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https://issues.apache.org/jira/browse/YARN-3901?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Vrushali C updated YARN-3901:
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Attachment: YARN-3901-YARN-2928.1.patch
Uploading patch v01. This patch contains the code that creates and updates the
flowrun and flowactivity (YARN-4063) tables and their unit tests. Both tables
have coprocessors defined for them. They use the same scanner class since the
functionalities to deal with cell versions are common to both.
Min and max for flows are calculated as per the cells stored with those tags.
The cells with metric tag are aggregated.
The flush and compaction for these tables in yet to be done, being tracked in
YARN-4062 and YARN-4070. The flush/compaction will collapse the cells that can
be collapsed together based on their tags (application_finished) etc. This will
help improve read performance. Functional correctness is not affected by
flush/compaction.
Please let me know your feedback on the patch!
> Populate flow run data in the flow_run table
> --------------------------------------------
>
> Key: YARN-3901
> URL: https://issues.apache.org/jira/browse/YARN-3901
> Project: Hadoop YARN
> Issue Type: Sub-task
> Components: timelineserver
> Reporter: Vrushali C
> Assignee: Vrushali C
> Attachments: YARN-3901-YARN-2928.1.patch,
> YARN-3901-YARN-2928.WIP.2.patch, YARN-3901-YARN-2928.WIP.patch
>
>
> As per the schema proposed in YARN-3815 in
> https://issues.apache.org/jira/secure/attachment/12743391/hbase-schema-proposal-for-aggregation.pdf
> filing jira to track creation and population of data in the flow run table.
> Some points that are being considered:
> - Stores per flow run information aggregated across applications, flow version
> RM’s collector writes to on app creation and app completion
> - Per App collector writes to it for metric updates at a slower frequency
> than the metric updates to application table
> primary key: cluster ! user ! flow ! flow run id
> - Only the latest version of flow-level aggregated metrics will be kept, even
> if the entity and application level keep a timeseries.
> - The running_apps column will be incremented on app creation, and
> decremented on app completion.
> - For min_start_time the RM writer will simply write a value with the tag for
> the applicationId. A coprocessor will return the min value of all written
> values. -
> - Upon flush and compactions, the min value between all the cells of this
> column will be written to the cell without any tag (empty tag) and all the
> other cells will be discarded.
> - Ditto for the max_end_time, but then the max will be kept.
> - Tags are represented as #type:value. The type can be not set (0), or can
> indicate running (1) or complete (2). In those cases (for metrics) only
> complete app metrics are collapsed on compaction.
> - The m! values are aggregated (summed) upon read. Only when applications are
> completed (indicated by tag type 2) can the values be collapsed.
> - The application ids that have completed and been aggregated into the flow
> numbers are retained in a separate column for historical tracking: we don’t
> want to re-aggregate for those upon replay
>
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