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From "Apache Spark (JIRA)" <j...@apache.org>
Subject [jira] [Assigned] (SPARK-21045) Spark executor blocked instead of throwing exception because exception occur when python worker send exception info to Java Gateway
Date Sat, 10 Jun 2017 16:06:19 GMT

     [ https://issues.apache.org/jira/browse/SPARK-21045?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]

Apache Spark reassigned SPARK-21045:
------------------------------------

    Assignee:     (was: Apache Spark)

> Spark executor blocked instead of throwing exception because exception occur when python
worker send exception info to Java Gateway
> -----------------------------------------------------------------------------------------------------------------------------------
>
>                 Key: SPARK-21045
>                 URL: https://issues.apache.org/jira/browse/SPARK-21045
>             Project: Spark
>          Issue Type: Bug
>          Components: PySpark
>    Affects Versions: 2.0.1, 2.0.2, 2.1.1
>            Reporter: Joshuawangzj
>
> My pyspark program is always blocking in product yarn cluster. Then I jstack and found
:
> {code}
> "Executor task launch worker for task 0" #60 daemon prio=5 os_prio=31 tid=0x00007fb2f44e3000
nid=0xa003 runnable [0x0000000123b4a000]
>    java.lang.Thread.State: RUNNABLE
>         at java.net.SocketInputStream.socketRead0(Native Method)
>         at java.net.SocketInputStream.socketRead(SocketInputStream.java:116)
>         at java.net.SocketInputStream.read(SocketInputStream.java:170)
>         at java.net.SocketInputStream.read(SocketInputStream.java:141)
>         at java.io.BufferedInputStream.fill(BufferedInputStream.java:246)
>         at java.io.BufferedInputStream.read(BufferedInputStream.java:265)
>         - locked <0x00000007acab1c98> (a java.io.BufferedInputStream)
>         at java.io.DataInputStream.readInt(DataInputStream.java:387)
>         at org.apache.spark.api.python.PythonRunner$$anon$1.read(PythonRDD.scala:190)
>         at org.apache.spark.api.python.PythonRunner$$anon$1.<init>(PythonRDD.scala:234)
>         at org.apache.spark.api.python.PythonRunner.compute(PythonRDD.scala:152)
>         at org.apache.spark.api.python.PythonRDD.compute(PythonRDD.scala:63)
>         at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
>         at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
>         at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:87)
>         at org.apache.spark.scheduler.Task.run(Task.scala:99)
>         at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:322)
>         at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
>         at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
>         at java.lang.Thread.run(Thread.java:745)
> {code}
> It is blocking in socket read.  I view the log on blocking executor and found error:
> {code}
> Traceback (most recent call last):
>   File "/opt/spark/python/lib/pyspark.zip/pyspark/worker.py", line 178, in main
>     write_with_length(traceback.format_exc().encode("utf-8"), outfile)
> UnicodeDecodeError: 'ascii' codec can't decode byte 0xe4 in position 618: ordinal not
in range(128)
> {code}
> Finally I found the problem:
> {code:title=worker.py|borderStyle=solid}
>     # 178 line in spark 2.1.1
>     except Exception:
>         try:
>             write_int(SpecialLengths.PYTHON_EXCEPTION_THROWN, outfile)
>             write_with_length(traceback.format_exc().encode("utf-8"), outfile)
>         except IOError:
>             # JVM close the socket
>             pass
>         except Exception:
>             # Write the error to stderr if it happened while serializing
>             print("PySpark worker failed with exception:", file=sys.stderr)
>             print(traceback.format_exc(), file=sys.stderr)
> {code}
> when write_with_length(traceback.format_exc().encode("utf-8"), outfile) occur exception
like UnicodeDecodeError, the python worker can't send the trace info, but when the PythonRDD
get PYTHON_EXCEPTION_THROWN, It should read the trace info length next. So it is blocking.
> {code:title=PythonRDD.scala|borderStyle=solid}
>     # 190 line in spark 2.1.1
>     case SpecialLengths.PYTHON_EXCEPTION_THROWN =>
>      // Signals that an exception has been thrown in python
>      val exLength = stream.readInt()  // It is possible to be blocked
> {code}
> {color:red}
> We can triggle the bug use simple program:
> {color}
> {code:title=test.py|borderStyle=solid}
>     spark = SparkSession.builder.master('local').getOrCreate()
>     rdd = spark.sparkContext.parallelize(['δΈ­']).map(lambda x: x.encode("utf8"))
>     rdd.collect()
> {code}



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