[ https://issues.apache.org/jira/browse/SPARK-3336?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Reynold Xin updated SPARK-3336: ------------------------------- Description: 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$$anonfun$receive$2.applyOrElse(DAGScheduler.scala:1391) at akka.actor.ActorCell.receiveMessage(ActorCell.scala:498) at akka.actor.ActorCell.invoke(ActorCell.scala:456) at akka.dispatch.Mailbox.processMailbox(Mailbox.scala:237) at akka.dispatch.Mailbox.run(Mailbox.scala:219) at akka.dispatch.ForkJoinExecutorConfigurator$AkkaForkJoinTask.exec(AbstractDispatcher.scala:386) at scala.concurrent.forkjoin.ForkJoinTask.doExec(ForkJoinTask.java:260) at scala.concurrent.forkjoin.ForkJoinPool$WorkQueue.runTask(ForkJoinPool.java:1339) at scala.concurrent.forkjoin.ForkJoinPool.runWorker(ForkJoinPool.java:1979) at scala.concurrent.forkjoin.ForkJoinWorkerThread.run(ForkJoinWorkerThread.java:107) {code} was: Running pyspark on a spark cluster with standalone master. Cannot group by field on a UDF. But we can group by UDF in Scala. For example: q = sqlContext.sql('SELECT COUNT(*), MYUDF(foo) FROM bar GROUP BY MYUDF(foo)') out = q.collect() I got this exception: Py4JJavaError: An error occurred while calling o183.collect. : org.apache.spark.SparkException: Job aborted due to stage failure: Task 26 in stage 56.0 failed 4 times, most recent failure: Lost task 26.3 in stage 56.0 (TID 14038, ip-10-33-9-144.us-west-2.compute.internal): org.apache.spark.sql.catalyst.errors.package$TreeNodeException: Binding attribute, tree: pythonUDF#1278 org.apache.spark.sql.catalyst.errors.package$.attachTree(package.scala:47) org.apache.spark.sql.catalyst.expressions.BindReferences$$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$WorkQueue.runTask(ForkJoinPool.java:1339) at scala.concurrent.forkjoin.ForkJoinPool.runWorker(ForkJoinPool.java:1979) at scala.concurrent.forkjoin.ForkJoinWorkerThread.run(ForkJoinWorkerThread.java:107) > [Spark SQL] In pyspark, cannot group by field on UDF > ---------------------------------------------------- > > Key: SPARK-3336 > URL: https://issues.apache.org/jira/browse/SPARK-3336 > Project: Spark > Issue Type: Bug > Components: PySpark, SQL > Affects Versions: 1.1.0 > Reporter: kay feng > Assignee: Davies Liu > > Running pyspark on a spark cluster with standalone master. > Cannot group by field on a UDF. But we can group by UDF in Scala. > For example: > q = sqlContext.sql('SELECT COUNT(*), MYUDF(foo) FROM bar GROUP BY > MYUDF(foo)') > out = q.collect() > I got this exception: > {code} > Py4JJavaError: An error occurred while calling o183.collect. > : org.apache.spark.SparkException: Job aborted due to stage failure: Task 26 > in stage 56.0 failed 4 times, most recent failure: Lost task 26.3 in stage > 56.0 (TID 14038, ip-10-33-9-144.us-west-2.compute.internal): > org.apache.spark.sql.catalyst.errors.package$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} -- This message was sent by Atlassian JIRA (v6.3.4#6332) --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org