diff options
| author | Liwei Lin <lwlin7@gmail.com> | 2016-09-07 10:04:00 +0100 |
|---|---|---|
| committer | Sean Owen <sowen@cloudera.com> | 2016-09-07 10:04:00 +0100 |
| commit | 3ce3a282c8463408f9a2db93c1748e8df8087e07 (patch) | |
| tree | 7814535174f3ef7294cfd20e4dfeae28fecd4693 /mllib/src/main | |
| parent | 9fccde4ff80fb0fd65a9e90eb3337965e4349de4 (diff) | |
| download | spark-3ce3a282c8463408f9a2db93c1748e8df8087e07.tar.gz spark-3ce3a282c8463408f9a2db93c1748e8df8087e07.tar.bz2 spark-3ce3a282c8463408f9a2db93c1748e8df8087e07.zip | |
[SPARK-17359][SQL][MLLIB] Use ArrayBuffer.+=(A) instead of ArrayBuffer.append(A) in performance critical paths
## What changes were proposed in this pull request?
We should generally use `ArrayBuffer.+=(A)` rather than `ArrayBuffer.append(A)`, because `append(A)` would involve extra boxing / unboxing.
## How was this patch tested?
N/A
Author: Liwei Lin <lwlin7@gmail.com>
Closes #14914 from lw-lin/append_to_plus_eq_v2.
Diffstat (limited to 'mllib/src/main')
3 files changed, 4 insertions, 4 deletions
diff --git a/mllib/src/main/scala/org/apache/spark/mllib/linalg/Matrices.scala b/mllib/src/main/scala/org/apache/spark/mllib/linalg/Matrices.scala index 8659cea4b8..6642999a21 100644 --- a/mllib/src/main/scala/org/apache/spark/mllib/linalg/Matrices.scala +++ b/mllib/src/main/scala/org/apache/spark/mllib/linalg/Matrices.scala @@ -1128,7 +1128,7 @@ object Matrices { val data = new ArrayBuffer[(Int, Int, Double)]() dnMat.foreachActive { (i, j, v) => if (v != 0.0) { - data.append((i, j + startCol, v)) + data += Tuple3(i, j + startCol, v) } } startCol += nCols @@ -1198,7 +1198,7 @@ object Matrices { val data = new ArrayBuffer[(Int, Int, Double)]() dnMat.foreachActive { (i, j, v) => if (v != 0.0) { - data.append((i + startRow, j, v)) + data += Tuple3(i + startRow, j, v) } } startRow += nRows diff --git a/mllib/src/main/scala/org/apache/spark/mllib/linalg/distributed/BlockMatrix.scala b/mllib/src/main/scala/org/apache/spark/mllib/linalg/distributed/BlockMatrix.scala index 9782350587..ff1068417d 100644 --- a/mllib/src/main/scala/org/apache/spark/mllib/linalg/distributed/BlockMatrix.scala +++ b/mllib/src/main/scala/org/apache/spark/mllib/linalg/distributed/BlockMatrix.scala @@ -257,7 +257,7 @@ class BlockMatrix @Since("1.3.0") ( val colStart = blockColIndex.toLong * colsPerBlock val entryValues = new ArrayBuffer[MatrixEntry]() mat.foreachActive { (i, j, v) => - if (v != 0.0) entryValues.append(new MatrixEntry(rowStart + i, colStart + j, v)) + if (v != 0.0) entryValues += new MatrixEntry(rowStart + i, colStart + j, v) } entryValues } diff --git a/mllib/src/main/scala/org/apache/spark/mllib/optimization/GradientDescent.scala b/mllib/src/main/scala/org/apache/spark/mllib/optimization/GradientDescent.scala index f372355005..123e0bb3e6 100644 --- a/mllib/src/main/scala/org/apache/spark/mllib/optimization/GradientDescent.scala +++ b/mllib/src/main/scala/org/apache/spark/mllib/optimization/GradientDescent.scala @@ -252,7 +252,7 @@ object GradientDescent extends Logging { * lossSum is computed using the weights from the previous iteration * and regVal is the regularization value computed in the previous iteration as well. */ - stochasticLossHistory.append(lossSum / miniBatchSize + regVal) + stochasticLossHistory += lossSum / miniBatchSize + regVal val update = updater.compute( weights, Vectors.fromBreeze(gradientSum / miniBatchSize.toDouble), stepSize, i, regParam) |