Hi,
I don't think there is a Flink specific answer to this question. Just do
what you would normally do with a normal Java application running inside a
JVM. If there is an OOM on heap space, you can either try to bump the heap
space, or reduce usage of it. The only Flink specific part is probably
Hi, Piotr
Thanks for replying. I asked this because such a pattern might imply memory
oversubscription. For example, I tuned down the memory of one app from heap
2.63GB to 367MB and the job still runs fine:
before:
https://drive.google.com/file/d/1o8k9Vv3yb5gXITi4GvmlXMteQcRfmOhr/view?usp=sharing
Hi,
this should be posted on the user mailing list not the dev.
Apart from that, this looks like normal/standard behaviour of JVM, and has
very little to do with Flink. Garbage Collector (GC) is kicking in when
memory usage is approaching some threshold:
https://www.google.com/search?q=jvm+heap+m
