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From Kai Huang <texasred2...@hotmail.com>
Subject Re: Review Request 59699: Improve task history pruning by batch deleting tasks
Date Thu, 01 Jun 2017 22:41:51 GMT

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This is an automatically generated e-mail. To reply, visit:
https://reviews.apache.org/r/59699/
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(Updated June 1, 2017, 10:41 p.m.)


Review request for Aurora, David McLaughlin and Santhosh Kumar.


Changes
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- 1. Refactored the deletTasks code to post a single event for all task deletions.

- 2. Upload benchmark result for task history pruning.


Bugs: AURORA-1929
    https://issues.apache.org/jira/browse/AURORA-1929


Repository: aurora


Description
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Improve task history pruning by batch deleting tasks.

The `'aurora_admin prune_tasks'` endpoint seems to be very slow when the cluster has a large
number of inactive tasks.

This CR batches all removeTasks operations and execute them all at once to avoid additional
cost of coalescing. The fix will also benefit implicit task history pruning since it has similar
underlying implementation. See https://issues.apache.org/jira/browse/AURORA-1929 for more
information and details.


Diffs (updated)
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  src/main/java/org/apache/aurora/scheduler/state/StateManagerImpl.java 73878210f9028901fda3b08e66c6a63c24260d35



Diff: https://reviews.apache.org/r/59699/diff/3/

Changes: https://reviews.apache.org/r/59699/diff/2-3/


Testing (updated)
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__unit_tests:__

./build-support/jenkins/build.sh

No unit tests were created for this patch since it does not add new functionalities or alter
the interface, but improves the efficiency of the existing code.

__e2e tests:__

Attached was a screenshot of the task history pruning benchmark obtained from a scale test
in Twitter's test cluster.

- Before applying this patch, the task history pruning takes ~30 minutes on 130K tasks.

- After applying the patch, the pruning takes ~1 minute.


File Attachments (updated)
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task_history_pruning_benchmark.png
  https://reviews.apache.org/media/uploaded/files/2017/06/01/74eb5104-d338-4530-abd2-b82fbdc6bf84__task_history_pruning_benchmark.png


Thanks,

Kai Huang


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