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author | Stephen Haberman <stephen@exigencecorp.com> | 2013-03-13 17:17:34 -0500 |
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committer | Stephen Haberman <stephen@exigencecorp.com> | 2013-03-13 17:17:34 -0500 |
commit | 63fe22558791e6a511eb1f48efb88e2afdf77659 (patch) | |
tree | fd0e482ff43d984cb280acd0647e9398aac6934b /core | |
parent | cbf8f0d4dda41ffd45855eab8401fda9b64168cd (diff) | |
download | spark-63fe22558791e6a511eb1f48efb88e2afdf77659.tar.gz spark-63fe22558791e6a511eb1f48efb88e2afdf77659.tar.bz2 spark-63fe22558791e6a511eb1f48efb88e2afdf77659.zip |
Simplify SubtractedRDD in preparation from subtractByKey.
Diffstat (limited to 'core')
-rw-r--r-- | core/src/main/scala/spark/PairRDDFunctions.scala | 2 | ||||
-rw-r--r-- | core/src/main/scala/spark/RDD.scala | 24 | ||||
-rw-r--r-- | core/src/main/scala/spark/rdd/SubtractedRDD.scala | 78 |
3 files changed, 58 insertions, 46 deletions
diff --git a/core/src/main/scala/spark/PairRDDFunctions.scala b/core/src/main/scala/spark/PairRDDFunctions.scala index e7408e4352..1bd1741a71 100644 --- a/core/src/main/scala/spark/PairRDDFunctions.scala +++ b/core/src/main/scala/spark/PairRDDFunctions.scala @@ -639,6 +639,8 @@ class OrderedRDDFunctions[K <% Ordered[K]: ClassManifest, V: ClassManifest]( } }, true) } + + // def subtractByKey(other: RDD[K]): RDD[(K,V)] = subtract(other, partitioner.getOrElse(new HashPartitioner(partitions.size))) } private[spark] diff --git a/core/src/main/scala/spark/RDD.scala b/core/src/main/scala/spark/RDD.scala index 584efa8adf..3451136fd4 100644 --- a/core/src/main/scala/spark/RDD.scala +++ b/core/src/main/scala/spark/RDD.scala @@ -408,8 +408,24 @@ abstract class RDD[T: ClassManifest]( * Uses `this` partitioner/partition size, because even if `other` is huge, the resulting * RDD will be <= us. */ - def subtract(other: RDD[T]): RDD[T] = - subtract(other, partitioner.getOrElse(new HashPartitioner(partitions.size))) + def subtract(other: RDD[T]): RDD[T] = { + // If we do have a partitioner, our T is really (K, V), and we'll need to + // unwrap the (T, null) that subtract does to get back to the K + val rdd = subtract(other, partitioner match { + case None => new HashPartitioner(partitions.size) + case Some(p) => new Partitioner() { + override def numPartitions = p.numPartitions + override def getPartition(k: Any) = p.getPartition(k.asInstanceOf[(Any, _)]._1) + } + }) + // Hacky, but if we did have a partitioner, we can keep using it + new RDD[T](rdd) { + override def getPartitions = rdd.partitions + override def getDependencies = rdd.dependencies + override def compute(split: Partition, context: TaskContext) = rdd.compute(split, context) + override val partitioner = RDD.this.partitioner + } + } /** * Return an RDD with the elements from `this` that are not in `other`. @@ -420,7 +436,9 @@ abstract class RDD[T: ClassManifest]( /** * Return an RDD with the elements from `this` that are not in `other`. */ - def subtract(other: RDD[T], p: Partitioner): RDD[T] = new SubtractedRDD[T](this, other, p) + def subtract(other: RDD[T], p: Partitioner): RDD[T] = { + new SubtractedRDD[T, Any](this.map((_, null)), other.map((_, null)), p).keys + } /** * Reduces the elements of this RDD using the specified commutative and associative binary operator. diff --git a/core/src/main/scala/spark/rdd/SubtractedRDD.scala b/core/src/main/scala/spark/rdd/SubtractedRDD.scala index 43ec90cac5..1bc84f7e1e 100644 --- a/core/src/main/scala/spark/rdd/SubtractedRDD.scala +++ b/core/src/main/scala/spark/rdd/SubtractedRDD.scala @@ -1,7 +1,8 @@ package spark.rdd -import java.util.{HashSet => JHashSet} +import java.util.{HashMap => JHashMap} import scala.collection.JavaConversions._ +import scala.collection.mutable.ArrayBuffer import spark.RDD import spark.Partitioner import spark.Dependency @@ -27,39 +28,20 @@ import spark.OneToOneDependency * you can use `rdd1`'s partitioner/partition size and not worry about running * out of memory because of the size of `rdd2`. */ -private[spark] class SubtractedRDD[T: ClassManifest]( - @transient var rdd1: RDD[T], - @transient var rdd2: RDD[T], - part: Partitioner) extends RDD[T](rdd1.context, Nil) { +private[spark] class SubtractedRDD[K: ClassManifest, V: ClassManifest]( + @transient var rdd1: RDD[(K, V)], + @transient var rdd2: RDD[(K, V)], + part: Partitioner) extends RDD[(K, V)](rdd1.context, Nil) { override def getDependencies: Seq[Dependency[_]] = { Seq(rdd1, rdd2).map { rdd => - if (rdd.partitioner == Some(part)) { - logInfo("Adding one-to-one dependency with " + rdd) - new OneToOneDependency(rdd) - } else { - logInfo("Adding shuffle dependency with " + rdd) - val mapSideCombinedRDD = rdd.mapPartitions(i => { - val set = new JHashSet[T]() - while (i.hasNext) { - set.add(i.next) - } - set.iterator - }, true) - // ShuffleDependency requires a tuple (k, v), which it will partition by k. - // We need this to partition to map to the same place as the k for - // OneToOneDependency, which means: - // - for already-tupled RDD[(A, B)], into getPartition(a) - // - for non-tupled RDD[C], into getPartition(c) - val part2 = new Partitioner() { - def numPartitions = part.numPartitions - def getPartition(key: Any) = key match { - case (k, v) => part.getPartition(k) - case k => part.getPartition(k) - } - } - new ShuffleDependency(mapSideCombinedRDD.map((_, null)), part2) - } + if (rdd.partitioner == Some(part)) { + logInfo("Adding one-to-one dependency with " + rdd) + new OneToOneDependency(rdd) + } else { + logInfo("Adding shuffle dependency with " + rdd) + new ShuffleDependency(rdd, part) + } } } @@ -81,22 +63,32 @@ private[spark] class SubtractedRDD[T: ClassManifest]( override val partitioner = Some(part) - override def compute(p: Partition, context: TaskContext): Iterator[T] = { + override def compute(p: Partition, context: TaskContext): Iterator[(K, V)] = { val partition = p.asInstanceOf[CoGroupPartition] - val set = new JHashSet[T] - def integrate(dep: CoGroupSplitDep, op: T => Unit) = dep match { + val map = new JHashMap[K, ArrayBuffer[V]] + def getSeq(k: K): ArrayBuffer[V] = { + val seq = map.get(k) + if (seq != null) { + seq + } else { + val seq = new ArrayBuffer[V]() + map.put(k, seq) + seq + } + } + def integrate(dep: CoGroupSplitDep, op: ((K, V)) => Unit) = dep match { case NarrowCoGroupSplitDep(rdd, _, itsSplit) => - for (k <- rdd.iterator(itsSplit, context)) - op(k.asInstanceOf[T]) + for (t <- rdd.iterator(itsSplit, context)) + op(t.asInstanceOf[(K, V)]) case ShuffleCoGroupSplitDep(shuffleId) => - for ((k, _) <- SparkEnv.get.shuffleFetcher.fetch(shuffleId, partition.index, context.taskMetrics)) - op(k.asInstanceOf[T]) + for (t <- SparkEnv.get.shuffleFetcher.fetch(shuffleId, partition.index, context.taskMetrics)) + op(t.asInstanceOf[(K, V)]) } - // the first dep is rdd1; add all keys to the set - integrate(partition.deps(0), set.add) - // the second dep is rdd2; remove all of its keys from the set - integrate(partition.deps(1), set.remove) - set.iterator + // the first dep is rdd1; add all values to the map + integrate(partition.deps(0), t => getSeq(t._1) += t._2) + // the second dep is rdd2; remove all of its keys + integrate(partition.deps(1), t => map.remove(t._1) ) + map.iterator.map { t => t._2.iterator.map { (t._1, _) } }.flatten } override def clearDependencies() { |