Hello all, we are running Solr 9.8.1 on Kubernetes using the official Solr Operator 0.9.1.
After many asynchronous REINDEXCOLLECTION requests we are encountering a significant RAM allocation increase which is itself neither surprising nor problematic, but after those requests have successfully completed, the consumption stays constant and does not decrease. Manually restarting the SolrCloud deployment always resolves that issue, so for me it seems like either the allocated blocks are afterwards not being freed up correctly or, they *are* deallocated correctly but after the requests completed, the heap itself is fragmented too much. If the heap allocation increased and increased after several REINDEXCOLLECTION requests and we did not restart the pods, this led to OOM crashes for us in the past. In this case, the REINDEXCOLLECTION async requests were interrupted which required manual intervention. It's easy for me to reproduce this RAM allocation behavior, but after diving into how to create JVM memory dumps with 'jcmd' and 'jmap', it seems to me like it's not trivially possible to create such a heap dump with the current tools installed into the Solr pods. However, I'm not that expert regarding Solr and the Java ecosystem, so if there are any solutions to create memory dumps to help the Solr development team tracing the RAM consumption issues explained above, any ideas are welcome. Many thanks! Florian Schieder
