If you just want to control the number of reducers, then setting the numPartitions is sufficient. If you want to control how exact partitioning scheme (that is some other scheme other than hash-based) then you need to implement a custom partitioner. It can be used to improve data skews, etc. which ultimately improves performance.
On Tue, Oct 27, 2015 at 1:20 PM, swetha <swethakasire...@gmail.com> wrote: > Hi, > > We currently use reduceByKey to reduce by a particular metric name in our > Streaming/Batch job. It seems to be doing a lot of shuffles and it has > impact on performance. Does using a custompartitioner before calling > reduceByKey improve performance? > > > Thanks, > Swetha > > > > -- > View this message in context: > http://apache-spark-user-list.1001560.n3.nabble.com/Does-using-Custom-Partitioner-before-calling-reduceByKey-improve-performance-tp25214.html > Sent from the Apache Spark User List mailing list archive at Nabble.com. > > --------------------------------------------------------------------- > To unsubscribe, e-mail: user-unsubscr...@spark.apache.org > For additional commands, e-mail: user-h...@spark.apache.org > >
