Sure, just add ".toList.sorted" in there. Putting together in one big expression:
val rdd = sc.parallelize(List(List(1,2,3,4,5),List(6,7,8,9,10))) val result = rdd.flatMap(_.zipWithIndex).groupBy(_._2).values.map(_.map(_._1).toList.sorted) List(2, 7) List(1, 6) List(4, 9) List(3, 8) List(5, 10) On Tue, Aug 12, 2014 at 8:58 AM, Kevin Jung <itsjb.j...@samsung.com> wrote: > Thanks for your answer. > Yes, I want to transpose data. > At this point, I have one more question. > I tested it with > RDD1 > List(1, 2, 3, 4, 5) > List(6, 7, 8, 9, 10) > List(11, 12, 13, 14, 15) > List(16, 17, 18, 19, 20) > > And the result is... > ArrayBuffer(11, 1, 16, 6) > ArrayBuffer(2, 12, 7, 17) > ArrayBuffer(3, 13, 18, 8) > ArrayBuffer(9, 19, 4, 14) > ArrayBuffer(15, 20, 10, 5) > > It collects well but the order is shuffled. > Can I maintain the order? --------------------------------------------------------------------- To unsubscribe, e-mail: user-unsubscr...@spark.apache.org For additional commands, e-mail: user-h...@spark.apache.org
