[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

2 files changed, 175 insertions, 0 deletions

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)
+    }
+  }
+
+}