Hi I have Spark job which does group by and I cant avoid it because of my use
case. I have large dataset around 1 TB which I need to process/update in
DataFrame. Now my jobs shuffles huge data and slows things because of
shuffling and groupby. One reason I see is my data is skew some of my group
by keys are empty. How do I avoid empty group by keys in DataFrame? Does
DataFrame avoid empty group by key? I have around 8 keys on which I do group
by.
sourceFrame.select("blabla").groupby("col1","col2","col3",..."col8").agg("bla
bla");
How do I change above code into using reduceByKey() can we apply aggregation
on reduceByKey()? Please guide. Thanks in advance.
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