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From Stephan Ewen <se...@apache.org>
Subject Re: Batch Processing as Streaming
Date Thu, 02 Jul 2015 11:13:34 GMT

I am actually working to get some more docs out there, there is a lack
right now, agreed.

Concerning your questions:

(1) Batch programs basically recover from the data sources right now.
Checkpointing as in the streaming case does not happen for batch programs.
We have branches that materialize the intermediate streams and apply
backtracking logic for batch programs, but they are not merged into the
master at this point.

(2) Streaming operators and user functions are long lived. They are started
once and live to the end of the stream, or the machine failure.


On Thu, Jul 2, 2015 at 11:48 AM, tambunanw <if05041@gmail.com> wrote:

> Hi All,
> I see that the way batch processing works in Flink is quite different with
> Spark. It's all about using streaming engine in Flink.
> I have a couple of question
> 1. Is there any support on Checkpointing on batch processing also ? Or
> that's only for streaming
> 2. I want to ask about operator lifecyle ? is that short live or long live
> ?
> Any docs where i can read about this more ?
> Cheers
> --
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> at Nabble.com.

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