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https://issues.apache.org/jira/browse/SPARK-13330?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15996217#comment-15996217
]
Al Johri commented on SPARK-13330:
----------------------------------
Can this be backported to 2.0 or 2.1? I'm having trouble using Python 3 on
spark at the moment. Currently I have to set
`SPARK_YARN_USER_ENV=PYTHONHASHSEED=0` before running spark-submit. Until 2.2
is released, would it be best practice to put this variable into spark-env.sh?
> PYTHONHASHSEED is not propgated to python worker
> ------------------------------------------------
>
> Key: SPARK-13330
> URL: https://issues.apache.org/jira/browse/SPARK-13330
> Project: Spark
> Issue Type: Bug
> Components: PySpark
> Affects Versions: 1.6.0
> Reporter: Jeff Zhang
> Assignee: Jeff Zhang
> Fix For: 2.2.0
>
>
> when using python 3.3 , PYTHONHASHSEED is only set in driver, but not
> propagated to executor, and cause the following error.
> {noformat}
> File "/Users/jzhang/github/spark/python/pyspark/rdd.py", line 74, in
> portable_hash
> raise Exception("Randomness of hash of string should be disabled via
> PYTHONHASHSEED")
> Exception: Randomness of hash of string should be disabled via PYTHONHASHSEED
> at
> org.apache.spark.api.python.PythonRunner$$anon$1.read(PythonRDD.scala:166)
> at
> org.apache.spark.api.python.PythonRunner$$anon$1.<init>(PythonRDD.scala:207)
> at org.apache.spark.api.python.PythonRunner.compute(PythonRDD.scala:125)
> at org.apache.spark.api.python.PythonRDD.compute(PythonRDD.scala:70)
> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:313)
> at org.apache.spark.rdd.RDD.iterator(RDD.scala:277)
> at org.apache.spark.api.python.PairwiseRDD.compute(PythonRDD.scala:342)
> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:313)
> at org.apache.spark.rdd.RDD.iterator(RDD.scala:277)
> at
> org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:77)
> at
> org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:45)
> at org.apache.spark.scheduler.Task.run(Task.scala:81)
> at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:214)
> at
> java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
> {noformat}
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