Repository: spark Updated Branches: refs/heads/branch-1.0 8097bb281 -> 5d696996d
SPARK-1770: Load balance elements when repartitioning. This patch adds better balancing when performing a repartition of an RDD. Previously the elements in the RDD were hash partitioned, meaning if the RDD was skewed certain partitions would end up being very large. This commit adds load balancing of elements across the repartitioned RDD splits. The load balancing is not perfect: a given output partition can have up to N more elements than the average if there are N input partitions. However, some randomization is used to minimize the probabiliy that this happens. Author: Patrick Wendell <[email protected]> Closes #727 from pwendell/load-balance and squashes the following commits: f9da752 [Patrick Wendell] Response to Matei's feedback acfa46a [Patrick Wendell] SPARK-1770: Load balance elements when repartitioning. (cherry picked from commit 7d9cc9214bd06495f6838e355331dd2b5f1f7407) Signed-off-by: Patrick Wendell <[email protected]> Project: http://git-wip-us.apache.org/repos/asf/spark/repo Commit: http://git-wip-us.apache.org/repos/asf/spark/commit/5d696996 Tree: http://git-wip-us.apache.org/repos/asf/spark/tree/5d696996 Diff: http://git-wip-us.apache.org/repos/asf/spark/diff/5d696996 Branch: refs/heads/branch-1.0 Commit: 5d696996db175b0b40fc3f5a701331ea4ac7d96b Parents: 8097bb2 Author: Patrick Wendell <[email protected]> Authored: Sun May 11 17:11:55 2014 -0700 Committer: Patrick Wendell <[email protected]> Committed: Sun May 11 17:12:17 2014 -0700 ---------------------------------------------------------------------- .../main/scala/org/apache/spark/rdd/RDD.scala | 15 +++++++-- .../scala/org/apache/spark/rdd/RDDSuite.scala | 33 ++++++++++++++++++++ 2 files changed, 46 insertions(+), 2 deletions(-) ---------------------------------------------------------------------- http://git-wip-us.apache.org/repos/asf/spark/blob/5d696996/core/src/main/scala/org/apache/spark/rdd/RDD.scala ---------------------------------------------------------------------- diff --git a/core/src/main/scala/org/apache/spark/rdd/RDD.scala b/core/src/main/scala/org/apache/spark/rdd/RDD.scala index a1ca612..aa03e92 100644 --- a/core/src/main/scala/org/apache/spark/rdd/RDD.scala +++ b/core/src/main/scala/org/apache/spark/rdd/RDD.scala @@ -328,11 +328,22 @@ abstract class RDD[T: ClassTag]( def coalesce(numPartitions: Int, shuffle: Boolean = false)(implicit ord: Ordering[T] = null) : RDD[T] = { if (shuffle) { + /** Distributes elements evenly across output partitions, starting from a random partition. */ + def distributePartition(index: Int, items: Iterator[T]): Iterator[(Int, T)] = { + var position = (new Random(index)).nextInt(numPartitions) + items.map { t => + // Note that the hash code of the key will just be the key itself. The HashPartitioner + // will mod it with the number of total partitions. + position = position + 1 + (position, t) + } + } + // include a shuffle step so that our upstream tasks are still distributed new CoalescedRDD( - new ShuffledRDD[T, Null, (T, Null)](map(x => (x, null)), + new ShuffledRDD[Int, T, (Int, T)](mapPartitionsWithIndex(distributePartition), new HashPartitioner(numPartitions)), - numPartitions).keys + numPartitions).values } else { new CoalescedRDD(this, numPartitions) } http://git-wip-us.apache.org/repos/asf/spark/blob/5d696996/core/src/test/scala/org/apache/spark/rdd/RDDSuite.scala ---------------------------------------------------------------------- diff --git a/core/src/test/scala/org/apache/spark/rdd/RDDSuite.scala b/core/src/test/scala/org/apache/spark/rdd/RDDSuite.scala index 8da9a0d..e686068 100644 --- a/core/src/test/scala/org/apache/spark/rdd/RDDSuite.scala +++ b/core/src/test/scala/org/apache/spark/rdd/RDDSuite.scala @@ -202,6 +202,39 @@ class RDDSuite extends FunSuite with SharedSparkContext { assert(repartitioned2.collect().toSet === (1 to 1000).toSet) } + test("repartitioned RDDs perform load balancing") { + // Coalesce partitions + val input = Array.fill(1000)(1) + val initialPartitions = 10 + val data = sc.parallelize(input, initialPartitions) + + val repartitioned1 = data.repartition(2) + assert(repartitioned1.partitions.size == 2) + val partitions1 = repartitioned1.glom().collect() + // some noise in balancing is allowed due to randomization + assert(math.abs(partitions1(0).length - 500) < initialPartitions) + assert(math.abs(partitions1(1).length - 500) < initialPartitions) + assert(repartitioned1.collect() === input) + + def testSplitPartitions(input: Seq[Int], initialPartitions: Int, finalPartitions: Int) { + val data = sc.parallelize(input, initialPartitions) + val repartitioned = data.repartition(finalPartitions) + assert(repartitioned.partitions.size === finalPartitions) + val partitions = repartitioned.glom().collect() + // assert all elements are present + assert(repartitioned.collect().sortWith(_ > _).toSeq === input.toSeq.sortWith(_ > _).toSeq) + // assert no bucket is overloaded + for (partition <- partitions) { + val avg = input.size / finalPartitions + val maxPossible = avg + initialPartitions + assert(partition.length <= maxPossible) + } + } + + testSplitPartitions(Array.fill(100)(1), 10, 20) + testSplitPartitions(Array.fill(10000)(1) ++ Array.fill(10000)(2), 20, 100) + } + test("coalesced RDDs") { val data = sc.parallelize(1 to 10, 10)
