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Posted to issues@flink.apache.org by GitBox <gi...@apache.org> on 2019/12/06 03:57:28 UTC

[GitHub] [flink] dianfu opened a new pull request #10453: [FLINK-14026][python] Manage the resource of Python worker properly

dianfu opened a new pull request #10453: [FLINK-14026][python] Manage the resource of Python worker properly
URL: https://github.com/apache/flink/pull/10453
 
 
   ## What is the purpose of the change
   
   *This pull request add support to manage the resource of the Python worker. The memory of the Python worker will be accounted as the managed memory and managed by Flink.*
   
   Note: This feature is still [voting](http://apache-flink-mailing-list-archive.1008284.n3.nabble.com/VOTE-FLIP-88-PyFlink-User-Defined-Function-Resource-Management-tt35439.html). Just submit the PR for review to make sure we can commit this change before the code freeze of 1.10. (Should only be merged after vote passed)
   
   ## Brief change log
   
     - *Introduce configuration python.fn-execution.framework.memory.size and python.fn-execution.buffer.memory.size*
     - *At compile phase, request the required amount of memory for the Python worker*
     - *At runtime phase, reserve the required amount of memory for the Python worker from MemoryManager*
   
   ## Verifying this change
   
   This change added tests and can be verified as follows:
     - *Added test in PythonOptionsTest*
   
   ## Does this pull request potentially affect one of the following parts:
   
     - Dependencies (does it add or upgrade a dependency): (no)
     - The public API, i.e., is any changed class annotated with `@Public(Evolving)`: (yes)
     - The serializers: (no)
     - The runtime per-record code paths (performance sensitive): (no)
     - Anything that affects deployment or recovery: JobManager (and its components), Checkpointing, Yarn/Mesos, ZooKeeper: (no)
     - The S3 file system connector: (no)
   
   ## Documentation
   
     - Does this pull request introduce a new feature? (no)
     - If yes, how is the feature documented? (not applicable)
   

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