[SPARK-7895] [STREAMING] [EXAMPLES] Move Kafka examples from scala-2.10/src to src

Since `spark-streaming-kafka` now is published for both Scala 2.10 and 2.11, we can move `KafkaWordCount` and `DirectKafkaWordCount` from `examples/scala-2.10/src/` to `examples/src/` so that they will appear in `spark-examples-***-jar` for Scala 2.11.

Author: zsxwing <zsxwing@gmail.com>

Closes #6436 from zsxwing/SPARK-7895 and squashes the following commits:

c6052f1 [zsxwing] Update examples/pom.xml
0bcfa87 [zsxwing] Fix the sleep time
b9d1256 [zsxwing] Move Kafka examples from scala-2.10/src to src

4 files changed, 401 insertions, 0 deletions

diff --git a/examples/src/main/java/org/apache/spark/examples/streaming/JavaDirectKafkaWordCount.java b/examples/src/main/java/org/apache/spark/examples/streaming/JavaDirectKafkaWordCount.java
new file mode 100644
index 0000000000..bab9f2478e
--- /dev/null
+++ b/examples/src/main/java/org/apache/spark/examples/streaming/JavaDirectKafkaWordCount.java
@@ -0,0 +1,113 @@
+/*
+ * 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.examples.streaming;
+
+import java.util.HashMap;
+import java.util.HashSet;
+import java.util.Arrays;
+import java.util.regex.Pattern;
+
+import scala.Tuple2;
+
+import com.google.common.collect.Lists;
+import kafka.serializer.StringDecoder;
+
+import org.apache.spark.SparkConf;
+import org.apache.spark.api.java.function.*;
+import org.apache.spark.streaming.api.java.*;
+import org.apache.spark.streaming.kafka.KafkaUtils;
+import org.apache.spark.streaming.Durations;
+
+/**
+ * Consumes messages from one or more topics in Kafka and does wordcount.
+ * Usage: DirectKafkaWordCount <brokers> <topics>
+ *   <brokers> is a list of one or more Kafka brokers
+ *   <topics> is a list of one or more kafka topics to consume from
+ *
+ * Example:
+ *    $ bin/run-example streaming.KafkaWordCount broker1-host:port,broker2-host:port topic1,topic2
+ */
+
+public final class JavaDirectKafkaWordCount {
+  private static final Pattern SPACE = Pattern.compile(" ");
+
+  public static void main(String[] args) {
+    if (args.length < 2) {
+      System.err.println("Usage: DirectKafkaWordCount <brokers> <topics>\n" +
+          "  <brokers> is a list of one or more Kafka brokers\n" +
+          "  <topics> is a list of one or more kafka topics to consume from\n\n");
+      System.exit(1);
+    }
+
+    StreamingExamples.setStreamingLogLevels();
+
+    String brokers = args[0];
+    String topics = args[1];
+
+    // Create context with 2 second batch interval
+    SparkConf sparkConf = new SparkConf().setAppName("JavaDirectKafkaWordCount");
+    JavaStreamingContext jssc = new JavaStreamingContext(sparkConf, Durations.seconds(2));
+
+    HashSet<String> topicsSet = new HashSet<String>(Arrays.asList(topics.split(",")));
+    HashMap<String, String> kafkaParams = new HashMap<String, String>();
+    kafkaParams.put("metadata.broker.list", brokers);
+
+    // Create direct kafka stream with brokers and topics
+    JavaPairInputDStream<String, String> messages = KafkaUtils.createDirectStream(
+        jssc,
+        String.class,
+        String.class,
+        StringDecoder.class,
+        StringDecoder.class,
+        kafkaParams,
+        topicsSet
+    );
+
+    // Get the lines, split them into words, count the words and print
+    JavaDStream<String> lines = messages.map(new Function<Tuple2<String, String>, String>() {
+      @Override
+      public String call(Tuple2<String, String> tuple2) {
+        return tuple2._2();
+      }
+    });
+    JavaDStream<String> words = lines.flatMap(new FlatMapFunction<String, String>() {
+      @Override
+      public Iterable<String> call(String x) {
+        return Lists.newArrayList(SPACE.split(x));
+      }
+    });
+    JavaPairDStream<String, Integer> wordCounts = words.mapToPair(
+      new PairFunction<String, String, Integer>() {
+        @Override
+        public Tuple2<String, Integer> call(String s) {
+          return new Tuple2<String, Integer>(s, 1);
+        }
+      }).reduceByKey(
+        new Function2<Integer, Integer, Integer>() {
+        @Override
+        public Integer call(Integer i1, Integer i2) {
+          return i1 + i2;
+        }
+      });
+    wordCounts.print();
+
+    // Start the computation
+    jssc.start();
+    jssc.awaitTermination();
+  }
+}
diff --git a/examples/src/main/java/org/apache/spark/examples/streaming/JavaKafkaWordCount.java b/examples/src/main/java/org/apache/spark/examples/streaming/JavaKafkaWordCount.java
new file mode 100644
index 0000000000..16ae9a3319
--- /dev/null
+++ b/examples/src/main/java/org/apache/spark/examples/streaming/JavaKafkaWordCount.java
@@ -0,0 +1,113 @@
+/*
+ * 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.examples.streaming;
+
+import java.util.Map;
+import java.util.HashMap;
+import java.util.regex.Pattern;
+
+
+import scala.Tuple2;
+
+import com.google.common.collect.Lists;
+import org.apache.spark.SparkConf;
+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.examples.streaming.StreamingExamples;
+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.JavaPairReceiverInputDStream;
+import org.apache.spark.streaming.api.java.JavaStreamingContext;
+import org.apache.spark.streaming.kafka.KafkaUtils;
+
+/**
+ * Consumes messages from one or more topics in Kafka and does wordcount.
+ *
+ * Usage: JavaKafkaWordCount <zkQuorum> <group> <topics> <numThreads>
+ *   <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
+ *
+ * To run this example:
+ *   `$ bin/run-example org.apache.spark.examples.streaming.JavaKafkaWordCount zoo01,zoo02, \
+ *    zoo03 my-consumer-group topic1,topic2 1`
+ */
+
+public final class JavaKafkaWordCount {
+  private static final Pattern SPACE = Pattern.compile(" ");
+
+  private JavaKafkaWordCount() {
+  }
+
+  public static void main(String[] args) {
+    if (args.length < 4) {
+      System.err.println("Usage: JavaKafkaWordCount <zkQuorum> <group> <topics> <numThreads>");
+      System.exit(1);
+    }
+
+    StreamingExamples.setStreamingLogLevels();
+    SparkConf sparkConf = new SparkConf().setAppName("JavaKafkaWordCount");
+    // Create the context with a 1 second batch size
+    JavaStreamingContext jssc = new JavaStreamingContext(sparkConf, new Duration(2000));
+
+    int numThreads = Integer.parseInt(args[3]);
+    Map<String, Integer> topicMap = new HashMap<String, Integer>();
+    String[] topics = args[2].split(",");
+    for (String topic: topics) {
+      topicMap.put(topic, numThreads);
+    }
+
+    JavaPairReceiverInputDStream<String, String> messages =
+            KafkaUtils.createStream(jssc, args[0], args[1], topicMap);
+
+    JavaDStream<String> lines = messages.map(new Function<Tuple2<String, String>, String>() {
+      @Override
+      public String call(Tuple2<String, String> tuple2) {
+        return tuple2._2();
+      }
+    });
+
+    JavaDStream<String> words = lines.flatMap(new FlatMapFunction<String, String>() {
+      @Override
+      public Iterable<String> call(String x) {
+        return Lists.newArrayList(SPACE.split(x));
+      }
+    });
+
+    JavaPairDStream<String, Integer> wordCounts = words.mapToPair(
+      new PairFunction<String, String, Integer>() {
+        @Override
+        public Tuple2<String, Integer> call(String s) {
+          return new Tuple2<String, Integer>(s, 1);
+        }
+      }).reduceByKey(new Function2<Integer, Integer, Integer>() {
+        @Override
+        public Integer call(Integer i1, Integer i2) {
+          return i1 + i2;
+        }
+      });
+
+    wordCounts.print();
+    jssc.start();
+    jssc.awaitTermination();
+  }
+}
diff --git a/examples/src/main/scala/org/apache/spark/examples/streaming/DirectKafkaWordCount.scala b/examples/src/main/scala/org/apache/spark/examples/streaming/DirectKafkaWordCount.scala
new file mode 100644
index 0000000000..11a8cf0953
--- /dev/null
+++ b/examples/src/main/scala/org/apache/spark/examples/streaming/DirectKafkaWordCount.scala
@@ -0,0 +1,72 @@
+/*
+ * 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.examples.streaming
+
+import kafka.serializer.StringDecoder
+
+import org.apache.spark.streaming._
+import org.apache.spark.streaming.kafka._
+import org.apache.spark.SparkConf
+
+/**
+ * Consumes messages from one or more topics in Kafka and does wordcount.
+ * Usage: DirectKafkaWordCount <brokers> <topics>
+ *   <brokers> is a list of one or more Kafka brokers
+ *   <topics> is a list of one or more kafka topics to consume from
+ *
+ * Example:
+ *    $ bin/run-example streaming.DirectKafkaWordCount broker1-host:port,broker2-host:port \
+ *    topic1,topic2
+ */
+object DirectKafkaWordCount {
+  def main(args: Array[String]) {
+    if (args.length < 2) {
+      System.err.println(s"""
+        |Usage: DirectKafkaWordCount <brokers> <topics>
+        |  <brokers> is a list of one or more Kafka brokers
+        |  <topics> is a list of one or more kafka topics to consume from
+        |
+        """.stripMargin)
+      System.exit(1)
+    }
+
+    StreamingExamples.setStreamingLogLevels()
+
+    val Array(brokers, topics) = args
+
+    // Create context with 2 second batch interval
+    val sparkConf = new SparkConf().setAppName("DirectKafkaWordCount")
+    val ssc =  new StreamingContext(sparkConf, Seconds(2))
+
+    // Create direct kafka stream with brokers and topics
+    val topicsSet = topics.split(",").toSet
+    val kafkaParams = Map[String, String]("metadata.broker.list" -> brokers)
+    val messages = KafkaUtils.createDirectStream[String, String, StringDecoder, StringDecoder](
+      ssc, kafkaParams, topicsSet)
+
+    // Get the lines, split them into words, count the words and print
+    val lines = messages.map(_._2)
+    val words = lines.flatMap(_.split(" "))
+    val wordCounts = words.map(x => (x, 1L)).reduceByKey(_ + _)
+    wordCounts.print()
+
+    // Start the computation
+    ssc.start()
+    ssc.awaitTermination()
+  }
+}
diff --git a/examples/src/main/scala/org/apache/spark/examples/streaming/KafkaWordCount.scala b/examples/src/main/scala/org/apache/spark/examples/streaming/KafkaWordCount.scala
new file mode 100644
index 0000000000..9ae1b045c2
--- /dev/null
+++ b/examples/src/main/scala/org/apache/spark/examples/streaming/KafkaWordCount.scala
@@ -0,0 +1,103 @@
+/*
+ * 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.examples.streaming
+
+import java.util.HashMap
+
+import org.apache.kafka.clients.producer.{ProducerConfig, KafkaProducer, ProducerRecord}
+
+import org.apache.spark.streaming._
+import org.apache.spark.streaming.kafka._
+import org.apache.spark.SparkConf
+
+/**
+ * Consumes messages from one or more topics in Kafka and does wordcount.
+ * Usage: KafkaWordCount <zkQuorum> <group> <topics> <numThreads>
+ *   <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:
+ *    `$ bin/run-example \
+ *      org.apache.spark.examples.streaming.KafkaWordCount zoo01,zoo02,zoo03 \
+ *      my-consumer-group topic1,topic2 1`
+ */
+object KafkaWordCount {
+  def main(args: Array[String]) {
+    if (args.length < 4) {
+      System.err.println("Usage: KafkaWordCount <zkQuorum> <group> <topics> <numThreads>")
+      System.exit(1)
+    }
+
+    StreamingExamples.setStreamingLogLevels()
+
+    val Array(zkQuorum, group, topics, numThreads) = args
+    val sparkConf = new SparkConf().setAppName("KafkaWordCount")
+    val ssc =  new StreamingContext(sparkConf, Seconds(2))
+    ssc.checkpoint("checkpoint")
+
+    val topicMap = topics.split(",").map((_,numThreads.toInt)).toMap
+    val lines = KafkaUtils.createStream(ssc, zkQuorum, group, topicMap).map(_._2)
+    val words = lines.flatMap(_.split(" "))
+    val wordCounts = words.map(x => (x, 1L))
+      .reduceByKeyAndWindow(_ + _, _ - _, Minutes(10), Seconds(2), 2)
+    wordCounts.print()
+
+    ssc.start()
+    ssc.awaitTermination()
+  }
+}
+
+// Produces some random words between 1 and 100.
+object KafkaWordCountProducer {
+
+  def main(args: Array[String]) {
+    if (args.length < 4) {
+      System.err.println("Usage: KafkaWordCountProducer <metadataBrokerList> <topic> " +
+        "<messagesPerSec> <wordsPerMessage>")
+      System.exit(1)
+    }
+
+    val Array(brokers, topic, messagesPerSec, wordsPerMessage) = args
+
+    // Zookeeper connection properties
+    val props = new HashMap[String, Object]()
+    props.put(ProducerConfig.BOOTSTRAP_SERVERS_CONFIG, brokers)
+    props.put(ProducerConfig.VALUE_SERIALIZER_CLASS_CONFIG,
+      "org.apache.kafka.common.serialization.StringSerializer")
+    props.put(ProducerConfig.KEY_SERIALIZER_CLASS_CONFIG,
+      "org.apache.kafka.common.serialization.StringSerializer")
+
+    val producer = new KafkaProducer[String, String](props)
+
+    // Send some messages
+    while(true) {
+      (1 to messagesPerSec.toInt).foreach { messageNum =>
+        val str = (1 to wordsPerMessage.toInt).map(x => scala.util.Random.nextInt(10).toString)
+          .mkString(" ")
+
+        val message = new ProducerRecord[String, String](topic, null, str)
+        producer.send(message)
+      }
+
+      Thread.sleep(1000)
+    }
+  }
+
+}