Merge branch 'scala210-master' of github.com:colorant/incubator-spark into scala-2.10

Conflicts:
	core/src/main/scala/org/apache/spark/deploy/client/Client.scala
	core/src/main/scala/org/apache/spark/deploy/worker/Worker.scala
	core/src/main/scala/org/apache/spark/executor/CoarseGrainedExecutorBackend.scala
	core/src/test/scala/org/apache/spark/MapOutputTrackerSuite.scala

9 files changed, 274 insertions, 30 deletions

diff --git a/examples/pom.xml b/examples/pom.xml
index c6c9def5be..a10dee7847 100644
--- a/examples/pom.xml
+++ b/examples/pom.xml
@@ -32,13 +32,20 @@
   <url>http://spark.incubator.apache.org/</url>
 
   <repositories>
-    <!-- A repository in the local filesystem for the Kafka JAR, which we modified for Scala 2.9 -->
     <repository>
-      <id>lib</id>
-      <url>file://${project.basedir}/lib</url>
+      <id>apache-repo</id>
+      <name>Apache Repository</name>
+      <url>https://repository.apache.org/content/repositories/releases</url>
+      <releases>
+        <enabled>true</enabled>
+      </releases>
+      <snapshots>
+        <enabled>false</enabled>
+      </snapshots>
     </repository>
   </repositories>
 
+
   <dependencies>
     <dependency>
       <groupId>org.apache.spark</groupId>
@@ -81,9 +88,18 @@
     </dependency>
     <dependency>
       <groupId>org.apache.kafka</groupId>
-      <artifactId>kafka</artifactId>
-      <version>0.7.2-spark</version>  <!-- Comes from our in-project repository -->
-      <scope>provided</scope>
+      <artifactId>kafka_2.9.2</artifactId>
+      <version>0.8.0-beta1</version>
+      <exclusions>
+        <exclusion>
+          <groupId>com.sun.jmx</groupId>
+          <artifactId>jmxri</artifactId>
+        </exclusion>
+        <exclusion>
+          <groupId>com.sun.jdmk</groupId>
+          <artifactId>jmxtools</artifactId>
+        </exclusion>
+      </exclusions>
     </dependency>
     <dependency>
       <groupId>org.eclipse.jetty</groupId>
@@ -137,6 +153,14 @@
           <groupId>org.apache.cassandra.deps</groupId>
           <artifactId>avro</artifactId>
         </exclusion>
+        <exclusion>
+          <groupId>org.sonatype.sisu.inject</groupId>
+          <artifactId>*</artifactId>
+        </exclusion>
+        <exclusion>
+          <groupId>org.xerial.snappy</groupId>
+          <artifactId>*</artifactId>
+        </exclusion>
       </exclusions>
     </dependency>
   </dependencies>
diff --git a/examples/src/main/java/org/apache/spark/streaming/examples/JavaKafkaWordCount.java b/examples/src/main/java/org/apache/spark/streaming/examples/JavaKafkaWordCount.java
new file mode 100644
index 0000000000..9a8e4209ed
--- /dev/null
+++ b/examples/src/main/java/org/apache/spark/streaming/examples/JavaKafkaWordCount.java
@@ -0,0 +1,98 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements.  See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License.  You may obtain a copy of the License at
+ *
+ *    http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.spark.streaming.examples;
+
+import java.util.Map;
+import java.util.HashMap;
+
+import com.google.common.collect.Lists;
+import org.apache.spark.api.java.function.FlatMapFunction;
+import org.apache.spark.api.java.function.Function;
+import org.apache.spark.api.java.function.Function2;
+import org.apache.spark.api.java.function.PairFunction;
+import org.apache.spark.streaming.Duration;
+import org.apache.spark.streaming.api.java.JavaDStream;
+import org.apache.spark.streaming.api.java.JavaPairDStream;
+import org.apache.spark.streaming.api.java.JavaStreamingContext;
+import scala.Tuple2;
+
+/**
+ * Consumes messages from one or more topics in Kafka and does wordcount.
+ * Usage: JavaKafkaWordCount <master> <zkQuorum> <group> <topics> <numThreads>
+ *   <master> is the Spark master URL. In local mode, <master> should be 'local[n]' with n > 1.
+ *   <zkQuorum> is a list of one or more zookeeper servers that make quorum
+ *   <group> is the name of kafka consumer group
+ *   <topics> is a list of one or more kafka topics to consume from
+ *   <numThreads> is the number of threads the kafka consumer should use
+ *
+ * Example:
+ *    `./run-example org.apache.spark.streaming.examples.JavaKafkaWordCount local[2] zoo01,zoo02,
+ *    zoo03 my-consumer-group topic1,topic2 1`
+ */
+
+public class JavaKafkaWordCount {
+  public static void main(String[] args) {
+    if (args.length < 5) {
+      System.err.println("Usage: KafkaWordCount <master> <zkQuorum> <group> <topics> <numThreads>");
+      System.exit(1);
+    }
+
+    // Create the context with a 1 second batch size
+    JavaStreamingContext ssc = new JavaStreamingContext(args[0], "NetworkWordCount",
+            new Duration(2000), System.getenv("SPARK_HOME"), System.getenv("SPARK_EXAMPLES_JAR"));
+
+    int numThreads = Integer.parseInt(args[4]);
+    Map<String, Integer> topicMap = new HashMap<String, Integer>();
+    String[] topics = args[3].split(",");
+    for (String topic: topics) {
+      topicMap.put(topic, numThreads);
+    }
+
+    JavaPairDStream<String, String> messages = ssc.kafkaStream(args[1], args[2], topicMap);
+
+    JavaDStream<String> lines = messages.map(new Function<Tuple2<String, String>, String>() {
+      @Override
+      public String call(Tuple2<String, String> tuple2) throws Exception {
+        return tuple2._2();
+      }
+    });
+
+    JavaDStream<String> words = lines.flatMap(new FlatMapFunction<String, String>() {
+      @Override
+      public Iterable<String> call(String x) {
+        return Lists.newArrayList(x.split(" "));
+      }
+    });
+
+    JavaPairDStream<String, Integer> wordCounts = words.map(
+      new PairFunction<String, String, Integer>() {
+        @Override
+        public Tuple2<String, Integer> call(String s) throws Exception {
+          return new Tuple2<String, Integer>(s, 1);
+        }
+      }).reduceByKey(new Function2<Integer, Integer, Integer>() {
+        @Override
+        public Integer call(Integer i1, Integer i2) throws Exception {
+          return i1 + i2;
+        }
+      });
+
+    wordCounts.print();
+    ssc.start();
+  }
+}
diff --git a/examples/src/main/scala/org/apache/spark/examples/BroadcastTest.scala b/examples/src/main/scala/org/apache/spark/examples/BroadcastTest.scala
index 868ff81f67..529709c2f9 100644
--- a/examples/src/main/scala/org/apache/spark/examples/BroadcastTest.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/BroadcastTest.scala
@@ -22,12 +22,19 @@ import org.apache.spark.SparkContext
 object BroadcastTest {
   def main(args: Array[String]) {
     if (args.length == 0) {
-      System.err.println("Usage: BroadcastTest <master> [<slices>] [numElem]")
+      System.err.println("Usage: BroadcastTest <master> [slices] [numElem] [broadcastAlgo] [blockSize]")
       System.exit(1)
     }  
     
-    val sc = new SparkContext(args(0), "Broadcast Test",
+    val bcName = if (args.length > 3) args(3) else "Http"
+    val blockSize = if (args.length > 4) args(4) else "4096"
+
+    System.setProperty("spark.broadcast.factory", "org.apache.spark.broadcast." + bcName + "BroadcastFactory")
+    System.setProperty("spark.broadcast.blockSize", blockSize)
+
+    val sc = new SparkContext(args(0), "Broadcast Test 2",
       System.getenv("SPARK_HOME"), Seq(System.getenv("SPARK_EXAMPLES_JAR")))
+    
     val slices = if (args.length > 1) args(1).toInt else 2
     val num = if (args.length > 2) args(2).toInt else 1000000
 
@@ -36,13 +43,15 @@ object BroadcastTest {
       arr1(i) = i
     }
     
-    for (i <- 0 until 2) {
+    for (i <- 0 until 3) {
       println("Iteration " + i)
       println("===========")
+      val startTime = System.nanoTime
       val barr1 = sc.broadcast(arr1)
       sc.parallelize(1 to 10, slices).foreach {
         i => println(barr1.value.size)
       }
+      println("Iteration %d took %.0f milliseconds".format(i, (System.nanoTime - startTime) / 1E6))
     }
 
     System.exit(0)
diff --git a/examples/src/main/scala/org/apache/spark/examples/SparkHdfsLR.scala b/examples/src/main/scala/org/apache/spark/examples/SparkHdfsLR.scala
index 646682878f..86dd9ca1b3 100644
--- a/examples/src/main/scala/org/apache/spark/examples/SparkHdfsLR.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/SparkHdfsLR.scala
@@ -21,6 +21,7 @@ import java.util.Random
 import scala.math.exp
 import org.apache.spark.util.Vector
 import org.apache.spark._
+import org.apache.spark.deploy.SparkHadoopUtil
 import org.apache.spark.scheduler.InputFormatInfo
 
 /**
@@ -51,7 +52,7 @@ object SparkHdfsLR {
       System.exit(1)
     }
     val inputPath = args(1)
-    val conf = SparkEnv.get.hadoop.newConfiguration()
+    val conf = SparkHadoopUtil.get.newConfiguration()
     val sc = new SparkContext(args(0), "SparkHdfsLR",
       System.getenv("SPARK_HOME"), Seq(System.getenv("SPARK_EXAMPLES_JAR")), Map(), 
       InputFormatInfo.computePreferredLocations(
diff --git a/examples/src/main/scala/org/apache/spark/examples/SparkKMeans.scala b/examples/src/main/scala/org/apache/spark/examples/SparkKMeans.scala
index f7bf75b4e5..bc2db39c12 100644
--- a/examples/src/main/scala/org/apache/spark/examples/SparkKMeans.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/SparkKMeans.scala
@@ -21,8 +21,6 @@ import java.util.Random
 import org.apache.spark.SparkContext
 import org.apache.spark.util.Vector
 import org.apache.spark.SparkContext._
-import scala.collection.mutable.HashMap
-import scala.collection.mutable.HashSet
 
 /**
  * K-means clustering.
diff --git a/examples/src/main/scala/org/apache/spark/examples/SparkPi.scala b/examples/src/main/scala/org/apache/spark/examples/SparkPi.scala
index 5a2bc9b0d0..a689e5a360 100644
--- a/examples/src/main/scala/org/apache/spark/examples/SparkPi.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/SparkPi.scala
@@ -38,6 +38,6 @@ object SparkPi {
       if (x*x + y*y < 1) 1 else 0
     }.reduce(_ + _)
     println("Pi is roughly " + 4.0 * count / n)
-    System.exit(0)
+    spark.stop()
   }
 }
diff --git a/examples/src/main/scala/org/apache/spark/streaming/examples/KafkaWordCount.scala b/examples/src/main/scala/org/apache/spark/streaming/examples/KafkaWordCount.scala
index 12f939d5a7..570ba4c81a 100644
--- a/examples/src/main/scala/org/apache/spark/streaming/examples/KafkaWordCount.scala
+++ b/examples/src/main/scala/org/apache/spark/streaming/examples/KafkaWordCount.scala
@@ -18,13 +18,11 @@
 package org.apache.spark.streaming.examples
 
 import java.util.Properties
-import kafka.message.Message
-import kafka.producer.SyncProducerConfig
+
 import kafka.producer._
-import org.apache.spark.SparkContext
+
 import org.apache.spark.streaming._
 import org.apache.spark.streaming.StreamingContext._
-import org.apache.spark.storage.StorageLevel
 import org.apache.spark.streaming.util.RawTextHelper._
 
 /**
@@ -54,9 +52,10 @@ object KafkaWordCount {
     ssc.checkpoint("checkpoint")
 
     val topicpMap = topics.split(",").map((_,numThreads.toInt)).toMap
-    val lines = ssc.kafkaStream(zkQuorum, group, topicpMap)
+    val lines = ssc.kafkaStream(zkQuorum, group, topicpMap).map(_._2)
     val words = lines.flatMap(_.split(" "))
-    val wordCounts = words.map(x => (x, 1l)).reduceByKeyAndWindow(add _, subtract _, Minutes(10), Seconds(2), 2)
+    val wordCounts = words.map(x => (x, 1l))
+      .reduceByKeyAndWindow(add _, subtract _, Minutes(10), Seconds(2), 2)
     wordCounts.print()
     
     ssc.start()
@@ -68,15 +67,16 @@ object KafkaWordCountProducer {
 
   def main(args: Array[String]) {
     if (args.length < 2) {
-      System.err.println("Usage: KafkaWordCountProducer <zkQuorum> <topic> <messagesPerSec> <wordsPerMessage>")
+      System.err.println("Usage: KafkaWordCountProducer <metadataBrokerList> <topic> " +
+        "<messagesPerSec> <wordsPerMessage>")
       System.exit(1)
     }
 
-    val Array(zkQuorum, topic, messagesPerSec, wordsPerMessage) = args
+    val Array(brokers, topic, messagesPerSec, wordsPerMessage) = args
 
     // Zookeper connection properties
     val props = new Properties()
-    props.put("zk.connect", zkQuorum)
+    props.put("metadata.broker.list", brokers)
     props.put("serializer.class", "kafka.serializer.StringEncoder")
     
     val config = new ProducerConfig(props)
@@ -85,11 +85,13 @@ object KafkaWordCountProducer {
     // Send some messages
     while(true) {
       val messages = (1 to messagesPerSec.toInt).map { messageNum =>
-        (1 to wordsPerMessage.toInt).map(x => scala.util.Random.nextInt(10).toString).mkString(" ")
+        val str = (1 to wordsPerMessage.toInt).map(x => scala.util.Random.nextInt(10).toString)
+          .mkString(" ")
+
+        new KeyedMessage[String, String](topic, str)
       }.toArray
-      println(messages.mkString(","))
-      val data = new ProducerData[String, String](topic, messages)
-      producer.send(data)
+
+      producer.send(messages: _*)
       Thread.sleep(100)
     }
   }
diff --git a/examples/src/main/scala/org/apache/spark/streaming/examples/MQTTWordCount.scala b/examples/src/main/scala/org/apache/spark/streaming/examples/MQTTWordCount.scala
new file mode 100644
index 0000000000..af698a01d5
--- /dev/null
+++ b/examples/src/main/scala/org/apache/spark/streaming/examples/MQTTWordCount.scala
@@ -0,0 +1,107 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements.  See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License.  You may obtain a copy of the License at
+ *
+ *    http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.spark.streaming.examples
+
+import org.apache.spark.streaming.{ Seconds, StreamingContext }
+import org.apache.spark.streaming.StreamingContext._
+import org.apache.spark.streaming.dstream.MQTTReceiver
+import org.apache.spark.storage.StorageLevel
+
+import org.eclipse.paho.client.mqttv3.MqttClient
+import org.eclipse.paho.client.mqttv3.MqttClientPersistence
+import org.eclipse.paho.client.mqttv3.persist.MqttDefaultFilePersistence
+import org.eclipse.paho.client.mqttv3.MqttException
+import org.eclipse.paho.client.mqttv3.MqttMessage
+import org.eclipse.paho.client.mqttv3.MqttTopic
+
+/**
+ * A simple Mqtt publisher for demonstration purposes, repeatedly publishes 
+ * Space separated String Message "hello mqtt demo for spark streaming"
+ */
+object MQTTPublisher {
+
+  var client: MqttClient = _
+
+  def main(args: Array[String]) {
+    if (args.length < 2) {
+      System.err.println("Usage: MQTTPublisher <MqttBrokerUrl> <topic>")
+      System.exit(1)
+    }
+
+    val Seq(brokerUrl, topic) = args.toSeq
+
+    try {
+      var peristance:MqttClientPersistence =new MqttDefaultFilePersistence("/tmp")
+      client = new MqttClient(brokerUrl, MqttClient.generateClientId(), peristance)
+    } catch {
+      case e: MqttException => println("Exception Caught: " + e)
+    }
+
+    client.connect()
+
+    val msgtopic: MqttTopic = client.getTopic(topic);
+    val msg: String = "hello mqtt demo for spark streaming"
+
+    while (true) {
+      val message: MqttMessage = new MqttMessage(String.valueOf(msg).getBytes())
+      msgtopic.publish(message);
+      println("Published data. topic: " + msgtopic.getName() + " Message: " + message)
+    }
+   client.disconnect()
+  }
+}
+
+/**
+ * A sample wordcount with MqttStream stream
+ *
+ * To work with Mqtt, Mqtt Message broker/server required.
+ * Mosquitto (http://mosquitto.org/) is an open source Mqtt Broker
+ * In ubuntu mosquitto can be installed using the command  `$ sudo apt-get install mosquitto`
+ * Eclipse paho project provides Java library for Mqtt Client http://www.eclipse.org/paho/
+ * Example Java code for Mqtt Publisher and Subscriber can be found here https://bitbucket.org/mkjinesh/mqttclient
+ * Usage: MQTTWordCount <master> <MqttbrokerUrl> <topic>
+ * In local mode, <master> should be 'local[n]' with n > 1
+ *   <MqttbrokerUrl> and <topic> describe where Mqtt publisher is running.
+ *
+ * To run this example locally, you may run publisher as
+ *    `$ ./run-example org.apache.spark.streaming.examples.MQTTPublisher tcp://localhost:1883 foo`
+ * and run the example as
+ *    `$ ./run-example org.apache.spark.streaming.examples.MQTTWordCount local[2] tcp://localhost:1883 foo`
+ */
+object MQTTWordCount {
+
+  def main(args: Array[String]) {
+    if (args.length < 3) {
+      System.err.println(
+        "Usage: MQTTWordCount <master> <MqttbrokerUrl> <topic>" +
+          " In local mode, <master> should be 'local[n]' with n > 1")
+      System.exit(1)
+    }
+
+    val Seq(master, brokerUrl, topic) = args.toSeq
+
+    val ssc = new StreamingContext(master, "MqttWordCount", Seconds(2), System.getenv("SPARK_HOME"), 
+    Seq(System.getenv("SPARK_EXAMPLES_JAR")))
+    val lines = ssc.mqttStream(brokerUrl, topic, StorageLevel.MEMORY_ONLY)
+
+    val words = lines.flatMap(x => x.toString.split(" "))
+    val wordCounts = words.map(x => (x, 1)).reduceByKey(_ + _)
+    wordCounts.print()
+    ssc.start()
+  }
+}
diff --git a/examples/src/main/scala/org/apache/spark/streaming/examples/clickstream/PageViewGenerator.scala b/examples/src/main/scala/org/apache/spark/streaming/examples/clickstream/PageViewGenerator.scala
index 884d6d6f34..de70c50473 100644
--- a/examples/src/main/scala/org/apache/spark/streaming/examples/clickstream/PageViewGenerator.scala
+++ b/examples/src/main/scala/org/apache/spark/streaming/examples/clickstream/PageViewGenerator.scala
@@ -17,17 +17,19 @@
 
 package org.apache.spark.streaming.examples.clickstream
 
-import java.net.{InetAddress,ServerSocket,Socket,SocketException}
-import java.io.{InputStreamReader, BufferedReader, PrintWriter}
+import java.net.ServerSocket
+import java.io.PrintWriter
 import util.Random
 
 /** Represents a page view on a website with associated dimension data.*/
-class PageView(val url : String, val status : Int, val zipCode : Int, val userID : Int) {
+class PageView(val url : String, val status : Int, val zipCode : Int, val userID : Int)
+    extends Serializable {
   override def toString() : String = {
     "%s\t%s\t%s\t%s\n".format(url, status, zipCode, userID)
   }
 }
-object PageView {
+
+object PageView extends Serializable {
   def fromString(in : String) : PageView = {
     val parts = in.split("\t")
     new PageView(parts(0), parts(1).toInt, parts(2).toInt, parts(3).toInt)
@@ -39,6 +41,9 @@ object PageView {
   * This should be used in tandem with PageViewStream.scala. Example:
   * $ ./run-example spark.streaming.examples.clickstream.PageViewGenerator 44444 10
   * $ ./run-example spark.streaming.examples.clickstream.PageViewStream errorRatePerZipCode localhost 44444
+  *
+  * When running this, you may want to set the root logging level to ERROR in
+  * conf/log4j.properties to reduce the verbosity of the output.
   * */
 object PageViewGenerator {
   val pages = Map("http://foo.com/"        -> .7,