You are viewing a plain text version of this content. The canonical link for it is here.
Posted to issues@spark.apache.org by "Michael Armbrust (JIRA)" <ji...@apache.org> on 2014/09/04 04:10:51 UTC
[jira] [Resolved] (SPARK-3335) [Spark SQL] In pyspark, cannot use
broadcast variables in UDF
[ https://issues.apache.org/jira/browse/SPARK-3335?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Michael Armbrust resolved SPARK-3335.
-------------------------------------
Resolution: Fixed
Fix Version/s: 1.2.0
> [Spark SQL] In pyspark, cannot use broadcast variables in UDF
> --------------------------------------------------------------
>
> Key: SPARK-3335
> URL: https://issues.apache.org/jira/browse/SPARK-3335
> Project: Spark
> Issue Type: Bug
> Components: PySpark, SQL
> Affects Versions: 1.1.0
> Reporter: kay feng
> Assignee: Davies Liu
> Fix For: 1.2.0
>
>
> Running pyspark on a spark cluster with standalone master, spark sql cannot use broadcast variables in UDF. But we can use broadcast variable in spark in scala.
> For example,
> bar={"a":"aa", "b":"bb", "c":"abc"}
> foo=sc.broadcast(bar)
> sqlContext.registerFunction("MYUDF", lambda x: foo.value[x] if x else '').
> q= sqlContext.sql('SELECT MYUDF(c) FROM foobar')
> out = q.collect()
> Got the following exception:
> Py4JJavaError: An error occurred while calling o169.collect.
> : org.apache.spark.SparkException: Job aborted due to stage failure: Task 4 in stage 51.0 failed 4 times, most recent failure: Lost task 4.3 in stage 51.0 (TID 13040, ip-10-33-9-144.us-west-2.compute.internal): org.apache.spark.api.python.PythonException: Traceback (most recent call last):
> File "/root/spark/python/pyspark/worker.py", line 75, in main
> command = pickleSer._read_with_length(infile)
> File "/root/spark/python/pyspark/serializers.py", line 150, in _read_with_length
> return self.loads(obj)
> File "/root/spark/python/pyspark/broadcast.py", line 41, in _from_id
> raise Exception("Broadcast variable '%s' not loaded!" % bid)
> Exception: (Exception("Broadcast variable '21' not loaded!",), <function _from_id at 0x35042a8>, (21L,))
> org.apache.spark.api.python.PythonRDD$$anon$1.read(PythonRDD.scala:124)
> org.apache.spark.api.python.PythonRDD$$anon$1.<init>(PythonRDD.scala:154)
> org.apache.spark.api.python.PythonRDD.compute(PythonRDD.scala:87)
> org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:262)
> org.apache.spark.rdd.RDD.iterator(RDD.scala:229)
> org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:35)
> org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:262)
> org.apache.spark.rdd.RDD.iterator(RDD.scala:229)
> org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:35)
> org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:262)
> org.apache.spark.rdd.RDD.iterator(RDD.scala:229)
> org.apache.spark.rdd.ZippedPartitionsRDD2.compute(ZippedPartitionsRDD.scala:87)
> org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:262)
> org.apache.spark.rdd.RDD.iterator(RDD.scala:229)
> org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:35)
> org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:262)
> org.apache.spark.rdd.RDD.iterator(RDD.scala:229)
> org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:35)
> org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:262)
> org.apache.spark.rdd.RDD.iterator(RDD.scala:229)
> org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:35)
> org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:262)
> org.apache.spark.rdd.RDD.iterator(RDD.scala:229)
> org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:68)
> org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:41)
> org.apache.spark.scheduler.Task.run(Task.scala:54)
> org.apache.spark.executor.Executor$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)
>
--
This message was sent by Atlassian JIRA
(v6.3.4#6332)
---------------------------------------------------------------------
To unsubscribe, e-mail: issues-unsubscribe@spark.apache.org
For additional commands, e-mail: issues-help@spark.apache.org