I'm currently trying to join two large tables (order 1B rows each) using
Spark SQL (1.3.0) and am running into long GC pauses which bring the job to
a halt.
I'm reading in both tables using a HiveContext with the underlying files
stored as Parquet Files. I'm using something along the lines of
HiveContext.sql("SELECT a.col1, b.col2 FROM a JOIN b ON a.col1 = b.col1") to
set up the join.
When I execute this (with an action such as .count) I see the first few
stages complete, but the job eventually stalls. The GC counts keep
increasing for each executor.
Running with 6 workers, each with 2T disk and 100GB RAM.
Has anyone else run into this issue? I'm thinking I might be running into
issues with the shuffling of the data, but I'm unsure of how to get around
this? Is there a way to redistribute the rows based on the join key first,
and then do the join?
Thanks in advance.
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