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Posted to issues@spark.apache.org by "Davies Liu (JIRA)" <ji...@apache.org> on 2014/10/09 00:09:33 UTC
[jira] [Resolved] (SPARK-3336) [Spark SQL] In pyspark, cannot group
by field on UDF
[ https://issues.apache.org/jira/browse/SPARK-3336?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Davies Liu resolved SPARK-3336.
-------------------------------
Resolution: Duplicate
duplicated to https://issues.apache.org/jira/browse/SPARK-3855
> [Spark SQL] In pyspark, cannot group by field on UDF
> ----------------------------------------------------
>
> Key: SPARK-3336
> URL: https://issues.apache.org/jira/browse/SPARK-3336
> Project: Spark
> Issue Type: Bug
> Components: PySpark, SQL
> Affects Versions: 1.1.0
> Reporter: kay feng
> Assignee: Davies Liu
>
> Running pyspark on a spark cluster with standalone master.
> Cannot group by field on a UDF. But we can group by UDF in Scala.
> For example:
> q = sqlContext.sql('SELECT COUNT(*), MYUDF(foo) FROM bar GROUP BY MYUDF(foo)')
> out = q.collect()
> I got this exception:
> {code}
> Py4JJavaError: An error occurred while calling o183.collect.
> : org.apache.spark.SparkException: Job aborted due to stage failure: Task 26 in stage 56.0 failed 4 times, most recent failure: Lost task 26.3 in stage 56.0 (TID 14038, ip-10-33-9-144.us-west-2.compute.internal): org.apache.spark.sql.catalyst.errors.package$TreeNodeException: Binding attribute, tree: pythonUDF#1278
> org.apache.spark.sql.catalyst.errors.package$.attachTree(package.scala:47)
> org.apache.spark.sql.catalyst.expressions.BindReferences$$anonfun$bindReference$1.applyOrElse(BoundAttribute.scala:43)
> org.apache.spark.sql.catalyst.expressions.BindReferences$$anonfun$bindReference$1.applyOrElse(BoundAttribute.scala:42)
> org.apache.spark.sql.catalyst.trees.TreeNode.transformDown(TreeNode.scala:165)
> org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$4.apply(TreeNode.scala:183)
> scala.collection.Iterator$$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$class.toArray(TraversableOnce.scala:252)
> scala.collection.AbstractIterator.toArray(Iterator.scala:1157)
> org.apache.spark.sql.catalyst.trees.TreeNode.transformChildrenDown(TreeNode.scala:212)
> org.apache.spark.sql.catalyst.trees.TreeNode.transformDown(TreeNode.scala:168)
> org.apache.spark.sql.catalyst.trees.TreeNode.transform(TreeNode.scala:156)
> org.apache.spark.sql.catalyst.expressions.BindReferences$.bindReference(BoundAttribute.scala:42)
> org.apache.spark.sql.catalyst.expressions.InterpretedMutableProjection$$anonfun$$init$$2.apply(Projection.scala:52)
> org.apache.spark.sql.catalyst.expressions.InterpretedMutableProjection$$anonfun$$init$$2.apply(Projection.scala:52)
> scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:244)
> scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:244)
> scala.collection.immutable.List.foreach(List.scala:318)
> scala.collection.TraversableLike$class.map(TraversableLike.scala:244)
> scala.collection.AbstractTraversable.map(Traversable.scala:105)
> org.apache.spark.sql.catalyst.expressions.InterpretedMutableProjection.<init>(Projection.scala:52)
> org.apache.spark.sql.execution.Aggregate$$anonfun$execute$1$$anonfun$7$$anon$1.<init>(Aggregate.scala:176)
> org.apache.spark.sql.execution.Aggregate$$anonfun$execute$1$$anonfun$7.apply(Aggregate.scala:172)
> org.apache.spark.sql.execution.Aggregate$$anonfun$execute$1$$anonfun$7.apply(Aggregate.scala:151)
> org.apache.spark.rdd.RDD$$anonfun$13.apply(RDD.scala:596)
> org.apache.spark.rdd.RDD$$anonfun$13.apply(RDD.scala:596)
> org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:35)
> org.apache.spark.sql.SchemaRDD.compute(SchemaRDD.scala:115)
> org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:262)
> org.apache.spark.rdd.RDD.iterator(RDD.scala:229)
> org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:35)
> org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:262)
> org.apache.spark.rdd.RDD.iterator(RDD.scala:229)
> org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:62)
> org.apache.spark.scheduler.Task.run(Task.scala:54)
> org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:177)
> java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
> java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
> java.lang.Thread.run(Thread.java:745)
> Driver stacktrace:
> at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1185)
> at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1174)
> at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1173)
> at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
> at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47)
> at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1173)
> at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:688)
> at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:688)
> at scala.Option.foreach(Option.scala:236)
> at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:688)
> at org.apache.spark.scheduler.DAGSchedulerEventProcessActor$$anonfun$receive$2.applyOrElse(DAGScheduler.scala:1391)
> at akka.actor.ActorCell.receiveMessage(ActorCell.scala:498)
> at akka.actor.ActorCell.invoke(ActorCell.scala:456)
> at akka.dispatch.Mailbox.processMailbox(Mailbox.scala:237)
> at akka.dispatch.Mailbox.run(Mailbox.scala:219)
> at akka.dispatch.ForkJoinExecutorConfigurator$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)
> {code}
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