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https://issues.apache.org/jira/browse/YARN-3901?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14731633#comment-14731633
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Sangjin Lee commented on YARN-3901:
-----------------------------------

I went through the code by myself, and also with [~vrushalic] and 
[~jrottinghuis]. The following is feedback I have in addition to what's already 
brought up.

(HBaseTimelineWriterImpl.java)
- l.147: At minimum, we should write flow metrics only if the entity is an 
application; currently it would trigger for any entity write, which I don't 
think is correct.
- l.180: extra space before the semicolon
- l.228: use isApplicationEntity(te)
- l.246: this check is unnecessary because you come here only if you're writing 
an application
- l.304: I think we should check if the metrics is null before getting the row 
key and the rest
- l.316: I think it's fine not to check if metric is null as this is a private 
method and in both cases it's already checked
(FlowActivityCoprocessor.java)
- some javadoc and/or comments would be helpful
(FlowRunCoprocessor.java)
- some javadoc and/or comments would be helpful
- l.116: as we discussed offline, the cell timestamp issue will need to be 
addressed to avoid collision of puts
(FlowScanner.java)
- l.144: as we discussed in YARN-4074, we need to fix the order in which cells 
are added to ensure they are added in the right order
- l.228-229: as we discussed offline, to be consistent we should use 
GenericObjectMapper.read() here
- l.249-251: as we discussed offline, to be consistent we should use 
GenericObjectMapper.read() here

I'll add some more comments on details of some of these issues we observed down 
below.

> Populate flow run data in the flow_run & flow activity tables
> -------------------------------------------------------------
>
>                 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-2928.2.patch, YARN-3901-YARN-2928.3.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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