Github user mengxr commented on a diff in the pull request:
https://github.com/apache/spark/pull/493#discussion_r12080905
--- Diff:
mllib/src/main/scala/org/apache/spark/mllib/recommendation/ALS.scala ---
@@ -708,6 +709,123 @@ object ALS {
trainImplicit(ratings, rank, iterations, 0.01, -1, 1.0)
}
+ @DeveloperApi
+ case class IterationCost(inboundBytes: Double, computation: Double,
outboundBytes: Double)
+
+ /**
+ * :: DeveloperApi ::
+ * Given an RDD of ratings, a rank, and two partitioners, compute rough
estimates of the
+ * computation time and communication cost of one iteration of ALS.
Returns a pair of pairs of
+ * Maps. The first pair of maps represents computation time in
unspecified units. The second
+ * pair of maps represents communication cost in uncompressed bytes.
The first element of each
+ * pair is the cost attributable to user partitioning, while the second
is the cost attributable
+ * to product partitioning.
+ *
+ * @param ratings RDD of Rating objects
+ * @param rank number of features to use
+ * @param userPartitioner partitioner for partitioning users
+ * @param productPartitioner partitioner for partitioning products
+ */
+ @DeveloperApi
+ def estimateCost(ratings: RDD[Rating], rank: Int, userPartitioner:
Partitioner,
+ productPartitioner: Partitioner):
+ (Map[Int, IterationCost], Map[Int, IterationCost]) = {
+ // user partition -> set of products
+ val utalk = ratings.mapPartitions(x => {
+ val ht = new mutable.HashSet[(Int, Int)]()
+ while (x.hasNext) {
+ val rat = x.next()
+ val u = userPartitioner.getPartition(rat.user)
+ val p = rat.product
+ ht += ((u, p))
--- End diff --
So you want to de-dup? It is safe to assume that the (u, p) pairs are
different from each other.
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