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

core/src/test/scala/org/apache/spark/CheckpointSuite.scala

@@ -500,7 +500,7 @@ class CheckpointSuite extends SparkFunSuite with RDDCheckpointTester with LocalS
   }
 
   runTest("CheckpointRDD with zero partitions") { reliableCheckpoint: Boolean =>
-    val rdd = new BlockRDD[Int](sc, Array[BlockId]())
+    val rdd = new BlockRDD[Int](sc, Array.empty[BlockId])
     assert(rdd.partitions.size === 0)
     assert(rdd.isCheckpointed === false)
     assert(rdd.isCheckpointedAndMaterialized === false)

core/src/test/scala/org/apache/spark/deploy/JsonProtocolSuite.scala

@@ -65,7 +65,7 @@ class JsonProtocolSuite extends SparkFunSuite with JsonTestUtils {
   test("writeMasterState") {
     val workers = Array(createWorkerInfo(), createWorkerInfo())
     val activeApps = Array(createAppInfo())
-    val completedApps = Array[ApplicationInfo]()
+    val completedApps = Array.empty[ApplicationInfo]
     val activeDrivers = Array(createDriverInfo())
     val completedDrivers = Array(createDriverInfo())
     val stateResponse = new MasterStateResponse(

core/src/test/scala/org/apache/spark/deploy/SparkSubmitSuite.scala

@@ -91,7 +91,7 @@ class SparkSubmitSuite
 
   // scalastyle:off println
   test("prints usage on empty input") {
-    testPrematureExit(Array[String](), "Usage: spark-submit")
+    testPrematureExit(Array.empty[String], "Usage: spark-submit")
   }
 
   test("prints usage with only --help") {

core/src/test/scala/org/apache/spark/deploy/history/HistoryServerArgumentsSuite.scala

@@ -33,7 +33,7 @@ class HistoryServerArgumentsSuite extends SparkFunSuite {
     .set("spark.testing", "true")
 
   test("No Arguments Parsing") {
-    val argStrings = Array[String]()
+    val argStrings = Array.empty[String]
     val hsa = new HistoryServerArguments(conf, argStrings)
     assert(conf.get("spark.history.fs.logDirectory") === logDir.getAbsolutePath)
     assert(conf.get("spark.history.fs.updateInterval") === "1")

core/src/test/scala/org/apache/spark/io/ChunkedByteBufferSuite.scala

@@ -57,7 +57,7 @@ class ChunkedByteBufferSuite extends SparkFunSuite {
   }
 
   test("toArray()") {
-    val empty = ByteBuffer.wrap(Array[Byte]())
+    val empty = ByteBuffer.wrap(Array.empty[Byte])
     val bytes = ByteBuffer.wrap(Array.tabulate(8)(_.toByte))
     val chunkedByteBuffer = new ChunkedByteBuffer(Array(bytes, bytes, empty))
     assert(chunkedByteBuffer.toArray === bytes.array() ++ bytes.array())
@@ -74,7 +74,7 @@ class ChunkedByteBufferSuite extends SparkFunSuite {
   }
 
   test("toInputStream()") {
-    val empty = ByteBuffer.wrap(Array[Byte]())
+    val empty = ByteBuffer.wrap(Array.empty[Byte])
     val bytes1 = ByteBuffer.wrap(Array.tabulate(256)(_.toByte))
     val bytes2 = ByteBuffer.wrap(Array.tabulate(128)(_.toByte))
     val chunkedByteBuffer = new ChunkedByteBuffer(Array(empty, bytes1, bytes2))

core/src/test/scala/org/apache/spark/serializer/KryoSerializerSuite.scala

@@ -100,7 +100,7 @@ class KryoSerializerSuite extends SparkFunSuite with SharedSparkContext {
     check(Array("aaa", "bbb", null))
     check(Array(true, false, true))
     check(Array('a', 'b', 'c'))
-    check(Array[Int]())
+    check(Array.empty[Int])
     check(Array(Array("1", "2"), Array("1", "2", "3", "4")))
   }
 

mllib-local/src/test/scala/org/apache/spark/ml/linalg/MatricesSuite.scala

@@ -287,7 +287,7 @@ class MatricesSuite extends SparkMLFunSuite {
     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)
@@ -341,7 +341,7 @@ class MatricesSuite extends SparkMLFunSuite {
     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)

mllib-local/src/test/scala/org/apache/spark/ml/util/TestingUtilsSuite.scala

@@ -110,9 +110,9 @@ class TestingUtilsSuite extends SparkMLFunSuite {
     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 SparkMLFunSuite {
       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 SparkMLFunSuite {
     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 SparkMLFunSuite {
     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 SparkMLFunSuite {
     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 SparkMLFunSuite {
     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 SparkMLFunSuite {
     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.") {

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.

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
   }
 

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))

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)

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])
     }
   }
 

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)

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
 

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)

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.") {

sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/expressions/StringExpressionsSuite.scala

@@ -215,13 +215,13 @@ class StringExpressionsSuite extends SparkFunSuite with ExpressionEvalHelper {
     checkEvaluation(Substring(bytes, 2, 2), Array[Byte](2, 3))
     checkEvaluation(Substring(bytes, 3, 2), Array[Byte](3, 4))
     checkEvaluation(Substring(bytes, 4, 2), Array[Byte](4))
-    checkEvaluation(Substring(bytes, 8, 2), Array[Byte]())
+    checkEvaluation(Substring(bytes, 8, 2), Array.empty[Byte])
     checkEvaluation(Substring(bytes, -1, 2), Array[Byte](4))
     checkEvaluation(Substring(bytes, -2, 2), Array[Byte](3, 4))
     checkEvaluation(Substring(bytes, -3, 2), Array[Byte](2, 3))
     checkEvaluation(Substring(bytes, -4, 2), Array[Byte](1, 2))
     checkEvaluation(Substring(bytes, -5, 2), Array[Byte](1))
-    checkEvaluation(Substring(bytes, -8, 2), Array[Byte]())
+    checkEvaluation(Substring(bytes, -8, 2), Array.empty[Byte])
   }
 
   test("string substring_index function") {
@@ -275,7 +275,7 @@ class StringExpressionsSuite extends SparkFunSuite with ExpressionEvalHelper {
     checkEvaluation(Base64(UnBase64(a)), "AQIDBA==", create_row("AQIDBA=="))
 
     checkEvaluation(Base64(b), "AQIDBA==", create_row(bytes))
-    checkEvaluation(Base64(b), "", create_row(Array[Byte]()))
+    checkEvaluation(Base64(b), "", create_row(Array.empty[Byte]))
     checkEvaluation(Base64(b), null, create_row(null))
     checkEvaluation(Base64(Literal.create(null, BinaryType)), null, create_row("abdef"))
 
@@ -526,13 +526,13 @@ class StringExpressionsSuite extends SparkFunSuite with ExpressionEvalHelper {
     // non ascii characters are not allowed in the source code, so we disable the scalastyle.
     checkEvaluation(Length(Literal("a花花c")), 4, create_row(string))
     // scalastyle:on
-    checkEvaluation(Length(Literal(bytes)), 5, create_row(Array[Byte]()))
+    checkEvaluation(Length(Literal(bytes)), 5, create_row(Array.empty[Byte]))
 
     checkEvaluation(Length(a), 5, create_row(string))
     checkEvaluation(Length(b), 5, create_row(bytes))
 
     checkEvaluation(Length(a), 0, create_row(""))
-    checkEvaluation(Length(b), 0, create_row(Array[Byte]()))
+    checkEvaluation(Length(b), 0, create_row(Array.empty[Byte]))
 
     checkEvaluation(Length(a), null, create_row(null))
     checkEvaluation(Length(b), null, create_row(null))

sql/core/src/test/scala/org/apache/spark/sql/DataFrameFunctionsSuite.scala

@@ -273,7 +273,7 @@ class DataFrameFunctionsSuite extends QueryTest with SharedSQLContext {
   test("sort_array function") {
     val df = Seq(
       (Array[Int](2, 1, 3), Array("b", "c", "a")),
-      (Array[Int](), Array[String]()),
+      (Array.empty[Int], Array.empty[String]),
       (null, null)
     ).toDF("a", "b")
     checkAnswer(