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https://issues.apache.org/jira/browse/YARN-3134?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14518458#comment-14518458
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Li Lu commented on YARN-3134:
-----------------------------

Hi [~sjlee0], thanks for the review! We do not need to call Connection.close() 
after every write, since they're cached by the loading cache, and will be 
closed upon removal. However, I treat tryInitTable as a special case because 
there are potentially less reuse after the table creation. Not sure if this 
makes sense so I can change it once more. 

A quick question about this comment:

bq. l.216: conn.close() is called twice

I'm a little bit confused here because I was trying to close the connection 
after a commit (for potentially pending data). Could you please give me a hint 
on why it's closed twice? Thanks! 

> [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-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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