use ArrayBuilder to build primitive arrays

Author: mengxr

mllib/src/main/scala/org/apache/spark/mllib/feature/Word2Vec.scala

@@ -21,7 +21,7 @@ import java.lang.{Iterable => JavaIterable}
 
 import scala.collection.JavaConverters._
 import scala.collection.mutable
-import scala.collection.mutable.ArrayBuffer
+import scala.collection.mutable.ArrayBuilder
 
 import com.github.fommil.netlib.BLAS.{getInstance => blas}
 
@@ -272,7 +272,7 @@ class Word2Vec extends Serializable with Logging {
         def hasNext: Boolean = iter.hasNext
 
         def next(): Array[Int] = {
-          var sentence = new ArrayBuffer[Int]
+          val sentence = ArrayBuilder.make[Int]
           var sentenceLength = 0
           while (iter.hasNext && sentenceLength < MAX_SENTENCE_LENGTH) {
             val word = bcVocabHash.value.get(iter.next())
@@ -283,7 +283,7 @@ class Word2Vec extends Serializable with Logging {
               case None =>
             }
           }
-          sentence.toArray
+          sentence.result()
         }
       }
     }

mllib/src/main/scala/org/apache/spark/mllib/tree/DecisionTree.scala

@@ -19,7 +19,7 @@ package org.apache.spark.mllib.tree
 
 import scala.collection.JavaConverters._
 import scala.collection.mutable
-import scala.collection.mutable.ArrayBuffer
+import scala.collection.mutable.ArrayBuilder
 
 
 import org.apache.spark.annotation.Experimental
@@ -1140,7 +1140,7 @@ object DecisionTree extends Serializable with Logging {
         logDebug("stride = " + stride)
 
         // iterate `valueCount` to find splits
-        val splits = new ArrayBuffer[Double]
+        val splitsBuilder = ArrayBuilder.make[Double]
         var index = 1
         // currentCount: sum of counts of values that have been visited
         var currentCount = valueCounts(0)._2
@@ -1158,13 +1158,13 @@ object DecisionTree extends Serializable with Logging {
           // makes the gap between currentCount and targetCount smaller,
           // previous value is a split threshold.
           if (previousGap < currentGap) {
-            splits.append(valueCounts(index - 1)._1)
+            splitsBuilder += valueCounts(index - 1)._1
             targetCount += stride
           }
           index += 1
         }
 
-        splits.toArray
+        splitsBuilder.result()
       }
     }
 

mllib/src/main/scala/org/apache/spark/mllib/util/NumericParser.scala

@@ -19,7 +19,7 @@ package org.apache.spark.mllib.util
 
 import java.util.StringTokenizer
 
-import scala.collection.mutable.{ArrayBuffer, ListBuffer}
+import scala.collection.mutable.{ArrayBuilder, ListBuffer}
 
 import org.apache.spark.SparkException
 
@@ -51,7 +51,7 @@ private[mllib] object NumericParser {
   }
 
   private def parseArray(tokenizer: StringTokenizer): Array[Double] = {
-    val values = ArrayBuffer.empty[Double]
+    val values = ArrayBuilder.make[Double]
     var parsing = true
     var allowComma = false
     var token: String = null
@@ -67,14 +67,14 @@ private[mllib] object NumericParser {
         }
       } else {
         // expecting a number
-        values.append(parseDouble(token))
+        values += parseDouble(token)
         allowComma = true
       }
     }
     if (parsing) {
       throw new SparkException(s"An array must end with ']'.")
     }
-    values.toArray
+    values.result()
   }
 
   private def parseTuple(tokenizer: StringTokenizer): Seq[_] = {
@@ -114,7 +114,7 @@ private[mllib] object NumericParser {
     try {
       java.lang.Double.parseDouble(s)
     } catch {
-      case e: Throwable =>
+      case e: NumberFormatException =>
         throw new SparkException(s"Cannot parse a double from: $s", e)
     }
   }