Github user jinxing64 commented on the issue: https://github.com/apache/spark/pull/21424 @cloud-fan > I also found that we may throw OOM My previous understanding is that Spark throw `SparkOutOfMemoryError` when expect there's no memory -- such expectation is from Spark scope of memory management. So that it's safe to catch `SparkOutOfMemoryError` and mark the corresponding task as failed rather than the executor. If `OutOfMemoryError` is thrown from JVM, e.g. OOM when `new Array[bigSize]`, is it ok to catch it and continue running the executor as if nothing happened ? If it's ok, does it mean that an executor should never exit when `OutOfMemoryError`?
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