zhengruifeng commented on code in PR #37728: URL: https://github.com/apache/spark/pull/37728#discussion_r960290810
########## core/src/main/scala/org/apache/spark/rdd/RDD.scala: ########## @@ -1523,22 +1523,21 @@ abstract class RDD[T: ClassTag]( * @return an array of top elements */ def takeOrdered(num: Int)(implicit ord: Ordering[T]): Array[T] = withScope { - if (num == 0) { + if (num == 0 || this.getNumPartitions == 0) { Array.empty } else { - val mapRDDs = mapPartitions { items => - // Priority keeps the largest elements, so let's reverse the ordering. - val queue = new BoundedPriorityQueue[T](num)(ord.reverse) - queue ++= collectionUtils.takeOrdered(items, num)(ord) - Iterator.single(queue) - } - if (mapRDDs.partitions.length == 0) { - Array.empty - } else { - mapRDDs.reduce { (queue1, queue2) => - queue1 ++= queue2 - queue1 - }.toArray.sorted(ord) + this.mapPartitionsWithIndex { case (pid, iter) => + if (iter.nonEmpty) { + // Priority keeps the largest elements, so let's reverse the ordering. + Iterator.single(collectionUtils.takeOrdered(iter, num)(ord).toArray) + } else if (pid == 0) { + // make sure partition 0 always returns an array to avoid reduce on empty RDD + Iterator.single(Array.empty[T]) + } else { + Iterator.empty + } + }.reduce { (array1, array2) => + collectionUtils.mergeOrdered[T](Seq(array1, array2))(ord).take(num).toArray Review Comment: if the concern is that one new array will be created at each merge, I guess we can switch to an [in-place merge sort](https://www.techiedelight.com/inplace-merge-two-sorted-arrays/) -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For queries about this service, please contact Infrastructure at: us...@infra.apache.org --------------------------------------------------------------------- To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org