There may be cases where you want to adjust the number of partitions or explicitly call RDD.repartition or RDD.coalesce. However, I would start with the defaults and then adjust if necessary to improve performance (for example, if cores are idling because there aren't enough tasks you may want more partitions).
Looks like PairRDDFunctions has a countByKey (though you'd still need to distinct first). You might also look at combineByKey and foldByKey as alternatives to reduceByKey or groupByKey. On Thu, Aug 14, 2014 at 4:14 PM, bdev <buntu...@gmail.com> wrote: > Thanks Daniel for the detailed information. Since the RDD is already > partitioned, there is no need to worry about repartitioning. > > > > -- > View this message in context: > http://apache-spark-user-list.1001560.n3.nabble.com/Ways-to-partition-the-RDD-tp12083p12136.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 > > -- Daniel Siegmann, Software Developer Velos Accelerating Machine Learning 440 NINTH AVENUE, 11TH FLOOR, NEW YORK, NY 10001 E: daniel.siegm...@velos.io W: www.velos.io
