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From "Andrew Purtell (JIRA)" <j...@apache.org>
Subject [jira] Updated: (HBASE-1062) Compactions at (re)start on a large table can overwhelm DFS
Date Sun, 14 Dec 2008 13:24:44 GMT

     [ https://issues.apache.org/jira/browse/HBASE-1062?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel

Andrew Purtell updated HBASE-1062:

      Component/s: regionserver
         Priority: Critical  (was: Major)
    Fix Version/s: 0.20.0
         Assignee: Andrew Purtell

Made this a critical issue for 0.20.0, and took ownership. I think I am done with this issue
for now :-), until the patch anyhow. 

Of course the proposed solution will impact cluster (re)start time by lengthening it, perhaps
substantially, but I think that is better than data loss. 

A better solution might be to interrogate DFS for its current load before attempting any action
that might load it, but definitely the Hadoop filesystem abstraction layer does not support
this and the DFS protocols do not either. What do you think about filing an issue about this

> Compactions at (re)start on a large table can overwhelm DFS
> -----------------------------------------------------------
>                 Key: HBASE-1062
>                 URL: https://issues.apache.org/jira/browse/HBASE-1062
>             Project: Hadoop HBase
>          Issue Type: Bug
>          Components: regionserver
>            Reporter: Andrew Purtell
>            Assignee: Andrew Purtell
>            Priority: Critical
>             Fix For: 0.20.0
> Given a large table, > 1000 regions for example, if a cluster restart is necessary,
the compactions undertaken by the regionservers when the master makes initial region assignments
can overwhelm DFS, leading to file errors and data loss. This condition is exacerbated if
write load was heavy before restart and so many regions want to split as soon as they are

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