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From "anthonyjschulte@gmail.com" <anthonyjschu...@gmail.com>
Subject Re: heterogeneous cluster hardware
Date Thu, 21 Aug 2014 21:33:21 GMT
This is what I thought the simplest method would be, but I can't seem to
figure out how to configure it--
When you set:

SPARK_WORKER_INSTANCES, to set the number of worker processes per node

but when you set 

SPARK_WORKER_MEMORY, to set how much total memory workers have to give
executors (e.g. 1000m, 2g)

I believe it is shared across all workers! So when worker memory gets set by
the master (I tried setting it in the spark-env.sh on a worker, but was
overridden by the setting on the master) it is not multiplied by the number
of workers?

(also, I'm not sure Worker_Instances isn't also overridden by the master...)

How would you suggest setting this up?



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