Github user mengxr commented on a diff in the pull request:
https://github.com/apache/spark/pull/5855#discussion_r43822533
--- Diff: mllib/src/main/scala/org/apache/spark/mllib/rdd/SlidingRDD.scala
---
@@ -66,36 +69,54 @@ class SlidingRDD[T: ClassTag](@transient val parent:
RDD[T], val windowSize: Int
if (n == 0) {
Array.empty
} else if (n == 1) {
- Array(new SlidingRDDPartition[T](0, parentPartitions(0), Seq.empty))
+ Array(new SlidingRDDPartition[T](0, parentPartitions(0), Seq.empty,
0))
} else {
val n1 = n - 1
- val w1 = windowSize - 1
- // Get the first w1 items of each partition, starting from the
second partition.
- val nextHeads =
- parent.context.runJob(parent, (iter: Iterator[T]) =>
iter.take(w1).toArray, 1 until n)
+ // Get partitions sizes
+ val sizes =
+ parent.context.runJob(parent, (iter: Iterator[T]) => iter.length,
0 until n)
--- End diff --
If `step > 1`, in a single Spark job, we can collect the following:
1. the first `w1` elements from each partition (except the first one)
2. the size of each partition
Then we can compute the offset for each partition.
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