Added Java API and added more Scala and Java unit tests. Also updated…

… docs.

external/kafka/src/main/scala/org/apache/spark/streaming/kafka/DirectKafkaInputDStream.scala

@@ -55,8 +55,8 @@ private[streaming]
 class DirectKafkaInputDStream[
   K: ClassTag,
   V: ClassTag,
-  U <: Decoder[_]: ClassTag,
-  T <: Decoder[_]: ClassTag,
+  U <: Decoder[K]: ClassTag,
+  T <: Decoder[V]: ClassTag,
   R: ClassTag](
     @transient ssc_ : StreamingContext,
     val kafkaParams: Map[String, String],

external/kafka/src/main/scala/org/apache/spark/streaming/kafka/KafkaCluster.scala

@@ -332,6 +332,9 @@ object KafkaCluster {
       extends ConsumerConfig(originalProps) {
     val seedBrokers: Array[(String, Int)] = brokers.split(",").map { hp =>
       val hpa = hp.split(":")
+      if (hpa.size == 1) {
+        throw new SparkException(s"Broker not the in correct format of <host>:<port> [$brokers]")
+      }
       (hpa(0), hpa(1).toInt)
     }
   }

external/kafka/src/test/java/org/apache/spark/streaming/kafka/JavaDirectKafkaStreamSuite.java

@@ -0,0 +1,171 @@
+/*
+ * 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.kafka;
+
+import java.io.Serializable;
+import java.util.HashMap;
+import java.util.HashSet;
+import java.util.Random;
+import java.util.List;
+import java.util.ArrayList;
+
+import org.apache.spark.SparkConf;
+import org.apache.spark.streaming.Duration;
+import scala.Predef;
+import scala.Tuple2;
+import scala.collection.JavaConverters;
+
+import junit.framework.Assert;
+
+import kafka.common.TopicAndPartition;
+import kafka.message.MessageAndMetadata;
+import kafka.serializer.StringDecoder;
+
+import org.apache.spark.api.java.JavaRDD;
+import org.apache.spark.api.java.function.Function;
+import org.apache.spark.streaming.api.java.JavaDStream;
+import org.apache.spark.streaming.Durations;
+import org.apache.spark.streaming.api.java.JavaStreamingContext;
+
+import org.junit.Test;
+import org.junit.After;
+import org.junit.Before;
+
+public class JavaDirectKafkaStreamSuite implements Serializable {
+  private transient JavaStreamingContext ssc = null;
+  private transient Random random = new Random();
+  private transient KafkaStreamSuiteBase suiteBase = null;
+
+  @Before
+  public void setUp() {
+      suiteBase = new KafkaStreamSuiteBase() { };
+      suiteBase.setupKafka();
+      System.clearProperty("spark.driver.port");
+      SparkConf sparkConf = new SparkConf()
+              .setMaster("local[4]").setAppName(this.getClass().getSimpleName());
+      ssc = new JavaStreamingContext(sparkConf, Durations.milliseconds(200));
+  }
+
+  @After
+  public void tearDown() {
+      ssc.stop();
+      ssc = null;
+      System.clearProperty("spark.driver.port");
+      suiteBase.tearDownKafka();
+  }
+
+  @Test
+  public void testKafkaStream() throws InterruptedException {
+    String topic1 = "topic1";
+    String topic2 = "topic2";
+
+    List<String> topic1data = createTopicAndSendData(topic1);
+    List<String> topic2data = createTopicAndSendData(topic2);
+
+    HashSet<String> sent = new HashSet<String>();
+    sent.addAll(topic1data);
+    sent.addAll(topic2data);
+
+    HashMap<String, String> kafkaParams = new HashMap<String, String>();
+    kafkaParams.put("metadata.broker.list", suiteBase.brokerAddress());
+    kafkaParams.put("auto.offset.reset", "smallest");
+
+    JavaDStream<String> stream1 = KafkaUtils.createDirectStream(
+        ssc,
+        String.class,
+        String.class,
+        StringDecoder.class,
+        StringDecoder.class,
+        kafkaParams,
+        topicToSet(topic1)
+    ).map(
+        new Function<Tuple2<String, String>, String>() {
+          @Override
+          public String call(scala.Tuple2<String, String> kv) throws Exception {
+            return kv._2();
+          }
+        }
+    );
+
+    JavaDStream<String> stream2 = KafkaUtils.createDirectStream(
+        ssc,
+        String.class,
+        String.class,
+        StringDecoder.class,
+        StringDecoder.class,
+        String.class,
+        kafkaParams,
+        topicOffsetToMap(topic2, (long) 0),
+        new Function<MessageAndMetadata<String, String>, String>() {
+          @Override
+          public String call(MessageAndMetadata<String, String> msgAndMd) throws Exception {
+            return msgAndMd.message();
+          }
+        }
+    );
+    JavaDStream<String> unifiedStream = stream1.union(stream2);
+
+    final HashSet<String> result = new HashSet<String>();
+    unifiedStream.foreachRDD(
+        new Function<JavaRDD<String>, Void> () {
+          @Override
+          public Void call(org.apache.spark.api.java.JavaRDD<String> rdd) throws Exception {
+            result.addAll(rdd.collect());
+            return null;
+          }
+        }
+    );
+    ssc.start();
+    long startTime = System.currentTimeMillis();
+    boolean matches = false;
+    while (!matches && System.currentTimeMillis() - startTime < 20000) {
+      matches = sent.size() == result.size();
+      Thread.sleep(50);
+    }
+    Assert.assertEquals(sent, result);
+    ssc.stop();
+  }
+
+  private HashSet<String> topicToSet(String topic) {
+    HashSet<String> topicSet = new HashSet<String>();
+    topicSet.add(topic);
+    return topicSet;
+  }
+
+  private HashMap<TopicAndPartition, Long> topicOffsetToMap(String topic, Long offsetToStart) {
+    HashMap<TopicAndPartition, Long> topicMap = new HashMap<TopicAndPartition, Long>();
+    topicMap.put(new TopicAndPartition(topic, scala.Int.box(0)), offsetToStart);
+    return topicMap;
+  }
+
+  private  List<String> createTopicAndSendData(String topic) {
+    List<String> data = java.util.Arrays.asList(topic+"-1", topic+"-2", topic+"-3");
+    HashMap<String, Integer> sent = new HashMap<String, Integer>();
+    for(String i: data) {
+      sent.put(i, 1);
+    }
+
+    suiteBase.createTopic(topic);
+
+    HashMap<String, Object> tmp = new HashMap<String, Object>(sent);
+    suiteBase.produceAndSendMessage(topic,
+        JavaConverters.mapAsScalaMapConverter(tmp).asScala().toMap(
+            Predef.<Tuple2<String, Object>>conforms()));
+    return data;
+  }
+}

external/kafka/src/test/scala/org/apache/spark/streaming/kafka/DirectKafkaStreamSuite.scala

@@ -32,19 +32,15 @@ import org.apache.spark.rdd.RDD
 import org.apache.spark.streaming.{Milliseconds, StreamingContext, Time}
 import org.apache.spark.streaming.dstream.{DStream, InputDStream}
 import org.apache.spark.util.Utils
+import kafka.common.TopicAndPartition
+import kafka.message.MessageAndMetadata
 
 class DirectKafkaStreamSuite extends KafkaStreamSuiteBase
   with BeforeAndAfter with BeforeAndAfterAll with Eventually {
   val sparkConf = new SparkConf()
     .setMaster("local[4]")
     .setAppName(this.getClass.getSimpleName)
 
-  val brokerHost = "localhost"
-
-  val kafkaParams = Map(
-    "metadata.broker.list" -> s"$brokerHost:$brokerPort",
-    "auto.offset.reset" -> "smallest"
-  )
 
   var ssc: StreamingContext = _
   var testDir: File = _
@@ -66,13 +62,18 @@ class DirectKafkaStreamSuite extends KafkaStreamSuiteBase
     }
   }
 
-  test("basic receiving with multiple topics") {
-    val topics = Set("newA", "newB")
+  test("basic receiving with multiple topics and smallest starting offset") {
+    val topics = Set("topic1", "topic2", "topic3")
     val data = Map("a" -> 7, "b" -> 9)
     topics.foreach { t =>
       createTopic(t)
       produceAndSendMessage(t, data)
     }
+    val kafkaParams = Map(
+      "metadata.broker.list" -> s"$brokerAddress",
+      "auto.offset.reset" -> "smallest"
+    )
+
     ssc = new StreamingContext(sparkConf, Milliseconds(200))
     val stream = withClue("Error creating direct stream") {
       KafkaUtils.createDirectStream[String, String, StringDecoder, StringDecoder](
@@ -106,13 +107,107 @@ class DirectKafkaStreamSuite extends KafkaStreamSuiteBase
     }
     ssc.stop()
   }
+  test("receiving from largest starting offset") {
+    val topic = "largest"
+    val topicPartition = TopicAndPartition(topic, 0)
+    val data = Map("a" -> 10)
+    createTopic(topic)
+    val kafkaParams = Map(
+      "metadata.broker.list" -> s"$brokerAddress",
+      "auto.offset.reset" -> "largest"
+    )
+    val kc = new KafkaCluster(kafkaParams)
+    def getLatestOffset(): Long = {
+      kc.getLatestLeaderOffsets(Set(topicPartition)).right.get(topicPartition).offset
+    }
+
+    // Send some initial messages before starting context
+    produceAndSendMessage(topic, data)
+    eventually(timeout(10 seconds), interval(20 milliseconds)) {
+      assert(getLatestOffset() > 3)
+    }
+    val offsetBeforeStart = getLatestOffset()
+
+    // Setup context and kafka stream with largest offset
+    ssc = new StreamingContext(sparkConf, Milliseconds(200))
+    val stream = withClue("Error creating direct stream") {
+      KafkaUtils.createDirectStream[String, String, StringDecoder, StringDecoder](
+        ssc, kafkaParams, Set(topic))
+    }
+    assert(
+      stream.asInstanceOf[DirectKafkaInputDStream[_, _, _, _, _]]
+        .fromOffsets(topicPartition) >= offsetBeforeStart,
+      "Start offset not from latest"
+    )
+
+    val collectedData = new mutable.ArrayBuffer[String]()
+    stream.map { _._2 }.foreachRDD { rdd => collectedData ++= rdd.collect() }
+    ssc.start()
+    val newData = Map("b" -> 10)
+    produceAndSendMessage(topic, newData)
+    eventually(timeout(10 seconds), interval(50 milliseconds)) {
+      collectedData.contains("b")
+    }
+    assert(!collectedData.contains("a"))
+  }
+
+
+  test("creating stream by offset") {
+    val topic = "offset"
+    val topicPartition = TopicAndPartition(topic, 0)
+    val data = Map("a" -> 10)
+    createTopic(topic)
+    val kafkaParams = Map(
+      "metadata.broker.list" -> s"$brokerAddress",
+      "auto.offset.reset" -> "largest"
+    )
+    val kc = new KafkaCluster(kafkaParams)
+    def getLatestOffset(): Long = {
+      kc.getLatestLeaderOffsets(Set(topicPartition)).right.get(topicPartition).offset
+    }
+
+    // Send some initial messages before starting context
+    produceAndSendMessage(topic, data)
+    eventually(timeout(10 seconds), interval(20 milliseconds)) {
+      assert(getLatestOffset() >= 10)
+    }
+    val offsetBeforeStart = getLatestOffset()
+
+    // Setup context and kafka stream with largest offset
+    ssc = new StreamingContext(sparkConf, Milliseconds(200))
+    val stream = withClue("Error creating direct stream") {
+      KafkaUtils.createDirectStream[String, String, StringDecoder, StringDecoder, String](
+        ssc, kafkaParams, Map(topicPartition -> 11L),
+        (m: MessageAndMetadata[String, String]) => m.message())
+    }
+    assert(
+      stream.asInstanceOf[DirectKafkaInputDStream[_, _, _, _, _]]
+        .fromOffsets(topicPartition) >= offsetBeforeStart,
+      "Start offset not from latest"
+    )
+
+    val collectedData = new mutable.ArrayBuffer[String]()
+    stream.foreachRDD { rdd => collectedData ++= rdd.collect() }
+    ssc.start()
+    val newData = Map("b" -> 10)
+    produceAndSendMessage(topic, newData)
+    eventually(timeout(10 seconds), interval(50 milliseconds)) {
+      collectedData.contains("b")
+    }
+    assert(!collectedData.contains("a"))
+  }
 
   // Test to verify the offset ranges can be recovered from the checkpoints
   test("offset recovery") {
     val topic = "recovery"
     createTopic(topic)
     testDir = Utils.createTempDir()
 
+    val kafkaParams = Map(
+      "metadata.broker.list" -> s"$brokerAddress",
+      "auto.offset.reset" -> "smallest"
+    )
+
     // Send data to Kafka and wait for it to be received
     def sendDataAndWaitForReceive(data: Seq[Int]) {
       val strings = data.map { _.toString}

external/kafka/src/test/scala/org/apache/spark/streaming/kafka/KafkaClusterSuite.scala

@@ -23,14 +23,10 @@ import org.scalatest.BeforeAndAfter
 import kafka.common.TopicAndPartition
 
 class KafkaClusterSuite extends KafkaStreamSuiteBase with BeforeAndAfter {
-  val brokerHost = "localhost"
-
-  val kafkaParams = Map("metadata.broker.list" -> s"$brokerHost:$brokerPort")
 
+  val kafkaParams = Map("metadata.broker.list" -> s"$brokerAddress")
   val kc = new KafkaCluster(kafkaParams)
-
   val topic = "kcsuitetopic" + Random.nextInt(10000)
-
   val topicAndPartition = TopicAndPartition(topic, 0)
 
   before {

external/kafka/src/test/scala/org/apache/spark/streaming/kafka/KafkaStreamSuite.scala

@@ -48,15 +48,18 @@ import org.apache.spark.util.Utils
  */
 abstract class KafkaStreamSuiteBase extends FunSuite with Eventually with Logging {
 
+  val zkHost = "localhost"
+  var zkPort: Int = 0
   var zkAddress: String = _
   var zkClient: ZkClient = _
 
-  private val zkHost = "localhost"
+  val brokerHost = "localhost"
+  var brokerPort = 9092
+  var brokerAddress: String = _
+
   private val zkConnectionTimeout = 6000
   private val zkSessionTimeout = 6000
   private var zookeeper: EmbeddedZookeeper = _
-  private var zkPort: Int = 0
-  protected var brokerPort = 9092
   private var brokerConf: KafkaConfig = _
   private var server: KafkaServer = _
   private var producer: Producer[String, String] = _
@@ -67,6 +70,7 @@ abstract class KafkaStreamSuiteBase extends FunSuite with Eventually with Loggin
     // Get the actual zookeeper binding port
     zkPort = zookeeper.actualPort
     zkAddress = s"$zkHost:$zkPort"
+
     logInfo("==================== 0 ====================")
 
     zkClient = new ZkClient(zkAddress, zkSessionTimeout, zkConnectionTimeout,
@@ -94,6 +98,7 @@ abstract class KafkaStreamSuiteBase extends FunSuite with Eventually with Loggin
     }
 
     Thread.sleep(2000)
+    brokerAddress = s"$brokerHost:$brokerPort"
     logInfo("==================== 4 ====================")
   }