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Posted to issues@beam.apache.org by "ASF GitHub Bot (Jira)" <ji...@apache.org> on 2021/03/02 22:37:00 UTC
[jira] [Work logged] (BEAM-11213) Beam metrics should be displayed
in Spark UI
[ https://issues.apache.org/jira/browse/BEAM-11213?focusedWorklogId=560170&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-560170 ]
ASF GitHub Bot logged work on BEAM-11213:
-----------------------------------------
Author: ASF GitHub Bot
Created on: 02/Mar/21 22:36
Start Date: 02/Mar/21 22:36
Worklog Time Spent: 10m
Work Description: iemejia opened a new pull request #14132:
URL: https://github.com/apache/beam/pull/14132
R: @ibzib
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Issue Time Tracking
-------------------
Worklog Id: (was: 560170)
Time Spent: 10h (was: 9h 50m)
> Beam metrics should be displayed in Spark UI
> --------------------------------------------
>
> Key: BEAM-11213
> URL: https://issues.apache.org/jira/browse/BEAM-11213
> Project: Beam
> Issue Type: Wish
> Components: runner-spark
> Reporter: Kyle Weaver
> Assignee: Tomasz Szerszen
> Priority: P2
> Labels: portability-spark
> Fix For: 2.29.0
>
> Time Spent: 10h
> Remaining Estimate: 0h
>
> All Beam metrics are visible in the Spark UI in a single accumulator value (in the "Accumulators" tab), which is a large, hard-to-read blob. Originally, this blob was rendered in a bespoke format (https://github.com/apache/beam/blob/ead80b469ffeeddcd8e9e5c8dc462eec0b0ffc6b/sdks/java/core/src/main/java/org/apache/beam/sdk/metrics/MetricQueryResults.java#L63-L72). I changed the format to JSON so it could be easily deserialized (BEAM-9600). But then an issue was filed (BEAM-10294) reporting that the new JSON format was harder to read than the original bespoke format. The temporary fix was to revert to the bespoke format in Spark, while allowing Flink to continue to use JSON. However, if Beam metrics are only visible as an accumulator, then they are also unreadable because the payloads are in binary form (BEAM-10719).
> Having metrics visible in Spark's "Metrics" tab would A) make metrics easier to read (even compared to the bespoke accumulator string format), and closer to what users of Beamless Spark expect, and B) free us to use the accumulator however we wish for Beam internal purposes, without worrying about readability.
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