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From Matei Zaharia <matei.zaha...@gmail.com>
Subject Re: computation slows down 10x because of cached RDDs
Date Mon, 10 Mar 2014 22:27:18 GMT
Does this happen repeatedly if you keep running the computation, or just the first time? It
may take time to move these Java objects to the old generation the first time you run queries,
which could lead to a GC pause that also slows down the small queries.

If you can run with -XX:+PrintGCDetails in your Java options, it would also be good to see
what percent of each GC generation is used.

The concurrent mark-and-sweep GC -XX:+UseConcMarkSweepGC or the G1 GC in Java 7 (-XX:+UseG1GC)
might also avoid these pauses by GCing concurrently with your application threads.

Matei

On Mar 10, 2014, at 3:18 PM, Koert Kuipers <koert@tresata.com> wrote:

> hello all,
> i am observing a strange result. i have a computation that i run on a cached RDD in spark-standalone.
it typically takes about 4 seconds. 
> 
> but when other RDDs that are not relevant to the computation at hand are cached in memory
(in same spark context), the computation takes 40 seconds or more.
> 
> the problem seems to be GC time, which goes from milliseconds to tens of seconds.
> 
> note that my issue is not that memory is full. i have cached about 14G in RDDs with 66G
available across workers for the application. also my computation did not push any cached
RDD out of memory.
> 
> any ideas?


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