---- On Thu, 04 Apr 2019 06:52:26 -0700 firstname.lastname@example.org
Have you tried something like this?
spark.conf.set("spark.sql.shuffle.partitions", "5" )
I noticed that in my spark application, the number of tasks in the first stage is equal to the number of files read by the application(at least for Avro) if the number of cpu cores is less than the number of files. Though If cpu cores are more than number of files, it's usually equal to default parallelism number. Why is it behave like this? Would this require a lot of resource from the driver? Is there any way we can do to decrease the number of tasks(partitions) in the first stage without merge files before loading?
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