Dear Jena support team, We would like to ask you to help us in configuring the memory for our jena-fuseki instance running in kubernetes.
*We have the following setup:* * Jena-fuseki deployed as StatefulSet to a k8s cluster with the resource config: Limits: cpu: 2 memory: 16Gi Requests: cpu: 100m memory: 11Gi * The JVM_ARGS has the following value: -Xmx10G * Our main dataset of type TDB2 contains ~1 million triples. * We execute the following type of UPDATE operations: - There are triggers in the system (e.g. users of the application changing the data) which start ~50 other update operations containing up to ~30K triples. Most of them run in parallel, some are delayed with seconds or minutes. - There are scheduled UPDATE operations (executed on hourly basis) containing 30K-500K triples. - These UPDATE operations usually delete and insert the same amount of triples in the dataset. We use the compact API as a nightly job. *We are noticing the following behaviour:* * Fuseki consumes 5-10G of heap memory continuously, as configured in the JVM_ARGS. * There are points in time when the volume usage of the k8s container starts to increase suddenly. This does not drop even though compaction is successfully executed and the dataset size (triple count) does not increase. See attachment below. *Our suspicions:* * garbage collection in Java is often delayed; memory is not freed as quickly as we would expect it, and the heap limit is reached quickly if multiple parallel queries are run * long running database queries can send regular memory to Gen2, that is not actively cleaned by the garbage collector * memory-mapped files are also garbage-collected (and perhaps they could go to Gen2 as well, using more and more storage space). Could you please explain the possible reasons behind such a behaviour? And finally could you please suggest a more appropriate configuration for our use case? Thanks in advance and best wishes, Gaspar Bartalus
