e124_1543893582405_6126857_01_000011) at org.apache.hadoop.hive.ql.io.HiveFileFormatUtils.getHiveRecordWriter(HiveFileFormatUtils.java:249)` Current spark sql generate a local temporary path in local staging directory.The schema of local temporary path start with `file`, so the HiveException appears. This PR change the local temporary path to HDFS temporary path, and use DistributedFileSystem instance copy the data from HDFS temporary path to local directory. If Spark run on local deploy mode, 'insert overwrite local directory' works fine. ## How was this patch tested? UT cannot support yarn-client mode.The test is in my product environment. Closes apache#23841 from beliefer/fix-bug-of-insert-overwrite-local-dir. Authored-by: gengjiaan <[email protected]> Signed-off-by: Sean Owen <[email protected]>

## What changes were proposed in this pull request? This PR supports `OpenJ9` in addition to `IBM JDK` and `OpenJDK` in Spark by handling `System.getProperty("java.vendor") = "Eclipse OpenJ9"`. In `inferDefaultMemory()` and `getKrb5LoginModuleName()`, this PR uses non `IBM` way. ``` $ ~/jdk-11.0.2+9_openj9-0.12.1/bin/jshell | Welcome to JShell -- Version 11.0.2 | For an introduction type: /help intro jshell> System.out.println(System.getProperty("java.vendor")) Eclipse OpenJ9 jshell> System.out.println(System.getProperty("java.vm.info")) JRE 11 Linux amd64-64-Bit Compressed References 20190204_127 (JIT enabled, AOT enabled) OpenJ9 - 90dd8cb40 OMR - d2f4534b JCL - 289c70b6844 based on jdk-11.0.2+9 jshell> System.out.println(Class.forName("com.ibm.lang.management.OperatingSystemMXBean").getDeclaredMethod("getTotalPhysicalMemory")) public abstract long com.ibm.lang.management.OperatingSystemMXBean.getTotalPhysicalMemory() jshell> System.out.println(Class.forName("com.sun.management.OperatingSystemMXBean").getDeclaredMethod("getTotalPhysicalMemorySize")) public abstract long com.sun.management.OperatingSystemMXBean.getTotalPhysicalMemorySize() jshell> System.out.println(Class.forName("com.ibm.security.auth.module.Krb5LoginModule")) | Exception java.lang.ClassNotFoundException: com.ibm.security.auth.module.Krb5LoginModule | at Class.forNameImpl (Native Method) | at Class.forName (Class.java:339) | at (#1:1) jshell> System.out.println(Class.forName("com.sun.security.auth.module.Krb5LoginModule")) class com.sun.security.auth.module.Krb5LoginModule ``` ## How was this patch tested? Existing test suites Manual testing with OpenJ9. Closes apache#24308 from kiszk/SPARK-27397. Authored-by: Kazuaki Ishizaki <[email protected]> Signed-off-by: Sean Owen <[email protected]>

…comparison assertions ## What changes were proposed in this pull request? This PR removes a few hardware-dependent assertions which can cause a failure in `aarch64`. **x86_64** ``` rootdonotdel-openlab-allinone-l00242678:/home/ubuntu# uname -a Linux donotdel-openlab-allinone-l00242678 4.4.0-154-generic apache#181-Ubuntu SMP Tue Jun 25 05:29:03 UTC 2019 x86_64 x86_64 x86_64 GNU/Linux scala> import java.lang.Float.floatToRawIntBits import java.lang.Float.floatToRawIntBits scala> floatToRawIntBits(0.0f/0.0f) res0: Int = -4194304 scala> floatToRawIntBits(Float.NaN) res1: Int = 2143289344 ``` **aarch64** ``` [rootarm-huangtianhua spark]# uname -a Linux arm-huangtianhua 4.14.0-49.el7a.aarch64 #1 SMP Tue Apr 10 17:22:26 UTC 2018 aarch64 aarch64 aarch64 GNU/Linux scala> import java.lang.Float.floatToRawIntBits import java.lang.Float.floatToRawIntBits scala> floatToRawIntBits(0.0f/0.0f) res1: Int = 2143289344 scala> floatToRawIntBits(Float.NaN) res2: Int = 2143289344 ``` ## How was this patch tested? Pass the Jenkins (This removes the test coverage). Closes apache#25186 from huangtianhua/special-test-case-for-aarch64. Authored-by: huangtianhua <[email protected]> Signed-off-by: Dongjoon Hyun <[email protected]>

### What changes were proposed in this pull request? `org.apache.spark.sql.kafka010.KafkaDelegationTokenSuite` failed lately. After had a look at the logs it just shows the following fact without any details: ``` Caused by: sbt.ForkMain$ForkError: sun.security.krb5.KrbException: Server not found in Kerberos database (7) - Server not found in Kerberos database ``` Since the issue is intermittent and not able to reproduce it we should add more debug information and wait for reproduction with the extended logs. ### Why are the changes needed? Failing test doesn't give enough debug information. ### Does this PR introduce any user-facing change? No. ### How was this patch tested? I've started the test manually and checked that such additional debug messages show up: ``` >>> KrbApReq: APOptions are 00000000 00000000 00000000 00000000 >>> EType: sun.security.krb5.internal.crypto.Aes128CtsHmacSha1EType Looking for keys for: kafka/localhostEXAMPLE.COM Added key: 17version: 0 Added key: 23version: 0 Added key: 16version: 0 Found unsupported keytype (3) for kafka/localhostEXAMPLE.COM >>> EType: sun.security.krb5.internal.crypto.Aes128CtsHmacSha1EType Using builtin default etypes for permitted_enctypes default etypes for permitted_enctypes: 17 16 23. >>> EType: sun.security.krb5.internal.crypto.Aes128CtsHmacSha1EType MemoryCache: add 1571936500/174770/16C565221B70AAB2BEFE31A83D13A2F4/client/localhostEXAMPLE.COM to client/localhostEXAMPLE.COM|kafka/localhostEXAMPLE.COM MemoryCache: Existing AuthList: #3: 1571936493/200803/8CD70D280B0862C5DA1FF901ECAD39FE/client/localhostEXAMPLE.COM #2: 1571936499/985009/BAD33290D079DD4E3579A8686EC326B7/client/localhostEXAMPLE.COM #1: 1571936499/995208/B76B9D78A9BE283AC78340157107FD40/client/localhostEXAMPLE.COM ``` Closes apache#26252 from gaborgsomogyi/SPARK-29580. Authored-by: Gabor Somogyi <[email protected]> Signed-off-by: Dongjoon Hyun <[email protected]>

### What changes were proposed in this pull request? Currently the join operators are not well abstracted, since there are lot of common logic. A trait can be created for easier pattern matching and other future handiness. This is a follow-up PR based on comment apache#27509 (comment) . This PR refined from the following aspects: 1. Refined structure of all physical join operators 2. Add missing joinType field for CartesianProductExec operator 3. Refined codes related to Explain Formatted The EXPLAIN FORMATTED changes are 1. Converge all join operator `verboseStringWithOperatorId` implementations to `BaseJoinExec`. Join condition displayed, and join keys displayed if it’s not empty. 2. `#1` will add Join condition to `BroadcastNestedLoopJoinExec`. 3. `#1` will **NOT** affect `CartesianProductExec`,`SortMergeJoin` and `HashJoin`s, since they already got there override implementation before. 4. Converge all join operator `simpleStringWithNodeId` to `BaseJoinExec`, which will enhance the one line description for `CartesianProductExec` with `JoinType` added. 5. Override `simpleStringWithNodeId` in `BroadcastNestedLoopJoinExec` to show `BuildSide`, which was only done for `HashJoin`s before. ### Why are the changes needed? Make the code consistent with other operators and for future handiness of join operators. ### Does this PR introduce any user-facing change? No ### How was this patch tested? Existing tests Closes apache#27595 from Eric5553/RefineJoin. Authored-by: Eric Wu <[email protected]> Signed-off-by: Wenchen Fan <[email protected]>

… correctly ### What changes were proposed in this pull request? This PR proposes: 1. `CREATE OR REPLACE TEMP VIEW USING` should use `TemporaryViewRelation` to store temp views. 2. By doing #1, it fixes the issue where the temp view being replaced is not uncached. ### Why are the changes needed? This is a part of an ongoing work to wrap all the temporary views with `TemporaryViewRelation`: [SPARK-34698](https://issues.apache.org/jira/browse/SPARK-34698). This also fixes a bug where the temp view being replaced is not uncached. ### Does this PR introduce _any_ user-facing change? Yes, the temp view being replaced with `CREATE OR REPLACE TEMP VIEW USING` is correctly uncached if the temp view is cached. ### How was this patch tested? Added new tests. Closes apache#31825 from imback82/create_temp_view_using. Authored-by: Terry Kim <[email protected]> Signed-off-by: Wenchen Fan <[email protected]>

…ly equivalent children in `RewriteDistinctAggregates` ### What changes were proposed in this pull request? In `RewriteDistinctAggregates`, when grouping aggregate expressions by function children, treat children that are semantically equivalent as the same. ### Why are the changes needed? This PR will reduce the number of projections in the Expand operator when there are multiple distinct aggregations with superficially different children. In some cases, it will eliminate the need for an Expand operator. Example: In the following query, the Expand operator creates 3\*n rows (where n is the number of incoming rows) because it has a projection for each of function children `b + 1`, `1 + b` and `c`. ``` create or replace temp view v1 as select * from values (1, 2, 3.0), (1, 3, 4.0), (2, 4, 2.5), (2, 3, 1.0) v1(a, b, c); select a, count(distinct b + 1), avg(distinct 1 + b) filter (where c > 0), sum(c) from v1 group by a; ``` The Expand operator has three projections (each producing a row for each incoming row): ``` [a#87, null, null, 0, null, UnscaledValue(c#89)], <== projection #1 (for regular aggregation) [a#87, (b#88 + 1), null, 1, null, null], <== projection #2 (for distinct aggregation of b + 1) [a#87, null, (1 + b#88), 2, (c#89 > 0.0), null]], <== projection #3 (for distinct aggregation of 1 + b) ``` In reality, the Expand only needs one projection for `1 + b` and `b + 1`, because they are semantically equivalent. With the proposed change, the Expand operator's projections look like this: ``` [a#67, null, 0, null, UnscaledValue(c#69)], <== projection #1 (for regular aggregations) [a#67, (b#68 + 1), 1, (c#69 > 0.0), null]], <== projection #2 (for distinct aggregation on b + 1 and 1 + b) ``` With one less projection, Expand produces 2\*n rows instead of 3\*n rows, but still produces the correct result. In the case where all distinct aggregates have semantically equivalent children, the Expand operator is not needed at all. Benchmark code in the JIRA (SPARK-40382). Before the PR: ``` distinct aggregates: Best Time(ms) Avg Time(ms) Stdev(ms) Rate(M/s) Per Row(ns) Relative ------------------------------------------------------------------------------------------------------------------------ all semantically equivalent 14721 14859 195 5.7 175.5 1.0X some semantically equivalent 14569 14572 5 5.8 173.7 1.0X none semantically equivalent 14408 14488 113 5.8 171.8 1.0X ``` After the PR: ``` distinct aggregates: Best Time(ms) Avg Time(ms) Stdev(ms) Rate(M/s) Per Row(ns) Relative ------------------------------------------------------------------------------------------------------------------------ all semantically equivalent 3658 3692 49 22.9 43.6 1.0X some semantically equivalent 9124 9214 127 9.2 108.8 0.4X none semantically equivalent 14601 14777 250 5.7 174.1 0.3X ``` ### Does this PR introduce _any_ user-facing change? No. ### How was this patch tested? New unit tests. Closes apache#37825 from bersprockets/rewritedistinct_issue. Authored-by: Bruce Robbins <[email protected]> Signed-off-by: Wenchen Fan <[email protected]>

…nto w/ and w/o `ansi` suffix to pass sql analyzer test in ansi mode ### What changes were proposed in this pull request? After apache#40496, run ``` SPARK_ANSI_SQL_MODE=true build/sbt "sql/testOnly org.apache.spark.sql.SQLQueryTestSuite" ``` There is one test faild with `spark.sql.ansi.enabled = true` ``` [info] - timestampNTZ/datetime-special.sql_analyzer_test *** FAILED *** (11 milliseconds) [info] timestampNTZ/datetime-special.sql_analyzer_test [info] Expected "...date(999999, 3, 18, [false) AS make_date(999999, 3, 18)#x, make_date(-1, 1, 28, fals]e) AS make_date(-1, ...", but got "...date(999999, 3, 18, [true) AS make_date(999999, 3, 18)#x, make_date(-1, 1, 28, tru]e) AS make_date(-1, ..." Result did not match for query #1 [info] select make_date(999999, 3, 18), make_date(-1, 1, 28) (SQLQueryTestSuite.scala:777) [info] org.scalatest.exceptions.TestFailedException: ``` The failure reason is the last parameter of function `MakeDate` is `failOnError: Boolean = SQLConf.get.ansiEnabled`. So this pr split `timestampNTZ/datetime-special.sql` into w/ and w/o ansi to mask this test difference. ### Why are the changes needed? Make SQLQueryTestSuite test pass with `spark.sql.ansi.enabled = true`. ### Does this PR introduce _any_ user-facing change? No ### How was this patch tested? - Pass GitHub Actions - Manual checked `SPARK_ANSI_SQL_MODE=true build/sbt "sql/testOnly org.apache.spark.sql.SQLQueryTestSuite"` Closes apache#40552 from LuciferYang/SPARK-42921. Authored-by: yangjie01 <[email protected]> Signed-off-by: Hyukjin Kwon <[email protected]>

### What changes were proposed in this pull request? This PR uses SMALLINT (as TINYINT ranges [0, 255]) instead of BYTE to fix the ByteType mapping for MsSQLServer JDBC ```java [info] com.microsoft.sqlserver.jdbc.SQLServerException: Column, parameter, or variable #1: Cannot find data type BYTE. [info] at com.microsoft.sqlserver.jdbc.SQLServerException.makeFromDatabaseError(SQLServerException.java:265) [info] at com.microsoft.sqlserver.jdbc.SQLServerStatement.getNextResult(SQLServerStatement.java:1662) [info] at com.microsoft.sqlserver.jdbc.SQLServerStatement.doExecuteStatement(SQLServerStatement.java:898) [info] at com.microsoft.sqlserver.jdbc.SQLServerStatement$StmtExecCmd.doExecute(SQLServerStatement.java:793) [info] at com.microsoft.sqlserver.jdbc.TDSCommand.execute(IOBuffer.java:7417) [info] at com.microsoft.sqlserver.jdbc.SQLServerConnection.executeCommand(SQLServerConnection.java:3488) [info] at com.microsoft.sqlserver.jdbc.SQLServerStatement.executeCommand(SQLServerStatement.java:262) [info] at com.microsoft.sqlserver.jdbc.SQLServerStatement.executeStatement(SQLServerStatement.java:237) [info] at com.microsoft.sqlserver.jdbc.SQLServerStatement.executeUpdate(SQLServerStatement.java:733) [info] at org.apache.spark.sql.jdbc.JdbcDialect.createTable(JdbcDialects.scala:267) ``` ### Why are the changes needed? bugfix ### Does this PR introduce _any_ user-facing change? no ### How was this patch tested? new tests ### Was this patch authored or co-authored using generative AI tooling? no Closes apache#46164 from yaooqinn/SPARK-47938. Lead-authored-by: Kent Yao <[email protected]> Co-authored-by: Dongjoon Hyun <[email protected]> Signed-off-by: Dongjoon Hyun <[email protected]>

…rtition data results should return user-facing error ### What changes were proposed in this pull request? Create an example parquet table with partitions and insert data in Spark: ``` create table t(col1 string, col2 string, col3 string) using parquet location 'some/path/parquet-test' partitioned by (col1, col2); insert into t (col1, col2, col3) values ('a', 'b', 'c'); ``` Go into the `parquet-test` path in the filesystem and try to copy parquet data file from path `col1=a/col2=b` directory into `col1=a`. After that, try to create new table based on parquet data in Spark: ``` create table broken_table using parquet location 'some/path/parquet-test'; ``` This query errors with internal error. Stack trace excerpts: ``` org.apache.spark.SparkException: [INTERNAL_ERROR] Eagerly executed command failed. You hit a bug in Spark or the Spark plugins you use. Please, report this bug to the corresponding communities or vendors, and provide the full stack trace. SQLSTATE: XX000 ... Caused by: java.lang.AssertionError: assertion failed: Conflicting partition column names detected: Partition column name list #0: col1 Partition column name list #1: col1, col2For partitioned table directories, data files should only live in leaf directories. And directories at the same level should have the same partition column name. Please check the following directories for unexpected files or inconsistent partition column names: file:some/path/parquet-test/col1=a file:some/path/parquet-test/col1=a/col2=b at scala.Predef$.assert(Predef.scala:279) at org.apache.spark.sql.execution.datasources.PartitioningUtils$.resolvePartitions(PartitioningUtils.scala:391) ... ``` Fix this by changing internal error to user-facing error. ### Why are the changes needed? Replace internal error with user-facing one for valid sequence of Spark SQL operations. ### Does this PR introduce _any_ user-facing change? Yes, it presents the user with regular error instead of internal error. ### How was this patch tested? Added checks to `ParquetPartitionDiscoverySuite` which simulate the described scenario by manually breaking parquet table in the filesystem. ### Was this patch authored or co-authored using generative AI tooling? No. Closes apache#47668 from nikolamand-db/SPARK-49163. Authored-by: Nikola Mandic <[email protected]> Signed-off-by: Wenchen Fan <[email protected]>

…in/load-spark-env.sh ### What changes were proposed in this pull request? The last action in [bin/load-spark-env.sh](https://github.com/apache/spark/blob/d5da49d56d7dec5f8a96c5252384d865f7efd4d9/bin/load-spark-env.sh#L68) performs a test to determine whether running in a terminal or not, and whether `stdin` is reading from a pipe. A more portable test is needed. ### Why are the changes needed? The current approach relies on `ps` with options that vary significantly between different Unix-like systems. Specifically, it prints an error message in both `cygwin` and `msys2` (and by extension, in all of the variations of `git-for-windows`). It doesn't print an error message, but fails to detect a terminal session in `Linux` and `Osx/Darwin homebrew` (always thinks STDIN is a pipe). Here's what the problem looks like in a `cygwin64` session (with `set -x` just ahead of the section of interest): If called directly: ```bash $ bin/load-spark-env.sh ++ ps -o stat= -p 1947 ps: unknown option -- o Try `ps --help' for more information. + [[ ! '' =~ \+ ]] + [[ -p /dev/stdin ]] + export 'SPARK_BEELINE_OPTS= -Djline.terminal=jline.UnsupportedTerminal' + SPARK_BEELINE_OPTS=' -Djline.terminal=jline.UnsupportedTerminal' ``` Interestingly, due to the 2-part test, it does the right thing w.r.t. the Terminal test, the main problem being the error message. If called downstream from a pipe: ```bash $ echo "yo" | bin/load-spark-env.sh ++ ps -o stat= -p 1955 ps: unknown option -- o Try `ps --help' for more information. + [[ ! '' =~ \+ ]] + [[ -p /dev/stdin ]] ``` Again, it correctly detects the pipe environment, but with an error message. In WSL2 Ubuntu, the test doesn't correctly detect a non-pipe terminal session: ```bash # /opt/spark$ bin/load-spark-env.sh ++ ps -o stat= -p 1423 + [[ ! S+ =~ \+ ]] # echo "yo!" | bin/load-spark-env.sh ++ ps -o stat= -p 1416 + [[ ! S+ =~ \+ ]] ``` In `apache#134-Ubuntu SMP Fri Sep 27 20:20:17 UTC 2024`, the same failure occurs (it doesn't recognize terminal environments). ### Does this PR introduce _any_ user-facing change? This is a proposed bug fix, and, other than fixing the bug, should be invisible to users. ### How was this patch tested? The patch was verified to behave as intended in terminal sessions, both interactive and piped, in the following 5 environments. ``` - Linux quadd 5.15.0-124-generic apache#134-Ubuntu SMP Fri Sep 27 20:20:17 UTC 2024 x86_64 x86_64 x86_64 GNU/Linux - Linux d5 5.15.153.1-microsoft-standard-WSL2 #1 SMP Fri Mar 29 23:14:13 UTC 2024 x86_64 x86_64 x86_64 GNU/Linux - MINGW64_NT-10.0-22631 d5 3.5.4-0bc1222b.x86_64 2024-09-04 18:28 UTC x86_64 Msys - CYGWIN_NT-10.0-22631 d5 3.5.3-1.x86_64 2024-04-03 17:25 UTC x86_64 Cygwin - Darwin suemac.local 23.6.0 Darwin Kernel Version 23.6.0: Mon Jul 29 21:14:21 PDT 2024; root:xnu-10063.141.2~1/RELEASE_ARM64_T8103 arm64 ``` The test was to manually run the following script, verifying the expected response to both pipe and terminal sessions. ```bash #!/bin/bash if [ -e /usr/bin/tty -a "`tty`" != "not a tty" -a ! -p /dev/stdin ]; then echo "not a pipe" else echo "is a pipe" fi ``` The output of the manual test in all 5 tested environments. ``` philwalkquadd:/opt/spark $ isPipe not a pipe # $ echo "yo" | isPipe is a pipe # ``` ### Was this patch authored or co-authored using generative AI tooling? No Closes apache#48937 from philwalk/portability-fix-for-load-spark-env.sh. Authored-by: philwalk <[email protected]> Signed-off-by: yangjie01 <[email protected]>

…in/load-spark-env.sh ### What changes were proposed in this pull request? The last action in [bin/load-spark-env.sh](https://github.com/apache/spark/blob/d5da49d56d7dec5f8a96c5252384d865f7efd4d9/bin/load-spark-env.sh#L68) performs a test to determine whether running in a terminal or not, and whether `stdin` is reading from a pipe. A more portable test is needed. ### Why are the changes needed? The current approach relies on `ps` with options that vary significantly between different Unix-like systems. Specifically, it prints an error message in both `cygwin` and `msys2` (and by extension, in all of the variations of `git-for-windows`). It doesn't print an error message, but fails to detect a terminal session in `Linux` and `Osx/Darwin homebrew` (always thinks STDIN is a pipe). Here's what the problem looks like in a `cygwin64` session (with `set -x` just ahead of the section of interest): If called directly: ```bash $ bin/load-spark-env.sh ++ ps -o stat= -p 1947 ps: unknown option -- o Try `ps --help' for more information. + [[ ! '' =~ \+ ]] + [[ -p /dev/stdin ]] + export 'SPARK_BEELINE_OPTS= -Djline.terminal=jline.UnsupportedTerminal' + SPARK_BEELINE_OPTS=' -Djline.terminal=jline.UnsupportedTerminal' ``` Interestingly, due to the 2-part test, it does the right thing w.r.t. the Terminal test, the main problem being the error message. If called downstream from a pipe: ```bash $ echo "yo" | bin/load-spark-env.sh ++ ps -o stat= -p 1955 ps: unknown option -- o Try `ps --help' for more information. + [[ ! '' =~ \+ ]] + [[ -p /dev/stdin ]] ``` Again, it correctly detects the pipe environment, but with an error message. In WSL2 Ubuntu, the test doesn't correctly detect a non-pipe terminal session: ```bash # /opt/spark$ bin/load-spark-env.sh ++ ps -o stat= -p 1423 + [[ ! S+ =~ \+ ]] # echo "yo!" | bin/load-spark-env.sh ++ ps -o stat= -p 1416 + [[ ! S+ =~ \+ ]] ``` In `apache#134-Ubuntu SMP Fri Sep 27 20:20:17 UTC 2024`, the same failure occurs (it doesn't recognize terminal environments). ### Does this PR introduce _any_ user-facing change? This is a proposed bug fix, and, other than fixing the bug, should be invisible to users. ### How was this patch tested? The patch was verified to behave as intended in terminal sessions, both interactive and piped, in the following 5 environments. ``` - Linux quadd 5.15.0-124-generic apache#134-Ubuntu SMP Fri Sep 27 20:20:17 UTC 2024 x86_64 x86_64 x86_64 GNU/Linux - Linux d5 5.15.153.1-microsoft-standard-WSL2 #1 SMP Fri Mar 29 23:14:13 UTC 2024 x86_64 x86_64 x86_64 GNU/Linux - MINGW64_NT-10.0-22631 d5 3.5.4-0bc1222b.x86_64 2024-09-04 18:28 UTC x86_64 Msys - CYGWIN_NT-10.0-22631 d5 3.5.3-1.x86_64 2024-04-03 17:25 UTC x86_64 Cygwin - Darwin suemac.local 23.6.0 Darwin Kernel Version 23.6.0: Mon Jul 29 21:14:21 PDT 2024; root:xnu-10063.141.2~1/RELEASE_ARM64_T8103 arm64 ``` The test was to manually run the following script, verifying the expected response to both pipe and terminal sessions. ```bash #!/bin/bash if [ -e /usr/bin/tty -a "`tty`" != "not a tty" -a ! -p /dev/stdin ]; then echo "not a pipe" else echo "is a pipe" fi ``` The output of the manual test in all 5 tested environments. ``` philwalkquadd:/opt/spark $ isPipe not a pipe # $ echo "yo" | isPipe is a pipe # ``` ### Was this patch authored or co-authored using generative AI tooling? No Closes apache#48937 from philwalk/portability-fix-for-load-spark-env.sh. Authored-by: philwalk <[email protected]> Signed-off-by: yangjie01 <[email protected]> (cherry picked from commit 8d26008) Signed-off-by: yangjie01 <[email protected]>

### What changes were proposed in this pull request? This PR aims to disable `SparkBloomFilterSuite` due to the excessive running time. - SPARK-53077 is filed to re-enable this with the reasonable running time. ### Why are the changes needed? Previously, `common/sketch` module took less than 10s. ``` $ mvn package --pl common/sketch ... [INFO] ------------------------------------------------------------------------ [INFO] BUILD SUCCESS [INFO] ------------------------------------------------------------------------ [INFO] Total time: 7.177 s [INFO] Finished at: 2025-08-02T08:25:43-07:00 [INFO] ------------------------------------------------------------------------ ``` After `SparkBloomFilterSuite` was added newly, `SparkBloomFilterSuite` took over 12 minutes. It's too long as a unit test. - apache#50933 ``` [info] Test org.apache.spark.util.sketch.SparkBloomFilterSuite#testAccuracyRandomDistribution(long, double, int, org.junit.jupiter.api.TestInfo):#1 started [info] Test org.apache.spark.util.sketch.SparkBloomFilterSuite#testAccuracyEvenOdd(long, double, int, org.junit.jupiter.api.TestInfo):#1 started [info] Test run finished: 0 failed, 0 ignored, 2 total, 721.939s ``` ### Does this PR introduce _any_ user-facing change? No, this is a test change. ### How was this patch tested? Pass the CIs. ### Was this patch authored or co-authored using generative AI tooling? No. Closes apache#51788 from dongjoon-hyun/SPARK-53076. Authored-by: Dongjoon Hyun <[email protected]> Signed-off-by: yangjie01 <[email protected]>

… `SparkBloomFilterSuite` ### What changes were proposed in this pull request? This pr adds an environment variable named `SPARK_TEST_SPARK_BLOOM_FILTER_SUITE_ENABLED` to control whether the test case `SparkBloomFilterSuite` is executed. It also ensures that this test case is only run for validation in the daily tests specified in `build_non_ansi.yml`. ### Why are the changes needed? The `SparkBloomFilterSuite` requires periodic validation, but due to its excessively long execution time (over 10 minutes), it is not suitable for execution in the Change Pipeline. ### Does this PR introduce _any_ user-facing change? No ### How was this patch tested? Manual verification: - maven ``` build/mvn package --pl common/sketch [INFO] Running org.apache.spark.util.sketch.SparkBloomFilterSuite [WARNING] Tests run: 2, Failures: 0, Errors: 0, Skipped: 2, Time elapsed: 0.001 s -- in org.apache.spark.util.sketch.SparkBloomFilterSuite ``` ``` SPARK_TEST_SPARK_BLOOM_FILTER_SUITE_ENABLED=true build/mvn package --pl common/sketch [INFO] Running org.apache.spark.util.sketch.SparkBloomFilterSuite [INFO] Tests run: 2, Failures: 0, Errors: 0, Skipped: 0, Time elapsed: 401.9 s -- in org.apache.spark.util.sketch.SparkBloomFilterSuite ``` - sbt ``` build/sbt clean "sketch/test" [info] Test run started (JUnit Jupiter) [info] Test org.apache.spark.util.sketch.SparkBloomFilterSuite ignored: Environment variable [SPARK_TEST_SPARK_BLOOM_FILTER_SUITE_ENABLED] does not exist [info] Test run finished: 0 failed, 0 ignored, 0 total, 0.016s ``` ``` SPARK_TEST_SPARK_BLOOM_FILTER_SUITE_ENABLED=true build/sbt clean "sketch/test" [info] Test run started (JUnit Jupiter) [info] Test org.apache.spark.util.sketch.SparkBloomFilterSuite#testAccuracyRandomDistribution(long, double, int, org.junit.jupiter.api.TestInfo):#1 started [info] Test org.apache.spark.util.sketch.SparkBloomFilterSuite#testAccuracyEvenOdd(long, double, int, org.junit.jupiter.api.TestInfo):#1 started [info] Test run finished: 0 failed, 0 ignored, 2 total, 359.776s ``` ### Was this patch authored or co-authored using generative AI tooling? No Closes apache#51806 from LuciferYang/SPARK-53077. Authored-by: yangjie01 <[email protected]> Signed-off-by: yangjie01 <[email protected]>

…e of the closed PRs ### What changes were proposed in this pull request? This PR aims to improve `merge_spark_pr.py` to stop early in case of the closed PRs. ### Why are the changes needed? To help committers by removing the useless interactions. **BEFORE** ``` $ dev/merge_spark_pr.py git rev-parse --abbrev-ref HEAD Which pull request would you like to merge? (e.g. 34): 1 I've re-written the title as follows to match the standard format: Original: Removed reference to incubation in README.md. Modified: Removed reference to incubation in README.md Would you like to use the modified title? (y/N): ... ``` **AFTER** ``` $ dev/merge_spark_pr.py git rev-parse --abbrev-ref HEAD Which pull request would you like to merge? (e.g. 34): 1 #1 is closed already. Restoring head pointer to SPARK-53277 git checkout SPARK-53277 Already on 'SPARK-53277' git branch ``` ### Does this PR introduce _any_ user-facing change? No, this is used by committers only. ### How was this patch tested? Manually check. ### Was this patch authored or co-authored using generative AI tooling? No. Closes apache#52019 from dongjoon-hyun/SPARK-53277. Authored-by: Dongjoon Hyun <[email protected]> Signed-off-by: Dongjoon Hyun <[email protected]>

add regression test for doubly nested data

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marmbrus mentioned this pull request Sep 5, 2014

[SPARK-2096][SQL] Correctly parse dot notations apache/spark#2230

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cloud-fan merged this pull request into cloud-fan:dot Sep 5, 2014

marmbrus deleted the pr/2230 branch September 22, 2014 19:53

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add regression test for doubly nested data #1

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