[SPARK-17331][FOLLOWUP][ML][CORE] Avoid allocating 0-length arrays

## What changes were proposed in this pull request?

`Array[T]()` -> `Array.empty[T]` to avoid allocating 0-length arrays.
Use regex `find . -name '*.scala' | xargs -i bash -c 'egrep "Array\[[A-Za-z]+\]\(\)" -n {} && echo {}'` to find modification candidates.

cc srowen

## How was this patch tested?
existing tests

Author: Zheng RuiFeng <ruifengz@foxmail.com>

Closes #15564 from zhengruifeng/avoid_0_length_array.

9 files changed, 24 insertions, 23 deletions

diff --git a/mllib/src/main/scala/org/apache/spark/ml/classification/LogisticRegression.scala b/mllib/src/main/scala/org/apache/spark/ml/classification/LogisticRegression.scala
index 862a468745..8fdaae04c4 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/classification/LogisticRegression.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/classification/LogisticRegression.scala
@@ -622,7 +622,7 @@ class LogisticRegression @Since("1.2.0") (
             rawCoefficients(coefIndex)
           }
         } else {
-          Array[Double]()
+          Array.empty[Double]
         }
         val interceptVector = if (interceptsArray.nonEmpty && isMultinomial) {
           // The intercepts are never regularized, so we always center the mean.
diff --git a/mllib/src/main/scala/org/apache/spark/mllib/stat/test/KolmogorovSmirnovTest.scala b/mllib/src/main/scala/org/apache/spark/mllib/stat/test/KolmogorovSmirnovTest.scala
index c3de5d75f4..a8b5955a72 100644
--- a/mllib/src/main/scala/org/apache/spark/mllib/stat/test/KolmogorovSmirnovTest.scala
+++ b/mllib/src/main/scala/org/apache/spark/mllib/stat/test/KolmogorovSmirnovTest.scala
@@ -124,7 +124,8 @@ private[stat] object KolmogorovSmirnovTest extends Logging {
     val pResults = partDiffs.foldLeft(initAcc) { case ((pMin, pMax, pCt), (dl, dp)) =>
       (math.min(pMin, dl), math.max(pMax, dp), pCt + 1)
     }
-    val results = if (pResults == initAcc) Array[(Double, Double, Double)]() else Array(pResults)
+    val results =
+      if (pResults == initAcc) Array.empty[(Double, Double, Double)] else Array(pResults)
     results.iterator
   }
 
diff --git a/mllib/src/test/scala/org/apache/spark/ml/classification/MultilayerPerceptronClassifierSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/classification/MultilayerPerceptronClassifierSuite.scala
index c08cb69580..41684d92be 100644
--- a/mllib/src/test/scala/org/apache/spark/ml/classification/MultilayerPerceptronClassifierSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/ml/classification/MultilayerPerceptronClassifierSuite.scala
@@ -51,7 +51,7 @@ class MultilayerPerceptronClassifierSuite
   test("Input Validation") {
     val mlpc = new MultilayerPerceptronClassifier()
     intercept[IllegalArgumentException] {
-      mlpc.setLayers(Array[Int]())
+      mlpc.setLayers(Array.empty[Int])
     }
     intercept[IllegalArgumentException] {
       mlpc.setLayers(Array[Int](1))
diff --git a/mllib/src/test/scala/org/apache/spark/ml/python/MLSerDeSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/python/MLSerDeSuite.scala
index 5eaef9aabd..3bb760f2ec 100644
--- a/mllib/src/test/scala/org/apache/spark/ml/python/MLSerDeSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/ml/python/MLSerDeSuite.scala
@@ -54,7 +54,7 @@ class MLSerDeSuite extends SparkFunSuite {
     assert(matrix === nm)
 
     // Test conversion for empty matrix
-    val empty = Array[Double]()
+    val empty = Array.empty[Double]
     val emptyMatrix = Matrices.dense(0, 0, empty)
     val ne = MLSerDe.loads(MLSerDe.dumps(emptyMatrix)).asInstanceOf[DenseMatrix]
     assert(emptyMatrix == ne)
diff --git a/mllib/src/test/scala/org/apache/spark/ml/tree/impl/RandomForestSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/tree/impl/RandomForestSuite.scala
index 499d386e66..3bded9c017 100644
--- a/mllib/src/test/scala/org/apache/spark/ml/tree/impl/RandomForestSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/ml/tree/impl/RandomForestSuite.scala
@@ -154,10 +154,10 @@ class RandomForestSuite extends SparkFunSuite with MLlibTestSparkContext {
       val featureSamples = Array(0, 0, 0).map(_.toDouble)
       val featureSamplesEmpty = Array.empty[Double]
       val splits = RandomForest.findSplitsForContinuousFeature(featureSamples, fakeMetadata, 0)
-      assert(splits === Array[Double]())
+      assert(splits === Array.empty[Double])
       val splitsEmpty =
         RandomForest.findSplitsForContinuousFeature(featureSamplesEmpty, fakeMetadata, 0)
-      assert(splitsEmpty === Array[Double]())
+      assert(splitsEmpty === Array.empty[Double])
     }
   }
 
diff --git a/mllib/src/test/scala/org/apache/spark/mllib/api/python/PythonMLLibAPISuite.scala b/mllib/src/test/scala/org/apache/spark/mllib/api/python/PythonMLLibAPISuite.scala
index 0eb839f20c..5f85c0d65f 100644
--- a/mllib/src/test/scala/org/apache/spark/mllib/api/python/PythonMLLibAPISuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/mllib/api/python/PythonMLLibAPISuite.scala
@@ -72,7 +72,7 @@ class PythonMLLibAPISuite extends SparkFunSuite {
     assert(matrix === nm)
 
     // Test conversion for empty matrix
-    val empty = Array[Double]()
+    val empty = Array.empty[Double]
     val emptyMatrix = Matrices.dense(0, 0, empty)
     val ne = SerDe.loads(SerDe.dumps(emptyMatrix)).asInstanceOf[DenseMatrix]
     assert(emptyMatrix == ne)
diff --git a/mllib/src/test/scala/org/apache/spark/mllib/evaluation/RankingMetricsSuite.scala b/mllib/src/test/scala/org/apache/spark/mllib/evaluation/RankingMetricsSuite.scala
index 8e9d910e64..f334be2c2b 100644
--- a/mllib/src/test/scala/org/apache/spark/mllib/evaluation/RankingMetricsSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/mllib/evaluation/RankingMetricsSuite.scala
@@ -28,7 +28,7 @@ class RankingMetricsSuite extends SparkFunSuite with MLlibTestSparkContext {
       Seq(
         (Array(1, 6, 2, 7, 8, 3, 9, 10, 4, 5), Array(1, 2, 3, 4, 5)),
         (Array(4, 1, 5, 6, 2, 7, 3, 8, 9, 10), Array(1, 2, 3)),
-        (Array(1, 2, 3, 4, 5), Array[Int]())
+        (Array(1, 2, 3, 4, 5), Array.empty[Int])
       ), 2)
     val eps = 1.0E-5
 
@@ -55,7 +55,7 @@ class RankingMetricsSuite extends SparkFunSuite with MLlibTestSparkContext {
     val predictionAndLabels = sc.parallelize(
       Seq(
         (Array(1, 6, 2), Array(1, 2, 3, 4, 5)),
-        (Array[Int](), Array(1, 2, 3))
+        (Array.empty[Int], Array(1, 2, 3))
       ), 2)
     val eps = 1.0E-5
 
diff --git a/mllib/src/test/scala/org/apache/spark/mllib/linalg/MatricesSuite.scala b/mllib/src/test/scala/org/apache/spark/mllib/linalg/MatricesSuite.scala
index d0c4dd28e1..563756907d 100644
--- a/mllib/src/test/scala/org/apache/spark/mllib/linalg/MatricesSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/mllib/linalg/MatricesSuite.scala
@@ -289,7 +289,7 @@ class MatricesSuite extends SparkFunSuite {
     val spHorz2 = Matrices.horzcat(Array(spMat1, deMat2))
     val spHorz3 = Matrices.horzcat(Array(deMat1, spMat2))
     val deHorz1 = Matrices.horzcat(Array(deMat1, deMat2))
-    val deHorz2 = Matrices.horzcat(Array[Matrix]())
+    val deHorz2 = Matrices.horzcat(Array.empty[Matrix])
 
     assert(deHorz1.numRows === 3)
     assert(spHorz2.numRows === 3)
@@ -343,7 +343,7 @@ class MatricesSuite extends SparkFunSuite {
     val deVert1 = Matrices.vertcat(Array(deMat1, deMat3))
     val spVert2 = Matrices.vertcat(Array(spMat1, deMat3))
     val spVert3 = Matrices.vertcat(Array(deMat1, spMat3))
-    val deVert2 = Matrices.vertcat(Array[Matrix]())
+    val deVert2 = Matrices.vertcat(Array.empty[Matrix])
 
     assert(deVert1.numRows === 5)
     assert(spVert2.numRows === 5)
diff --git a/mllib/src/test/scala/org/apache/spark/mllib/util/TestingUtilsSuite.scala b/mllib/src/test/scala/org/apache/spark/mllib/util/TestingUtilsSuite.scala
index 1aff44480a..3fcf1cf2c2 100644
--- a/mllib/src/test/scala/org/apache/spark/mllib/util/TestingUtilsSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/mllib/util/TestingUtilsSuite.scala
@@ -110,9 +110,9 @@ class TestingUtilsSuite extends SparkFunSuite {
     assert(!(Vectors.dense(Array(3.1, 3.5)) !~= Vectors.dense(Array(3.130, 3.534)) relTol 0.01))
     assert(!(Vectors.dense(Array(3.1, 3.5)) ~= Vectors.dense(Array(3.135, 3.534)) relTol 0.01))
     assert(Vectors.dense(Array(3.1)) !~= Vectors.dense(Array(3.130, 3.534)) relTol 0.01)
-    assert(Vectors.dense(Array[Double]()) !~= Vectors.dense(Array(3.130, 3.534)) relTol 0.01)
+    assert(Vectors.dense(Array.empty[Double]) !~= Vectors.dense(Array(3.130, 3.534)) relTol 0.01)
     assert(Vectors.dense(Array(3.1)) !~== Vectors.dense(Array(3.130, 3.534)) relTol 0.01)
-    assert(Vectors.dense(Array[Double]()) !~== Vectors.dense(Array(3.130, 3.534)) relTol 0.01)
+    assert(Vectors.dense(Array.empty[Double]) !~== Vectors.dense(Array(3.130, 3.534)) relTol 0.01)
 
     // Should throw exception with message when test fails.
     intercept[TestFailedException](
@@ -125,7 +125,7 @@ class TestingUtilsSuite extends SparkFunSuite {
       Vectors.dense(Array(3.1)) ~== Vectors.dense(Array(3.535, 3.534)) relTol 0.01)
 
     intercept[TestFailedException](
-      Vectors.dense(Array[Double]()) ~== Vectors.dense(Array(3.135)) relTol 0.01)
+      Vectors.dense(Array.empty[Double]) ~== Vectors.dense(Array(3.135)) relTol 0.01)
 
     // Comparing against zero should fail the test and throw exception with message
     // saying that the relative error is meaningless in this situation.
@@ -145,7 +145,7 @@ class TestingUtilsSuite extends SparkFunSuite {
     assert(Vectors.dense(Array(3.1)) !~==
       Vectors.sparse(2, Array(0, 1), Array(3.130, 3.534)) relTol 0.01)
 
-    assert(Vectors.dense(Array[Double]()) !~==
+    assert(Vectors.dense(Array.empty[Double]) !~==
       Vectors.sparse(2, Array(0, 1), Array(3.130, 3.534)) relTol 0.01)
   }
 
@@ -176,14 +176,14 @@ class TestingUtilsSuite extends SparkFunSuite {
     assert(!(Vectors.dense(Array(3.1)) ~=
       Vectors.dense(Array(3.1 + 1E-6, 3.5 + 2E-7)) absTol 1E-5))
 
-    assert(Vectors.dense(Array[Double]()) !~=
+    assert(Vectors.dense(Array.empty[Double]) !~=
       Vectors.dense(Array(3.1 + 1E-6, 3.5 + 2E-7)) absTol 1E-5)
 
-    assert(!(Vectors.dense(Array[Double]()) ~=
+    assert(!(Vectors.dense(Array.empty[Double]) ~=
       Vectors.dense(Array(3.1 + 1E-6, 3.5 + 2E-7)) absTol 1E-5))
 
-    assert(Vectors.dense(Array[Double]()) ~=
-      Vectors.dense(Array[Double]()) absTol 1E-5)
+    assert(Vectors.dense(Array.empty[Double]) ~=
+      Vectors.dense(Array.empty[Double]) absTol 1E-5)
 
     // Should throw exception with message when test fails.
     intercept[TestFailedException](Vectors.dense(Array(3.1, 3.5, 0.0)) !~==
@@ -195,7 +195,7 @@ class TestingUtilsSuite extends SparkFunSuite {
     intercept[TestFailedException](Vectors.dense(Array(3.1)) ~==
       Vectors.dense(Array(3.1 + 1E-5, 3.5 + 2E-7)) absTol 1E-6)
 
-    intercept[TestFailedException](Vectors.dense(Array[Double]()) ~==
+    intercept[TestFailedException](Vectors.dense(Array.empty[Double]) ~==
       Vectors.dense(Array(3.1 + 1E-5, 3.5 + 2E-7)) absTol 1E-6)
 
     // Comparisons of two sparse vectors
@@ -214,7 +214,7 @@ class TestingUtilsSuite extends SparkFunSuite {
     assert(Vectors.sparse(3, Array(0, 2), Array(3.1 + 1E-6, 2.4)) !~==
       Vectors.sparse(1, Array(0), Array(3.1)) absTol 1E-3)
 
-    assert(Vectors.sparse(0, Array[Int](), Array[Double]()) !~==
+    assert(Vectors.sparse(0, Array.empty[Int], Array.empty[Double]) !~==
       Vectors.sparse(1, Array(0), Array(3.1)) absTol 1E-3)
 
     // Comparisons of a dense vector and a sparse vector
@@ -230,14 +230,14 @@ class TestingUtilsSuite extends SparkFunSuite {
     assert(Vectors.sparse(3, Array(0, 2), Array(3.1, 2.4)) !~==
       Vectors.dense(Array(3.1)) absTol 1E-6)
 
-    assert(Vectors.dense(Array[Double]()) !~==
+    assert(Vectors.dense(Array.empty[Double]) !~==
       Vectors.sparse(3, Array(0, 2), Array(0, 2.4)) absTol 1E-6)
 
     assert(Vectors.sparse(1, Array(0), Array(3.1)) !~==
       Vectors.dense(Array(3.1, 3.2)) absTol 1E-6)
 
     assert(Vectors.dense(Array(3.1)) !~==
-      Vectors.sparse(0, Array[Int](), Array[Double]()) absTol 1E-6)
+      Vectors.sparse(0, Array.empty[Int], Array.empty[Double]) absTol 1E-6)
   }
 
   test("Comparing Matrices using absolute error.") {