Hi Kane-
http://spark.apache.org/docs/latest/tuning.html has excellent information that
may be helpful. In particular increasing the number of tasks may help, as well
as confirming that you don’t have more data than you're expecting landing on a
key.
Also, if you are using spark < 1.2.0, setting spark.shuffle.manager=sort was a
huge help for many of our shuffle heavy workloads (this is the default in 1.2.0
now)
Cheers,
Sean
On Jan 22, 2015, at 3:15 PM, Kane Kim
mailto:kane.ist...@gmail.com>> wrote:
I'm trying to process a large dataset, mapping/filtering works ok, but
as long as I try to reduceByKey, I get out of memory errors:
http://pastebin.com/70M5d0Bn
Any ideas how I can fix that?
Thanks.
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