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https://issues.apache.org/jira/browse/NIFI-2732?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15467321#comment-15467321
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Joseph Witt commented on NIFI-2732:
-----------------------------------
had originally put the wrong JIRA on the commit. Fixed. here is the PR details
GitHub user joewitt opened a pull request:
https://github.com/apache/nifi/pull/987
NIFI-2372 ensure session and consumer aligned and has registered reba…
…lance listener. Make consumption far more memory and process efficient.
You can merge this pull request into a Git repository by running:
$ git pull https://github.com/joewitt/incubator-nifi NIFI-2732
Alternatively you can review and apply these changes as the patch at:
https://github.com/apache/nifi/pull/987.patch
To close this pull request, make a commit to your master/trunk branch
with (at least) the following in the commit message:
This closes #987
----
commit 6cca1eed679e8b9e3dbc020fa4de589e4578df92
Author: joewitt <[email protected]>
Date: 2016-08-31T05:25:12Z
NIFI-2732 ensure session and consumer aligned and has registered rebalance
listener. Make consumption far more memory and process efficient.
----
> ConsumeKafka 0.9 and 0.10 not handling partition reassignment case
> sufficiently
> -------------------------------------------------------------------------------
>
> Key: NIFI-2732
> URL: https://issues.apache.org/jira/browse/NIFI-2732
> Project: Apache NiFi
> Issue Type: Bug
> Reporter: Joseph Witt
> Assignee: Joseph Witt
> Priority: Critical
> Fix For: 1.1.0
>
>
> The new ConsumeKafka clients handle the threading model of the consumer api
> correctly. However, they are not yet honoring partition reassignment cases
> sufficiently which means we could have avoidable cases of duplication. By
> registering a partition reassignment listener we can handle it correctly.
> Further, the processor is loading subsequent polls of messages into memory
> rather than writing directly to the process session/disk. We could write
> them to disk and achieve far better performance and efficiency. Early
> testing shows easily achieving 100MB/s sustained per thread on a simple
> laptop setup with defaults which will scale very nicely on a legit installed
> content repository.
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