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From "Todd Lipcon (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (HDFS-1780) reduce need to rewrite fsimage on statrtup
Date Fri, 01 Apr 2011 03:36:05 GMT

    [ https://issues.apache.org/jira/browse/HDFS-1780?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13014384#comment-13014384
] 

Todd Lipcon commented on HDFS-1780:
-----------------------------------

Hi Matt. I agree with your analysis, and was thinking that with the work in HDFS-1073 we can
do away with this complicated logic entirely. Instead, we can use the normal thresholds (time-based
or number of edits) to decide whether we need to save an image at startup, to deal with the
rare case that someone isn't running a 2NN.

> reduce need to rewrite fsimage on statrtup
> ------------------------------------------
>
>                 Key: HDFS-1780
>                 URL: https://issues.apache.org/jira/browse/HDFS-1780
>             Project: Hadoop HDFS
>          Issue Type: New Feature
>            Reporter: Daryn Sharp
>
> On startup, the namenode will read the fs image, apply edits, then rewrite the fs image.
 This requires a non-trivial amount of time for very large directory structures.  Perhaps
the namenode should employ some logic to decide that the edits are simple enough that it doesn't
warrant rewriting the image back out to disk.
> A few ideas:
> Use the size of the edit logs, if the size is below a threshold, assume it's cheaper
to reprocess the edit log instead of writing the image back out.
> Time the processing of the edits and if the time is below a defined threshold, the image
isn't rewritten.
> Timing the reading of the image, and the processing of the edits.  Base the decision
on the time it would take to write the image (a multiplier is applied to the read time?) versus
the time it would take to reprocess the edits.  If a certain threshold (perhaps percentage
or expected time to rewrite) is exceeded, rewrite the image.
> Somethingalong the lines of the last suggestion may allow for defaults that adapt for
any size cluster, thus eliminating the need to keep tweaking a cluster's settings based on
its size.

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