Details
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Bug
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Status: Resolved
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Major
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Resolution: Duplicate
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2.2.0
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None
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None
Description
This is a duplicate of SPARK-18523, which was not really fixed for me (PySpark 2.2.0, Python 3.5, py4j 0.10.4 )
Original Summary:
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.
Latest Comment
In PySpark 2.2.0 this issue was not really fixed. While I could close the SparkContext (with an Exception message, but it was closed afterwards), I could not reopen any new spark contexts.
Current Workaround
If I resetted the global SparkContext variables like this, it worked :
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()
Attachments
Issue Links
- duplicates
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- Resolved
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- is a clone of
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- Resolved
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- is duplicated by
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- Resolved
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