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https://issues.apache.org/jira/browse/YARN-3134?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Li Lu updated YARN-3134:
------------------------
    Attachment: YARN-3134-YARN-2928.runJenkins.001.patch

In the latest patch I addressed all previous comments, and changed the storage 
type for config and info into byte arrays. I've also revised the storage of 
metrics, which no longer uses startTime and end Time. Right now I'm focusing on 
storing singleData since we need to discuss more about storing and aggregating 
time series data. 

Renaming the patch to the new format so that we can try jenkins on YARN-2928 
branch. Disable the Phoenix test for now since it's blocked by YARN-3529. 

> [Storage implementation] Exploiting the option of using Phoenix to access 
> HBase backend
> ---------------------------------------------------------------------------------------
>
>                 Key: YARN-3134
>                 URL: https://issues.apache.org/jira/browse/YARN-3134
>             Project: Hadoop YARN
>          Issue Type: Sub-task
>          Components: timelineserver
>            Reporter: Zhijie Shen
>            Assignee: Li Lu
>         Attachments: SettingupPhoenixstorageforatimelinev2end-to-endtest.pdf, 
> YARN-3134-040915_poc.patch, YARN-3134-041015_poc.patch, 
> YARN-3134-041415_poc.patch, YARN-3134-042115.patch, YARN-3134-042715.patch, 
> YARN-3134-YARN-2928.runJenkins.001.patch, YARN-3134DataSchema.pdf
>
>
> Quote the introduction on Phoenix web page:
> {code}
> Apache Phoenix is a relational database layer over HBase delivered as a 
> client-embedded JDBC driver targeting low latency queries over HBase data. 
> Apache Phoenix takes your SQL query, compiles it into a series of HBase 
> scans, and orchestrates the running of those scans to produce regular JDBC 
> result sets. The table metadata is stored in an HBase table and versioned, 
> such that snapshot queries over prior versions will automatically use the 
> correct schema. Direct use of the HBase API, along with coprocessors and 
> custom filters, results in performance on the order of milliseconds for small 
> queries, or seconds for tens of millions of rows.
> {code}
> It may simply our implementation read/write data from/to HBase, and can 
> easily build index and compose complex query.



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