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From "Hadoop QA (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (YARN-3134) [Storage implementation] Exploiting the option of using Phoenix to access HBase backend
Date Wed, 29 Apr 2015 23:32:07 GMT

    [ https://issues.apache.org/jira/browse/YARN-3134?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14520520#comment-14520520
] 

Hadoop QA commented on YARN-3134:
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| (x) *{color:red}-1 overall{color}* |
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|| Vote || Subsystem || Runtime || Comment ||
| {color:red}-1{color} | patch |   0m  0s | The patch command could not apply the patch during
dryrun. |
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|| Subsystem || Report/Notes ||
| Patch URL | http://issues.apache.org/jira/secure/attachment/12729341/YARN-3134-YARN-2928.runJenkins.001.patch
|
| Optional Tests | javadoc javac unit findbugs checkstyle |
| git revision | trunk / 4c1af15 |
| Console output | https://builds.apache.org/job/PreCommit-YARN-Build/7546/console |


This message was automatically generated.

> [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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