ODIn/spark-instrumented-optimizer
1
0
Fork 0
Code Issues Pull requests Projects Releases Wiki Activity

[SPARK-28159][ML][FOLLOWUP] fix typo & (0 until v.size).toList => List.range(0, v.size)

Browse source 
## What changes were proposed in this pull request?
fix typo in spark-28159
`transfromWithMean` -> `transformWithMean`

## How was this patch tested?
existing test

Closes #25129 from zhengruifeng/to_ml_vec_cleanup.

Authored-by: zhengruifeng <ruifengz@foxmail.com>
Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
This commit is contained in:
zhengruifeng 2019-07-12 11:00:16 -07:00 committed by Dongjoon Hyun
parent 687dd4eb55
commit aa41dcea4a
3 changed files with 4 additions and 4 deletions
Show stats Download patch file Download diff file Expand all files Collapse all files

2
mllib/src/main/scala/org/apache/spark/ml/clustering/LDA.scala
View file

@ -490,7 +490,7 @@ abstract class LDAModel private[ml] (
Vectors.zeros(k) Vectors.zeros(k)
} else { } else {
val (ids: List[Int], cts: Array[Double]) = vector match { val (ids: List[Int], cts: Array[Double]) = vector match {
case v: DenseVector => ((0 until v.size).toList, v.values) case v: DenseVector => (List.range(0, v.size), v.values)
case v: SparseVector => (v.indices.toList, v.values) case v: SparseVector => (v.indices.toList, v.values)
case other => case other =>
throw new UnsupportedOperationException( throw new UnsupportedOperationException(

2
mllib/src/main/scala/org/apache/spark/ml/feature/StandardScaler.scala
View file

@ -169,7 +169,7 @@ class StandardScalerModel private[ml] (
case d: DenseVector => d.values.clone() case d: DenseVector => d.values.clone()
case v: Vector => v.toArray case v: Vector => v.toArray
} }
val newValues = scaler.transfromWithMean(values) val newValues = scaler.transformWithMean(values)
Vectors.dense(newValues) Vectors.dense(newValues)
} else if ($(withStd)) { } else if ($(withStd)) {
vector: Vector => vector: Vector =>

4
mllib/src/main/scala/org/apache/spark/mllib/feature/StandardScaler.scala
View file

@ -141,7 +141,7 @@ class StandardScalerModel @Since("1.3.0") (
case d: DenseVector => d.values.clone() case d: DenseVector => d.values.clone()
case v: Vector => v.toArray case v: Vector => v.toArray
} }
val newValues = transfromWithMean(values) val newValues = transformWithMean(values)
Vectors.dense(newValues) Vectors.dense(newValues)
} else if (withStd) { } else if (withStd) {
vector match { vector match {
@ -161,7 +161,7 @@ class StandardScalerModel @Since("1.3.0") (
} }
} }
private[spark] def transfromWithMean(values: Array[Double]): Array[Double] = { private[spark] def transformWithMean(values: Array[Double]): Array[Double] = {
// By default, Scala generates Java methods for member variables. So every time when // By default, Scala generates Java methods for member variables. So every time when
// the member variables are accessed, `invokespecial` will be called which is expensive. // the member variables are accessed, `invokespecial` will be called which is expensive.
// This can be avoid by having a local reference of `shift`. // This can be avoid by having a local reference of `shift`.