[SPARK-2862] histogram method fails on some choices of bucketCount

Author: Chandan Kumar <chandan.kumar@imaginea.com>

Closes #1787 from nrchandan/spark-2862 and squashes the following commits:

a76bbf6 [Chandan Kumar] [SPARK-2862] Fix for a broken test case and add new test cases
4211eea [Chandan Kumar] [SPARK-2862] Add Scala bug id
13854f1 [Chandan Kumar] [SPARK-2862] Use shorthand range notation to avoid Scala bug

core/src/main/scala/org/apache/spark/rdd/DoubleRDDFunctions.scala

@@ -95,7 +95,12 @@ class DoubleRDDFunctions(self: RDD[Double]) extends Logging with Serializable {
    * If the elements in RDD do not vary (max == min) always returns a single bucket.
    */
   def histogram(bucketCount: Int): Pair[Array[Double], Array[Long]] = {
-    // Compute the minimum and the maxium
+    // Scala's built-in range has issues. See #SI-8782
+    def customRange(min: Double, max: Double, steps: Int): IndexedSeq[Double] = {
+      val span = max - min
+      Range.Int(0, steps, 1).map(s => min + (s * span) / steps) :+ max
+    }
+    // Compute the minimum and the maximum
     val (max: Double, min: Double) = self.mapPartitions { items =>
       Iterator(items.foldRight(Double.NegativeInfinity,
         Double.PositiveInfinity)((e: Double, x: Pair[Double, Double]) =>
@@ -107,9 +112,11 @@ class DoubleRDDFunctions(self: RDD[Double]) extends Logging with Serializable {
       throw new UnsupportedOperationException(
         "Histogram on either an empty RDD or RDD containing +/-infinity or NaN")
     }
-    val increment = (max-min)/bucketCount.toDouble
-    val range = if (increment != 0) {
-      Range.Double.inclusive(min, max, increment)
+    val range = if (min != max) {
+      // Range.Double.inclusive(min, max, increment)
+      // The above code doesn't always work. See Scala bug #SI-8782.
+      // https://issues.scala-lang.org/browse/SI-8782
+      customRange(min, max, bucketCount)
     } else {
       List(min, min)
     }

core/src/test/scala/org/apache/spark/rdd/DoubleRDDSuite.scala

@@ -245,6 +245,29 @@ class DoubleRDDSuite extends FunSuite with SharedSparkContext {
     assert(histogramBuckets === expectedHistogramBuckets)
   }
 
+  test("WorksWithoutBucketsForLargerDatasets") {
+    // Verify the case of slighly larger datasets
+    val rdd = sc.parallelize(6 to 99)
+    val (histogramBuckets, histogramResults) = rdd.histogram(8)
+    val expectedHistogramResults =
+      Array(12, 12, 11, 12, 12, 11, 12, 12)
+    val expectedHistogramBuckets =
+      Array(6.0, 17.625, 29.25, 40.875, 52.5, 64.125, 75.75, 87.375, 99.0)
+    assert(histogramResults === expectedHistogramResults)
+    assert(histogramBuckets === expectedHistogramBuckets)
+  }
+
+  test("WorksWithoutBucketsWithIrrationalBucketEdges") {
+    // Verify the case of buckets with irrational edges. See #SPARK-2862.
+    val rdd = sc.parallelize(6 to 99)
+    val (histogramBuckets, histogramResults) = rdd.histogram(9)
+    val expectedHistogramResults =
+      Array(11, 10, 11, 10, 10, 11, 10, 10, 11)
+    assert(histogramResults === expectedHistogramResults)
+    assert(histogramBuckets(0) === 6.0)
+    assert(histogramBuckets(9) === 99.0)
+  }
+
   // Test the failure mode with an invalid RDD
   test("ThrowsExceptionOnInvalidRDDs") {
     // infinity