44 lines
1.3 KiB
Scala
44 lines
1.3 KiB
Scala
package spark
|
|
|
|
@serializable class CartesianSplit(idx: Int, val s1: Split, val s2: Split)
|
|
extends Split {
|
|
override val index = idx
|
|
}
|
|
|
|
@serializable
|
|
class CartesianRDD[T: ClassManifest, U:ClassManifest](
|
|
sc: SparkContext, rdd1: RDD[T], rdd2: RDD[U])
|
|
extends RDD[Pair[T, U]](sc) {
|
|
val numSplitsInRdd2 = rdd2.splits.size
|
|
|
|
@transient val splits_ = {
|
|
// create the cross product split
|
|
val array = new Array[Split](rdd1.splits.size * rdd2.splits.size)
|
|
for (s1 <- rdd1.splits; s2 <- rdd2.splits) {
|
|
val idx = s1.index * numSplitsInRdd2 + s2.index
|
|
array(idx) = new CartesianSplit(idx, s1, s2)
|
|
}
|
|
array
|
|
}
|
|
|
|
override def splits = splits_.asInstanceOf[Array[Split]]
|
|
|
|
override def preferredLocations(split: Split) = {
|
|
val currSplit = split.asInstanceOf[CartesianSplit]
|
|
rdd1.preferredLocations(currSplit.s1) ++ rdd2.preferredLocations(currSplit.s2)
|
|
}
|
|
|
|
override def compute(split: Split) = {
|
|
val currSplit = split.asInstanceOf[CartesianSplit]
|
|
for (x <- rdd1.iterator(currSplit.s1); y <- rdd2.iterator(currSplit.s2)) yield (x, y)
|
|
}
|
|
|
|
override val dependencies = List(
|
|
new NarrowDependency(rdd1) {
|
|
def getParents(id: Int): Seq[Int] = List(id / numSplitsInRdd2)
|
|
},
|
|
new NarrowDependency(rdd2) {
|
|
def getParents(id: Int): Seq[Int] = List(id % numSplitsInRdd2)
|
|
}
|
|
)
|
|
} |