Here is a reproducible example of the DataStreamer memory leak: https://github.com/kellanburket/ignite-leak
I've also added a public image to DockerHub: miraco/ignite:leak This can be run on a machine with at least 22GB of memory available to Docker and probably 50GB of storage between WAL and persistent storage, just to be safe. I'm following the guidelines here: https://apacheignite.readme.io/docs/durable-memory-tuning#section-share-ram 10GB of Durable Memory 4GB of Heap with a 22GB memory limit in Docker that adds up to about 63% of overall RAM Now run this container: (You adjust the cpus as needed. I'm using AWS r4.4xl nodes with 16 cores running Amazon Linux): docker run -v $LOCAL_STORAGE:$CONTAINER_STORAGE -v $LOCAL_WAL:$CONTAINER_WAL -m 22G --cpus=12 --memory-swappiness 0 --name ignite.leak -d miraco/ignite:leak I would expect memory usage to stabilize somewhere around 18-19GB (4GB Heap + 10GB Durable + 640M WAL + 2GB Checkpoint Buffer + 1-2GB jdk overhead), but instead usage per docker stats rises to the container limit forcing an OOM kill. Feel free to increase the memory limit above 22GB. Results should be the same though it make take longer to get there. Now this is interesting. If I replace the cache value type, which is Array[Byte] with a Long and run it again, memory usage eventually stabilizes at around 19-20GB: docker run -v $LOCAL_STORAGE:$CONTAINER_STORAGE -v $LOCAL_WAL:$CONTAINER_WAL -e VALUE_TYPE=ValueLong -m 22G --cpus=12 --memory-swappiness 0 --name ignite.leak -d miraco/ignite:leak Is there something I'm missing here, or is this a bug? -- Sent from: http://apache-ignite-users.70518.x6.nabble.com/
