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From Sandy Ryza <>
Subject Re: spark-submit on YARN is slow
Date Fri, 05 Dec 2014 20:20:37 GMT
Hi Denny,

Those sleeps were only at startup, so if jobs are taking significantly
longer on YARN, that should be a different problem.  When you ran on YARN,
did you use the --executor-cores, --executor-memory, and --num-executors
arguments?  When running against a standalone cluster, by default Spark
will make use of all the cluster resources, but when running against YARN,
Spark defaults to a couple tiny executors.


On Fri, Dec 5, 2014 at 11:32 AM, Denny Lee <> wrote:

> My submissions of Spark on YARN (CDH 5.2) resulted in a few thousand
> steps. If I was running this on standalone cluster mode the query finished
> in 55s but on YARN, the query was still running 30min later. Would the hard
> coded sleeps potentially be in play here?
> On Fri, Dec 5, 2014 at 11:23 Sandy Ryza <> wrote:
>> Hi Tobias,
>> What version are you using?  In some recent versions, we had a couple of
>> large hardcoded sleeps on the Spark side.
>> -Sandy
>> On Fri, Dec 5, 2014 at 11:15 AM, Andrew Or <> wrote:
>>> Hey Tobias,
>>> As you suspect, the reason why it's slow is because the resource manager
>>> in YARN takes a while to grant resources. This is because YARN needs to
>>> first set up the application master container, and then this AM needs to
>>> request more containers for Spark executors. I think this accounts for most
>>> of the overhead. The remaining source probably comes from how our own YARN
>>> integration code polls application (every second) and cluster resource
>>> states (every 5 seconds IIRC). I haven't explored in detail whether there
>>> are optimizations there that can speed this up, but I believe most of the
>>> overhead comes from YARN itself.
>>> In other words, no I don't know of any quick fix on your end that you
>>> can do to speed this up.
>>> -Andrew
>>> 2014-12-03 20:10 GMT-08:00 Tobias Pfeiffer <>:
>>> Hi,
>>>> I am using spark-submit to submit my application to YARN in
>>>> "yarn-cluster" mode. I have both the Spark assembly jar file as well as my
>>>> application jar file put in HDFS and can see from the logging output that
>>>> both files are used from there. However, it still takes about 10 seconds
>>>> for my application's yarnAppState to switch from ACCEPTED to RUNNING.
>>>> I am aware that this is probably not a Spark issue, but some YARN
>>>> configuration setting (or YARN-inherent slowness), I was just wondering if
>>>> anyone has an advice for how to speed this up.
>>>> Thanks
>>>> Tobias

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