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Posted to user@spark.apache.org by Sonal Goyal <so...@gmail.com> on 2014/03/28 12:11:21 UTC

Re: How does Spark handle executor down? RDD in this executor will be recomputed automatically?

Each handle to the RDD holds its lineage information, which means it knows
how it was computed starting from data in a reliable storage or from other
RDDs. RDDs hence can be reconstructed when the node fails.

Best Regards,
Sonal
Nube Technologies <http://www.nubetech.co>

<http://in.linkedin.com/in/sonalgoyal>




On Fri, Mar 28, 2014 at 3:55 PM, colt_colt <we...@hotmail.com> wrote:

> I am curious about Spark fail over scenario, if some executor down,  that
> means the JVM crashed. AM will restart the executor, but how about the RDD
> data in JVM?  if I didn't persist RDD, does Spark will recompute lost RDD
> or
> just let it lose?  there is some description in Spark site: "Each RDD
> remembers the lineage of deterministic operations that were used on a
> fault-tolerant input dataset to create it."
>
> thanks in advance
>
>
>
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