hadoop-yarn-issues mailing list archives

Site index · List index
Message view « Date » · « Thread »
Top « Date » · « Thread »
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, 24 Apr 2015 22:18:39 GMT

    [ https://issues.apache.org/jira/browse/YARN-3134?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14511897#comment-14511897
] 

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

Hi [~sjlee0], thanks for the review! I'll address your comments soon, but one thing to discuss:
the original point for keeping writers inside managers, instead of collectors, is to reuse
the storage layer connection. Having static writers in collectors may be too restrictive,
while having writers for each collector may accidentally introduce too many heavy weight storage
layer connections? I think there might be some miscommunications in the collector design,
where I thought collectors will only hold for collection logic, and always need some sort
of managers to wrap other logics such as web server and writers. 

> [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: YARN-3134-040915_poc.patch, YARN-3134-041015_poc.patch, YARN-3134-041415_poc.patch,
YARN-3134-042115.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.



--
This message was sent by Atlassian JIRA
(v6.3.4#6332)

Mime
View raw message