We are running Spark 2.3 on a Kubernetes cluster. We have set the following
spark configuration options
"spark.executor.memory": "7g",
"spark.driver.memory": "2g",
"spark.memory.fraction": "0.75"
WHat we see is
a) In the SPark UI, 5G has been allocated to each executor, which makes
sense because we set spark.memory.fraction=0.75
b) Kubernetes reports the pod memory usage as 7.6G
WHen we run a lot of jobs on the Kubernetes cluster, Kubernetes starts
killing the executor pods, because it thinks that the pod is misbehaving.
We logged into a running pod, and ran the top command, and most of the 7.6G
is being allocated to the executor's java process
Why is Spark taking 7.6G instead of 7 G? Where is the 600MB being allocated
to? Is there some configuration that controls how much of the executor
memory gets allocated to Permgen vs the memory that gets allocated to the
heap?
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