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Posted to issues@spark.apache.org by "Hyukjin Kwon (JIRA)" <ji...@apache.org> on 2018/07/04 13:48:00 UTC
[jira] [Commented] (SPARK-24739) PySpark does not work with Python
3.7.0
[ https://issues.apache.org/jira/browse/SPARK-24739?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16532771#comment-16532771 ]
Hyukjin Kwon commented on SPARK-24739:
--------------------------------------
I am working on this.
> PySpark does not work with Python 3.7.0
> ---------------------------------------
>
> Key: SPARK-24739
> URL: https://issues.apache.org/jira/browse/SPARK-24739
> Project: Spark
> Issue Type: Bug
> Components: PySpark
> Affects Versions: 2.1.3, 2.2.2, 2.3.1
> Reporter: Hyukjin Kwon
> Assignee: Hyukjin Kwon
> Priority: Critical
>
> Python 3.7 is released in few days ago and our PySpark does not work. For example
> {code}
> sc.parallelize([1, 2]).take(1)
> {code}
> {code}
> File "/.../spark/python/pyspark/rdd.py", line 1343, in __main__.RDD.take
> Failed example:
> sc.parallelize(range(100), 100).filter(lambda x: x > 90).take(3)
> Exception raised:
> Traceback (most recent call last):
> File "/.../3.7/lib/python3.7/doctest.py", line 1329, in __run
> compileflags, 1), test.globs)
> File "<doctest __main__.RDD.take[2]>", line 1, in <module>
> sc.parallelize(range(100), 100).filter(lambda x: x > 90).take(3)
> File "/.../spark/python/pyspark/rdd.py", line 1377, in take
> res = self.context.runJob(self, takeUpToNumLeft, p)
> File "/.../spark/python/pyspark/context.py", line 1013, in runJob
> sock_info = self._jvm.PythonRDD.runJob(self._jsc.sc(), mappedRDD._jrdd, partitions)
> File "/.../spark/python/lib/py4j-0.10.7-src.zip/py4j/java_gateway.py", line 1257, in __call__
> answer, self.gateway_client, self.target_id, self.name)
> File "/.../spark/python/lib/py4j-0.10.7-src.zip/py4j/protocol.py", line 328, in get_return_value
> format(target_id, ".", name), value)
> py4j.protocol.Py4JJavaError: An error occurred while calling z:org.apache.spark.api.python.PythonRDD.runJob.
> : org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 143.0 failed 1 times, most recent failure: Lost task 0.0 in stage 143.0 (TID 688, localhost, executor driver): org.apache.spark.api.python.PythonException: Traceback (most recent call last):
> File "/.../spark/python/pyspark/rdd.py", line 1373, in takeUpToNumLeft
> yield next(iterator)
> StopIteration
> The above exception was the direct cause of the following exception:
> Traceback (most recent call last):
> File "/.../spark/python/lib/pyspark.zip/pyspark/worker.py", line 320, in main
> process()
> File "/.../spark/python/lib/pyspark.zip/pyspark/worker.py", line 315, in process
> serializer.dump_stream(func(split_index, iterator), outfile)
> File "/.../spark/python/lib/pyspark.zip/pyspark/serializers.py", line 378, in dump_stream
> vs = list(itertools.islice(iterator, batch))
> RuntimeError: generator raised StopIteration
> at org.apache.spark.api.python.BasePythonRunner$ReaderIterator.handlePythonException(PythonRunner.scala:309)
> at org.apache.spark.api.python.PythonRunner$$anon$1.read(PythonRunner.scala:449)
> at org.apache.spark.api.python.PythonRunner$$anon$1.read(PythonRunner.scala:432)
> at org.apache.spark.api.python.BasePythonRunner$ReaderIterator.hasNext(PythonRunner.scala:263)
> at org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:37)
> at scala.collection.Iterator$class.foreach(Iterator.scala:891)
> at org.apache.spark.InterruptibleIterator.foreach(InterruptibleIterator.scala:28)
> at scala.collection.generic.Growable$class.$plus$plus$eq(Growable.scala:59)
> at scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:104)
> at scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:48)
> at scala.collection.TraversableOnce$class.to(TraversableOnce.scala:310)
> at org.apache.spark.InterruptibleIterator.to(InterruptibleIterator.scala:28)
> at scala.collection.TraversableOnce$class.toBuffer(TraversableOnce.scala:302)
> at org.apache.spark.InterruptibleIterator.toBuffer(InterruptibleIterator.scala:28)
> at scala.collection.TraversableOnce$class.toArray(TraversableOnce.scala:289)
> at org.apache.spark.InterruptibleIterator.toArray(InterruptibleIterator.scala:28)
> at org.apache.spark.api.python.PythonRDD$$anonfun$3.apply(PythonRDD.scala:149)
> at org.apache.spark.api.python.PythonRDD$$anonfun$3.apply(PythonRDD.scala:149)
> at org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:2071)
> at org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:2071)
> at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:87)
> at org.apache.spark.scheduler.Task.run(Task.scala:109)
> at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:367)
> at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
> at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
> at java.lang.Thread.run(Thread.java:748)
> Driver stacktrace:
> at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1607)
> at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1595)
> at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1594)
> at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
> at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48)
> at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1594)
> at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:831)
> at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:831)
> at scala.Option.foreach(Option.scala:257)
> at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:831)
> at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:1828)
> at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1777)
> at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1766)
> at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:49)
> at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:642)
> at org.apache.spark.SparkContext.runJob(SparkContext.scala:2031)
> at org.apache.spark.SparkContext.runJob(SparkContext.scala:2052)
> at org.apache.spark.SparkContext.runJob(SparkContext.scala:2071)
> at org.apache.spark.api.python.PythonRDD$.runJob(PythonRDD.scala:149)
> at org.apache.spark.api.python.PythonRDD.runJob(PythonRDD.scala)
> at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
> at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
> at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
> at java.lang.reflect.Method.invoke(Method.java:498)
> at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:244)
> at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357)
> at py4j.Gateway.invoke(Gateway.java:282)
> at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132)
> at py4j.commands.CallCommand.execute(CallCommand.java:79)
> at py4j.GatewayConnection.run(GatewayConnection.java:238)
> at java.lang.Thread.run(Thread.java:748)
> Caused by: org.apache.spark.api.python.PythonException: Traceback (most recent call last):
> File "/.../spark/python/pyspark/rdd.py", line 1373, in takeUpToNumLeft
> yield next(iterator)
> StopIteration
> The above exception was the direct cause of the following exception:
> Traceback (most recent call last):
> File "/.../spark/python/lib/pyspark.zip/pyspark/worker.py", line 320, in main
> process()
> File "/.../spark/python/lib/pyspark.zip/pyspark/worker.py", line 315, in process
> serializer.dump_stream(func(split_index, iterator), outfile)
> File "/.../spark/python/lib/pyspark.zip/pyspark/serializers.py", line 378, in dump_stream
> vs = list(itertools.islice(iterator, batch))
> RuntimeError: generator raised StopIteration
> at org.apache.spark.api.python.BasePythonRunner$ReaderIterator.handlePythonException(PythonRunner.scala:309)
> at org.apache.spark.api.python.PythonRunner$$anon$1.read(PythonRunner.scala:449)
> at org.apache.spark.api.python.PythonRunner$$anon$1.read(PythonRunner.scala:432)
> at org.apache.spark.api.python.BasePythonRunner$ReaderIterator.hasNext(PythonRunner.scala:263)
> at org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:37)
> at scala.collection.Iterator$class.foreach(Iterator.scala:891)
> at org.apache.spark.InterruptibleIterator.foreach(InterruptibleIterator.scala:28)
> at scala.collection.generic.Growable$class.$plus$plus$eq(Growable.scala:59)
> at scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:104)
> at scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:48)
> at scala.collection.TraversableOnce$class.to(TraversableOnce.scala:310)
> at org.apache.spark.InterruptibleIterator.to(InterruptibleIterator.scala:28)
> at scala.collection.TraversableOnce$class.toBuffer(TraversableOnce.scala:302)
> at org.apache.spark.InterruptibleIterator.toBuffer(InterruptibleIterator.scala:28)
> at scala.collection.TraversableOnce$class.toArray(TraversableOnce.scala:289)
> at org.apache.spark.InterruptibleIterator.toArray(InterruptibleIterator.scala:28)
> at org.apache.spark.api.python.PythonRDD$$anonfun$3.apply(PythonRDD.scala:149)
> at org.apache.spark.api.python.PythonRDD$$anonfun$3.apply(PythonRDD.scala:149)
> at org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:2071)
> at org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:2071)
> at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:87)
> at org.apache.spark.scheduler.Task.run(Task.scala:109)
> at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:367)
> at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
> at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
> ... 1 more
> {code}
> Should check the behaviour changes or bugs in Python and PySpark.
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