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From "Li Lu (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (YARN-3134) [Storage implementation] Exploiting the option of using Phoenix to access HBase backend
Date Fri, 08 May 2015 05:19:01 GMT

    [ https://issues.apache.org/jira/browse/YARN-3134?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14533883#comment-14533883
] 

Li Lu commented on YARN-3134:
-----------------------------

Looked into the concurrency bug. The problem is caused by concurrent operations on Connections
and the Guava cache removalListener calls. So on cache evictions, active connections may be
mistakenly closed. I believe a concurrent algorithm to resolve this is possible, but not quite
trivial. For now, I'm removing the connection cache to make the first step right. I'll change
the description of YARN-3595 for the connection cache. 

In this JIRA, I'm focusing on code clean ups. 

> [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-3134-YARN-2928.004.patch, YARN-3134-YARN-2928.005.patch, YARN-3134-YARN-2928.006.patch,
YARN-3134DataSchema.pdf, hadoop-zshen-nodemanager-d-128-95-184-84.dhcp4.washington.edu.out
>
>
> 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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