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package spark.rdd
import spark.{OneToOneDependency, RDD, SparkContext, Split, TaskContext}
import java.io.{ObjectOutputStream, IOException}
private[spark] class ZippedSplit[T: ClassManifest, U: ClassManifest](
idx: Int,
@transient rdd1: RDD[T],
@transient rdd2: RDD[U]
) extends Split {
var split1 = rdd1.splits(idx)
var split2 = rdd1.splits(idx)
override val index: Int = idx
def splits = (split1, split2)
@throws(classOf[IOException])
private def writeObject(oos: ObjectOutputStream) {
// Update the reference to parent split at the time of task serialization
split1 = rdd1.splits(idx)
split2 = rdd2.splits(idx)
oos.defaultWriteObject()
}
}
class ZippedRDD[T: ClassManifest, U: ClassManifest](
sc: SparkContext,
var rdd1: RDD[T],
var rdd2: RDD[U])
extends RDD[(T, U)](sc, List(new OneToOneDependency(rdd1), new OneToOneDependency(rdd2)))
with Serializable {
// TODO: FIX THIS.
@transient
var splits_ : Array[Split] = {
if (rdd1.splits.size != rdd2.splits.size) {
throw new IllegalArgumentException("Can't zip RDDs with unequal numbers of partitions")
}
val array = new Array[Split](rdd1.splits.size)
for (i <- 0 until rdd1.splits.size) {
array(i) = new ZippedSplit(i, rdd1, rdd2)
}
array
}
override def getSplits = splits_
override def compute(s: Split, context: TaskContext): Iterator[(T, U)] = {
val (split1, split2) = s.asInstanceOf[ZippedSplit[T, U]].splits
rdd1.iterator(split1, context).zip(rdd2.iterator(split2, context))
}
override def getPreferredLocations(s: Split): Seq[String] = {
val (split1, split2) = s.asInstanceOf[ZippedSplit[T, U]].splits
rdd1.preferredLocations(split1).intersect(rdd2.preferredLocations(split2))
}
override def clearDependencies() {
splits_ = null
rdd1 = null
rdd2 = null
}
}
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