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* REPL cleanup.Michael Armbrust2014-04-191-22/+33
| | | | | | | | Author: Michael Armbrust <michael@databricks.com> Closes #451 from marmbrus/replCleanup and squashes the following commits: 088526a [Michael Armbrust] REPL cleanup.
* [SPARK-1535] ALS: Avoid the garbage-creating ctor of DoubleMatrixTor Myklebust2014-04-191-2/+11
| | | | | | | | | | | `new DoubleMatrix(double[])` creates a garbage `double[]` of the same length as its argument and immediately throws it away. This pull request avoids that constructor in the ALS code. Author: Tor Myklebust <tmyklebu@gmail.com> Closes #442 from tmyklebu/foo2 and squashes the following commits: 2784fc5 [Tor Myklebust] Mention that this is probably fixed as of jblas 1.2.4; repunctuate. a09904f [Tor Myklebust] Helper function for wrapping Array[Double]'s with DoubleMatrix's.
* Add insertInto and saveAsTable to Python API.Michael Armbrust2014-04-191-0/+13
| | | | | | | | | Author: Michael Armbrust <michael@databricks.com> Closes #447 from marmbrus/pythonInsert and squashes the following commits: c7ab692 [Michael Armbrust] Keep docstrings < 72 chars. ff62870 [Michael Armbrust] Add insertInto and saveAsTable to Python API.
* Use scala deprecation instead of java.Michael Armbrust2014-04-191-1/+1
| | | | | | | | | | This gets rid of a warning when compiling core (since we were depending on a deprecated interface with a non-deprecated function). I also tested with javac, and this does the right thing when compiling java code. Author: Michael Armbrust <michael@databricks.com> Closes #452 from marmbrus/scalaDeprecation and squashes the following commits: f628b4d [Michael Armbrust] Use scala deprecation instead of java.
* README updateReynold Xin2014-04-181-11/+24
| | | | | | | | | Author: Reynold Xin <rxin@apache.org> Closes #443 from rxin/readme and squashes the following commits: 16853de [Reynold Xin] Updated SBT and Scala instructions. 3ac3ceb [Reynold Xin] README update
* SPARK-1482: Fix potential resource leaks in saveAsHadoopDataset and save...zsxwing2014-04-181-12/+18
| | | | | | | | | | | | | | ...AsNewAPIHadoopDataset `writer.close` should be put in the `finally` block to avoid potential resource leaks. JIRA: https://issues.apache.org/jira/browse/SPARK-1482 Author: zsxwing <zsxwing@gmail.com> Closes #400 from zsxwing/SPARK-1482 and squashes the following commits: 06b197a [zsxwing] SPARK-1482: Fix potential resource leaks in saveAsHadoopDataset and saveAsNewAPIHadoopDataset
* SPARK-1456 Remove view bounds on Ordered in favor of a context bound on ↵Michael Armbrust2014-04-185-18/+30
| | | | | | | | | | | | | | | Ordering. This doesn't require creating new Ordering objects per row. Additionally, [view bounds are going to be deprecated](https://issues.scala-lang.org/browse/SI-7629), so we should get rid of them while APIs are still flexible. Author: Michael Armbrust <michael@databricks.com> Closes #410 from marmbrus/viewBounds and squashes the following commits: c574221 [Michael Armbrust] fix example. 812008e [Michael Armbrust] Update Java API. 1b9b85c [Michael Armbrust] Update scala doc. 35798a8 [Michael Armbrust] Remove view bounds on Ordered in favor of a context bound on Ordering.
* Fixed broken pyspark shell.Reynold Xin2014-04-181-2/+2
| | | | | | | | | Author: Reynold Xin <rxin@apache.org> Closes #444 from rxin/pyspark and squashes the following commits: fc11356 [Reynold Xin] Made the PySpark shell version checking compatible with Python 2.6. 571830b [Reynold Xin] Fixed broken pyspark shell.
* SPARK-1523: improve the readability of code in AkkaUtilCodingCat2014-04-181-1/+1
| | | | | | | | | | | | | | | | | | | | | | Actually it is separated from https://github.com/apache/spark/pull/85 as suggested by @rxin compare https://github.com/apache/spark/blob/master/core/src/main/scala/org/apache/spark/util/AkkaUtils.scala#L122 and https://github.com/apache/spark/blob/master/core/src/main/scala/org/apache/spark/util/AkkaUtils.scala#L117 the first one use get and then toLong, the second one getLong....better to make them consistent very very small fix........ Author: CodingCat <zhunansjtu@gmail.com> Closes #434 from CodingCat/SPARK-1523 and squashes the following commits: 0e86f3f [CodingCat] improve the readability of code in AkkaUtil
* SPARK-1357 (addendum). More Experimental items in MLlibSean Owen2014-04-183-0/+10
| | | | | | | | | | | | Per discussion, this is my suggestion to make ALS Rating, ClassificationModel, RegressionModel experimental for now, to reserve the right to possibly change after 1.0. See what you think of this much. Author: Sean Owen <sowen@cloudera.com> Closes #372 from srowen/SPARK-1357Addendum and squashes the following commits: 17cf1ea [Sean Owen] Remove (another) blank line after ":: Experimental ::" 6800e4c [Sean Owen] Remove blank line after ":: Experimental ::" b3a88d2 [Sean Owen] Make ALS Rating, ClassificationModel, RegressionModel experimental for now, to reserve the right to possibly change after 1.0
* [SPARK-1520] remove fastutil from dependenciesXiangrui Meng2014-04-182-2/+9
| | | | | | | | | | | | | | A quick fix for https://issues.apache.org/jira/browse/SPARK-1520 By excluding fastutil, we bring the number of files in the assembly jar back under 65536, so Java 7 won't create the assembly jar in zip64 format, which cannot be read by Java 6. With this change, the assembly jar now has about 60000 entries (58000 files), tested with both sbt and maven. Author: Xiangrui Meng <meng@databricks.com> Closes #437 from mengxr/remove-fastutil and squashes the following commits: 00f9beb [Xiangrui Meng] remove fastutil from dependencies
* Reuses Row object in ExistingRdd.productToRowRdd()Cheng Lian2014-04-181-3/+18
| | | | | | | | | Author: Cheng Lian <lian.cs.zju@gmail.com> Closes #432 from liancheng/reuseRow and squashes the following commits: 9e6d083 [Cheng Lian] Simplified code with BufferedIterator 52acec9 [Cheng Lian] Reuses Row object in ExistingRdd.productToRowRdd()
* SPARK-1483: Rename minSplits to minPartitions in public APIsCodingCat2014-04-188-55/+70
| | | | | | | | | | | | | https://issues.apache.org/jira/browse/SPARK-1483 From the original JIRA: " The parameter name is part of the public API in Scala and Python, since you can pass named parameters to a method, so we should name it to this more descriptive term. Everywhere else we refer to "splits" as partitions." - @mateiz Author: CodingCat <zhunansjtu@gmail.com> Closes #430 from CodingCat/SPARK-1483 and squashes the following commits: 4b60541 [CodingCat] deprecate defaultMinSplits ba2c663 [CodingCat] Rename minSplits to minPartitions in public APIs
* HOTFIX: Ignore streaming UI testPatrick Wendell2014-04-171-1/+2
| | | | | | | | | | | | This is currently causing many builds to hang. https://issues.apache.org/jira/browse/SPARK-1530 Author: Patrick Wendell <pwendell@gmail.com> Closes #440 from pwendell/uitest-fix and squashes the following commits: 9a143dc [Patrick Wendell] Ignore streaming UI test
* FIX: Don't build Hive in assembly unless running Hive tests.Patrick Wendell2014-04-172-8/+9
| | | | | | | | | | This will make the tests more stable when not running SQL tests. Author: Patrick Wendell <pwendell@gmail.com> Closes #439 from pwendell/hive-tests and squashes the following commits: 88a6032 [Patrick Wendell] FIX: Don't build Hive in assembly unless running Hive tests.
* SPARK-1408 Modify Spark on Yarn to point to the history server when app ...Thomas Graves2014-04-173-4/+4
| | | | | | | | | | | | | | | | ...finishes Note this is dependent on https://github.com/apache/spark/pull/204 to have a working history server, but there are no code dependencies. This also fixes SPARK-1288 yarn stable finishApplicationMaster incomplete. Since I was in there I made the diagnostic message be passed properly. Author: Thomas Graves <tgraves@apache.org> Closes #362 from tgravescs/SPARK-1408 and squashes the following commits: ec89705 [Thomas Graves] Fix typo. 446122d [Thomas Graves] Make config yarn specific f5d5373 [Thomas Graves] SPARK-1408 Modify Spark on Yarn to point to the history server when app finishes
* [SPARK-1395] Allow "local:" URIs to work on Yarn.Marcelo Vanzin2014-04-176-79/+142
| | | | | | | | | | | | | This only works for the three paths defined in the environment (SPARK_JAR, SPARK_YARN_APP_JAR and SPARK_LOG4J_CONF). Tested by running SparkPi with local: and file: URIs against Yarn cluster (no "upload" shows up in logs in the local case). Author: Marcelo Vanzin <vanzin@cloudera.com> Closes #303 from vanzin/yarn-local and squashes the following commits: 82219c1 [Marcelo Vanzin] [SPARK-1395] Allow "local:" URIs to work on Yarn.
* [python alternative] pyspark require Python2, failing if system default is ↵AbhishekKr2014-04-161-6/+14
| | | | | | | | | | | | Py3 from shell.py Python alternative for https://github.com/apache/spark/pull/392; managed from shell.py Author: AbhishekKr <abhikumar163@gmail.com> Closes #399 from abhishekkr/pyspark_shell and squashes the following commits: 134bdc9 [AbhishekKr] pyspark require Python2, failing if system default is Py3 from shell.py
* SPARK-1462: Examples of ML algorithms are using deprecated APIsSandeep2014-04-1620-66/+100
| | | | | | | | | | | | This will also fix SPARK-1464: Update MLLib Examples to Use Breeze. Author: Sandeep <sandeep@techaddict.me> Closes #416 from techaddict/1462 and squashes the following commits: a43638e [Sandeep] Some Style Changes 3ce69c3 [Sandeep] Fix Ordering and Naming of Imports in Examples 6c7e543 [Sandeep] SPARK-1462: Examples of ML algorithms are using deprecated APIs
* Include stack trace for exceptions thrown by user code.Michael Armbrust2014-04-161-3/+3
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | It is very confusing when your code throws an exception, but the only stack trace show is in the DAGScheduler. This is a simple patch to include the stack trace for the actual failure in the error message. Suggestions on formatting welcome. Before: ``` scala> sc.parallelize(1 :: Nil).map(_ => sys.error("Ahh!")).collect() org.apache.spark.SparkException: Job aborted due to stage failure: Task 0.0:3 failed 1 times (most recent failure: Exception failure in TID 3 on host localhost: java.lang.RuntimeException: Ahh!) at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1055) at org.apache.spark.scheduler.DAGScheduler$$anonfun$org$apache$spark$scheduler$DAGScheduler$$abortStage$1.apply(DAGScheduler.scala:1039) at org.apache.spark.scheduler.DAGScheduler$$anonfun$org$apache$spark$scheduler$DAGScheduler$$abortStage$1.apply(DAGScheduler.scala:1037) ... ``` After: ``` org.apache.spark.SparkException: Job aborted due to stage failure: Task 0.0:3 failed 1 times, most recent failure: Exception failure in TID 3 on host localhost: java.lang.RuntimeException: Ahh! scala.sys.package$.error(package.scala:27) $iwC$$iwC$$iwC$$iwC$$anonfun$1.apply(<console>:13) $iwC$$iwC$$iwC$$iwC$$anonfun$1.apply(<console>:13) scala.collection.Iterator$$anon$11.next(Iterator.scala:328) scala.collection.Iterator$class.foreach(Iterator.scala:727) scala.collection.AbstractIterator.foreach(Iterator.scala:1157) scala.collection.generic.Growable$class.$plus$plus$eq(Growable.scala:48) scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:103) scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:47) scala.collection.TraversableOnce$class.to(TraversableOnce.scala:273) scala.collection.AbstractIterator.to(Iterator.scala:1157) scala.collection.TraversableOnce$class.toBuffer(TraversableOnce.scala:265) scala.collection.AbstractIterator.toBuffer(Iterator.scala:1157) scala.collection.TraversableOnce$class.toArray(TraversableOnce.scala:252) scala.collection.AbstractIterator.toArray(Iterator.scala:1157) org.apache.spark.rdd.RDD$$anonfun$6.apply(RDD.scala:676) org.apache.spark.rdd.RDD$$anonfun$6.apply(RDD.scala:676) org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:1048) org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:1048) org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:110) org.apache.spark.scheduler.Task.run(Task.scala:50) org.apache.spark.executor.Executor$TaskRunner$$anonfun$run$1.apply$mcV$sp(Executor.scala:211) org.apache.spark.deploy.SparkHadoopUtil.runAsUser(SparkHadoopUtil.scala:46) org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:176) java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145) java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615) java.lang.Thread.run(Thread.java:744) Driver stacktrace: at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1055) at org.apache.spark.scheduler.DAGScheduler$$anonfun$org$apache$spark$scheduler$DAGScheduler$$abortStage$1.apply(DAGScheduler.scala:1039) at org.apache.spark.scheduler.DAGScheduler$$anonfun$org$apache$spark$scheduler$DAGScheduler$$abortStage$1.apply(DAGScheduler.scala:1037) at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59) at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47) at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$abortStage(DAGScheduler.scala:1037) at org.apache.spark.scheduler.DAGScheduler$$anonfun$processEvent$10.apply(DAGScheduler.scala:614) at org.apache.spark.scheduler.DAGScheduler$$anonfun$processEvent$10.apply(DAGScheduler.scala:614) at scala.Option.foreach(Option.scala:236) at org.apache.spark.scheduler.DAGScheduler.processEvent(DAGScheduler.scala:614) at org.apache.spark.scheduler.DAGScheduler$$anonfun$start$1$$anon$2$$anonfun$receive$1.applyOrElse(DAGScheduler.scala:143) at akka.actor.ActorCell.receiveMessage(ActorCell.scala:498) at akka.actor.ActorCell.invoke(ActorCell.scala:456) at akka.dispatch.Mailbox.processMailbox(Mailbox.scala:237) at akka.dispatch.Mailbox.run(Mailbox.scala:219) at akka.dispatch.ForkJoinExecutorConfigurator$AkkaForkJoinTask.exec(AbstractDispatcher.scala:386) at scala.concurrent.forkjoin.ForkJoinTask.doExec(ForkJoinTask.java:260) at scala.concurrent.forkjoin.ForkJoinPool$WorkQueue.runTask(ForkJoinPool.java:1339) at scala.concurrent.forkjoin.ForkJoinPool.runWorker(ForkJoinPool.java:1979) at scala.concurrent.forkjoin.ForkJoinWorkerThread.run(ForkJoinWorkerThread.java:107) ``` Author: Michael Armbrust <michael@databricks.com> Closes #409 from marmbrus/stacktraces and squashes the following commits: 3e4eb65 [Michael Armbrust] indent. include header for driver stack trace. 018b06b [Michael Armbrust] Include stack trace for exceptions in user code.
* Update ReducedWindowedDStream.scalabaishuo(白硕)2014-04-161-1/+1
| | | | | | | | | | change _slideDuration to _windowDuration Author: baishuo(白硕) <vc_java@hotmail.com> Closes #425 from baishuo/master and squashes the following commits: 6f09ea1 [baishuo(白硕)] Update ReducedWindowedDStream.scala
* misleading task number of groupByKeyChen Chao2014-04-161-2/+2
| | | | | | | | | | | | | | | | | | | | | | | | | | "By default, this uses only 8 parallel tasks to do the grouping." is a big misleading. Please refer to https://github.com/apache/spark/pull/389 detail is as following code : def defaultPartitioner(rdd: RDD[_], others: RDD[_]*): Partitioner = { val bySize = (Seq(rdd) ++ others).sortBy(_.partitions.size).reverse for (r <- bySize if r.partitioner.isDefined) { return r.partitioner.get } if (rdd.context.conf.contains("spark.default.parallelism")) { new HashPartitioner(rdd.context.defaultParallelism) } else { new HashPartitioner(bySize.head.partitions.size) } } Author: Chen Chao <crazyjvm@gmail.com> Closes #403 from CrazyJvm/patch-4 and squashes the following commits: 42f6c9e [Chen Chao] fix format 829a995 [Chen Chao] fix format 1568336 [Chen Chao] misleading task number of groupByKey
* Fixing a race condition in event listener unit testKan Zhang2014-04-162-13/+19
| | | | | | | | Author: Kan Zhang <kzhang@apache.org> Closes #401 from kanzhang/fix-1475 and squashes the following commits: c6058bd [Kan Zhang] Fixing a race condition in event listener unit test
* remove unnecessary brace and semicolon in 'putBlockInfo.synchronize' blockChen Chao2014-04-161-7/+4
| | | | | | | | | | | delete semicolon Author: Chen Chao <crazyjvm@gmail.com> Closes #411 from CrazyJvm/patch-5 and squashes the following commits: 72333a3 [Chen Chao] remove unnecessary brace de5d9a7 [Chen Chao] style fix
* SPARK-1329: Create pid2vid with correct number of partitionsAnkur Dave2014-04-162-2/+14
| | | | | | | | | | | | | | Each vertex partition is co-located with a pid2vid array created in RoutingTable.scala. This array maps edge partition IDs to the list of vertices in the current vertex partition that are mentioned by edges in that partition. Therefore the pid2vid array should have one entry per edge partition. GraphX currently creates one entry per *vertex* partition, which is a bug that leads to an ArrayIndexOutOfBoundsException when there are more edge partitions than vertex partitions. This commit fixes the bug and adds a test for this case. Resolves SPARK-1329. Thanks to Daniel Darabos for reporting this bug. Author: Ankur Dave <ankurdave@gmail.com> Closes #368 from ankurdave/fix-pid2vid-size and squashes the following commits: 5a5c52a [Ankur Dave] SPARK-1329: Create pid2vid with correct number of partitions
* Rebuild routing table after Graph.reverseAnkur Dave2014-04-162-1/+11
| | | | | | | | | | | | | | | | GraphImpl.reverse used to reverse edges in each partition of the edge RDD but preserve the routing table and replicated vertex view, since reversing should not affect partitioning. However, the old routing table would then have incorrect information for srcAttrOnly and dstAttrOnly. These RDDs should be switched. A simple fix is for Graph.reverse to rebuild the routing table and replicated vertex view. Thanks to Bogdan Ghidireac for reporting this issue on the [mailing list](http://apache-spark-user-list.1001560.n3.nabble.com/graph-reverse-amp-Pregel-API-td4338.html). Author: Ankur Dave <ankurdave@gmail.com> Closes #431 from ankurdave/fix-reverse-bug and squashes the following commits: 75d63cb [Ankur Dave] Rebuild routing table after Graph.reverse
* Add clean to buildPatrick Wendell2014-04-161-1/+1
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* [SPARK-1511] use Files.move instead of renameTo in TestUtils.scalaYe Xianjin2014-04-161-2/+7
| | | | | | | | | | | | | | | JIRA issue:[SPARK-1511](https://issues.apache.org/jira/browse/SPARK-1511) TestUtils.createCompiledClass method use renameTo() to move files which fails when the src and dest files are in different disks or partitions. This pr uses Files.move() instead. The move method will try to use renameTo() and then fall back to copy() and delete(). I think this should handle this issue. I didn't found a test suite for this file, so I add file existence detection after file moving. Author: Ye Xianjin <advancedxy@gmail.com> Closes #427 from advancedxy/SPARK-1511 and squashes the following commits: a2b97c7 [Ye Xianjin] Based on @srowen's comment, assert file existence. 6f95550 [Ye Xianjin] use Files.move instead of renameTo to handle the src and dest files are in different disks or partitions.
* SPARK-1465: Spark compilation is broken with the latest hadoop-2.4.0 releasexuan2014-04-163-15/+85
| | | | | | | | | | | | | YARN-1824 changes the APIs (addToEnvironment, setEnvFromInputString) in Apps, which causes the spark build to break if built against a version 2.4.0. To fix this, create the spark own function to do that functionality which will not break compiling against 2.3 and other 2.x versions. Author: xuan <xuan@MacBook-Pro.local> Author: xuan <xuan@macbook-pro.home> Closes #396 from xgong/master and squashes the following commits: 42b5984 [xuan] Remove two extra imports bc0926f [xuan] Remove usage of org.apache.hadoop.util.Shell be89fa7 [xuan] fix Spark compilation is broken with the latest hadoop-2.4.0 release
* SPARK-1469: Scheduler mode should accept lower-case definitions and have...Sandeep2014-04-162-3/+8
| | | | | | | | | | | | | | ... nicer error messages There are two improvements to Scheduler Mode: 1. Made the built in ones case insensitive (fair/FAIR, fifo/FIFO). 2. If an invalid mode is given we should print a better error message. Author: Sandeep <sandeep@techaddict.me> Closes #388 from techaddict/1469 and squashes the following commits: a31bbd5 [Sandeep] SPARK-1469: Scheduler mode should accept lower-case definitions and have nicer error messages There are two improvements to Scheduler Mode: 1. Made the built in ones case insensitive (fair/FAIR, fifo/FIFO). 2. If an invalid mode is given we should print a better error message.
* Minor addition to SPARK-1497Patrick Wendell2014-04-161-3/+5
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* SPARK-1497. Fix scalastyle warnings in YARN, Hive codeSean Owen2014-04-166-20/+34
| | | | | | | | | | | | (I wasn't sure how to automatically set `SPARK_YARN=true` and `SPARK_HIVE=true` when running scalastyle, but these are the errors that turn up.) Author: Sean Owen <sowen@cloudera.com> Closes #413 from srowen/SPARK-1497 and squashes the following commits: f0c9318 [Sean Owen] Fix more scalastyle warnings in yarn 80bf4c3 [Sean Owen] Add YARN alpha / YARN profile to scalastyle check 026319c [Sean Owen] Fix scalastyle warnings in YARN, Hive code
* SPARK-1310: Start adding k-fold cross validation to MLLib [adds kFold to ↵Holden Karau2014-04-164-9/+82
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | MLUtils & fixes bug in BernoulliSampler] Author: Holden Karau <holden@pigscanfly.ca> Closes #18 from holdenk/addkfoldcrossvalidation and squashes the following commits: 208db9b [Holden Karau] Fix a bad space e84f2fc [Holden Karau] Fix the test, we should be looking at the second element instead 6ddbf05 [Holden Karau] swap training and validation order 7157ae9 [Holden Karau] CR feedback 90896c7 [Holden Karau] New line 150889c [Holden Karau] Fix up error messages in the MLUtilsSuite 2cb90b3 [Holden Karau] Fix the names in kFold c702a96 [Holden Karau] Fix imports in MLUtils e187e35 [Holden Karau] Move { up to same line as whenExecuting(random) in RandomSamplerSuite.scala c5b723f [Holden Karau] clean up 7ebe4d5 [Holden Karau] CR feedback, remove unecessary learners (came back during merge mistake) and insert an empty line bb5fa56 [Holden Karau] extra line sadness 163c5b1 [Holden Karau] code review feedback 1.to -> 1 to and folds -> numFolds 5a33f1d [Holden Karau] Code review follow up. e8741a7 [Holden Karau] CR feedback b78804e [Holden Karau] Remove cross validation [TODO in another pull request] 91eae64 [Holden Karau] Consolidate things in mlutils 264502a [Holden Karau] Add a test for the bug that was found with BernoulliSampler not copying the complement param dd0b737 [Holden Karau] Wrap long lines (oops) c0b7fa4 [Holden Karau] Switch FoldedRDD to use BernoulliSampler and PartitionwiseSampledRDD 08f8e4d [Holden Karau] Fix BernoulliSampler to respect complement a751ec6 [Holden Karau] Add k-fold cross validation to MLLib
* update spark.default.parallelismChen Chao2014-04-161-1/+7
| | | | | | | | | | | | | | | | | | | | | | actually, the value 8 is only valid in mesos fine-grained mode : <code> override def defaultParallelism() = sc.conf.getInt("spark.default.parallelism", 8) </code> while in coarse-grained model including mesos coares-grained, the value of the property depending on core numbers! <code> override def defaultParallelism(): Int = { conf.getInt("spark.default.parallelism", math.max(totalCoreCount.get(), 2)) } </code> Author: Chen Chao <crazyjvm@gmail.com> Closes #389 from CrazyJvm/patch-2 and squashes the following commits: 84a7fe4 [Chen Chao] miss </li> at the end of every single line 04a9796 [Chen Chao] change format ee0fae0 [Chen Chao] update spark.default.parallelism
* Loads test tables when running "sbt hive/console" without HIVE_DEV_HOMECheng Lian2014-04-161-1/+6
| | | | | | | | | | When running Hive tests, the working directory is `$SPARK_HOME/sql/hive`, while when running `sbt hive/console`, it becomes `$SPARK_HOME`, and test tables are not loaded if `HIVE_DEV_HOME` is not defined. Author: Cheng Lian <lian.cs.zju@gmail.com> Closes #417 from liancheng/loadTestTables and squashes the following commits: 7cea8d6 [Cheng Lian] Loads test tables when running "sbt hive/console" without HIVE_DEV_HOME
* Make "spark logo" link refer to "/".Marcelo Vanzin2014-04-161-1/+1
| | | | | | | | | | | | | | | | | | | | This is not an issue with the driver UI, but when you fire up the history server, there's currently no way to go back to the app listing page without editing the browser's location field (since the logo's link points to the root of the application's own UI - i.e. the "stages" tab). The change just points the logo link to "/", which is the app listing for the history server, and the stages tab for the driver's UI. Tested with both history server and live driver. Author: Marcelo Vanzin <vanzin@cloudera.com> Closes #408 from vanzin/web-ui-root and squashes the following commits: 1b60cb6 [Marcelo Vanzin] Make "spark logo" link refer to "/".
* [SPARK-959] Updated SBT from 0.13.1 to 0.13.2Cheng Lian2014-04-162-3/+1
| | | | | | | | | | | | JIRA issue: [SPARK-959](https://spark-project.atlassian.net/browse/SPARK-959) SBT 0.13.2 has been officially released. This version updated Ivy 2.0 to Ivy 2.3, which fixes [IVY-899](https://issues.apache.org/jira/browse/IVY-899). This PR also removed previous workaround. Author: Cheng Lian <lian.cs.zju@gmail.com> Closes #426 from liancheng/updateSbt and squashes the following commits: 95e3dc8 [Cheng Lian] Updated SBT from 0.13.1 to 0.13.2 to fix SPARK-959
* [SQL] SPARK-1424 Generalize insertIntoTable functions on SchemaRDDsMichael Armbrust2014-04-1516-160/+535
| | | | | | | | | | | | | | | | | This makes it possible to create tables and insert into them using the DSL and SQL for the scala and java apis. Author: Michael Armbrust <michael@databricks.com> Closes #354 from marmbrus/insertIntoTable and squashes the following commits: 6c6f227 [Michael Armbrust] Create random temporary files in python parquet unit tests. f5e6d5c [Michael Armbrust] Merge remote-tracking branch 'origin/master' into insertIntoTable 765c506 [Michael Armbrust] Add to JavaAPI. 77b512c [Michael Armbrust] typos. 5c3ef95 [Michael Armbrust] use names for boolean args. 882afdf [Michael Armbrust] Change createTableAs to saveAsTable. Clean up api annotations. d07d94b [Michael Armbrust] Add tests, support for creating parquet files and hive tables. fa3fe81 [Michael Armbrust] Make insertInto available on JavaSchemaRDD as well. Add createTableAs function.
* [WIP] SPARK-1430: Support sparse data in Python MLlibMatei Zaharia2014-04-1518-214/+1368
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | This PR adds a SparseVector class in PySpark and updates all the regression, classification and clustering algorithms and models to support sparse data, similar to MLlib. I chose to add this class because SciPy is quite difficult to install in many environments (more so than NumPy), but I plan to add support for SciPy sparse vectors later too, and make the methods work transparently on objects of either type. On the Scala side, we keep Python sparse vectors sparse and pass them to MLlib. We always return dense vectors from our models. Some to-do items left: - [x] Support SciPy's scipy.sparse matrix objects when SciPy is available. We can easily add a function to convert these to our own SparseVector. - [x] MLlib currently uses a vector with one extra column on the left to represent what we call LabeledPoint in Scala. Do we really want this? It may get annoying once you deal with sparse data since you must add/subtract 1 to each feature index when training. We can remove this API in 1.0 and use tuples for labeling. - [x] Explain how to use these in the Python MLlib docs. CC @mengxr, @joshrosen Author: Matei Zaharia <matei@databricks.com> Closes #341 from mateiz/py-ml-update and squashes the following commits: d52e763 [Matei Zaharia] Remove no-longer-needed slice code and handle review comments ea5a25a [Matei Zaharia] Fix remaining uses of copyto() after merge b9f97a3 [Matei Zaharia] Fix test 1e1bd0f [Matei Zaharia] Add MLlib logistic regression example in Python 88bc01f [Matei Zaharia] Clean up inheritance of LinearModel in Python, and expose its parametrs 37ab747 [Matei Zaharia] Fix some examples and docs due to changes in MLlib API da0f27e [Matei Zaharia] Added a MLlib K-means example and updated docs to discuss sparse data c48e85a [Matei Zaharia] Added some tests for passing lists as input, and added mllib/tests.py to run-tests script. a07ba10 [Matei Zaharia] Fix some typos and calculation of initial weights 74eefe7 [Matei Zaharia] Added LabeledPoint class in Python 889dde8 [Matei Zaharia] Support scipy.sparse matrices in all our algorithms and models ab244d1 [Matei Zaharia] Allow SparseVectors to be initialized using a dict a5d6426 [Matei Zaharia] Add linalg.py to run-tests script 0e7a3d8 [Matei Zaharia] Keep vectors sparse in Java when reading LabeledPoints eaee759 [Matei Zaharia] Update regression, classification and clustering models for sparse data 2abbb44 [Matei Zaharia] Further work to get linear models working with sparse data 154f45d [Matei Zaharia] Update docs, name some magic values 881fef7 [Matei Zaharia] Added a sparse vector in Python and made Java-Python format more compact
* [FIX] update sbt-idea to version 1.6.0Xiangrui Meng2014-04-151-1/+1
| | | | | | | | | | I saw `No "scala-library*.jar" in Scala compiler library` error in IDEA. It seems upgrading `sbt-idea` to 1.6.0 fixed the problem. Author: Xiangrui Meng <meng@databricks.com> Closes #419 from mengxr/idea-plugin and squashes the following commits: fb3c35f [Xiangrui Meng] update sbt-idea to version 1.6.0
* SPARK-1455: Better isolation for unit tests.Patrick Wendell2014-04-151-7/+25
| | | | | | | | | | | This is a simple first step towards avoiding running the Hive tests whenever possible. Author: Patrick Wendell <pwendell@gmail.com> Closes #420 from pwendell/test-isolation and squashes the following commits: 350c8af [Patrick Wendell] SPARK-1455: Better isolation for unit tests.
* Decision Tree documentation for MLlib programming guideManish Amde2014-04-153-16/+723
| | | | | | | | | | | | | | | | | | | | | | | | | | | | Added documentation for user to use the decision tree algorithms for classification and regression in Spark 1.0 release. Apart from a general review, I need specific input on the following: * I had to move a lot of the existing documentation under the *linear methods* umbrella to accommodate decision trees. I wonder if there is a better way to organize the programming guide given we are so close to the release. * I have not looked closely at pyspark but I am wondering new mllib algorithms are automatically plugged in or do we need to some extra work to call mllib functions from pyspark. I will add to the pyspark examples based upon the advice I get. cc: @mengxr, @hirakendu, @etrain, @atalwalkar Author: Manish Amde <manish9ue@gmail.com> Closes #402 from manishamde/tree_doc and squashes the following commits: 022485a [Manish Amde] more documentation 865826e [Manish Amde] minor: grammar dbb0e5e [Manish Amde] minor improvements to text b9ef6c4 [Manish Amde] basic decision tree code examples 6e297d7 [Manish Amde] added subsections f427e84 [Manish Amde] renaming sections 9c0c4be [Manish Amde] split candidate 6925275 [Manish Amde] impurity and information gain 94fd2f9 [Manish Amde] more reorg b93125c [Manish Amde] more subsection reorg 3ecb2ad [Manish Amde] minor text addition 1537dd3 [Manish Amde] added placeholders and some doc d06511d [Manish Amde] basic skeleton
* [SPARK-1157][MLlib] L-BFGS Optimizer based on Breeze's implementation.DB Tsai2014-04-153-14/+480
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | This PR uses Breeze's L-BFGS implement, and Breeze dependency has already been introduced by Xiangrui's sparse input format work in SPARK-1212. Nice work, @mengxr ! When use with regularized updater, we need compute the regVal and regGradient (the gradient of regularized part in the cost function), and in the currently updater design, we can compute those two values by the following way. Let's review how updater works when returning newWeights given the input parameters. w' = w - thisIterStepSize * (gradient + regGradient(w)) Note that regGradient is function of w! If we set gradient = 0, thisIterStepSize = 1, then regGradient(w) = w - w' As a result, for regVal, it can be computed by val regVal = updater.compute( weights, new DoubleMatrix(initialWeights.length, 1), 0, 1, regParam)._2 and for regGradient, it can be obtained by val regGradient = weights.sub( updater.compute(weights, new DoubleMatrix(initialWeights.length, 1), 1, 1, regParam)._1) The PR includes the tests which compare the result with SGD with/without regularization. We did a comparison between LBFGS and SGD, and often we saw 10x less steps in LBFGS while the cost of per step is the same (just computing the gradient). The following is the paper by Prof. Ng at Stanford comparing different optimizers including LBFGS and SGD. They use them in the context of deep learning, but worth as reference. http://cs.stanford.edu/~jngiam/papers/LeNgiamCoatesLahiriProchnowNg2011.pdf Author: DB Tsai <dbtsai@alpinenow.com> Closes #353 from dbtsai/dbtsai-LBFGS and squashes the following commits: 984b18e [DB Tsai] L-BFGS Optimizer based on Breeze's implementation. Also fixed indentation issue in GradientDescent optimizer.
* SPARK-1501: Ensure assertions in Graph.apply are asserted.William Benton2014-04-151-1/+1
| | | | | | | | | | | | | | | | | | The Graph.apply test in GraphSuite had some assertions in a closure in a graph transformation. As a consequence, these assertions never actually executed. Furthermore, these closures had a reference to (non-serializable) test harness classes because they called assert(), which could be a problem if we proactively check closure serializability in the future. This commit simply changes the Graph.apply test to collect the graph triplets so it can assert about each triplet from a map method. Author: William Benton <willb@redhat.com> Closes #415 from willb/graphsuite-nop-fix and squashes the following commits: 0b63658 [William Benton] Ensure assertions in Graph.apply are asserted.
* SPARK-1426: Make MLlib work with NumPy versions older than 1.7Sandeep2014-04-154-16/+16
| | | | | | | | | | | Currently it requires NumPy 1.7 due to using the copyto method (http://docs.scipy.org/doc/numpy/reference/generated/numpy.copyto.html) for extracting data out of an array. Replace it with a fallback Author: Sandeep <sandeep@techaddict.me> Closes #391 from techaddict/1426 and squashes the following commits: d365962 [Sandeep] SPARK-1426: Make MLlib work with NumPy versions older than 1.7 Currently it requires NumPy 1.7 due to using the copyto method (http://docs.scipy.org/doc/numpy/reference/generated/numpy.copyto.html) for extracting data out of an array. Replace it with a fallback
* SPARK-1374: PySpark API for SparkSQLAhir Reddy2014-04-1517-12/+589
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | An initial API that exposes SparkSQL functionality in PySpark. A PythonRDD composed of dictionaries, with string keys and primitive values (boolean, float, int, long, string) can be converted into a SchemaRDD that supports sql queries. ``` from pyspark.context import SQLContext sqlCtx = SQLContext(sc) rdd = sc.parallelize([{"field1" : 1, "field2" : "row1"}, {"field1" : 2, "field2": "row2"}, {"field1" : 3, "field2": "row3"}]) srdd = sqlCtx.applySchema(rdd) sqlCtx.registerRDDAsTable(srdd, "table1") srdd2 = sqlCtx.sql("SELECT field1 AS f1, field2 as f2 from table1") srdd2.collect() ``` The last line yields ```[{"f1" : 1, "f2" : "row1"}, {"f1" : 2, "f2": "row2"}, {"f1" : 3, "f2": "row3"}]``` Author: Ahir Reddy <ahirreddy@gmail.com> Author: Michael Armbrust <michael@databricks.com> Closes #363 from ahirreddy/pysql and squashes the following commits: 0294497 [Ahir Reddy] Updated log4j properties to supress Hive Warns 307d6e0 [Ahir Reddy] Style fix 6f7b8f6 [Ahir Reddy] Temporary fix MIMA checker. Since we now assemble Spark jar with Hive, we don't want to check the interfaces of all of our hive dependencies 3ef074a [Ahir Reddy] Updated documentation because classes moved to sql.py 29245bf [Ahir Reddy] Cache underlying SchemaRDD instead of generating and caching PythonRDD f2312c7 [Ahir Reddy] Moved everything into sql.py a19afe4 [Ahir Reddy] Doc fixes 6d658ba [Ahir Reddy] Remove the metastore directory created by the HiveContext tests in SparkSQL 521ff6d [Ahir Reddy] Trying to get spark to build with hive ab95eba [Ahir Reddy] Set SPARK_HIVE=true on jenkins ded03e7 [Ahir Reddy] Added doc test for HiveContext 22de1d4 [Ahir Reddy] Fixed maven pyrolite dependency e4da06c [Ahir Reddy] Display message if hive is not built into spark 227a0be [Michael Armbrust] Update API links. Fix Hive example. 58e2aa9 [Michael Armbrust] Build Docs for pyspark SQL Api. Minor fixes. 4285340 [Michael Armbrust] Fix building of Hive API Docs. 38a92b0 [Michael Armbrust] Add note to future non-python developers about python docs. 337b201 [Ahir Reddy] Changed com.clearspring.analytics stream version from 2.4.0 to 2.5.1 to match SBT build, and added pyrolite to maven build 40491c9 [Ahir Reddy] PR Changes + Method Visibility 1836944 [Michael Armbrust] Fix comments. e00980f [Michael Armbrust] First draft of python sql programming guide. b0192d3 [Ahir Reddy] Added Long, Double and Boolean as usable types + unit test f98a422 [Ahir Reddy] HiveContexts 79621cf [Ahir Reddy] cleaning up cruft b406ba0 [Ahir Reddy] doctest formatting 20936a5 [Ahir Reddy] Added tests and documentation e4d21b4 [Ahir Reddy] Added pyrolite dependency 79f739d [Ahir Reddy] added more tests 7515ba0 [Ahir Reddy] added more tests :) d26ec5e [Ahir Reddy] added test e9f5b8d [Ahir Reddy] adding tests 906d180 [Ahir Reddy] added todo explaining cost of creating Row object in python 251f99d [Ahir Reddy] for now only allow dictionaries as input 09b9980 [Ahir Reddy] made jrdd explicitly lazy c608947 [Ahir Reddy] SchemaRDD now has all RDD operations 725c91e [Ahir Reddy] awesome row objects 55d1c76 [Ahir Reddy] return row objects 4fe1319 [Ahir Reddy] output dictionaries correctly be079de [Ahir Reddy] returning dictionaries works cd5f79f [Ahir Reddy] Switched to using Scala SQLContext e948bd9 [Ahir Reddy] yippie 4886052 [Ahir Reddy] even better c0fb1c6 [Ahir Reddy] more working 043ca85 [Ahir Reddy] working 5496f9f [Ahir Reddy] doesn't crash b8b904b [Ahir Reddy] Added schema rdd class 67ba875 [Ahir Reddy] java to python, and python to java bcc0f23 [Ahir Reddy] Java to python ab6025d [Ahir Reddy] compiling
* SPARK-1488. Resolve scalac feature warnings during buildSean Owen2014-04-1449-5/+58
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | For your consideration: scalac currently notes a number of feature warnings during compilation: ``` [warn] there were 65 feature warning(s); re-run with -feature for details ``` Warnings are like: ``` [warn] /Users/srowen/Documents/spark/core/src/main/scala/org/apache/spark/SparkContext.scala:1261: implicit conversion method rddToPairRDDFunctions should be enabled [warn] by making the implicit value scala.language.implicitConversions visible. [warn] This can be achieved by adding the import clause 'import scala.language.implicitConversions' [warn] or by setting the compiler option -language:implicitConversions. [warn] See the Scala docs for value scala.language.implicitConversions for a discussion [warn] why the feature should be explicitly enabled. [warn] implicit def rddToPairRDDFunctions[K: ClassTag, V: ClassTag](rdd: RDD[(K, V)]) = [warn] ^ ``` scalac is suggesting that it's just best practice to explicitly enable certain language features by importing them where used. This PR simply adds the imports it suggests (and squashes one other Java warning along the way). This leaves just deprecation warnings in the build. Author: Sean Owen <sowen@cloudera.com> Closes #404 from srowen/SPARK-1488 and squashes the following commits: 8598980 [Sean Owen] Quiet scalac warnings about language features by explicitly importing language features. 39bc831 [Sean Owen] Enable -feature in scalac to emit language feature warnings
* HOTFIX: Use file name and not paths for excludesPatrick Wendell2014-04-141-2/+2
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* [BUGFIX] In-memory columnar storage bug fixesCheng Lian2014-04-1417-66/+109
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | Fixed several bugs of in-memory columnar storage to make `HiveInMemoryCompatibilitySuite` pass. @rxin @marmbrus It is reasonable to include `HiveInMemoryCompatibilitySuite` in this PR, but I didn't, since it significantly increases test execution time. What do you think? **UPDATE** `HiveCompatibilitySuite` has been made to cache tables in memory. `HiveInMemoryCompatibilitySuite` was removed. Author: Cheng Lian <lian.cs.zju@gmail.com> Author: Michael Armbrust <michael@databricks.com> Closes #374 from liancheng/inMemBugFix and squashes the following commits: 6ad6d9b [Cheng Lian] Merged HiveCompatibilitySuite and HiveInMemoryCompatibilitySuite 5bdbfe7 [Cheng Lian] Revert 882c538 & 8426ddc, which introduced regression 882c538 [Cheng Lian] Remove attributes field from InMemoryColumnarTableScan 32cc9ce [Cheng Lian] Code style cleanup 99382bf [Cheng Lian] Enable compression by default 4390bcc [Cheng Lian] Report error for any Throwable in HiveComparisonTest d1df4fd [Michael Armbrust] Remove test tables that might always get created anyway? ab9e807 [Michael Armbrust] Fix the logged console version of failed test cases to use the new syntax. 1965123 [Michael Armbrust] Don't use coalesce for gathering all data to a single partition, as it does not work correctly with mutable rows. e36cdd0 [Michael Armbrust] Spelling. 2d0e168 [Michael Armbrust] Run Hive tests in-memory too. 6360723 [Cheng Lian] Made PreInsertionCasts support SparkLogicalPlan and InMemoryColumnarTableScan c9b0f6f [Cheng Lian] Let InsertIntoTable support InMemoryColumnarTableScan 9c8fc40 [Cheng Lian] Disable compression by default e619995 [Cheng Lian] Bug fix: incorrect byte order in CompressionScheme.columnHeaderSize 8426ddc [Cheng Lian] Bug fix: InMemoryColumnarTableScan should cache columns specified by the attributes argument 036cd09 [Cheng Lian] Clean up unused imports 44591a5 [Cheng Lian] Bug fix: NullableColumnAccessor.hasNext must take nulls into account 052bf41 [Cheng Lian] Bug fix: should only gather compressibility info for non-null values 95b3301 [Cheng Lian] Fixed bugs in IntegralDelta
* [SPARK-1415] Hadoop min split for wholeTextFiles()Xusen Yin2014-04-136-19/+90
| | | | | | | | | | | | | | | | | | | JIRA issue [here](https://issues.apache.org/jira/browse/SPARK-1415). New Hadoop API of `InputFormat` does not provide the `minSplits` parameter, which makes the API incompatible between `HadoopRDD` and `NewHadoopRDD`. The PR is for constructing compatible APIs. Though `minSplits` is deprecated by New Hadoop API, we think it is better to make APIs compatible here. **Note** that `minSplits` in `wholeTextFiles` could only be treated as a *suggestion*, the real number of splits may not be greater than `minSplits` due to `isSplitable()=false`. Author: Xusen Yin <yinxusen@gmail.com> Closes #376 from yinxusen/hadoop-min-split and squashes the following commits: 76417f6 [Xusen Yin] refine comments c10af60 [Xusen Yin] refine comments and rewrite new class for wholeTextFile 766d05b [Xusen Yin] refine Java API and comments 4875755 [Xusen Yin] add minSplits for WholeTextFiles
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