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Posted to issues@spark.apache.org by "Kai Londenberg (JIRA)" <ji...@apache.org> on 2017/08/31 07:07:00 UTC
[jira] [Comment Edited] (SPARK-18523) OOM killer may leave
SparkContext in broken state causing Connection Refused errors
[ https://issues.apache.org/jira/browse/SPARK-18523?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16148544#comment-16148544 ]
Kai Londenberg edited comment on SPARK-18523 at 8/31/17 7:06 AM:
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In PySpark 2.2.0 this issue was not really fixed for me. While I could close the SparkContext (with an Exception message), I could not reopen any new spark contexts.
If I resetted the global SparkContext variables like this, it worked:
{code:none}
def reset_spark():
import pyspark
from threading import RLock
pyspark.SparkContext._jvm = None
pyspark.SparkContext._gateway = None
pyspark.SparkContext._next_accum_id = 0
pyspark.SparkContext._active_spark_context = None
pyspark.SparkContext._lock = RLock()
pyspark.SparkContext._python_includes = None
reset_spark()
{code}
was (Author: kadeng):
In PySpark 2.2.0 this issue was not really fixed for me. While I could close the SparkContext (with an Exception message), I could not reopen any new spark contexts.
If I resetted the global SparkContext variables like this, it worked:
{code:python}
def reset_spark():
import pyspark
from threading import RLock
pyspark.SparkContext._jvm = None
pyspark.SparkContext._gateway = None
pyspark.SparkContext._next_accum_id = 0
pyspark.SparkContext._active_spark_context = None
pyspark.SparkContext._lock = RLock()
pyspark.SparkContext._python_includes = None
reset_spark()
{code}
> OOM killer may leave SparkContext in broken state causing Connection Refused errors
> -----------------------------------------------------------------------------------
>
> Key: SPARK-18523
> URL: https://issues.apache.org/jira/browse/SPARK-18523
> Project: Spark
> Issue Type: Bug
> Components: PySpark
> Affects Versions: 1.6.1, 2.0.0
> Reporter: Alexander Shorin
> Assignee: Alexander Shorin
> Fix For: 2.1.0
>
>
> When you run some memory-heavy spark job, Spark driver may consume more memory resources than host available to provide.
> In this case OOM killer comes on scene and successfully kills a spark-submit process.
> The pyspark.SparkContext is not able to handle such state of things and becomes completely broken.
> You cannot stop it as on stop it tries to call stop method of bounded java context (jsc) and fails with Py4JError, because such process no longer exists as like as the connection to it.
> You cannot start new SparkContext because you have your broken one as active one and pyspark still is not able to not have SparkContext as sort of singleton.
> The only thing you can do is shutdown your IPython Notebook and start it over. Or dive into SparkContext internal attributes and reset them manually to initial None state.
> The OOM killer case is just one of the many: any reason of spark-submit crash in the middle of something leaves SparkContext in a broken state.
> Example on error log on {{sc.stop()}} in broken state:
> {code}
> ERROR:root:Exception while sending command.
> Traceback (most recent call last):
> File "/usr/local/lib/python2.7/site-packages/py4j/java_gateway.py", line 883, in send_command
> response = connection.send_command(command)
> File "/usr/local/lib/python2.7/site-packages/py4j/java_gateway.py", line 1040, in send_command
> "Error while receiving", e, proto.ERROR_ON_RECEIVE)
> Py4JNetworkError: Error while receiving
> ERROR:py4j.java_gateway:An error occurred while trying to connect to the Java server (127.0.0.1:59911)
> Traceback (most recent call last):
> File "/usr/local/lib/python2.7/site-packages/py4j/java_gateway.py", line 963, in start
> self.socket.connect((self.address, self.port))
> File "/usr/local/lib/python2.7/socket.py", line 224, in meth
> return getattr(self._sock,name)(*args)
> error: [Errno 61] Connection refused
> ---------------------------------------------------------------------------
> Py4JError Traceback (most recent call last)
> <ipython-input-2-f154e069615b> in <module>()
> ----> 1 sc.stop()
> /usr/local/share/spark/python/pyspark/context.py in stop(self)
> 360 """
> 361 if getattr(self, "_jsc", None):
> --> 362 self._jsc.stop()
> 363 self._jsc = None
> 364 if getattr(self, "_accumulatorServer", None):
> /usr/local/lib/python2.7/site-packages/py4j/java_gateway.pyc in __call__(self, *args)
> 1131 answer = self.gateway_client.send_command(command)
> 1132 return_value = get_return_value(
> -> 1133 answer, self.gateway_client, self.target_id, self.name)
> 1134
> 1135 for temp_arg in temp_args:
> /usr/local/share/spark/python/pyspark/sql/utils.py in deco(*a, **kw)
> 43 def deco(*a, **kw):
> 44 try:
> ---> 45 return f(*a, **kw)
> 46 except py4j.protocol.Py4JJavaError as e:
> 47 s = e.java_exception.toString()
> /usr/local/lib/python2.7/site-packages/py4j/protocol.pyc in get_return_value(answer, gateway_client, target_id, name)
> 325 raise Py4JError(
> 326 "An error occurred while calling {0}{1}{2}".
> --> 327 format(target_id, ".", name))
> 328 else:
> 329 type = answer[1]
> Py4JError: An error occurred while calling o47.stop
> {code}
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