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What is the purpose of the change

(For example: This pull request makes task deployment go through the blob server, rather than through RPC. That way we avoid re-transferring them on each deployment (during recovery).)

Brief change log

(for example:)

  • The TaskInfo is stored in the blob store on job creation time as a persistent artifact
  • Deployments RPC transmits only the blob storage reference
  • TaskManagers retrieve the TaskInfo from the blob cache

Verifying this change

(Please pick either of the following options)

This change is a trivial rework / code cleanup without any test coverage.

(or)

This change is already covered by existing tests, such as (please describe tests).

(or)

This change added tests and can be verified as follows:

(example:)

  • Added integration tests for end-to-end deployment with large payloads (100MB)
  • Extended integration test for recovery after master (JobManager) failure
  • Added test that validates that TaskInfo is transferred only once across recoveries
  • Manually verified the change by running a 4 node cluser with 2 JobManagers and 4 TaskManagers, a stateful streaming program, and killing one JobManager and two TaskManagers during the execution, verifying that recovery happens correctly.

Does this pull request potentially affect one of the following parts:

  • Dependencies (does it add or upgrade a dependency): (yes / no)
  • The public API, i.e., is any changed class annotated with @Public(Evolving): (yes / no)
  • The serializers: (yes / no / don't know)
  • The runtime per-record code paths (performance sensitive): (yes / no / don't know)
  • Anything that affects deployment or recovery: JobManager (and its components), Checkpointing, Yarn/Mesos, ZooKeeper: (yes / no / don't know)
  • The S3 file system connector: (yes / no / don't know)

Documentation

  • Does this pull request introduce a new feature? (yes / no)
  • If yes, how is the feature documented? (not applicable / docs / JavaDocs / not documented)

…n using mmap blocking partition

As reported by users in mail list, the container would be killed by yarn because of exceeding physical memory limits. It is mainly because
the memory usage of mmap in BoundedBlockingSubpartition is not capped and not accounted by configured memory limits, but yarn would track
this memory usage and kill the container once exceeding some threshold.

To solve this issue, we adjust the default option of "taskmanager.network.bounded-blocking-subpartition-type" from `auto` to `file` for safety usage.
And users can still enable mmap way via configuration if they make a proper adjustment in yarn configuration to avoid container killing.

In order to make this option consistent with existing compression option, we also rename it to "taskmanager.network.blocking-shuffle.type".
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flinkbot commented Dec 12, 2019

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@zhijiangW zhijiangW changed the title [FLINK-14952][network] Solve the issue of exceeding memory limits when using mmap blocking partition Solve the issue of exceeding memory limits when using mmap blocking partition Dec 13, 2019
@zhijiangW zhijiangW changed the title Solve the issue of exceeding memory limits when using mmap blocking partition [FLINK-14952][network] Solve the issue of exceeding memory limits when using mmap blocking partition Dec 13, 2019
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duplicate one, closing

@zhijiangW zhijiangW closed this Dec 13, 2019
@zhijiangW zhijiangW deleted the 14952 branch February 10, 2020 10:36
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