[SPARK-4964][Streaming][Kafka] More updates to Exactly-once Kafka stream

Changes
- Added example
- Added a critical unit test that verifies that offset ranges can be recovered through checkpoints

Might add more changes.

Author: Tathagata Das <tathagata.das1565@gmail.com>

Closes #4384 from tdas/new-kafka-fixes and squashes the following commits:

7c931c3 [Tathagata Das] Small update
3ed9284 [Tathagata Das] updated scala doc
83d0402 [Tathagata Das] Added JavaDirectKafkaWordCount example.
26df23c [Tathagata Das] Updates based on PR comments from Cody
e4abf69 [Tathagata Das] Scala doc improvements and stuff.
bb65232 [Tathagata Das] Fixed test bug and refactored KafkaStreamSuite
50f2b56 [Tathagata Das] Added Java API and added more Scala and Java unit tests. Also updated docs.
e73589c [Tathagata Das] Minor changes.
4986784 [Tathagata Das] Added unit test to kafka offset recovery
6a91cab [Tathagata Das] Added example

2 files changed, 184 insertions, 0 deletions

diff --git a/examples/scala-2.10/src/main/java/org/apache/spark/examples/streaming/JavaDirectKafkaWordCount.java b/examples/scala-2.10/src/main/java/org/apache/spark/examples/streaming/JavaDirectKafkaWordCount.java
new file mode 100644
index 0000000000..bab9f2478e
--- /dev/null
+++ b/examples/scala-2.10/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/scala-2.10/src/main/scala/org/apache/spark/examples/streaming/DirectKafkaWordCount.scala b/examples/scala-2.10/src/main/scala/org/apache/spark/examples/streaming/DirectKafkaWordCount.scala
new file mode 100644
index 0000000000..deb08fd57b
--- /dev/null
+++ b/examples/scala-2.10/src/main/scala/org/apache/spark/examples/streaming/DirectKafkaWordCount.scala
@@ -0,0 +1,71 @@
+/*
+ * 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.KafkaWordCount 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()
+  }
+}