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From "Li Lu (JIRA)" <j...@apache.org>
Subject [jira] [Updated] (YARN-3134) [Storage implementation] Exploiting the option of using Phoenix to access HBase backend
Date Tue, 05 May 2015 00:26:07 GMT

     [ https://issues.apache.org/jira/browse/YARN-3134?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]

Li Lu updated YARN-3134:
------------------------
    Attachment: YARN-3134-YARN-2928.003.patch

Updated my patch according to the latest comments. I've rebased the patch to the latest YARN-2928
branch, with YARN-3551 in. In this version we're no longer swallowing exceptions. I have not
made the change on the Phoenix connection string since, according to our previous discussion,
we're planning to address this after we've decided which implementation to pursue in the future.


A special note to [~zjshen]: I'm not sure my current way to access the "singleData" section
of a TimelineMetric is correct (since the field no longer exists). It would be great if you
can take a look at it. 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-3134-YARN-2928.001.patch, YARN-3134-YARN-2928.002.patch, YARN-3134-YARN-2928.003.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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