diff --git a/examples/src/main/scala/spark/examples/LocalKMeans.scala b/examples/src/main/scala/spark/examples/LocalKMeans.scala
index b07e799cef5afcfb855d64da4858326e17c4d8e7..4849f216fb2933faa17542897a584a70d88c2fda 100644
--- a/examples/src/main/scala/spark/examples/LocalKMeans.scala
+++ b/examples/src/main/scala/spark/examples/LocalKMeans.scala
@@ -10,73 +10,73 @@ import scala.collection.mutable.HashSet
* K-means clustering.
*/
object LocalKMeans {
- val N = 1000
- val R = 1000 // Scaling factor
- val D = 10
- val K = 10
- val convergeDist = 0.001
- val rand = new Random(42)
-
- def generateData = {
- def generatePoint(i: Int) = {
- Vector(D, _ => rand.nextDouble * R)
- }
- Array.tabulate(N)(generatePoint)
- }
-
- def closestPoint(p: Vector, centers: HashMap[Int, Vector]): Int = {
- var index = 0
- var bestIndex = 0
- var closest = Double.PositiveInfinity
-
- for (i <- 1 to centers.size) {
- val vCurr = centers.get(i).get
- val tempDist = p.squaredDist(vCurr)
- if (tempDist < closest) {
- closest = tempDist
- bestIndex = i
- }
- }
-
- return bestIndex
- }
-
- def main(args: Array[String]) {
- val data = generateData
- var points = new HashSet[Vector]
- var kPoints = new HashMap[Int, Vector]
- var tempDist = 1.0
-
- while (points.size < K) {
- points.add(data(rand.nextInt(N)))
- }
-
- val iter = points.iterator
- for (i <- 1 to points.size) {
- kPoints.put(i, iter.next())
- }
-
- println("Initial centers: " + kPoints)
-
- while(tempDist > convergeDist) {
- var closest = data.map (p => (closestPoint(p, kPoints), (p, 1)))
-
- var mappings = closest.groupBy[Int] (x => x._1)
-
- var pointStats = mappings.map(pair => pair._2.reduceLeft [(Int, (Vector, Int))] {case ((id1, (x1, y1)), (id2, (x2, y2))) => (id1, (x1 + x2, y1+y2))})
-
- var newPoints = pointStats.map {mapping => (mapping._1, mapping._2._1/mapping._2._2)}
-
- tempDist = 0.0
- for (mapping <- newPoints) {
- tempDist += kPoints.get(mapping._1).get.squaredDist(mapping._2)
- }
-
- for (newP <- newPoints) {
- kPoints.put(newP._1, newP._2)
- }
- }
-
- println("Final centers: " + kPoints)
- }
+ val N = 1000
+ val R = 1000 // Scaling factor
+ val D = 10
+ val K = 10
+ val convergeDist = 0.001
+ val rand = new Random(42)
+
+ def generateData = {
+ def generatePoint(i: Int) = {
+ Vector(D, _ => rand.nextDouble * R)
+ }
+ Array.tabulate(N)(generatePoint)
+ }
+
+ def closestPoint(p: Vector, centers: HashMap[Int, Vector]): Int = {
+ var index = 0
+ var bestIndex = 0
+ var closest = Double.PositiveInfinity
+
+ for (i <- 1 to centers.size) {
+ val vCurr = centers.get(i).get
+ val tempDist = p.squaredDist(vCurr)
+ if (tempDist < closest) {
+ closest = tempDist
+ bestIndex = i
+ }
+ }
+
+ return bestIndex
+ }
+
+ def main(args: Array[String]) {
+ val data = generateData
+ var points = new HashSet[Vector]
+ var kPoints = new HashMap[Int, Vector]
+ var tempDist = 1.0
+
+ while (points.size < K) {
+ points.add(data(rand.nextInt(N)))
+ }
+
+ val iter = points.iterator
+ for (i <- 1 to points.size) {
+ kPoints.put(i, iter.next())
+ }
+
+ println("Initial centers: " + kPoints)
+
+ while(tempDist > convergeDist) {
+ var closest = data.map (p => (closestPoint(p, kPoints), (p, 1)))
+
+ var mappings = closest.groupBy[Int] (x => x._1)
+
+ var pointStats = mappings.map(pair => pair._2.reduceLeft [(Int, (Vector, Int))] {case ((id1, (x1, y1)), (id2, (x2, y2))) => (id1, (x1 + x2, y1+y2))})
+
+ var newPoints = pointStats.map {mapping => (mapping._1, mapping._2._1/mapping._2._2)}
+
+ tempDist = 0.0
+ for (mapping <- newPoints) {
+ tempDist += kPoints.get(mapping._1).get.squaredDist(mapping._2)
+ }
+
+ for (newP <- newPoints) {
+ kPoints.put(newP._1, newP._2)
+ }
+ }
+
+ println("Final centers: " + kPoints)
+ }
}
diff --git a/examples/src/main/scala/spark/examples/MultiBroadcastTest.scala b/examples/src/main/scala/spark/examples/MultiBroadcastTest.scala
index 92cd81c48742fb7fe1e7c598512d5bd91e0dc5ee..a0aaf609186b74813f010ea419465102ecdfd0d0 100644
--- a/examples/src/main/scala/spark/examples/MultiBroadcastTest.scala
+++ b/examples/src/main/scala/spark/examples/MultiBroadcastTest.scala
@@ -8,7 +8,7 @@ object MultiBroadcastTest {
System.err.println("Usage: BroadcastTest <master> [<slices>] [numElem]")
System.exit(1)
}
-
+
val sc = new SparkContext(args(0), "Broadcast Test",
System.getenv("SPARK_HOME"), Seq(System.getenv("SPARK_EXAMPLES_JAR")))
@@ -19,7 +19,7 @@ object MultiBroadcastTest {
for (i <- 0 until arr1.length) {
arr1(i) = i
}
-
+
var arr2 = new Array[Int](num)
for (i <- 0 until arr2.length) {
arr2(i) = i
@@ -30,7 +30,7 @@ object MultiBroadcastTest {
sc.parallelize(1 to 10, slices).foreach {
i => println(barr1.value.size + barr2.value.size)
}
-
+
System.exit(0)
}
}
diff --git a/examples/src/main/scala/spark/examples/SimpleSkewedGroupByTest.scala b/examples/src/main/scala/spark/examples/SimpleSkewedGroupByTest.scala
index 0d17bda004b6e2f1fc4d5b43f703dd11f97c79e8..461b84a2c66232d7a2c01e31b97b9ded377909a2 100644
--- a/examples/src/main/scala/spark/examples/SimpleSkewedGroupByTest.scala
+++ b/examples/src/main/scala/spark/examples/SimpleSkewedGroupByTest.scala
@@ -11,7 +11,7 @@ object SimpleSkewedGroupByTest {
"[numMappers] [numKVPairs] [valSize] [numReducers] [ratio]")
System.exit(1)
}
-
+
var numMappers = if (args.length > 1) args(1).toInt else 2
var numKVPairs = if (args.length > 2) args(2).toInt else 1000
var valSize = if (args.length > 3) args(3).toInt else 1000
@@ -20,7 +20,7 @@ object SimpleSkewedGroupByTest {
val sc = new SparkContext(args(0), "GroupBy Test",
System.getenv("SPARK_HOME"), Seq(System.getenv("SPARK_EXAMPLES_JAR")))
-
+
val pairs1 = sc.parallelize(0 until numMappers, numMappers).flatMap { p =>
val ranGen = new Random
var result = new Array[(Int, Array[Byte])](numKVPairs)
diff --git a/examples/src/main/scala/spark/examples/SkewedGroupByTest.scala b/examples/src/main/scala/spark/examples/SkewedGroupByTest.scala
index 83be3fc27b5b0a5c3ad2549f0b443136417d55a6..435675f9de489d65988fded440e91084a820cdf0 100644
--- a/examples/src/main/scala/spark/examples/SkewedGroupByTest.scala
+++ b/examples/src/main/scala/spark/examples/SkewedGroupByTest.scala
@@ -10,7 +10,7 @@ object SkewedGroupByTest {
System.err.println("Usage: GroupByTest <master> [numMappers] [numKVPairs] [KeySize] [numReducers]")
System.exit(1)
}
-
+
var numMappers = if (args.length > 1) args(1).toInt else 2
var numKVPairs = if (args.length > 2) args(2).toInt else 1000
var valSize = if (args.length > 3) args(3).toInt else 1000
@@ -18,7 +18,7 @@ object SkewedGroupByTest {
val sc = new SparkContext(args(0), "GroupBy Test",
System.getenv("SPARK_HOME"), Seq(System.getenv("SPARK_EXAMPLES_JAR")))
-
+
val pairs1 = sc.parallelize(0 until numMappers, numMappers).flatMap { p =>
val ranGen = new Random