SPARK-1446: Spark examples should not do a System.exit

Spark examples should exit nice using SparkContext.stop() method, rather than System.exit
System.exit can cause issues like in SPARK-1407

examples/src/main/java/org/apache/spark/examples/JavaHdfsLR.java

@@ -138,6 +138,6 @@ public static void main(String[] args) {
 
     System.out.print("Final w: ");
     printWeights(w);
-    System.exit(0);
+    sc.stop();
   }
 }

examples/src/main/java/org/apache/spark/examples/JavaLogQuery.java

@@ -126,6 +126,6 @@ public Stats call(Stats stats, Stats stats2) {
     for (Tuple2<?,?> t : output) {
       System.out.println(t._1() + "\t" + t._2());
     }
-    System.exit(0);
+    jsc.stop();
   }
 }

examples/src/main/java/org/apache/spark/examples/JavaPageRank.java

@@ -117,6 +117,6 @@ public Double call(Double sum) {
         System.out.println(tuple._1() + " has rank: " + tuple._2() + ".");
     }
 
-    System.exit(0);
+    ctx.stop();
   }
 }

examples/src/main/java/org/apache/spark/examples/JavaTC.java

@@ -96,6 +96,6 @@ public Tuple2<Integer, Integer> call(Tuple2<Integer, Integer> e) {
     } while (nextCount != oldCount);
 
     System.out.println("TC has " + tc.count() + " edges.");
-    System.exit(0);
+    sc.stop();
   }
 }

examples/src/main/java/org/apache/spark/examples/JavaWordCount.java

@@ -48,14 +48,14 @@ public Iterable<String> call(String s) {
         return Arrays.asList(SPACE.split(s));
       }
     });
-    
+
     JavaPairRDD<String, Integer> ones = words.mapToPair(new PairFunction<String, String, Integer>() {
       @Override
       public Tuple2<String, Integer> call(String s) {
         return new Tuple2<String, Integer>(s, 1);
       }
     });
-    
+
     JavaPairRDD<String, Integer> counts = ones.reduceByKey(new Function2<Integer, Integer, Integer>() {
       @Override
       public Integer call(Integer i1, Integer i2) {
@@ -67,6 +67,6 @@ public Integer call(Integer i1, Integer i2) {
     for (Tuple2<?,?> tuple : output) {
       System.out.println(tuple._1() + ": " + tuple._2());
     }
-    System.exit(0);
+    ctx.stop();
   }
 }

examples/src/main/java/org/apache/spark/mllib/examples/JavaALS.java

@@ -85,6 +85,6 @@ public static void main(String[] args) {
         outputDir + "/productFeatures");
     System.out.println("Final user/product features written to " + outputDir);
 
-    System.exit(0);
+    sc.stop();
   }
 }

examples/src/main/java/org/apache/spark/mllib/examples/JavaKMeans.java

@@ -79,6 +79,6 @@ public static void main(String[] args) {
     double cost = model.computeCost(points.rdd());
     System.out.println("Cost: " + cost);
 
-    System.exit(0);
+    sc.stop();
   }
 }

examples/src/main/java/org/apache/spark/mllib/examples/JavaLR.java

@@ -77,6 +77,6 @@ public static void main(String[] args) {
 
     System.out.print("Final w: " + model.weights());
 
-    System.exit(0);
+    sc.stop();
   }
 }

examples/src/main/scala/org/apache/spark/examples/BroadcastTest.scala

@@ -56,6 +56,6 @@ object BroadcastTest {
       println("Iteration %d took %.0f milliseconds".format(i, (System.nanoTime - startTime) / 1E6))
     }
 
-    System.exit(0)
+    sc.stop()
   }
 }

examples/src/main/scala/org/apache/spark/examples/CassandraCQLTest.scala

@@ -58,7 +58,7 @@ import org.apache.spark.SparkContext._
     prod_id,
     quantity) VALUES ('charlie', 1385983649000, 'iphone', 2);
 */
- 
+
 /**
  * This example demonstrates how to read and write to cassandra column family created using CQL3
  * using Spark.

examples/src/main/scala/org/apache/spark/examples/ExceptionHandlingTest.scala

@@ -34,6 +34,6 @@ object ExceptionHandlingTest {
       }
     }
 
-    System.exit(0)
+    sc.stop()
   }
 }

examples/src/main/scala/org/apache/spark/examples/GroupByTest.scala

@@ -28,7 +28,7 @@ object GroupByTest {
         "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
@@ -52,7 +52,6 @@ object GroupByTest {
 
     println(pairs1.groupByKey(numReducers).count)
 
-    System.exit(0)
+    sc.stop()
   }
 }
-

examples/src/main/scala/org/apache/spark/examples/HBaseTest.scala

@@ -30,7 +30,7 @@ object HBaseTest {
 
     val conf = HBaseConfiguration.create()
 
-    // Other options for configuring scan behavior are available. More information available at 
+    // Other options for configuring scan behavior are available. More information available at
     // http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/mapreduce/TableInputFormat.html
     conf.set(TableInputFormat.INPUT_TABLE, args(1))
 
@@ -41,12 +41,12 @@ object HBaseTest {
       admin.createTable(tableDesc)
     }
 
-    val hBaseRDD = sc.newAPIHadoopRDD(conf, classOf[TableInputFormat], 
+    val hBaseRDD = sc.newAPIHadoopRDD(conf, classOf[TableInputFormat],
       classOf[org.apache.hadoop.hbase.io.ImmutableBytesWritable],
       classOf[org.apache.hadoop.hbase.client.Result])
 
     hBaseRDD.count()
 
-    System.exit(0)
+    sc.stop()
   }
 }

examples/src/main/scala/org/apache/spark/examples/HdfsTest.scala

@@ -32,6 +32,6 @@ object HdfsTest {
       val end = System.currentTimeMillis()
       println("Iteration " + iter + " took " + (end-start) + " ms")
     }
-    System.exit(0)
+    sc.stop()
   }
 }

examples/src/main/scala/org/apache/spark/examples/LocalALS.scala

@@ -120,7 +120,7 @@ object LocalALS {
       }
     }
     printf("Running with M=%d, U=%d, F=%d, iters=%d\n", M, U, F, ITERATIONS)
-    
+
     val R = generateR()
 
     // Initialize m and u randomly

examples/src/main/scala/org/apache/spark/examples/MultiBroadcastTest.scala

@@ -51,6 +51,6 @@ object MultiBroadcastTest {
     // Collect the small RDD so we can print the observed sizes locally.
     observedSizes.collect().foreach(i => println(i))
 
-    System.exit(0)
+    sc.stop()
   }
 }

examples/src/main/scala/org/apache/spark/examples/SimpleSkewedGroupByTest.scala

@@ -27,7 +27,7 @@ object SimpleSkewedGroupByTest {
       System.err.println("Usage: SimpleSkewedGroupByTest <master> " +
         "[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
@@ -58,14 +58,13 @@ object SimpleSkewedGroupByTest {
     }.cache
     // Enforce that everything has been calculated and in cache
     pairs1.count
-    
+
     println("RESULT: " + pairs1.groupByKey(numReducers).count)
     // Print how many keys each reducer got (for debugging)
     // println("RESULT: " + pairs1.groupByKey(numReducers)
     //                           .map{case (k,v) => (k, v.size)}
     //                           .collectAsMap)
 
-    System.exit(0)
+    sc.stop()
   }
 }
-

examples/src/main/scala/org/apache/spark/examples/SkewedGroupByTest.scala

@@ -27,7 +27,7 @@ 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
@@ -53,10 +53,9 @@ object SkewedGroupByTest {
     }.cache()
     // Enforce that everything has been calculated and in cache
     pairs1.count()
-    
+
     println(pairs1.groupByKey(numReducers).count())
 
-    System.exit(0)
+    sc.stop()
   }
 }
-

examples/src/main/scala/org/apache/spark/examples/SparkALS.scala

@@ -112,7 +112,7 @@ object SparkALS {
 
     val sc = new SparkContext(host, "SparkALS",
       System.getenv("SPARK_HOME"), SparkContext.jarOfClass(this.getClass))
-    
+
     val R = generateR()
 
     // Initialize m and u randomly
@@ -137,6 +137,6 @@ object SparkALS {
       println()
     }
 
-    System.exit(0)
+    sc.stop()
   }
 }

examples/src/main/scala/org/apache/spark/examples/SparkHdfsLR.scala

@@ -52,7 +52,7 @@ object SparkHdfsLR {
     val inputPath = args(1)
     val conf = SparkHadoopUtil.get.newConfiguration()
     val sc = new SparkContext(args(0), "SparkHdfsLR",
-      System.getenv("SPARK_HOME"), SparkContext.jarOfClass(this.getClass), Map(), 
+      System.getenv("SPARK_HOME"), SparkContext.jarOfClass(this.getClass), Map(),
       InputFormatInfo.computePreferredLocations(
         Seq(new InputFormatInfo(conf, classOf[org.apache.hadoop.mapred.TextInputFormat], inputPath))
       ))
@@ -73,6 +73,6 @@ object SparkHdfsLR {
     }
 
     println("Final w: " + w)
-    System.exit(0)
+    sc.stop()
   }
 }

examples/src/main/scala/org/apache/spark/examples/SparkKMeans.scala

@@ -28,24 +28,24 @@ import org.apache.spark.SparkContext._
 object SparkKMeans {
   val R = 1000     // Scaling factor
   val rand = new Random(42)
-    
+
   def parseVector(line: String): Vector = {
     new Vector(line.split(' ').map(_.toDouble))
   }
-  
+
   def closestPoint(p: Vector, centers: Array[Vector]): Int = {
     var index = 0
     var bestIndex = 0
     var closest = Double.PositiveInfinity
-  
+
     for (i <- 0 until centers.length) {
       val tempDist = p.squaredDist(centers(i))
       if (tempDist < closest) {
         closest = tempDist
         bestIndex = i
       }
     }
-  
+
     bestIndex
   }
 
@@ -60,22 +60,22 @@ object SparkKMeans {
     val data = lines.map(parseVector _).cache()
     val K = args(2).toInt
     val convergeDist = args(3).toDouble
-  
+
     val kPoints = data.takeSample(withReplacement = false, K, 42).toArray
     var tempDist = 1.0
 
     while(tempDist > convergeDist) {
       val closest = data.map (p => (closestPoint(p, kPoints), (p, 1)))
-      
+
       val pointStats = closest.reduceByKey{case ((x1, y1), (x2, y2)) => (x1 + x2, y1 + y2)}
-      
+
       val newPoints = pointStats.map {pair => (pair._1, pair._2._1 / pair._2._2)}.collectAsMap()
-      
+
       tempDist = 0.0
       for (i <- 0 until K) {
         tempDist += kPoints(i).squaredDist(newPoints(i))
       }
-      
+
       for (newP <- newPoints) {
         kPoints(newP._1) = newP._2
       }
@@ -84,6 +84,6 @@ object SparkKMeans {
 
     println("Final centers:")
     kPoints.foreach(println)
-    System.exit(0)
+    sc.stop()
   }
 }

examples/src/main/scala/org/apache/spark/examples/SparkLR.scala

@@ -66,6 +66,6 @@ object SparkLR {
     }
 
     println("Final w: " + w)
-    System.exit(0)
+    sc.stop()
   }
 }

examples/src/main/scala/org/apache/spark/examples/SparkPageRank.scala

@@ -57,7 +57,6 @@ object SparkPageRank {
     val output = ranks.collect()
     output.foreach(tup => println(tup._1 + " has rank: " + tup._2 + "."))
 
-    System.exit(0)
+    ctx.stop()
   }
 }
-

examples/src/main/scala/org/apache/spark/examples/SparkTC.scala

@@ -70,6 +70,6 @@ object SparkTC {
     } while (nextCount != oldCount)
 
     println("TC has " + tc.count() + " edges.")
-    System.exit(0)
+    spark.stop()
   }
 }

examples/src/main/scala/org/apache/spark/examples/SparkTachyonHdfsLR.scala

@@ -75,6 +75,6 @@ object SparkTachyonHdfsLR {
     }
 
     println("Final w: " + w)
-    System.exit(0)
+    sc.stop()
   }
 }

examples/src/main/scala/org/apache/spark/examples/SparkTachyonPi.scala

@@ -34,10 +34,10 @@ object SparkTachyonPi {
     }
     val spark = new SparkContext(args(0), "SparkTachyonPi",
       System.getenv("SPARK_HOME"), SparkContext.jarOfClass(this.getClass))
-    
+
     val slices = if (args.length > 1) args(1).toInt else 2
     val n = 100000 * slices
-    
+
     val rdd = spark.parallelize(1 to n, slices)
     rdd.persist(StorageLevel.OFF_HEAP)
     val count = rdd.map { i =>
@@ -46,7 +46,7 @@ object SparkTachyonPi {
       if (x * x + y * y < 1) 1 else 0
     }.reduce(_ + _)
     println("Pi is roughly " + 4.0 * count / n)
-    
+
     spark.stop()
   }
 }

examples/src/main/scala/org/apache/spark/examples/bagel/WikipediaPageRankStandalone.scala

@@ -79,7 +79,7 @@ object WikipediaPageRankStandalone {
     val time = (System.currentTimeMillis - startTime) / 1000.0
     println("Completed %d iterations in %f seconds: %f seconds per iteration"
       .format(numIterations, time, time / numIterations))
-    System.exit(0)
+    sc.stop()
   }
 
   def parseArticle(line: String): (String, Array[String]) = {

examples/src/main/scala/org/apache/spark/examples/mllib/TallSkinnyPCA.scala

@@ -16,7 +16,7 @@
  */
 
 package org.apache.spark.examples.mllib
-      
+
 import org.apache.spark.{SparkConf, SparkContext}
 import org.apache.spark.mllib.linalg.distributed.RowMatrix
 import org.apache.spark.mllib.linalg.Vectors