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* HOTFIX: Ignore flaky tests in YARNPatrick Wendell2014-09-301-2/+2
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* Revert "[SPARK-3007][SQL]Add Dynamic Partition support to Spark Sql hive"Patrick Wendell2014-09-3014-443/+299
| | | | This reverts commit 0bbe7faeffa17577ae8a33dfcd8c4c783db5c909.
* [SPARK-3734] DriverRunner should not read SPARK_HOME from submitter's ↵Josh Rosen2014-09-291-4/+1
| | | | | | | | | | | | | | | | | | | environment When using spark-submit in `cluster` mode to submit a job to a Spark Standalone cluster, if the JAVA_HOME environment variable was set on the submitting machine then DriverRunner would attempt to use the submitter's JAVA_HOME to launch the driver process (instead of the worker's JAVA_HOME), causing the driver to fail unless the submitter and worker had the same Java location. This commit fixes this by reading JAVA_HOME from sys.env instead of command.environment. Author: Josh Rosen <joshrosen@apache.org> Closes #2586 from JoshRosen/SPARK-3734 and squashes the following commits: e9513d9 [Josh Rosen] [SPARK-3734] DriverRunner should not read SPARK_HOME from submitter's environment.
* [SPARK-3709] Executors don't always report broadcast block removal properly ↵Reynold Xin2014-09-292-3/+3
| | | | | | | | | | | | | | | | back to the driver The problem was that the 2nd argument in RemoveBroadcast is not tellMaster! It is "removeFromDriver". Basically when removeFromDriver is not true, we don't report broadcast block removal back to the driver, and then other executors mistakenly think that the executor would still have the block, and try to fetch from it. cc @tdas Author: Reynold Xin <rxin@apache.org> Closes #2588 from rxin/debug and squashes the following commits: 6dab2e3 [Reynold Xin] Don't log random messages. f430686 [Reynold Xin] Always report broadcast removal back to master. 2a13f70 [Reynold Xin] iii
* [SPARK-3613] Record only average block size in MapStatus for large stagesReynold Xin2014-09-299-98/+240
| | | | | | | | | | | | | | | This changes the way we send MapStatus from executors back to driver for large stages (>2000 tasks). For large stages, we no longer send one byte per block. Instead, we just send the average block size. This makes large jobs (tens of thousands of tasks) much more reliable since the driver no longer sends huge amount of data. Author: Reynold Xin <rxin@apache.org> Closes #2470 from rxin/mapstatus and squashes the following commits: 822ff54 [Reynold Xin] Code review feedback. 3b86f56 [Reynold Xin] Added MimaExclude. f89d182 [Reynold Xin] Fixed a bug in MapStatus 6a0401c [Reynold Xin] [SPARK-3613] Record only average block size in MapStatus for large stages.
* Minor cleanup of code.Reynold Xin2014-09-293-47/+31
| | | | | | | | Author: Reynold Xin <rxin@apache.org> Closes #2581 from rxin/minor-cleanup and squashes the following commits: 736a91b [Reynold Xin] Minor cleanup of code.
* Fixed the condition in StronglyConnectedComponents Issue: SPARK-3635oded2014-09-291-1/+1
| | | | | | | | Author: oded <oded@HP-DV6.c4internal.c4-security.com> Closes #2486 from odedz/master and squashes the following commits: dd7890a [oded] Fixed the condition in StronglyConnectedComponents Issue: SPARK-3635
* [graphX] GraphOps: random pick vertex bugyingjieMiao2014-09-291-1/+1
| | | | | | | | | | When `numVertices > 50`, probability is set to 0. This would cause infinite loop. Author: yingjieMiao <yingjie@42go.com> Closes #2553 from yingjieMiao/graphx and squashes the following commits: 6adf3c8 [yingjieMiao] [graphX] GraphOps: random pick vertex bug
* [SPARK-3007][SQL]Add Dynamic Partition support to Spark Sql hivebaishuo(白硕)2014-09-2914-299/+443
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | a new PR base on new master. changes are the same as https://github.com/apache/spark/pull/1919 Author: baishuo(白硕) <vc_java@hotmail.com> Author: baishuo <vc_java@hotmail.com> Author: Cheng Lian <lian.cs.zju@gmail.com> Closes #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
* Add more debug message for ManagedBufferReynold Xin2014-09-292-6/+51
| | | | | | | | | | | This is to help debug the error reported at http://apache-spark-user-list.1001560.n3.nabble.com/SQL-queries-fail-in-1-2-0-SNAPSHOT-td15327.html Author: Reynold Xin <rxin@apache.org> Closes #2580 from rxin/buffer-debug and squashes the following commits: 5814292 [Reynold Xin] Logging close() in case close() fails. 323dfec [Reynold Xin] Add more debug message.
* [SPARK-3032][Shuffle] Fix key comparison integer overflow introduced sorting ↵jerryshao2014-09-292-1/+56
| | | | | | | | | | | | | | | exception Previous key comparison in `ExternalSorter` will get wrong sorting result or exception when key comparison overflows, details can be seen in [SPARK-3032](https://issues.apache.org/jira/browse/SPARK-3032). Here fix this and add a unit test to prove it. Author: jerryshao <saisai.shao@intel.com> Closes #2514 from jerryshao/SPARK-3032 and squashes the following commits: 6f3c302 [jerryshao] Improve the unit test according to comments 01911e6 [jerryshao] Change the test to show the contract violate exception 83acb38 [jerryshao] Minor changes according to comments fa2a08f [jerryshao] Fix key comparison integer overflow introduced sorting exception
* [MLlib] [SPARK-2885] DIMSUM: All-pairs similarityReza Zadeh2014-09-295-6/+259
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | # All-pairs similarity via DIMSUM Compute all pairs of similar vectors using brute force approach, and also DIMSUM sampling approach. Laying down some notation: we are looking for all pairs of similar columns in an m x n RowMatrix whose entries are denoted a_ij, with the i’th row denoted r_i and the j’th column denoted c_j. There is an oversampling parameter labeled ɣ that should be set to 4 log(n)/s to get provably correct results (with high probability), where s is the similarity threshold. The algorithm is stated with a Map and Reduce, with proofs of correctness and efficiency in published papers [1] [2]. The reducer is simply the summation reducer. The mapper is more interesting, and is also the heart of the scheme. As an exercise, you should try to see why in expectation, the map-reduce below outputs cosine similarities. ![dimsumv2](https://cloud.githubusercontent.com/assets/3220351/3807272/d1d9514e-1c62-11e4-9f12-3cfdb1d78b3a.png) [1] Bosagh-Zadeh, Reza and Carlsson, Gunnar (2013), Dimension Independent Matrix Square using MapReduce, arXiv:1304.1467 http://arxiv.org/abs/1304.1467 [2] Bosagh-Zadeh, Reza and Goel, Ashish (2012), Dimension Independent Similarity Computation, arXiv:1206.2082 http://arxiv.org/abs/1206.2082 # Testing Tests for all invocations included. Added L1 and L2 norm computation to MultivariateStatisticalSummary since it was needed. Added tests for both of them. Author: Reza Zadeh <rizlar@gmail.com> Author: Xiangrui Meng <meng@databricks.com> Closes #1778 from rezazadeh/dimsumv2 and squashes the following commits: 404c64c [Reza Zadeh] Merge remote-tracking branch 'upstream/master' into dimsumv2 4eb71c6 [Reza Zadeh] Add excludes for normL1 and normL2 ee8bd65 [Reza Zadeh] Merge remote-tracking branch 'upstream/master' into dimsumv2 976ddd4 [Reza Zadeh] Broadcast colMags. Avoid div by zero. 3467cff [Reza Zadeh] Merge remote-tracking branch 'upstream/master' into dimsumv2 aea0247 [Reza Zadeh] Allow large thresholds to promote sparsity 9fe17c0 [Xiangrui Meng] organize imports 2196ba5 [Xiangrui Meng] Merge branch 'rezazadeh-dimsumv2' into dimsumv2 254ca08 [Reza Zadeh] Merge remote-tracking branch 'upstream/master' into dimsumv2 f2947e4 [Xiangrui Meng] some optimization 3c4cf41 [Xiangrui Meng] Merge branch 'master' into rezazadeh-dimsumv2 0e4eda4 [Reza Zadeh] Use partition index for RNG 251bb9c [Reza Zadeh] Documentation 25e9d0d [Reza Zadeh] Line length for style fb296f6 [Reza Zadeh] renamed to normL1 and normL2 3764983 [Reza Zadeh] Documentation e9c6791 [Reza Zadeh] New interface and documentation 613f261 [Reza Zadeh] Column magnitude summary 75a0b51 [Reza Zadeh] Use Ints instead of Longs in the shuffle 0f12ade [Reza Zadeh] Style changes eb1dc20 [Reza Zadeh] Use Double.PositiveInfinity instead of Double.Max f56a882 [Reza Zadeh] Remove changes to MultivariateOnlineSummarizer dbc55ba [Reza Zadeh] Make colMagnitudes a method in RowMatrix 41e8ece [Reza Zadeh] style changes 139c8e1 [Reza Zadeh] Syntax changes 029aa9c [Reza Zadeh] javadoc and new test 75edb25 [Reza Zadeh] All tests passing! 05e59b8 [Reza Zadeh] Add test 502ce52 [Reza Zadeh] new interface 654c4fb [Reza Zadeh] default methods 3726ca9 [Reza Zadeh] Remove MatrixAlgebra 6bebabb [Reza Zadeh] remove changes to MatrixSuite 5b8cd7d [Reza Zadeh] Initial files
* [EC2] Sort long, manually-inputted dictionariesNicholas Chammas2014-09-291-31/+38
| | | | | | | | | | Similar to the work done in #2571, this PR just sorts the remaining manually-inputted dicts in the EC2 script so they are easier to maintain. Author: Nicholas Chammas <nicholas.chammas@gmail.com> Closes #2578 from nchammas/ec2-dict-sort and squashes the following commits: f55c692 [Nicholas Chammas] sort long dictionaries
* [CORE] Bugfix: LogErr format in DAGScheduler.scalaZhang, Liye2014-09-291-1/+1
| | | | | | | | Author: Zhang, Liye <liye.zhang@intel.com> Closes #2572 from liyezhang556520/DAGLogErr and squashes the following commits: 5be2491 [Zhang, Liye] Bugfix: LogErr format in DAGScheduler.scala
* [EC2] Cleanup Python parens and disk dictNicholas Chammas2014-09-281-30/+30
| | | | | | | | | | | | Minor fixes: * Remove unnecessary parens (Python style) * Sort `disks_by_instance` dict and remove duplicate `t1.micro` key Author: Nicholas Chammas <nicholas.chammas@gmail.com> Closes #2571 from nchammas/ec2-polish and squashes the following commits: 9d203d5 [Nicholas Chammas] paren and dict cleanup
* [SPARK-1545] [mllib] Add Random ForestsJoseph K. Bradley2014-09-2814-511/+1410
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | This PR adds RandomForest to MLlib. The implementation is basic, and future performance optimizations will be important. (Note: RFs = Random Forests.) # Overview ## RandomForest * trains multiple trees at once to reduce the number of passes over the data * allows feature subsets at each node * uses a queue of nodes instead of fixed groups for each level This implementation is based an implementation by manishamde and the [Alpine Labs Sequoia Forest](https://github.com/AlpineNow/SparkML2) by codedeft (in particular, the TreePoint, BaggedPoint, and node queue implementations). Thank you for your inputs! ## Testing Correctness: This has been tested for correctness with the test suites and with DecisionTreeRunner on example datasets. Performance: This has been performance tested using [this branch of spark-perf](https://github.com/jkbradley/spark-perf/tree/rfs). Results below. ### Regression tests for DecisionTree Summary: For training 1 tree, there are small regressions, especially from feature subsampling. In the table below, each row is a single (random) dataset. The 2 different sets of result columns are for 2 different RF implementations: * (numTrees): This is from an earlier commit, after implementing RandomForest to train multiple trees at once. It does not include any code for feature subsampling. * (feature subsets): This is from this current PR's code, after implementing feature subsampling. These tests were to identify regressions in DecisionTree, so they are training 1 tree with all of the features (i.e., no feature subsampling). These were run on an EC2 cluster with 15 workers, training 1 tree with maxDepth = 5 (= 6 levels). Speedup values < 1 indicate slowdowns from the old DecisionTree implementation. numInstances | numFeatures | runtime (sec) | speedup | runtime (sec) | speedup ---- | ---- | ---- | ---- | ---- | ---- | | (numTrees) | (numTrees) | (feature subsets) | (feature subsets) 20000 | 100 | 4.051 | 1.044433473 | 4.478 | 0.9448414471 20000 | 500 | 8.472 | 1.104461756 | 9.315 | 1.004508857 20000 | 1500 | 19.354 | 1.05854087 | 20.863 | 0.9819776638 20000 | 3500 | 43.674 | 1.072033704 | 45.887 | 1.020332556 200000 | 100 | 4.196 | 1.171830315 | 4.848 | 1.014232673 200000 | 500 | 8.926 | 1.082791844 | 9.771 | 0.989151571 200000 | 1500 | 20.58 | 1.068415938 | 22.134 | 0.9934038131 200000 | 3500 | 48.043 | 1.075203464 | 52.249 | 0.9886505005 2000000 | 100 | 4.944 | 1.01355178 | 5.796 | 0.8645617667 2000000 | 500 | 11.11 | 1.016831683 | 12.482 | 0.9050632911 2000000 | 1500 | 31.144 | 1.017852556 | 35.274 | 0.8986789136 2000000 | 3500 | 79.981 | 1.085382778 | 101.105 | 0.8586123337 20000000 | 100 | 8.304 | 0.9270231214 | 9.073 | 0.8484514494 20000000 | 500 | 28.174 | 1.083268262 | 34.236 | 0.8914592826 20000000 | 1500 | 143.97 | 0.9579634646 | 159.275 | 0.8659111599 ### Tests for forests I have run other tests with numTrees=10 and with sqrt(numFeatures), and those indicate that multi-model training and feature subsets can speed up training for forests, especially when training deeper trees. # Details on specific classes ## Changes to DecisionTree * Main train() method is now in RandomForest. * findBestSplits() is no longer needed. (It split levels into groups, but we now use a queue of nodes.) * Many small changes to support RFs. (Note: These methods should be moved to RandomForest.scala in a later PR, but are in DecisionTree.scala to make code comparison easier.) ## RandomForest * Main train() method is from old DecisionTree. * selectNodesToSplit: Note that it selects nodes and feature subsets jointly to track memory usage. ## RandomForestModel * Stores an Array[DecisionTreeModel] * Prediction: * For classification, most common label. For regression, mean. * We could support other methods later. ## examples/.../DecisionTreeRunner * This now takes numTrees and featureSubsetStrategy, to support RFs. ## DTStatsAggregator * 2 types of functionality (w/ and w/o subsampling features): These require different indexing methods. (We could treat both as subsampling, but this is less efficient DTStatsAggregator is now abstract, and 2 child classes implement these 2 types of functionality. ## impurities * These now take instance weights. ## Node * Some vals changed to vars. * This is unfortunately a public API change (DeveloperApi). This could be avoided by creating a LearningNode struct, but would be awkward. ## RandomForestSuite Please let me know if there are missing tests! ## BaggedPoint This wraps TreePoint and holds bootstrap weights/counts. # Design decisions * BaggedPoint: BaggedPoint is separate from TreePoint since it may be useful for other bagging algorithms later on. * RandomForest public API: What options should be easily supported by the train* methods? Should ALL options be in the Java-friendly constructors? Should there be a constructor taking Strategy? * Feature subsampling options: What options should be supported? scikit-learn supports the same options, except for "onethird." One option would be to allow users to specific fractions ("0.1"): the current options could be supported, and any unrecognized values would be parsed as Doubles in [0,1]. * Splits and bins are computed before bootstrapping, so all trees use the same discretization. * One queue, instead of one queue per tree. CC: mengxr manishamde codedeft chouqin Please let me know if you have suggestions---thanks! Author: Joseph K. Bradley <joseph.kurata.bradley@gmail.com> Author: qiping.lqp <qiping.lqp@alibaba-inc.com> Author: chouqin <liqiping1991@gmail.com> Closes #2435 from jkbradley/rfs-new and squashes the following commits: c694174 [Joseph K. Bradley] Fixed typo cc59d78 [Joseph K. Bradley] fixed imports e25909f [Joseph K. Bradley] Simplified node group maps. Specifically, created NodeIndexInfo to store node index in agg and feature subsets, and no longer create extra maps in findBestSplits fbe9a1e [Joseph K. Bradley] Changed default featureSubsetStrategy to be sqrt for classification, onethird for regression. Updated docs with references. ef7c293 [Joseph K. Bradley] Updates based on code review. Most substantial changes: * Simplified DTStatsAggregator * Made RandomForestModel.trees public * Added test for regression to RandomForestSuite 593b13c [Joseph K. Bradley] Fixed bug in metadata for computing log2(num features). Now it checks >= 1. a1a08df [Joseph K. Bradley] Removed old comments 866e766 [Joseph K. Bradley] Changed RandomForestSuite randomized tests to use multiple fixed random seeds. ff8bb96 [Joseph K. Bradley] removed usage of null from RandomForest and replaced with Option bf1a4c5 [Joseph K. Bradley] Merge remote-tracking branch 'upstream/master' into rfs-new 6b79c07 [Joseph K. Bradley] Added RandomForestSuite, and fixed small bugs, style issues. d7753d4 [Joseph K. Bradley] Added numTrees and featureSubsetStrategy to DecisionTreeRunner (to support RandomForest). Fixed bugs so that RandomForest now runs. 746d43c [Joseph K. Bradley] Implemented feature subsampling. Tested DecisionTree but not RandomForest. 6309d1d [Joseph K. Bradley] Merge remote-tracking branch 'upstream/master' into rfs-new. Added RandomForestModel.toString b7ae594 [Joseph K. Bradley] Updated docs. Small fix for bug which does not cause errors: No longer allocate unused child nodes for leaf nodes. 121c74e [Joseph K. Bradley] Basic random forests are implemented. Random features per node not yet implemented. Test suite not implemented. 325d18a [Joseph K. Bradley] Merge branch 'chouqin-dt-preprune' into rfs-new 4ef9bf1 [Joseph K. Bradley] Merge remote-tracking branch 'upstream/master' into rfs-new 61b2e72 [Joseph K. Bradley] Added max of 10GB for maxMemoryInMB in Strategy. a95e7c8 [Joseph K. Bradley] Merge remote-tracking branch 'upstream/master' into chouqin-dt-preprune 6da8571 [Joseph K. Bradley] RFs partly implemented, not done yet eddd1eb [Joseph K. Bradley] Merge remote-tracking branch 'upstream/master' into rfs-new 5c4ac33 [Joseph K. Bradley] Added check in Strategy to make sure minInstancesPerNode >= 1 0dd4d87 [Joseph K. Bradley] Merge remote-tracking branch 'upstream/master' into dt-spark-3160 95c479d [Joseph K. Bradley] * Fixed typo in tree suite test "do not choose split that does not satisfy min instance per node requirements" * small style fixes e2628b6 [Joseph K. Bradley] Merge remote-tracking branch 'upstream/master' into chouqin-dt-preprune 19b01af [Joseph K. Bradley] Merge remote-tracking branch 'chouqin/dt-preprune' into chouqin-dt-preprune f1d11d1 [chouqin] fix typo c7ebaf1 [chouqin] fix typo 39f9b60 [chouqin] change edge `minInstancesPerNode` to 2 and add one more test c6e2dfc [Joseph K. Bradley] Added minInstancesPerNode and minInfoGain parameters to DecisionTreeRunner.scala and to Python API in tree.py 306120f [Joseph K. Bradley] Fixed typo in DecisionTreeModel.scala doc eaa1dcf [Joseph K. Bradley] Added topNode doc in DecisionTree and scalastyle fix d4d7864 [Joseph K. Bradley] Marked Node.build as deprecated d4dbb99 [Joseph K. Bradley] Merge remote-tracking branch 'upstream/master' into dt-spark-3160 1a8f0ad [Joseph K. Bradley] Eliminated pre-allocated nodes array in main train() method. * Nodes are constructed and added to the tree structure as needed during training. 0278a11 [chouqin] remove `noSplit` and set `Predict` private to tree d593ec7 [chouqin] fix docs and change minInstancesPerNode to 1 2ab763b [Joseph K. Bradley] Simplifications to DecisionTree code: efcc736 [qiping.lqp] fix bug 10b8012 [qiping.lqp] fix style 6728fad [qiping.lqp] minor fix: remove empty lines bb465ca [qiping.lqp] Merge branch 'master' of https://github.com/apache/spark into dt-preprune cadd569 [qiping.lqp] add api docs 46b891f [qiping.lqp] fix bug e72c7e4 [qiping.lqp] add comments 845c6fa [qiping.lqp] fix style f195e83 [qiping.lqp] fix style 987cbf4 [qiping.lqp] fix bug ff34845 [qiping.lqp] separate calculation of predict of node from calculation of info gain ac42378 [qiping.lqp] add min info gain and min instances per node parameters in decision tree
* [SPARK-3543] TaskContext remaining cleanup work.Reynold Xin2014-09-285-13/+9
| | | | | | | | Author: Reynold Xin <rxin@apache.org> Closes #2560 from rxin/TaskContext and squashes the following commits: 9eff95a [Reynold Xin] [SPARK-3543] remaining cleanup work.
* SPARK-2761 refactor #maybeSpill into SpillableJim Lim2014-09-283-92/+133
| | | | | | | | | | | | | Moved `#maybeSpill` in ExternalSorter and EAOM into `Spillable`. Author: Jim Lim <jim@quixey.com> Closes #2416 from jimjh/SPARK-2761 and squashes the following commits: cf8be9a [Jim Lim] SPARK-2761 fix documentation, reorder code f94d522 [Jim Lim] SPARK-2761 refactor Spillable to simplify sig e75a24e [Jim Lim] SPARK-2761 use protected over protected[this] 7270e0d [Jim Lim] SPARK-2761 refactor #maybeSpill into Spillable
* Revert "[SPARK-1021] Defer the data-driven computation of partition bounds ↵Reynold Xin2014-09-283-66/+34
| | | | | | | | in so..." This reverts commit 2d972fd84ac54a89e416442508a6d4eaeff452c1. The commit was hanging correlationoptimizer14.
* [SPARK-3715][Docs]minor typoWangTaoTheTonic2014-09-281-3/+3
| | | | | | | | | | https://issues.apache.org/jira/browse/SPARK-3715 Author: WangTaoTheTonic <barneystinson@aliyun.com> Closes #2567 from WangTaoTheTonic/minortypo and squashes the following commits: 9cc3f7a [WangTaoTheTonic] minor typo
* SPARK-3699: SQL and Hive console tasks now clean up appropriatelyWilliam Benton2014-09-281-2/+4
| | | | | | | | | | | | The sbt tasks sql/console and hive/console will now `stop()` the `SparkContext` upon exit. Previously, they left an ugly stack trace when quitting. Author: William Benton <willb@redhat.com> Closes #2547 from willb/consoleCleanup and squashes the following commits: d5e431f [William Benton] SQL and Hive console tasks now clean up.
* Minor fix for the previous commit.Reynold Xin2014-09-272-6/+5
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* SPARK-CORE [SPARK-3651] Group common CoarseGrainedSchedulerBackend variables ↵Dale2014-09-272-38/+68
| | | | | | | | | | | | | | | | | | | | | | | together from [SPARK-3651] In CoarseGrainedSchedulerBackend, we have: private val executorActor = new HashMap[String, ActorRef] private val executorAddress = new HashMap[String, Address] private val executorHost = new HashMap[String, String] private val freeCores = new HashMap[String, Int] private val totalCores = new HashMap[String, Int] We only ever put / remove stuff from these maps together. It would simplify the code if we consolidate these all into one map as we have done in JobProgressListener in https://issues.apache.org/jira/browse/SPARK-2299. Author: Dale <tigerquoll@outlook.com> Closes #2533 from tigerquoll/SPARK-3651 and squashes the following commits: d1be0a9 [Dale] [SPARK-3651] implemented suggested changes. Changed a reference from executorInfo to executorData to be consistent with other usages 6890663 [Dale] [SPARK-3651] implemented suggested changes 7d671cf [Dale] [SPARK-3651] Grouped variables under a ExecutorDataObject, and reference them via a map entry as they are all retrieved under the same key
* [SPARK-3389] Add Converter for ease of Parquet reading in PySparkUri Laserson2014-09-274-30/+106
| | | | | | | | | | | | https://issues.apache.org/jira/browse/SPARK-3389 Author: Uri Laserson <laserson@cloudera.com> Closes #2256 from laserson/SPARK-3389 and squashes the following commits: 0ed363e [Uri Laserson] PEP8'd the python file 0b4b380 [Uri Laserson] Moved converter to examples and added python example eecf4dc [Uri Laserson] [SPARK-3389] Add Converter for ease of Parquet reading in PySpark
* [SPARK-3543] Clean up Java TaskContext implementation.Reynold Xin2014-09-275-29/+22
| | | | | | | | | | This addresses some minor issues in https://github.com/apache/spark/pull/2425 Author: Reynold Xin <rxin@apache.org> Closes #2557 from rxin/TaskContext and squashes the following commits: a51e5f6 [Reynold Xin] [SPARK-3543] Clean up Java TaskContext implementation.
* [SPARK-3681] [SQL] [PySpark] fix serialization of List and Map in SchemaRDDDavies Liu2014-09-272-27/+34
| | | | | | | | | | | | Currently, the schema of object in ArrayType or MapType is attached lazily, it will have better performance but introduce issues while serialization or accessing nested objects. This patch will apply schema to the objects of ArrayType or MapType immediately when accessing them, will be a little bit slower, but much robust. Author: Davies Liu <davies.liu@gmail.com> Closes #2526 from davies/nested and squashes the following commits: 2399ae5 [Davies Liu] fix serialization of List and Map in SchemaRDD
* [SPARK-3680][SQL] Fix bug caused by eager typing of HiveGenericUDFsMichael Armbrust2014-09-272-5/+12
| | | | | | | | | | Typing of UDFs should be lazy as it is often not valid to call `dataType` on an expression until after all of its children are `resolved`. Author: Michael Armbrust <michael@databricks.com> Closes #2525 from marmbrus/concatBug and squashes the following commits: 5b8efe7 [Michael Armbrust] fix bug with eager typing of udfs
* [SPARK-3676][SQL] Fix hive test suite failure due to diffs in JDK 1.6/1.7w002289702014-09-273-6/+11
| | | | | | | | | | | | | | | | | This is a bug in JDK6: http://bugs.java.com/bugdatabase/view_bug.do?bug_id=4428022 this is because jdk get different result to operate ```double```, ```System.out.println(1/500d)``` in different jdk get different result jdk 1.6.0(_31) ---- 0.0020 jdk 1.7.0(_05) ---- 0.002 this leads to HiveQuerySuite failed when generate golden answer in jdk 1.7 and run tests in jdk 1.6, result did not match Author: w00228970 <wangfei1@huawei.com> Closes #2517 from scwf/HiveQuerySuite and squashes the following commits: 0cb5e8d [w00228970] delete golden answer of division-0 and timestamp cast #1 1df3964 [w00228970] Jdk version leads to different query output for Double, this make HiveQuerySuite failed
* Docs : use "--total-executor-cores" rather than "--cores" after spark-shellCrazyJvm2014-09-271-1/+1
| | | | | | | | Author: CrazyJvm <crazyjvm@gmail.com> Closes #2540 from CrazyJvm/standalone-core and squashes the following commits: 66d9fc6 [CrazyJvm] use "--total-executor-cores" rather than "--cores" after spark-shell
* Minor cleanup to tighten visibility and remove compilation warning.Reynold Xin2014-09-274-62/+70
| | | | | | | | Author: Reynold Xin <rxin@apache.org> Closes #2555 from rxin/cleanup and squashes the following commits: 6add199 [Reynold Xin] Minor cleanup to tighten visibility and remove compilation warning.
* [SPARK-1021] Defer the data-driven computation of partition bounds in so...Erik Erlandson2014-09-263-34/+66
| | | | | | | | | | | | | | | | ...rtByKey() until evaluation. Author: Erik Erlandson <eerlands@redhat.com> Closes #1689 from erikerlandson/spark-1021-pr and squashes the following commits: 50b6da6 [Erik Erlandson] use standard getIteratorSize in countAsync 4e334a9 [Erik Erlandson] exception mystery fixed by fixing bug in ComplexFutureAction b88b5d4 [Erik Erlandson] tweak async actions to use ComplexFutureAction[T] so they handle RangePartitioner sampling job properly b2b20e8 [Erik Erlandson] Fix bug in exception passing with ComplexFutureAction[T] ca8913e [Erik Erlandson] RangePartition sampling job -> FutureAction 7143f97 [Erik Erlandson] [SPARK-1021] modify range bounds variable to be thread safe ac67195 [Erik Erlandson] [SPARK-1021] Defer the data-driven computation of partition bounds in sortByKey() until evaluation.
* stop, start and destroy require the EC2_REGIONJeff Steinmetz2014-09-261-10/+19
| | | | | | | | | | | | | | | | | i.e ./spark-ec2 --region=us-west-1 stop yourclustername Author: Jeff Steinmetz <jeffrey.steinmetz@gmail.com> Closes #2473 from jeffsteinmetz/master and squashes the following commits: 7491f2c [Jeff Steinmetz] fix case in EC2 cluster setup documentation bd3d777 [Jeff Steinmetz] standardized ec2 documenation to use <lower-case> sample args 2bf4a57 [Jeff Steinmetz] standardized ec2 documenation to use <lower-case> sample args 68d8372 [Jeff Steinmetz] standardized ec2 documenation to use <lower-case> sample args d2ab6e2 [Jeff Steinmetz] standardized ec2 documenation to use <lower-case> sample args 520e6dc [Jeff Steinmetz] standardized ec2 documenation to use <lower-case> sample args 37fc876 [Jeff Steinmetz] stop, start and destroy require the EC2_REGION
* [SPARK-3675][SQL] Allow starting a JDBC server on an existing contextMichael Armbrust2014-09-261-1/+14
| | | | | | | | Author: Michael Armbrust <michael@databricks.com> Closes #2515 from marmbrus/jdbcExistingContext and squashes the following commits: 7866fad [Michael Armbrust] Allows starting a JDBC server on an existing context.
* [SQL][DOCS] Clarify that the server is for JDBC and ODBCMichael Armbrust2014-09-261-5/+5
| | | | | | | | Author: Michael Armbrust <michael@databricks.com> Closes #2527 from marmbrus/patch-1 and squashes the following commits: a0f9f1c [Michael Armbrust] [SQL][DOCS] Clarify that the server is for JDBC and ODBC
* [Build]remove spark-staging-1030wangfei2014-09-261-12/+0
| | | | | | | | | | Since 1.1.0 has published, remove spark-staging-1030. Author: wangfei <wangfei1@huawei.com> Closes #2532 from scwf/patch-2 and squashes the following commits: bc9e00b [wangfei] remove spark-staging-1030
* Slaves file is now a template.Sarah Gerweck2014-09-261-1/+0
| | | | | | | | | | Change 0dc868e removed the `conf/slaves` file and made it a template like most of the other configuration files. This means you can no longer run `make-distribution.sh` unless you manually create a slaves file to be statically bundled in your distribution, which seems at odds with making it a template file. Author: Sarah Gerweck <sarah.a180@gmail.com> Closes #2549 from sarahgerweck/noMoreSlaves and squashes the following commits: d11d99a [Sarah Gerweck] Slaves file is now a template.
* Close #2194.Reynold Xin2014-09-260-0/+0
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* [SPARK-3543] Write TaskContext in Java and expose it through a static accessor.Prashant Sharma2014-09-267-131/+284
| | | | | | | | | | | | | | | Author: Prashant Sharma <prashant.s@imaginea.com> Author: Shashank Sharma <shashank21j@gmail.com> Closes #2425 from ScrapCodes/SPARK-3543/withTaskContext and squashes the following commits: 8ae414c [Shashank Sharma] CR ee8bd00 [Prashant Sharma] Added internal API in docs comments. ddb8cbe [Prashant Sharma] Moved setting the thread local to where TaskContext is instantiated. a7d5e23 [Prashant Sharma] Added doc comments. edf945e [Prashant Sharma] Code review git add -A f716fd1 [Prashant Sharma] introduced thread local for getting the task context. 333c7d6 [Prashant Sharma] Translated Task context from scala to java.
* Revert "[SPARK-3478] [PySpark] Profile the Python tasks"Josh Rosen2014-09-267-127/+7
| | | | This reverts commit 1aa549ba9839565274a12c52fa1075b424f138a6.
* [SPARK-3393] [SQL] Align the log4j configuration for Spark & SparkSQLCLICheng Hao2014-09-261-17/+0
| | | | | | | | | | | | User may be confused for the HQL logging & configurations, we'd better provide a default templates. Both files are copied from Hive. Author: Cheng Hao <hao.cheng@intel.com> Closes #2263 from chenghao-intel/hive_template and squashes the following commits: 53bffa9 [Cheng Hao] Remove the hive-log4j.properties initialization
* [SPARK-3531][SQL]select null from table would throw a MatchErrorDaoyuan Wang2014-09-263-0/+5
| | | | | | | | Author: Daoyuan Wang <daoyuan.wang@intel.com> Closes #2396 from adrian-wang/selectnull and squashes the following commits: 2458229 [Daoyuan Wang] rebase solution
* [SPARK-3476] Remove outdated memory checks in YarnAndrew Or2014-09-261-10/+3
| | | | | | | | | | | See description in [JIRA](https://issues.apache.org/jira/browse/SPARK-3476). Author: Andrew Or <andrewor14@gmail.com> Closes #2528 from andrewor14/yarn-memory-checks and squashes the following commits: c5400cd [Andrew Or] Simplify checks e30ffac [Andrew Or] Remove outdated memory checks
* [SPARK-3695]shuffle fetch fail outputDaoyuan Wang2014-09-261-1/+1
| | | | | | | | | | should output detailed host and port in error message Author: Daoyuan Wang <daoyuan.wang@intel.com> Closes #2539 from adrian-wang/fetchfail and squashes the following commits: 6c1b1e0 [Daoyuan Wang] shuffle fetch fail output
* [SPARK-3614][MLLIB] Add minimumOccurence filtering to IDFRJ Nowling2014-09-264-5/+103
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | This PR for [SPARK-3614](https://issues.apache.org/jira/browse/SPARK-3614) adds functionality for filtering out terms which do not appear in at least a minimum number of documents. This is implemented using a minimumOccurence parameter (default 0). When terms' document frequencies are less than minimumOccurence, their IDFs are set to 0, just like when the DF is 0. As a result, the TF-IDFs for the terms are found to be 0, as if the terms were not present in the documents. This PR makes the following changes: * Add a minimumOccurence parameter to the IDF and DocumentFrequencyAggregator classes. * Create a parameter-less constructor for IDF with a default minimumOccurence value of 0 to remain backwards-compatibility with the original IDF API. * Sets the IDFs to 0 for terms which DFs are less than minimumOccurence * Add tests to the Spark IDFSuite and Java JavaTfIdfSuite test suites * Updated the MLLib Feature Extraction programming guide to describe the new feature Author: RJ Nowling <rnowling@gmail.com> Closes #2494 from rnowling/spark-3614-idf-filter and squashes the following commits: 0aa3c63 [RJ Nowling] Fix identation e6523a8 [RJ Nowling] Remove unnecessary toDouble's from IDFSuite bfa82ec [RJ Nowling] Add space after if 30d20b3 [RJ Nowling] Add spaces around equals signs 9013447 [RJ Nowling] Add space before division operator 79978fc [RJ Nowling] Remove unnecessary semi-colon 40fd70c [RJ Nowling] Change minimumOccurence to minDocFreq in code and docs 47850ab [RJ Nowling] Changed minimumOccurence to Int from Long 9fb4093 [RJ Nowling] Remove unnecessary lines from IDF class docs 1fc09d8 [RJ Nowling] Add backwards-compatible constructor to DocumentFrequencyAggregator 1801fd2 [RJ Nowling] Fix style errors in IDF.scala 6897252 [RJ Nowling] Preface minimumOccurence members with val to make them final and immutable a200bab [RJ Nowling] Remove unnecessary else statement 4b974f5 [RJ Nowling] Remove accidentally-added import from testing c0cc643 [RJ Nowling] Add minimumOccurence filtering to IDF
* SPARK-3639 | Removed settings master in examplesaniketbhatnagar2014-09-262-13/+9
| | | | | | | | | | | | This patch removes setting of master as local in Kinesis examples so that users can set it using submit-job. Author: aniketbhatnagar <aniket.bhatnagar@gmail.com> Closes #2536 from aniketbhatnagar/Kinesis-Examples-Master-Unset and squashes the following commits: c9723ac [aniketbhatnagar] Merge remote-tracking branch 'origin/Kinesis-Examples-Master-Unset' into Kinesis-Examples-Master-Unset fec8ead [aniketbhatnagar] SPARK-3639 | Removed settings master in examples 31cdc59 [aniketbhatnagar] SPARK-3639 | Removed settings master in examples
* [SPARK-3478] [PySpark] Profile the Python tasksDavies Liu2014-09-267-7/+127
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | This patch add profiling support for PySpark, it will show the profiling results before the driver exits, here is one example: ``` ============================================================ Profile of RDD<id=3> ============================================================ 5146507 function calls (5146487 primitive calls) in 71.094 seconds Ordered by: internal time, cumulative time ncalls tottime percall cumtime percall filename:lineno(function) 5144576 68.331 0.000 68.331 0.000 statcounter.py:44(merge) 20 2.735 0.137 71.071 3.554 statcounter.py:33(__init__) 20 0.017 0.001 0.017 0.001 {cPickle.dumps} 1024 0.003 0.000 0.003 0.000 t.py:16(<lambda>) 20 0.001 0.000 0.001 0.000 {reduce} 21 0.001 0.000 0.001 0.000 {cPickle.loads} 20 0.001 0.000 0.001 0.000 copy_reg.py:95(_slotnames) 41 0.001 0.000 0.001 0.000 serializers.py:461(read_int) 40 0.001 0.000 0.002 0.000 serializers.py:179(_batched) 62 0.000 0.000 0.000 0.000 {method 'read' of 'file' objects} 20 0.000 0.000 71.072 3.554 rdd.py:863(<lambda>) 20 0.000 0.000 0.001 0.000 serializers.py:198(load_stream) 40/20 0.000 0.000 71.072 3.554 rdd.py:2093(pipeline_func) 41 0.000 0.000 0.002 0.000 serializers.py:130(load_stream) 40 0.000 0.000 71.072 1.777 rdd.py:304(func) 20 0.000 0.000 71.094 3.555 worker.py:82(process) ``` Also, use can show profile result manually by `sc.show_profiles()` or dump it into disk by `sc.dump_profiles(path)`, such as ```python >>> sc._conf.set("spark.python.profile", "true") >>> rdd = sc.parallelize(range(100)).map(str) >>> rdd.count() 100 >>> sc.show_profiles() ============================================================ Profile of RDD<id=1> ============================================================ 284 function calls (276 primitive calls) in 0.001 seconds Ordered by: internal time, cumulative time ncalls tottime percall cumtime percall filename:lineno(function) 4 0.000 0.000 0.000 0.000 serializers.py:198(load_stream) 4 0.000 0.000 0.000 0.000 {reduce} 12/4 0.000 0.000 0.001 0.000 rdd.py:2092(pipeline_func) 4 0.000 0.000 0.000 0.000 {cPickle.loads} 4 0.000 0.000 0.000 0.000 {cPickle.dumps} 104 0.000 0.000 0.000 0.000 rdd.py:852(<genexpr>) 8 0.000 0.000 0.000 0.000 serializers.py:461(read_int) 12 0.000 0.000 0.000 0.000 rdd.py:303(func) ``` The profiling is disabled by default, can be enabled by "spark.python.profile=true". Also, users can dump the results into disks automatically for future analysis, by "spark.python.profile.dump=path_to_dump" Author: Davies Liu <davies.liu@gmail.com> Closes #2351 from davies/profiler and squashes the following commits: 7ef2aa0 [Davies Liu] bugfix, add tests for show_profiles and dump_profiles() 2b0daf2 [Davies Liu] fix docs 7a56c24 [Davies Liu] bugfix cba9463 [Davies Liu] move show_profiles and dump_profiles to SparkContext fb9565b [Davies Liu] Merge branch 'master' of github.com:apache/spark into profiler 116d52a [Davies Liu] Merge branch 'master' of github.com:apache/spark into profiler 09d02c3 [Davies Liu] Merge branch 'master' into profiler c23865c [Davies Liu] Merge branch 'master' into profiler 15d6f18 [Davies Liu] add docs for two configs dadee1a [Davies Liu] add docs string and clear profiles after show or dump 4f8309d [Davies Liu] address comment, add tests 0a5b6eb [Davies Liu] fix Python UDF 4b20494 [Davies Liu] add profile for python
* [SPARK-3686][STREAMING] Wait for sink to commit the channel before check...Hari Shreedharan2014-09-254-10/+48
| | | | | | | | | | | ...ing for the channel size. Author: Hari Shreedharan <hshreedharan@apache.org> Closes #2531 from harishreedharan/sparksinksuite-fix and squashes the following commits: 30393c1 [Hari Shreedharan] Use more deterministic method to figure out when batches come in. 6ce9d8b [Hari Shreedharan] [SPARK-3686][STREAMING] Wait for sink to commit the channel before checking for the channel size.
* SPARK-2634: Change MapOutputTrackerWorker.mapStatuses to ConcurrentHashMapzsxwing2014-09-251-1/+7
| | | | | | | | | | MapOutputTrackerWorker.mapStatuses is used concurrently, it should be thread-safe. This bug has already been fixed in #1328. Nevertheless, considering #1328 won't be merged soon, I send this trivial fix and hope this issue can be solved soon. Author: zsxwing <zsxwing@gmail.com> Closes #1541 from zsxwing/SPARK-2634 and squashes the following commits: d450053 [zsxwing] SPARK-2634: Change MapOutputTrackerWorker.mapStatuses to ConcurrentHashMap
* [SPARK-3584] sbin/slaves doesn't work when we use password authentication ↵Kousuke Saruta2014-09-255-10/+30
| | | | | | | | | | | | | | | | | for SSH Author: Kousuke Saruta <sarutak@oss.nttdata.co.jp> Closes #2444 from sarutak/slaves-scripts-modification and squashes the following commits: eff7394 [Kousuke Saruta] Improve the description about Cluster Launch Script in docs/spark-standalone.md 7858225 [Kousuke Saruta] Modified sbin/slaves to use the environment variable "SPARK_SSH_FOREGROUND" as a flag 53d7121 [Kousuke Saruta] Merge branch 'master' of git://git.apache.org/spark into slaves-scripts-modification e570431 [Kousuke Saruta] Added a description for SPARK_SSH_FOREGROUND variable 7120a0c [Kousuke Saruta] Added a description about default host for sbin/slaves 1bba8a9 [Kousuke Saruta] Added SPARK_SSH_FOREGROUND flag to sbin/slaves 88e2f17 [Kousuke Saruta] Merge branch 'master' of git://git.apache.org/spark into slaves-scripts-modification 297e75d [Kousuke Saruta] Modified sbin/slaves not to export HOSTLIST
* [SPARK-1484][MLLIB] Warn when running an iterative algorithm on uncached data.Aaron Staple2014-09-257-30/+91
| | | | | | | | | | | | | | | | | | | Add warnings to KMeans, GeneralizedLinearAlgorithm, and computeSVD when called with input data that is not cached. KMeans is implemented iteratively, and I believe that GeneralizedLinearAlgorithm’s current optimizers are iterative and its future optimizers are also likely to be iterative. RowMatrix’s computeSVD is iterative against an RDD when run in DistARPACK mode. ALS and DecisionTree are iterative as well, but they implement RDD caching internally so do not require a warning. I added a warning to GeneralizedLinearAlgorithm rather than inside its optimizers, where the iteration actually occurs, because internally GeneralizedLinearAlgorithm maps its input data to an uncached RDD before passing it to an optimizer. (In other words, the warning would be printed for every GeneralizedLinearAlgorithm run, regardless of whether its input is cached, if the warning were in GradientDescent or other optimizer.) I assume that use of an uncached RDD by GeneralizedLinearAlgorithm is intentional, and that the mapping there (adding label, intercepts and scaling) is a lightweight operation. Arguably a user calling an optimizer such as GradientDescent will be knowledgable enough to cache their data without needing a log warning, so lack of a warning in the optimizers may be ok. Some of the documentation examples making use of these iterative algorithms did not cache their training RDDs (while others did). I updated the examples to always cache. I also fixed some (unrelated) minor errors in the documentation examples. Author: Aaron Staple <aaron.staple@gmail.com> Closes #2347 from staple/SPARK-1484 and squashes the following commits: bd49701 [Aaron Staple] Address review comments. ab2d4a4 [Aaron Staple] Disable warnings on python code path. a7a0f99 [Aaron Staple] Change code comments per review comments. 7cca1dc [Aaron Staple] Change warning message text. c77e939 [Aaron Staple] [SPARK-1484][MLLIB] Warn when running an iterative algorithm on uncached data. 3b6c511 [Aaron Staple] Minor doc example fixes.
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