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ASF GitHub Bot commented on FLINK-4545: --------------------------------------- Github user StephanEwen commented on the issue: https://github.com/apache/flink/pull/3467 @zhijiangW Yes, let's discuss this when the feature is complete. Our thinking so far is: - One can specify an absolute amount of network memory (similar as one can specify an absolute amount of managed memory for batch) - If no absolute amount is specified, a relative fraction of the JVM heap will be pre-allocated as network buffers. > Flink automatically manages TM network buffer > --------------------------------------------- > > Key: FLINK-4545 > URL: https://issues.apache.org/jira/browse/FLINK-4545 > Project: Flink > Issue Type: Wish > Components: Network > Reporter: Zhenzhong Xu > > Currently, the number of network buffer per task manager is preconfigured and > the memory is pre-allocated through taskmanager.network.numberOfBuffers > config. In a Job DAG with shuffle phase, this number can go up very high > depends on the TM cluster size. The formula for calculating the buffer count > is documented here > (https://ci.apache.org/projects/flink/flink-docs-master/setup/config.html#configuring-the-network-buffers). > > #slots-per-TM^2 * #TMs * 4 > In a standalone deployment, we may need to control the task manager cluster > size dynamically and then leverage the up-coming Flink feature to support > scaling job parallelism/rescaling at runtime. > If the buffer count config is static at runtime and cannot be changed without > restarting task manager process, this may add latency and complexity for > scaling process. I am wondering if there is already any discussion around > whether the network buffer should be automatically managed by Flink or at > least expose some API to allow it to be reconfigured. Let me know if there is > any existing JIRA that I should follow. -- This message was sent by Atlassian JIRA (v6.3.15#6346)