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From "ASF GitHub Bot (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (APEXCORE-714) Reusable instance operator recovery
Date Mon, 01 May 2017 19:12:04 GMT

    [ https://issues.apache.org/jira/browse/APEXCORE-714?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15991331#comment-15991331

ASF GitHub Bot commented on APEXCORE-714:

GitHub user PramodSSImmaneni opened a pull request:


    APEXCORE-714 Adding a new recovery mode where the operator instance before a failure event
can be reused when recovering from an upstream operator failure [Review Only]


You can merge this pull request into a Git repository by running:

    $ git pull https://github.com/PramodSSImmaneni/apex-core APEXCORE-714

Alternatively you can review and apply these changes as the patch at:


To close this pull request, make a commit to your master/trunk branch
with (at least) the following in the commit message:

    This closes #522
commit 72f56dda9d4d244bbbf23ccde657435b94267362
Author: Pramod Immaneni <pramod@datatorrent.com>
Date:   2017-03-08T03:29:02Z

    APEXCORE-714 Adding a new recovery mode where the operator instance before a failure event
can be reused when recovering from an upstream operator failure


> Reusable instance operator recovery
> -----------------------------------
>                 Key: APEXCORE-714
>                 URL: https://issues.apache.org/jira/browse/APEXCORE-714
>             Project: Apache Apex Core
>          Issue Type: Improvement
>            Reporter: Pramod Immaneni
>            Assignee: Pramod Immaneni
> In a failure scenario, when a container fails, it is redeployed along with all the operators
in it. The operators downstream to these operators are also redeployed within their containers.
The operators are restored from their checkpoint and connect to the appropriate point in the
stream according to the processing mode. In at least once mode, for example, the data is replayed
from the same checkpoint
> Restoring an operator state from checkpoint could turn out to be a costly operation depending
on the size of the state. In some use cases, based on the operator logic, when there is an
upstream failure, without restoring the operator from checkpoint and reusing the current instance,
will still produce the same results with the data replayed from the last fully processed window.
The operator state can remain the same as it was before the upstream failure by reusing the
same operator instance from before and only the streams and window reset to the window after
the last fully processed window to guarantee the at least once processing of tuples. If the
container where the operator itself is running goes down, it would need to be restored from
the checkpoint of course. This scenario occurs in some batch use cases with operators that
have a large state.
> I would like to propose adding the ability for a user to explicitly identify operators
to be of this type and the corresponding functionality in the engine to handle their recovery
in the way described above by not restoring their state from checkpoint, reusing the instance
and restoring the stream to the window after the last fully processed window for the operator.
When operators are not identified to be of this type, the default behavior is what it is today
and nothing changes.
> I have done some prototyping on the engine side to ensure that this is possible with
our current code base without requiring a massive overhaul, especially the restoration of
the operator instance within the Node in the streaming container, the re-establishment of
the subscriber stream to a window in the buffer server where the publisher (upstream) hasn't
yet reached as it would be restarting from checkpoint and have been able to get it all working

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