[jira] [Created] (FLINK-16267) Flink uses more memory than taskmanager.memory.process.size in Kubernetes

["ChangZhuo Chen (陳昌倬 Jira)" <ji...@apache.org>]

ChangZhuo Chen (陳昌倬) created FLINK-16267:
--------------------------------------------

             Summary: Flink uses more memory than taskmanager.memory.process.size in Kubernetes
                 Key: FLINK-16267
                 URL: https://issues.apache.org/jira/browse/FLINK-16267
             Project: Flink
          Issue Type: Bug
          Components: Runtime / Task
    Affects Versions: 1.10.0
         Environment: * Dockerized Flink 1.10.0, with the following docker file.

{{FROM flink:1.10-scala_2.11}}
{{RUN mkdir -p /opt/flink/plugins/s3 && \}}
{{ ln -s /opt/flink/opt/flink-s3-fs-presto-1.10.0.jar /opt/flink/plugins/s3/}}
{{RUN ln -s /opt/flink/opt/flink-metrics-prometheus-1.10.0.jar /opt/flink/lib/}}
            Reporter: ChangZhuo Chen (陳昌倬)


This issue is from [https://stackoverflow.com/questions/60336764/flink-uses-more-memory-than-taskmanager-memory-process-size-in-kubernetes]

In Flink 1.10.0, we try to use `taskmanager.memory.process.size` to limit the resource used by taskmanager to ensure they are not killed by Kubernetes. However, we still get lots of taskmanager `OOMKilled` with the following setup.
 * The Kubernetes setup is the same as described in https://ci.apache.org/projects/flink/flink-docs-release-1.10/ops/deployment/kubernetes.html.
 * The following is resource configuration for taskmanager deployment in Kubernetes:

{{resources:}}
{{  requests:}}
{{    cpu: 1000m}}
{{    memory: 4096Mi}}
{{  limits:}}
{{    cpu: 1000m}}
{{    memory: 4096Mi}}
 * The following are all memory related configurations in `flink-conf.yaml` in 1.10.0:

{{jobmanager.heap.size: 820m}}
{{taskmanager.memory.jvm-metaspace.size: 128m}}
{{taskmanager.memory.process.size: 4096m}}
 * We use RocksDB and we don't set `state.backend.rocksdb.memory.managed` in `flink-conf.yaml`.
 ** Use S3 as checkpoint storage.
 * The code uses DateStream API
 ** input/output are both Kafka.
 * The following is our dependencies FYI.

{{val flinkVersion = "1.10.0"}}{{libraryDependencies += "com.squareup.okhttp3" % "okhttp" % "4.2.2"}}
{{libraryDependencies += "com.typesafe" % "config" % "1.4.0"}}
{{libraryDependencies += "joda-time" % "joda-time" % "2.10.5"}}
{{libraryDependencies += "org.apache.flink" %% "flink-connector-kafka" % flinkVersion}}
{{libraryDependencies += "org.apache.flink" % "flink-metrics-dropwizard" % flinkVersion}}
{{libraryDependencies += "org.apache.flink" %% "flink-scala" % flinkVersion % "provided"}}
{{libraryDependencies += "org.apache.flink" %% "flink-statebackend-rocksdb" % flinkVersion % "provided"}}
{{libraryDependencies += "org.apache.flink" %% "flink-streaming-scala" % flinkVersion % "provided"}}
{{libraryDependencies += "org.json4s" %% "json4s-jackson" % "3.6.7"}}
{{libraryDependencies += "org.log4s" %% "log4s" % "1.8.2"}}
{{libraryDependencies += "org.rogach" %% "scallop" % "3.3.1"}}
 * The configuration we used in Flink 1.9.1 are the following. It does not have `OOMKilled`.
 * Kubernetes

{{resources:}}
{{  requests:}}
{{    cpu: 1200m}}
{{    memory: 2G}}
{{  limits:}}
{{    cpu: 1500m}}
{{    memory: 2G}}
 * Flink 1.9.1

{{jobmanager.heap.size: 820m}}
{{taskmanager.heap.size: 1024m}}



--
This message was sent by Atlassian Jira
(v8.3.4#803005)