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author | Stephen Haberman <stephen@exigencecorp.com> | 2013-03-22 08:54:44 -0500 |
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committer | Stephen Haberman <stephen@exigencecorp.com> | 2013-03-22 08:54:44 -0500 |
commit | 1c67c7dfd1660dd39226742eedcb2948ab1445d0 (patch) | |
tree | 6d20b0585e83a60f1a258372d53d12fca01656eb /core | |
parent | ca4d083ec825aa674fdd7d1dcd52a99ef8dcdf8b (diff) | |
download | spark-1c67c7dfd1660dd39226742eedcb2948ab1445d0.tar.gz spark-1c67c7dfd1660dd39226742eedcb2948ab1445d0.tar.bz2 spark-1c67c7dfd1660dd39226742eedcb2948ab1445d0.zip |
Add a shuffle parameter to coalesce.
This is useful for when you want just 1 output file (part-00000) but
still up the upstream RDD to be computed in parallel.
Diffstat (limited to 'core')
-rw-r--r-- | core/src/main/scala/spark/RDD.scala | 10 | ||||
-rw-r--r-- | core/src/main/scala/spark/api/java/JavaDoubleRDD.scala | 6 | ||||
-rw-r--r-- | core/src/main/scala/spark/api/java/JavaPairRDD.scala | 8 | ||||
-rw-r--r-- | core/src/main/scala/spark/api/java/JavaRDD.scala | 6 | ||||
-rw-r--r-- | core/src/test/scala/spark/RDDSuite.scala | 6 |
5 files changed, 33 insertions, 3 deletions
diff --git a/core/src/main/scala/spark/RDD.scala b/core/src/main/scala/spark/RDD.scala index 9bd8a0f98d..0cd904f89d 100644 --- a/core/src/main/scala/spark/RDD.scala +++ b/core/src/main/scala/spark/RDD.scala @@ -31,6 +31,7 @@ import spark.rdd.MapPartitionsRDD import spark.rdd.MapPartitionsWithIndexRDD import spark.rdd.PipedRDD import spark.rdd.SampledRDD +import spark.rdd.ShuffledRDD import spark.rdd.SubtractedRDD import spark.rdd.UnionRDD import spark.rdd.ZippedRDD @@ -237,7 +238,14 @@ abstract class RDD[T: ClassManifest]( /** * Return a new RDD that is reduced into `numPartitions` partitions. */ - def coalesce(numPartitions: Int): RDD[T] = new CoalescedRDD(this, numPartitions) + def coalesce(numPartitions: Int, shuffle: Boolean = false): RDD[T] = { + if (shuffle) { + // include a shuffle step so that are upstream tasks are still distributed + new CoalescedRDD(new ShuffledRDD(map(x => (x, null)), new HashPartitioner(numPartitions)), numPartitions).keys + } else { + new CoalescedRDD(this, numPartitions) + } + } /** * Return a sampled subset of this RDD. diff --git a/core/src/main/scala/spark/api/java/JavaDoubleRDD.scala b/core/src/main/scala/spark/api/java/JavaDoubleRDD.scala index ba00b6a844..26cbb1a641 100644 --- a/core/src/main/scala/spark/api/java/JavaDoubleRDD.scala +++ b/core/src/main/scala/spark/api/java/JavaDoubleRDD.scala @@ -58,6 +58,12 @@ class JavaDoubleRDD(val srdd: RDD[scala.Double]) extends JavaRDDLike[Double, Jav def coalesce(numPartitions: Int): JavaDoubleRDD = fromRDD(srdd.coalesce(numPartitions)) /** + * Return a new RDD that is reduced into `numPartitions` partitions. + */ + def coalesce(numPartitions: Int, shuffle: java.lang.Boolean): JavaDoubleRDD = + fromRDD(srdd.coalesce(numPartitions, shuffle)) + + /** * Return an RDD with the elements from `this` that are not in `other`. * * Uses `this` partitioner/partition size, because even if `other` is huge, the resulting diff --git a/core/src/main/scala/spark/api/java/JavaPairRDD.scala b/core/src/main/scala/spark/api/java/JavaPairRDD.scala index 49aaabf835..9ce77e8e84 100644 --- a/core/src/main/scala/spark/api/java/JavaPairRDD.scala +++ b/core/src/main/scala/spark/api/java/JavaPairRDD.scala @@ -66,7 +66,13 @@ class JavaPairRDD[K, V](val rdd: RDD[(K, V)])(implicit val kManifest: ClassManif /** * Return a new RDD that is reduced into `numPartitions` partitions. */ - def coalesce(numPartitions: Int): JavaPairRDD[K, V] = new JavaPairRDD[K, V](rdd.coalesce(numPartitions)) + def coalesce(numPartitions: Int): JavaPairRDD[K, V] = fromRDD(rdd.coalesce(numPartitions)) + + /** + * Return a new RDD that is reduced into `numPartitions` partitions. + */ + def coalesce(numPartitions: Int, shuffle: java.lang.Boolean): JavaPairRDD[K, V] = + fromRDD(rdd.coalesce(numPartitions, shuffle)) /** * Return a sampled subset of this RDD. diff --git a/core/src/main/scala/spark/api/java/JavaRDD.scala b/core/src/main/scala/spark/api/java/JavaRDD.scala index 3016888898..7223dbbe64 100644 --- a/core/src/main/scala/spark/api/java/JavaRDD.scala +++ b/core/src/main/scala/spark/api/java/JavaRDD.scala @@ -44,6 +44,12 @@ JavaRDDLike[T, JavaRDD[T]] { def coalesce(numPartitions: Int): JavaRDD[T] = rdd.coalesce(numPartitions) /** + * Return a new RDD that is reduced into `numPartitions` partitions. + */ + def coalesce(numPartitions: Int, shuffle: java.lang.Boolean): JavaRDD[T] = + rdd.coalesce(numPartitions, shuffle) + + /** * Return a sampled subset of this RDD. */ def sample(withReplacement: Boolean, fraction: Double, seed: Int): JavaRDD[T] = diff --git a/core/src/test/scala/spark/RDDSuite.scala b/core/src/test/scala/spark/RDDSuite.scala index 9739ba869b..bcbb472f6c 100644 --- a/core/src/test/scala/spark/RDDSuite.scala +++ b/core/src/test/scala/spark/RDDSuite.scala @@ -3,7 +3,7 @@ package spark import scala.collection.mutable.HashMap import org.scalatest.FunSuite import spark.SparkContext._ -import spark.rdd.{CoalescedRDD, PartitionPruningRDD} +import spark.rdd.{CoalescedRDD, PartitionPruningRDD, ShuffledRDD} class RDDSuite extends FunSuite with LocalSparkContext { @@ -154,6 +154,10 @@ class RDDSuite extends FunSuite with LocalSparkContext { assert(coalesced4.collect().toList === (1 to 10).toList) assert(coalesced4.glom().collect().map(_.toList).toList === (1 to 10).map(x => List(x)).toList) + + // we can optionally shuffle to keep the upstream parallel + val coalesced5 = data.coalesce(1, shuffle = true) + assert(coalesced5.dependencies.head.rdd.dependencies.head.rdd.asInstanceOf[ShuffledRDD[_, _]] ne null) } test("zipped RDDs") { |