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https://issues.apache.org/jira/browse/SPARK-26381?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16724750#comment-16724750
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Hyukjin Kwon commented on SPARK-26381:
--------------------------------------
[~ryan.clancy], please provide the codes to reproduce.
> Pickle Serialization Error Causing Crash
> ----------------------------------------
>
> Key: SPARK-26381
> URL: https://issues.apache.org/jira/browse/SPARK-26381
> Project: Spark
> Issue Type: Bug
> Components: PySpark
> Affects Versions: 2.3.1, 2.4.0
> Environment: Tested on two environments:
> * Spark 2.4.0 - single machine only
> * Spark 2.3.1 - YARN installation with 5 nodes and files on HDFS
> The error occurs in both environments.
> Reporter: Ryan
> Priority: Major
>
> There is a pickle serialization error when I try and use AllenNLP for doing
> NER within a Spark worker - it is causing a crash. When running on just the
> Spark driver or in a standalone program, everything works as expected.
>
> {code:java}
> Caused by: org.apache.spark.api.python.PythonException: Traceback (most
> recent call last):
> File
> "/data/disk12/yarn/local/usercache/raclancy/appcache/application_1543437939000_1040/container_1543437939000_1040_01_000002/pyspark.zip/pyspark/worker.py",
> line 217, in main
> func, profiler, deserializer, serializer = read_command(pickleSer, infile)
> File
> "/data/disk12/yarn/local/usercache/raclancy/appcache/application_1543437939000_1040/container_1543437939000_1040_01_000002/pyspark.zip/pyspark/worker.py",
> line 61, in read_command
> command = serializer.loads(command.value)
> File
> "/data/disk12/yarn/local/usercache/raclancy/appcache/application_1543437939000_1040/container_1543437939000_1040_01_000002/pyspark.zip/pyspark/serializers.py",
> line 559, in loads
> return pickle.loads(obj, encoding=encoding)
> TypeError: __init__() missing 3 required positional arguments:
> 'non_padded_namespaces', 'padding_token', and 'oov_token'
> at
> org.apache.spark.api.python.BasePythonRunner$ReaderIterator.handlePythonException(PythonRunner.scala:298)
>
> at
> org.apache.spark.api.python.PythonRunner$$anon$1.read(PythonRunner.scala:438)
> at
> org.apache.spark.api.python.PythonRunner$$anon$1.read(PythonRunner.scala:421)
> at
> org.apache.spark.api.python.BasePythonRunner$ReaderIterator.hasNext(PythonRunner.scala:252)
>
> at
> org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:37)
>
> at scala.collection.Iterator$class.foreach(Iterator.scala:893)
> at
> org.apache.spark.InterruptibleIterator.foreach(InterruptibleIterator.scala:28)
>
> at
> scala.collection.generic.Growable$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.rdd.RDD$$anonfun$collect$1$$anonfun$12.apply(RDD.scala:939)
> at
> org.apache.spark.rdd.RDD$$anonfun$collect$1$$anonfun$12.apply(RDD.scala:939)
> at
> org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:2074)
>
> at
> org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:2074)
>
> at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:87)
> at org.apache.spark.scheduler.Task.run(Task.scala:109)
> at
> org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:345)
> at
> java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
>
> at
> java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
>
> ... 1 more
> {code}
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