Thanks Steve for the info. I will play with it.

Yong

On Tue, Jan 13, 2015 at 10:02 AM, Steve Loughran <[email protected]>
wrote:

> My colleague oleg has actually got something better, with spark hooked up
> to the Tez dataflow engine, so giving dynamic node flexing during a run,
> automatically, including re-arranging bits of the flow and reacting to
> failures.
>
> https://issues.apache.org/jira/browse/SPARK-3561
>
> The spark team don't want it though; it's a disagreement about where plugin
> points go (if any).
>
> We've had that in hadoop core, and tend to take the path of "define the
> extensions points strictly (filesystem, shuffle, scheduler, ...)", write
> the reference tests, then let anyone else implementing them deal with the
> compatibility problems. Hopefully the Spark team will choose to do
> something similar.
>
> Anyway: the source for that patch is available —why not have a play with it
> and see what you think?
>
>
> On 13 January 2015 at 00:58, Yong Feng <[email protected]> wrote:
>
> > Hi Slider team
> >
> > I also played with "Spark/SparkR on Yarn" recently, and think we even
> could
> > run Spark on Slider. After that we could enhance Slider to have API scale
> > out/in Spark cluster horizontally or vertically. It is a little bit
> > overlapped with the enhancement on YarnClusterScheduler of Spark. The
> > Slider also may not have enough knowledge of Spark workload to make
> > allocate request with data locality. However it will be a more general
> > solution. After that Slider actually is a meta-app manager on Yarn. It
> will
> > be similar as the Marathon in Mesos.
> >
> > Does it make sense? or anyone else has similar idea to run Spark on
> Slider?
> > Does the data locality matter for Spark?
> >
> > Thanks,
> >
> > Yong
> >
>
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