Understanding spark.executor.memoryOverhead

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Understanding spark.executor.memoryOverhead

Akash Mishra
Hi *, 

I would like to know what part of spark codebase uses spark.executor.memoryOverhead? I have a job which has spark.executor.memory=18g but it requires spark.executor.memoryOverhead=4g for the same process otherwise I get task error, 

ExecutorLostFailure (executor 28 exited caused by one of the running tasks) Reason: Container killed by YARN for exceeding memory limits. 23.7 GB of 22 GB physical memory used. Consider boosting spark.yarn.executor.memoryOverhead.

There is only 1 task running on this executor and JVM Heap usage is around 14 GB. I am not able to understand that what exactly is using 5.7 GB of memory other than Java? 

Is it netty for block read or something else?


Akash Mishra.

"It's not our abilities that make us, but our decisions."--Albus Dumbledore