aboutsummaryrefslogtreecommitdiff
diff options
context:
space:
mode:
-rw-r--r--mllib/src/main/scala/org/apache/spark/mllib/recommendation/ALS.scala13
1 files changed, 11 insertions, 2 deletions
diff --git a/mllib/src/main/scala/org/apache/spark/mllib/recommendation/ALS.scala b/mllib/src/main/scala/org/apache/spark/mllib/recommendation/ALS.scala
index 102742c7c5..1f5c746a34 100644
--- a/mllib/src/main/scala/org/apache/spark/mllib/recommendation/ALS.scala
+++ b/mllib/src/main/scala/org/apache/spark/mllib/recommendation/ALS.scala
@@ -269,7 +269,7 @@ class ALS private (
private def computeYtY(factors: RDD[(Int, Array[Array[Double]])]) = {
val n = rank * (rank + 1) / 2
val LYtY = factors.values.aggregate(new DoubleMatrix(n))( seqOp = (L, Y) => {
- Y.foreach(y => dspr(1.0, new DoubleMatrix(y), L))
+ Y.foreach(y => dspr(1.0, wrapDoubleArray(y), L))
L
}, combOp = (L1, L2) => {
L1.addi(L2)
@@ -305,6 +305,15 @@ class ALS private (
}
/**
+ * Wrap a double array in a DoubleMatrix without creating garbage.
+ * This is a temporary fix for jblas 1.2.3; it should be safe to move back to the
+ * DoubleMatrix(double[]) constructor come jblas 1.2.4.
+ */
+ private def wrapDoubleArray(v: Array[Double]): DoubleMatrix = {
+ new DoubleMatrix(v.length, 1, v: _*)
+ }
+
+ /**
* Flatten out blocked user or product factors into an RDD of (id, factor vector) pairs
*/
private def unblockFactors(blockedFactors: RDD[(Int, Array[Array[Double]])],
@@ -457,7 +466,7 @@ class ALS private (
// block
for (productBlock <- 0 until numBlocks) {
for (p <- 0 until blockFactors(productBlock).length) {
- val x = new DoubleMatrix(blockFactors(productBlock)(p))
+ val x = wrapDoubleArray(blockFactors(productBlock)(p))
tempXtX.fill(0.0)
dspr(1.0, x, tempXtX)
val (us, rs) = inLinkBlock.ratingsForBlock(productBlock)(p)