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Date: Tue, 5 Apr 2016 09:46:59 -0700 (MST)
From: dsing001 <darshan.meel@gmail.com>
To: user@spark.apache.org
Message-ID: <1459874819476-26681.post@n3.nabble.com>
Subject: Plan issue with spark 1.5.2
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I am using spark 1.5.2. I have a question regarding plan generated by spark.
I have 3 data-frames which has the data for different countries. I have
around 150 countries and data is skewed.

My 95% queries will have country as criteria. However, I have seen issues
with the plans generated for queries which has country as join column.

Data-frames are partitioned based on the country.Not only these dataframes
are co-partitioned, these are co-located as well. E.g. Data for UK in
data-frame df1, df2 df3 will be at on same hdfs datanode. 

Then when i join these 3 tables and country is one of the join column. I
assume that the join should be the map side join but it shuffles the data
from 3 dataframes and then join using shuffled data. Apart from country
there are other columns in join.

Is this correct behavior? If it is an issue is it fixed in latest versions?

Thanks


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