I found a workaround. I can make my auxiliary data a RDD. Partition it and cache it. Later, I can cogroup it with other RDDs and Spark will try to keep the cached RDD partitions where they are and not shuffle them.
-- View this message in context: http://apache-spark-user-list.1001560.n3.nabble.com/How-to-make-spark-partition-sticky-i-e-stay-with-node-tp21322p21338.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
