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Andre Schumacher commented on SPARK-2620: ----------------------------------------- I also bumped into this issue (on Spark 1.1.0) and it is kind of extremely annoying although it only affects the REPL. Is anybody actively working on reolving this? Given it's already a few months old: are there any blockers for making this work? Matei mentioned the way code is wrapped inside the REPL. > case class cannot be used as key for reduce > ------------------------------------------- > > Key: SPARK-2620 > URL: https://issues.apache.org/jira/browse/SPARK-2620 > Project: Spark > Issue Type: Bug > Components: Spark Core > Affects Versions: 1.0.0, 1.1.0 > Environment: reproduced on spark-shell local[4] > Reporter: Gerard Maas > Priority: Critical > Labels: case-class, core > > Using a case class as a key doesn't seem to work properly on Spark 1.0.0 > A minimal example: > case class P(name:String) > val ps = Array(P("alice"), P("bob"), P("charly"), P("bob")) > sc.parallelize(ps).map(x=> (x,1)).reduceByKey((x,y) => x+y).collect > [Spark shell local mode] res : Array[(P, Int)] = Array((P(bob),1), > (P(bob),1), (P(abe),1), (P(charly),1)) > In contrast to the expected behavior, that should be equivalent to: > sc.parallelize(ps).map(x=> (x.name,1)).reduceByKey((x,y) => x+y).collect > Array[(String, Int)] = Array((charly,1), (abe,1), (bob,2)) > groupByKey and distinct also present the same behavior. -- This message was sent by Atlassian JIRA (v6.3.4#6332) --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org