Hi all,

I have a Crunch job that tries to combine the last four tasks of my program 
into one M/R job.
That’s normally not a problem, but my data starts small and grows exponentially 
in the most major of those DoFn tasks, resulting in spills to disk (local, not 
HDFS).

I’ve already:

  *   Implemented scaleFactor on the DoFn where the data will emit back more 
records than it consumed, which is 40.0f
  *   Set io.sort.mb parameter to cluster setting, which is 1792
  *   Implemented map-side compression with snappy

Data set I’m ingesting is from a previous map-reduce job, which comes out to 19 
files of 10mb size (which in Crunch comes to 2 splits).
Help?
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Landon Robinson
Big Data/Hadoop Engineer
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