Shawn Guo created SPARK-3321: -------------------------------- Summary: Defining a class within python main script Key: SPARK-3321 URL: https://issues.apache.org/jira/browse/SPARK-3321 Project: Spark Issue Type: Bug Components: PySpark Affects Versions: 1.0.1 Environment: Python version 2.6.6 Spark version version 1.0.1 jdk1.6.0_43
Reporter: Shawn Guo Priority: Blocker *leftOuterJoin(self, other, numPartitions=None)* Perform a left outer join of self and other. For each element (k, v) in self, the resulting RDD will either contain all pairs (k, (v, w)) for w in other, or the pair (k, (v, None)) if no elements in other have key k. *Background*: leftOuterJoin will produce None element in result dataset. I define a new class 'Null' in the main script to replace all python native None to new 'Null' object. 'Null' object overload the [] operator. {code:title=Class Null|borderStyle=solid} class Null(object): def __getitem__(self,key): return None; def __getstate__(self): pass; def __setstate__(self, dict): pass; def convert_to_null(x): return Null() if x is None else x X = A.leftOuterJoin(B) X.mapValues(lambda line: (line[0],convert_to_null(line[1])) {code} The code seems running good in pyspark console, however spark-submit failed with below error messages: /spark-1.0.1-bin-hadoop1/bin/spark-submit --master local[2] /tmp/python_test.py {noformat} File "/data/work/spark-1.0.1-bin-hadoop1/python/pyspark/worker.py", line 77, in main serializer.dump_stream(func(split_index, iterator), outfile) File "/data/work/spark-1.0.1-bin-hadoop1/python/pyspark/serializers.py", line 191, in dump_stream self.serializer.dump_stream(self._batched(iterator), stream) File "/data/work/spark-1.0.1-bin-hadoop1/python/pyspark/serializers.py", line 124, in dump_stream self._write_with_length(obj, stream) File "/data/work/spark-1.0.1-bin-hadoop1/python/pyspark/serializers.py", line 134, in _write_with_length serialized = self.dumps(obj) File "/data/work/spark-1.0.1-bin-hadoop1/python/pyspark/serializers.py", line 279, in dumps def dumps(self, obj): return cPickle.dumps(obj, 2) PicklingError: Can't pickle <class '__main__.Null'>: attribute lookup __main__.Null failed org.apache.spark.api.python.PythonRDD$$anon$1.read(PythonRDD.scala:115) org.apache.spark.api.python.PythonRDD$$anon$1.<init>(PythonRDD.scala:145) org.apache.spark.api.python.PythonRDD.compute(PythonRDD.scala:78) org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:262) org.apache.spark.rdd.RDD.iterator(RDD.scala:229) org.apache.spark.rdd.UnionPartition.iterator(UnionRDD.scala:33) org.apache.spark.rdd.UnionRDD.compute(UnionRDD.scala:74) org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:262) org.apache.spark.rdd.RDD.iterator(RDD.scala:229) org.apache.spark.api.python.PythonRDD$WriterThread$$anonfun$run$1.apply$mcV$sp(PythonRDD.scala:200) org.apache.spark.api.python.PythonRDD$WriterThread$$anonfun$run$1.apply(PythonRDD.scala:175) org.apache.spark.api.python.PythonRDD$WriterThread$$anonfun$run$1.apply(PythonRDD.scala:175) org.apache.spark.util.Utils$.logUncaughtExceptions(Utils.scala:1160) org.apache.spark.api.python.PythonRDD$WriterThread.run(PythonRDD.scala:174) Driver stacktrace: at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1044) at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1028) at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1026) at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59) at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47) at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1026) at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:634) at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:634) at scala.Option.foreach(Option.scala:236) at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:634) at org.apache.spark.scheduler.DAGSchedulerEventProcessActor$$anonfun$receive$2.applyOrElse(DAGScheduler.scala:1229) at akka.actor.ActorCell.receiveMessage(ActorCell.scala:498) at akka.actor.ActorCell.invoke(ActorCell.scala:456) at akka.dispatch.Mailbox.processMailbox(Mailbox.scala:237) at akka.dispatch.Mailbox.run(Mailbox.scala:219) at akka.dispatch.ForkJoinExecutorConfigurator$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) {noformat} I do google search a lot and fount it may caused by pickling problem in python pickle module. Please refer to the link below: [Python: defining a class and pickling an instance in the same file|http://stefaanlippens.net/pickleproblem] One workaround is to define the class in another module seperately, and import it in main script, meanwhile add .py file to be distributed with main script by --py-files parameter. /spark-1.0.1-bin-hadoop1/bin/spark-submit *--py-files Null.py* However I'm thinking if it is possible to define the new class in main script by improving the code? -- This message was sent by Atlassian JIRA (v6.2#6252) --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org