diff options
author | Andrew Or <andrewor14@gmail.com> | 2014-01-09 21:38:48 -0800 |
---|---|---|
committer | Andrew Or <andrewor14@gmail.com> | 2014-01-09 21:38:48 -0800 |
commit | d76e1f90a84755e9e68a27c9fda59f2175a73819 (patch) | |
tree | 848438461b2bbf711ef3dbd888e2c3463d0837b4 /streaming | |
parent | 80ba9f8ba06e623600469ddb3e59dffcbedee1d0 (diff) | |
parent | 300eaa994c399a0c991c1e39b4dd864a7aa4bdc6 (diff) | |
download | spark-d76e1f90a84755e9e68a27c9fda59f2175a73819.tar.gz spark-d76e1f90a84755e9e68a27c9fda59f2175a73819.tar.bz2 spark-d76e1f90a84755e9e68a27c9fda59f2175a73819.zip |
Merge github.com:apache/incubator-spark
Conflicts:
core/src/main/scala/org/apache/spark/SparkEnv.scala
streaming/src/test/java/org/apache/spark/streaming/JavaAPISuite.java
Diffstat (limited to 'streaming')
17 files changed, 135 insertions, 1189 deletions
diff --git a/streaming/pom.xml b/streaming/pom.xml index e3b6fee9b2..459756912d 100644 --- a/streaming/pom.xml +++ b/streaming/pom.xml @@ -61,59 +61,10 @@ <version>1.9.11</version> </dependency> <dependency> - <groupId>com.sksamuel.kafka</groupId> - <artifactId>kafka_${scala.binary.version}</artifactId> - <version>0.8.0-beta1</version> - <exclusions> - <exclusion> - <groupId>com.sun.jmx</groupId> - <artifactId>jmxri</artifactId> - </exclusion> - <exclusion> - <groupId>com.sun.jdmk</groupId> - <artifactId>jmxtools</artifactId> - </exclusion> - <exclusion> - <groupId>net.sf.jopt-simple</groupId> - <artifactId>jopt-simple</artifactId> - </exclusion> - </exclusions> - </dependency> - <dependency> - <groupId>org.apache.flume</groupId> - <artifactId>flume-ng-sdk</artifactId> - <version>1.2.0</version> - <exclusions> - <exclusion> - <groupId>org.jboss.netty</groupId> - <artifactId>netty</artifactId> - </exclusion> - <exclusion> - <groupId>org.xerial.snappy</groupId> - <artifactId>*</artifactId> - </exclusion> - </exclusions> - </dependency> - <dependency> - <groupId>org.twitter4j</groupId> - <artifactId>twitter4j-stream</artifactId> - <version>3.0.3</version> - <exclusions> - <exclusion> - <groupId>org.jboss.netty</groupId> - <artifactId>netty</artifactId> - </exclusion> - </exclusions> - </dependency> - <dependency> <groupId>org.scala-lang</groupId> <artifactId>scala-library</artifactId> </dependency> <dependency> - <groupId>${akka.group}</groupId> - <artifactId>akka-zeromq_${scala.binary.version}</artifactId> - </dependency> - <dependency> <groupId>org.scalatest</groupId> <artifactId>scalatest_${scala.binary.version}</artifactId> <scope>test</scope> @@ -137,11 +88,6 @@ <groupId>commons-io</groupId> <artifactId>commons-io</artifactId> </dependency> - <dependency> - <groupId>org.eclipse.paho</groupId> - <artifactId>mqtt-client</artifactId> - <version>0.4.0</version> - </dependency> </dependencies> <build> <outputDirectory>target/scala-${scala.binary.version}/classes</outputDirectory> @@ -151,6 +97,35 @@ <groupId>org.scalatest</groupId> <artifactId>scalatest-maven-plugin</artifactId> </plugin> + + <!-- + This plugin forces the generation of jar containing streaming test classes, + so that the tests classes of external modules can use them. The two execution profiles + are necessary - first one for 'mvn package', second one for 'mvn compile'. Ideally, + 'mvn compile' should not compile test classes and therefore should not need this. + However, an open Maven bug (http://jira.codehaus.org/browse/MNG-3559) + causes the compilation to fail if streaming test-jar is not generated. Hence, the + second execution profile for 'mvn compile'. + --> + <plugin> + <groupId>org.apache.maven.plugins</groupId> + <artifactId>maven-jar-plugin</artifactId> + <version>2.2</version> + <executions> + <execution> + <goals> + <goal>test-jar</goal> + </goals> + </execution> + <execution> + <id>test-jar-on-compile</id> + <phase>compile</phase> + <goals> + <goal>test-jar</goal> + </goals> + </execution> + </executions> + </plugin> </plugins> </build> </project> diff --git a/streaming/src/main/scala/org/apache/spark/streaming/StreamingContext.scala b/streaming/src/main/scala/org/apache/spark/streaming/StreamingContext.scala index 304986f187..693cb7fc30 100644 --- a/streaming/src/main/scala/org/apache/spark/streaming/StreamingContext.scala +++ b/streaming/src/main/scala/org/apache/spark/streaming/StreamingContext.scala @@ -17,23 +17,6 @@ package org.apache.spark.streaming -import akka.actor.Props -import akka.actor.SupervisorStrategy -import akka.zeromq.Subscribe -import akka.util.ByteString - -import org.apache.spark.streaming.dstream._ -import org.apache.spark.streaming.scheduler.StreamingListener - -import org.apache.spark._ -import org.apache.spark.rdd.RDD -import org.apache.spark.streaming.receivers.ReceiverSupervisorStrategy -import org.apache.spark.streaming.receivers.ZeroMQReceiver -import org.apache.spark.storage.StorageLevel -import org.apache.spark.util.MetadataCleaner -import org.apache.spark.streaming.receivers.ActorReceiver -import org.apache.spark.streaming.scheduler.{JobScheduler, NetworkInputTracker} - import scala.collection.mutable.Queue import scala.collection.Map import scala.reflect.ClassTag @@ -41,14 +24,21 @@ import scala.reflect.ClassTag import java.io.InputStream import java.util.concurrent.atomic.AtomicInteger +import akka.actor.Props +import akka.actor.SupervisorStrategy import org.apache.hadoop.io.LongWritable import org.apache.hadoop.io.Text import org.apache.hadoop.mapreduce.{InputFormat => NewInputFormat} import org.apache.hadoop.mapreduce.lib.input.TextInputFormat import org.apache.hadoop.fs.Path -import twitter4j.Status -import twitter4j.auth.Authorization +import org.apache.spark._ +import org.apache.spark.rdd.RDD +import org.apache.spark.storage.StorageLevel +import org.apache.spark.util.MetadataCleaner +import org.apache.spark.streaming.dstream._ +import org.apache.spark.streaming.receivers._ +import org.apache.spark.streaming.scheduler._ /** * A StreamingContext is the main entry point for Spark Streaming functionality. Besides the basic @@ -238,74 +228,6 @@ class StreamingContext private ( } /** - * Create an input stream that receives messages pushed by a zeromq publisher. - * @param publisherUrl Url of remote zeromq publisher - * @param subscribe topic to subscribe to - * @param bytesToObjects A zeroMQ stream publishes sequence of frames for each topic - * and each frame has sequence of byte thus it needs the converter - * (which might be deserializer of bytes) to translate from sequence - * of sequence of bytes, where sequence refer to a frame - * and sub sequence refer to its payload. - * @param storageLevel RDD storage level. Defaults to memory-only. - */ - def zeroMQStream[T: ClassTag]( - publisherUrl:String, - subscribe: Subscribe, - bytesToObjects: Seq[ByteString] ⇒ Iterator[T], - storageLevel: StorageLevel = StorageLevel.MEMORY_ONLY_SER_2, - supervisorStrategy: SupervisorStrategy = ReceiverSupervisorStrategy.defaultStrategy - ): DStream[T] = { - actorStream(Props(new ZeroMQReceiver(publisherUrl, subscribe, bytesToObjects)), - "ZeroMQReceiver", storageLevel, supervisorStrategy) - } - - /** - * Create an input stream that pulls messages from a Kafka Broker. - * @param zkQuorum Zookeper quorum (hostname:port,hostname:port,..). - * @param groupId The group id for this consumer. - * @param topics Map of (topic_name -> numPartitions) to consume. Each partition is consumed - * in its own thread. - * @param storageLevel Storage level to use for storing the received objects - * (default: StorageLevel.MEMORY_AND_DISK_SER_2) - */ - def kafkaStream( - zkQuorum: String, - groupId: String, - topics: Map[String, Int], - storageLevel: StorageLevel = StorageLevel.MEMORY_ONLY_SER_2 - ): DStream[(String, String)] = { - val kafkaParams = Map[String, String]( - "zookeeper.connect" -> zkQuorum, "group.id" -> groupId, - "zookeeper.connection.timeout.ms" -> "10000") - kafkaStream[String, String, kafka.serializer.StringDecoder, kafka.serializer.StringDecoder]( - kafkaParams, - topics, - storageLevel) - } - - /** - * Create an input stream that pulls messages from a Kafka Broker. - * @param kafkaParams Map of kafka configuration paramaters. - * See: http://kafka.apache.org/configuration.html - * @param topics Map of (topic_name -> numPartitions) to consume. Each partition is consumed - * in its own thread. - * @param storageLevel Storage level to use for storing the received objects - */ - def kafkaStream[ - K: ClassTag, - V: ClassTag, - U <: kafka.serializer.Decoder[_]: Manifest, - T <: kafka.serializer.Decoder[_]: Manifest]( - kafkaParams: Map[String, String], - topics: Map[String, Int], - storageLevel: StorageLevel - ): DStream[(K, V)] = { - val inputStream = new KafkaInputDStream[K, V, U, T](this, kafkaParams, topics, storageLevel) - registerInputStream(inputStream) - inputStream - } - - /** * Create a input stream from TCP source hostname:port. Data is received using * a TCP socket and the receive bytes is interpreted as UTF8 encoded `\n` delimited * lines. @@ -344,22 +266,6 @@ class StreamingContext private ( } /** - * Create a input stream from a Flume source. - * @param hostname Hostname of the slave machine to which the flume data will be sent - * @param port Port of the slave machine to which the flume data will be sent - * @param storageLevel Storage level to use for storing the received objects - */ - def flumeStream ( - hostname: String, - port: Int, - storageLevel: StorageLevel = StorageLevel.MEMORY_AND_DISK_SER_2 - ): DStream[SparkFlumeEvent] = { - val inputStream = new FlumeInputDStream[SparkFlumeEvent](this, hostname, port, storageLevel) - registerInputStream(inputStream) - inputStream - } - - /** * Create a input stream from network source hostname:port, where data is received * as serialized blocks (serialized using the Spark's serializer) that can be directly * pushed into the block manager without deserializing them. This is the most efficient @@ -434,24 +340,6 @@ class StreamingContext private ( } /** - * Create a input stream that returns tweets received from Twitter. - * @param twitterAuth Twitter4J authentication, or None to use Twitter4J's default OAuth - * authorization; this uses the system properties twitter4j.oauth.consumerKey, - * .consumerSecret, .accessToken and .accessTokenSecret. - * @param filters Set of filter strings to get only those tweets that match them - * @param storageLevel Storage level to use for storing the received objects - */ - def twitterStream( - twitterAuth: Option[Authorization] = None, - filters: Seq[String] = Nil, - storageLevel: StorageLevel = StorageLevel.MEMORY_AND_DISK_SER_2 - ): DStream[Status] = { - val inputStream = new TwitterInputDStream(this, twitterAuth, filters, storageLevel) - registerInputStream(inputStream) - inputStream - } - - /** * Create an input stream from a queue of RDDs. In each batch, * it will process either one or all of the RDDs returned by the queue. * @param queue Queue of RDDs @@ -484,21 +372,6 @@ class StreamingContext private ( inputStream } -/** - * Create an input stream that receives messages pushed by a mqtt publisher. - * @param brokerUrl Url of remote mqtt publisher - * @param topic topic name to subscribe to - * @param storageLevel RDD storage level. Defaults to memory-only. - */ - - def mqttStream( - brokerUrl: String, - topic: String, - storageLevel: StorageLevel = StorageLevel.MEMORY_ONLY_SER_2): DStream[String] = { - val inputStream = new MQTTInputDStream[String](this, brokerUrl, topic, storageLevel) - registerInputStream(inputStream) - inputStream - } /** * Create a unified DStream from multiple DStreams of the same type and same slide duration. */ @@ -595,6 +468,12 @@ object StreamingContext { new PairDStreamFunctions[K, V](stream) } + /** + * Find the JAR from which a given class was loaded, to make it easy for users to pass + * their JARs to SparkContext. + */ + def jarOfClass(cls: Class[_]) = SparkContext.jarOfClass(cls) + protected[streaming] def createNewSparkContext(conf: SparkConf): SparkContext = { // Set the default cleaner delay to an hour if not already set. // This should be sufficient for even 1 second batch intervals. diff --git a/streaming/src/main/scala/org/apache/spark/streaming/api/java/JavaStreamingContext.scala b/streaming/src/main/scala/org/apache/spark/streaming/api/java/JavaStreamingContext.scala index b79173c6aa..7068f32517 100644 --- a/streaming/src/main/scala/org/apache/spark/streaming/api/java/JavaStreamingContext.scala +++ b/streaming/src/main/scala/org/apache/spark/streaming/api/java/JavaStreamingContext.scala @@ -17,29 +17,23 @@ package org.apache.spark.streaming.api.java -import java.lang.{Integer => JInt} -import java.io.InputStream -import java.util.{Map => JMap, List => JList} import scala.collection.JavaConversions._ import scala.reflect.ClassTag -import org.apache.hadoop.mapreduce.{InputFormat => NewInputFormat} -import twitter4j.Status -import akka.actor.Props -import akka.actor.SupervisorStrategy -import akka.zeromq.Subscribe -import akka.util.ByteString +import java.io.InputStream +import java.lang.{Integer => JInt} +import java.util.{List => JList, Map => JMap} -import twitter4j.auth.Authorization +import akka.actor.{Props, SupervisorStrategy} +import org.apache.hadoop.mapreduce.{InputFormat => NewInputFormat} +import org.apache.spark.{SparkConf, SparkContext} +import org.apache.spark.api.java.{JavaPairRDD, JavaRDD, JavaSparkContext} +import org.apache.spark.api.java.function.{Function => JFunction, Function2 => JFunction2} import org.apache.spark.rdd.RDD import org.apache.spark.storage.StorageLevel -import org.apache.spark.api.java.function.{Function => JFunction, Function2 => JFunction2} -import org.apache.spark.api.java.{JavaPairRDD, JavaSparkContext, JavaRDD} import org.apache.spark.streaming._ -import org.apache.spark.streaming.dstream._ -import org.apache.spark.SparkConf import org.apache.spark.streaming.scheduler.StreamingListener /** @@ -143,81 +137,6 @@ class JavaStreamingContext(val ssc: StreamingContext) { val sc: JavaSparkContext = new JavaSparkContext(ssc.sc) /** - * Create an input stream that pulls messages form a Kafka Broker. - * @param zkQuorum Zookeper quorum (hostname:port,hostname:port,..). - * @param groupId The group id for this consumer. - * @param topics Map of (topic_name -> numPartitions) to consume. Each partition is consumed - * in its own thread. - */ - def kafkaStream( - zkQuorum: String, - groupId: String, - topics: JMap[String, JInt]) - : JavaPairDStream[String, String] = { - implicit val cmt: ClassTag[String] = - implicitly[ClassTag[AnyRef]].asInstanceOf[ClassTag[String]] - ssc.kafkaStream(zkQuorum, groupId, Map(topics.mapValues(_.intValue()).toSeq: _*), - StorageLevel.MEMORY_ONLY_SER_2) - - } - - /** - * Create an input stream that pulls messages form a Kafka Broker. - * @param zkQuorum Zookeper quorum (hostname:port,hostname:port,..). - * @param groupId The group id for this consumer. - * @param topics Map of (topic_name -> numPartitions) to consume. Each partition is consumed - * in its own thread. - * @param storageLevel RDD storage level. Defaults to memory-only - * - */ - def kafkaStream( - zkQuorum: String, - groupId: String, - topics: JMap[String, JInt], - storageLevel: StorageLevel) - : JavaPairDStream[String, String] = { - implicit val cmt: ClassTag[String] = - implicitly[ClassTag[AnyRef]].asInstanceOf[ClassTag[String]] - ssc.kafkaStream(zkQuorum, groupId, Map(topics.mapValues(_.intValue()).toSeq: _*), - storageLevel) - } - - /** - * Create an input stream that pulls messages form a Kafka Broker. - * @param keyTypeClass Key type of RDD - * @param valueTypeClass value type of RDD - * @param keyDecoderClass Type of kafka key decoder - * @param valueDecoderClass Type of kafka value decoder - * @param kafkaParams Map of kafka configuration paramaters. - * See: http://kafka.apache.org/configuration.html - * @param topics Map of (topic_name -> numPartitions) to consume. Each partition is consumed - * in its own thread. - * @param storageLevel RDD storage level. Defaults to memory-only - */ - def kafkaStream[K, V, U <: kafka.serializer.Decoder[_], T <: kafka.serializer.Decoder[_]]( - keyTypeClass: Class[K], - valueTypeClass: Class[V], - keyDecoderClass: Class[U], - valueDecoderClass: Class[T], - kafkaParams: JMap[String, String], - topics: JMap[String, JInt], - storageLevel: StorageLevel) - : JavaPairDStream[K, V] = { - implicit val keyCmt: ClassTag[K] = - implicitly[ClassTag[AnyRef]].asInstanceOf[ClassTag[K]] - implicit val valueCmt: ClassTag[V] = - implicitly[ClassTag[AnyRef]].asInstanceOf[ClassTag[V]] - - implicit val keyCmd: Manifest[U] = implicitly[Manifest[AnyRef]].asInstanceOf[Manifest[U]] - implicit val valueCmd: Manifest[T] = implicitly[Manifest[AnyRef]].asInstanceOf[Manifest[T]] - - ssc.kafkaStream[K, V, U, T]( - kafkaParams.toMap, - Map(topics.mapValues(_.intValue()).toSeq: _*), - storageLevel) - } - - /** * Create a input stream from network source hostname:port. Data is received using * a TCP socket and the receive bytes is interpreted as UTF8 encoded \n delimited * lines. @@ -331,98 +250,6 @@ class JavaStreamingContext(val ssc: StreamingContext) { } /** - * Creates a input stream from a Flume source. - * @param hostname Hostname of the slave machine to which the flume data will be sent - * @param port Port of the slave machine to which the flume data will be sent - * @param storageLevel Storage level to use for storing the received objects - */ - def flumeStream(hostname: String, port: Int, storageLevel: StorageLevel): - JavaDStream[SparkFlumeEvent] = { - ssc.flumeStream(hostname, port, storageLevel) - } - - - /** - * Create a input stream from a Flume source. - * @param hostname Hostname of the slave machine to which the flume data will be sent - * @param port Port of the slave machine to which the flume data will be sent - */ - def flumeStream(hostname: String, port: Int): JavaDStream[SparkFlumeEvent] = { - ssc.flumeStream(hostname, port) - } - - /** - * Create a input stream that returns tweets received from Twitter. - * @param twitterAuth Twitter4J Authorization object - * @param filters Set of filter strings to get only those tweets that match them - * @param storageLevel Storage level to use for storing the received objects - */ - def twitterStream( - twitterAuth: Authorization, - filters: Array[String], - storageLevel: StorageLevel - ): JavaDStream[Status] = { - ssc.twitterStream(Some(twitterAuth), filters, storageLevel) - } - - /** - * Create a input stream that returns tweets received from Twitter using Twitter4J's default - * OAuth authentication; this requires the system properties twitter4j.oauth.consumerKey, - * .consumerSecret, .accessToken and .accessTokenSecret to be set. - * @param filters Set of filter strings to get only those tweets that match them - * @param storageLevel Storage level to use for storing the received objects - */ - def twitterStream( - filters: Array[String], - storageLevel: StorageLevel - ): JavaDStream[Status] = { - ssc.twitterStream(None, filters, storageLevel) - } - - /** - * Create a input stream that returns tweets received from Twitter. - * @param twitterAuth Twitter4J Authorization - * @param filters Set of filter strings to get only those tweets that match them - */ - def twitterStream( - twitterAuth: Authorization, - filters: Array[String] - ): JavaDStream[Status] = { - ssc.twitterStream(Some(twitterAuth), filters) - } - - /** - * Create a input stream that returns tweets received from Twitter using Twitter4J's default - * OAuth authentication; this requires the system properties twitter4j.oauth.consumerKey, - * .consumerSecret, .accessToken and .accessTokenSecret to be set. - * @param filters Set of filter strings to get only those tweets that match them - */ - def twitterStream( - filters: Array[String] - ): JavaDStream[Status] = { - ssc.twitterStream(None, filters) - } - - /** - * Create a input stream that returns tweets received from Twitter. - * @param twitterAuth Twitter4J Authorization - */ - def twitterStream( - twitterAuth: Authorization - ): JavaDStream[Status] = { - ssc.twitterStream(Some(twitterAuth)) - } - - /** - * Create a input stream that returns tweets received from Twitter using Twitter4J's default - * OAuth authentication; this requires the system properties twitter4j.oauth.consumerKey, - * .consumerSecret, .accessToken and .accessTokenSecret to be set. - */ - def twitterStream(): JavaDStream[Status] = { - ssc.twitterStream() - } - - /** * Create an input stream with any arbitrary user implemented actor receiver. * @param props Props object defining creation of the actor * @param name Name of the actor @@ -485,70 +312,6 @@ class JavaStreamingContext(val ssc: StreamingContext) { } /** - * Create an input stream that receives messages pushed by a zeromq publisher. - * @param publisherUrl Url of remote zeromq publisher - * @param subscribe topic to subscribe to - * @param bytesToObjects A zeroMQ stream publishes sequence of frames for each topic and each frame has sequence - * of byte thus it needs the converter(which might be deserializer of bytes) - * to translate from sequence of sequence of bytes, where sequence refer to a frame - * and sub sequence refer to its payload. - * @param storageLevel Storage level to use for storing the received objects - */ - def zeroMQStream[T]( - publisherUrl:String, - subscribe: Subscribe, - bytesToObjects: Seq[ByteString] ⇒ Iterator[T], - storageLevel: StorageLevel, - supervisorStrategy: SupervisorStrategy - ): JavaDStream[T] = { - implicit val cm: ClassTag[T] = - implicitly[ClassTag[AnyRef]].asInstanceOf[ClassTag[T]] - ssc.zeroMQStream[T](publisherUrl, subscribe, bytesToObjects, storageLevel, supervisorStrategy) - } - - /** - * Create an input stream that receives messages pushed by a zeromq publisher. - * @param publisherUrl Url of remote zeromq publisher - * @param subscribe topic to subscribe to - * @param bytesToObjects A zeroMQ stream publishes sequence of frames for each topic and each frame has sequence - * of byte thus it needs the converter(which might be deserializer of bytes) - * to translate from sequence of sequence of bytes, where sequence refer to a frame - * and sub sequence refer to its payload. - * @param storageLevel RDD storage level. Defaults to memory-only. - */ - def zeroMQStream[T]( - publisherUrl:String, - subscribe: Subscribe, - bytesToObjects: JFunction[Array[Array[Byte]], java.lang.Iterable[T]], - storageLevel: StorageLevel - ): JavaDStream[T] = { - implicit val cm: ClassTag[T] = - implicitly[ClassTag[AnyRef]].asInstanceOf[ClassTag[T]] - def fn(x: Seq[ByteString]) = bytesToObjects.apply(x.map(_.toArray).toArray).toIterator - ssc.zeroMQStream[T](publisherUrl, subscribe, fn, storageLevel) - } - - /** - * Create an input stream that receives messages pushed by a zeromq publisher. - * @param publisherUrl Url of remote zeromq publisher - * @param subscribe topic to subscribe to - * @param bytesToObjects A zeroMQ stream publishes sequence of frames for each topic and each frame has sequence - * of byte thus it needs the converter(which might be deserializer of bytes) - * to translate from sequence of sequence of bytes, where sequence refer to a frame - * and sub sequence refer to its payload. - */ - def zeroMQStream[T]( - publisherUrl:String, - subscribe: Subscribe, - bytesToObjects: JFunction[Array[Array[Byte]], java.lang.Iterable[T]] - ): JavaDStream[T] = { - implicit val cm: ClassTag[T] = - implicitly[ClassTag[AnyRef]].asInstanceOf[ClassTag[T]] - def fn(x: Seq[ByteString]) = bytesToObjects.apply(x.map(_.toArray).toArray).toIterator - ssc.zeroMQStream[T](publisherUrl, subscribe, fn) - } - - /** * Registers an output stream that will be computed every interval */ def registerOutputStream(outputStream: JavaDStreamLike[_, _, _]) { @@ -716,5 +479,12 @@ class JavaStreamingContext(val ssc: StreamingContext) { * Sstops the execution of the streams. */ def stop() = ssc.stop() +} +object JavaStreamingContext { + /** + * Find the JAR from which a given class was loaded, to make it easy for users to pass + * their JARs to SparkContext. + */ + def jarOfClass(cls: Class[_]) = SparkContext.jarOfClass(cls).toArray } diff --git a/streaming/src/main/scala/org/apache/spark/streaming/dstream/FlumeInputDStream.scala b/streaming/src/main/scala/org/apache/spark/streaming/dstream/FlumeInputDStream.scala deleted file mode 100644 index 60d79175f1..0000000000 --- a/streaming/src/main/scala/org/apache/spark/streaming/dstream/FlumeInputDStream.scala +++ /dev/null @@ -1,154 +0,0 @@ -/* - * 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.dstream - -import java.net.InetSocketAddress -import java.io.{ObjectInput, ObjectOutput, Externalizable} -import java.nio.ByteBuffer - -import scala.collection.JavaConversions._ -import scala.reflect.ClassTag - -import org.apache.flume.source.avro.AvroSourceProtocol -import org.apache.flume.source.avro.AvroFlumeEvent -import org.apache.flume.source.avro.Status -import org.apache.avro.ipc.specific.SpecificResponder -import org.apache.avro.ipc.NettyServer - -import org.apache.spark.streaming.StreamingContext -import org.apache.spark.util.Utils -import org.apache.spark.storage.StorageLevel - -private[streaming] -class FlumeInputDStream[T: ClassTag]( - @transient ssc_ : StreamingContext, - host: String, - port: Int, - storageLevel: StorageLevel -) extends NetworkInputDStream[SparkFlumeEvent](ssc_) { - - override def getReceiver(): NetworkReceiver[SparkFlumeEvent] = { - new FlumeReceiver(host, port, storageLevel) - } -} - -/** - * A wrapper class for AvroFlumeEvent's with a custom serialization format. - * - * This is necessary because AvroFlumeEvent uses inner data structures - * which are not serializable. - */ -class SparkFlumeEvent() extends Externalizable { - var event : AvroFlumeEvent = new AvroFlumeEvent() - - /* De-serialize from bytes. */ - def readExternal(in: ObjectInput) { - val bodyLength = in.readInt() - val bodyBuff = new Array[Byte](bodyLength) - in.read(bodyBuff) - - val numHeaders = in.readInt() - val headers = new java.util.HashMap[CharSequence, CharSequence] - - for (i <- 0 until numHeaders) { - val keyLength = in.readInt() - val keyBuff = new Array[Byte](keyLength) - in.read(keyBuff) - val key : String = Utils.deserialize(keyBuff) - - val valLength = in.readInt() - val valBuff = new Array[Byte](valLength) - in.read(valBuff) - val value : String = Utils.deserialize(valBuff) - - headers.put(key, value) - } - - event.setBody(ByteBuffer.wrap(bodyBuff)) - event.setHeaders(headers) - } - - /* Serialize to bytes. */ - def writeExternal(out: ObjectOutput) { - val body = event.getBody.array() - out.writeInt(body.length) - out.write(body) - - val numHeaders = event.getHeaders.size() - out.writeInt(numHeaders) - for ((k, v) <- event.getHeaders) { - val keyBuff = Utils.serialize(k.toString) - out.writeInt(keyBuff.length) - out.write(keyBuff) - val valBuff = Utils.serialize(v.toString) - out.writeInt(valBuff.length) - out.write(valBuff) - } - } -} - -private[streaming] object SparkFlumeEvent { - def fromAvroFlumeEvent(in : AvroFlumeEvent) : SparkFlumeEvent = { - val event = new SparkFlumeEvent - event.event = in - event - } -} - -/** A simple server that implements Flume's Avro protocol. */ -private[streaming] -class FlumeEventServer(receiver : FlumeReceiver) extends AvroSourceProtocol { - override def append(event : AvroFlumeEvent) : Status = { - receiver.blockGenerator += SparkFlumeEvent.fromAvroFlumeEvent(event) - Status.OK - } - - override def appendBatch(events : java.util.List[AvroFlumeEvent]) : Status = { - events.foreach (event => - receiver.blockGenerator += SparkFlumeEvent.fromAvroFlumeEvent(event)) - Status.OK - } -} - -/** A NetworkReceiver which listens for events using the - * Flume Avro interface.*/ -private[streaming] -class FlumeReceiver( - host: String, - port: Int, - storageLevel: StorageLevel - ) extends NetworkReceiver[SparkFlumeEvent] { - - lazy val blockGenerator = new BlockGenerator(storageLevel) - - protected override def onStart() { - val responder = new SpecificResponder( - classOf[AvroSourceProtocol], new FlumeEventServer(this)) - val server = new NettyServer(responder, new InetSocketAddress(host, port)) - blockGenerator.start() - server.start() - logInfo("Flume receiver started") - } - - protected override def onStop() { - blockGenerator.stop() - logInfo("Flume receiver stopped") - } - - override def getLocationPreference = Some(host) -} diff --git a/streaming/src/main/scala/org/apache/spark/streaming/dstream/KafkaInputDStream.scala b/streaming/src/main/scala/org/apache/spark/streaming/dstream/KafkaInputDStream.scala deleted file mode 100644 index 526f5564c7..0000000000 --- a/streaming/src/main/scala/org/apache/spark/streaming/dstream/KafkaInputDStream.scala +++ /dev/null @@ -1,153 +0,0 @@ -/* - * 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.dstream - -import org.apache.spark.Logging -import org.apache.spark.storage.StorageLevel -import org.apache.spark.streaming.StreamingContext - -import java.util.Properties -import java.util.concurrent.Executors - -import kafka.consumer._ -import kafka.serializer.Decoder -import kafka.utils.VerifiableProperties -import kafka.utils.ZKStringSerializer -import org.I0Itec.zkclient._ - -import scala.collection.Map -import scala.reflect.ClassTag - -/** - * Input stream that pulls messages from a Kafka Broker. - * - * @param kafkaParams Map of kafka configuration paramaters. See: http://kafka.apache.org/configuration.html - * @param topics Map of (topic_name -> numPartitions) to consume. Each partition is consumed - * in its own thread. - * @param storageLevel RDD storage level. - */ -private[streaming] -class KafkaInputDStream[ - K: ClassTag, - V: ClassTag, - U <: Decoder[_]: Manifest, - T <: Decoder[_]: Manifest]( - @transient ssc_ : StreamingContext, - kafkaParams: Map[String, String], - topics: Map[String, Int], - storageLevel: StorageLevel - ) extends NetworkInputDStream[(K, V)](ssc_) with Logging { - - def getReceiver(): NetworkReceiver[(K, V)] = { - new KafkaReceiver[K, V, U, T](kafkaParams, topics, storageLevel) - .asInstanceOf[NetworkReceiver[(K, V)]] - } -} - -private[streaming] -class KafkaReceiver[ - K: ClassTag, - V: ClassTag, - U <: Decoder[_]: Manifest, - T <: Decoder[_]: Manifest]( - kafkaParams: Map[String, String], - topics: Map[String, Int], - storageLevel: StorageLevel - ) extends NetworkReceiver[Any] { - - // Handles pushing data into the BlockManager - lazy protected val blockGenerator = new BlockGenerator(storageLevel) - // Connection to Kafka - var consumerConnector : ConsumerConnector = null - - def onStop() { - blockGenerator.stop() - } - - def onStart() { - - blockGenerator.start() - - // In case we are using multiple Threads to handle Kafka Messages - val executorPool = Executors.newFixedThreadPool(topics.values.reduce(_ + _)) - - logInfo("Starting Kafka Consumer Stream with group: " + kafkaParams("group.id")) - - // Kafka connection properties - val props = new Properties() - kafkaParams.foreach(param => props.put(param._1, param._2)) - - // Create the connection to the cluster - logInfo("Connecting to Zookeper: " + kafkaParams("zookeeper.connect")) - val consumerConfig = new ConsumerConfig(props) - consumerConnector = Consumer.create(consumerConfig) - logInfo("Connected to " + kafkaParams("zookeeper.connect")) - - // When autooffset.reset is defined, it is our responsibility to try and whack the - // consumer group zk node. - if (kafkaParams.contains("auto.offset.reset")) { - tryZookeeperConsumerGroupCleanup(kafkaParams("zookeeper.connect"), kafkaParams("group.id")) - } - - val keyDecoder = manifest[U].runtimeClass.getConstructor(classOf[VerifiableProperties]) - .newInstance(consumerConfig.props) - .asInstanceOf[Decoder[K]] - val valueDecoder = manifest[T].runtimeClass.getConstructor(classOf[VerifiableProperties]) - .newInstance(consumerConfig.props) - .asInstanceOf[Decoder[V]] - - // Create Threads for each Topic/Message Stream we are listening - val topicMessageStreams = consumerConnector.createMessageStreams( - topics, keyDecoder, valueDecoder) - - - // Start the messages handler for each partition - topicMessageStreams.values.foreach { streams => - streams.foreach { stream => executorPool.submit(new MessageHandler(stream)) } - } - } - - // Handles Kafka Messages - private class MessageHandler[K: ClassTag, V: ClassTag](stream: KafkaStream[K, V]) - extends Runnable { - def run() { - logInfo("Starting MessageHandler.") - for (msgAndMetadata <- stream) { - blockGenerator += (msgAndMetadata.key, msgAndMetadata.message) - } - } - } - - // It is our responsibility to delete the consumer group when specifying autooffset.reset. This is because - // Kafka 0.7.2 only honors this param when the group is not in zookeeper. - // - // The kafka high level consumer doesn't expose setting offsets currently, this is a trick copied from Kafkas' - // ConsoleConsumer. See code related to 'autooffset.reset' when it is set to 'smallest'/'largest': - // https://github.com/apache/kafka/blob/0.7.2/core/src/main/scala/kafka/consumer/ConsoleConsumer.scala - private def tryZookeeperConsumerGroupCleanup(zkUrl: String, groupId: String) { - try { - val dir = "/consumers/" + groupId - logInfo("Cleaning up temporary zookeeper data under " + dir + ".") - val zk = new ZkClient(zkUrl, 30*1000, 30*1000, ZKStringSerializer) - zk.deleteRecursive(dir) - zk.close() - } catch { - case _ : Throwable => // swallow - } - } -} diff --git a/streaming/src/main/scala/org/apache/spark/streaming/dstream/MQTTInputDStream.scala b/streaming/src/main/scala/org/apache/spark/streaming/dstream/MQTTInputDStream.scala deleted file mode 100644 index ef4a737568..0000000000 --- a/streaming/src/main/scala/org/apache/spark/streaming/dstream/MQTTInputDStream.scala +++ /dev/null @@ -1,110 +0,0 @@ -/* - * 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.dstream - -import org.apache.spark.Logging -import org.apache.spark.storage.StorageLevel -import org.apache.spark.streaming.{ Time, DStreamCheckpointData, StreamingContext } - -import java.util.Properties -import java.util.concurrent.Executors -import java.io.IOException - -import org.eclipse.paho.client.mqttv3.MqttCallback -import org.eclipse.paho.client.mqttv3.MqttClient -import org.eclipse.paho.client.mqttv3.MqttClientPersistence -import org.eclipse.paho.client.mqttv3.persist.MemoryPersistence -import org.eclipse.paho.client.mqttv3.IMqttDeliveryToken -import org.eclipse.paho.client.mqttv3.MqttException -import org.eclipse.paho.client.mqttv3.MqttMessage -import org.eclipse.paho.client.mqttv3.MqttTopic - -import scala.collection.Map -import scala.collection.mutable.HashMap -import scala.collection.JavaConversions._ -import scala.reflect.ClassTag - -/** - * Input stream that subscribe messages from a Mqtt Broker. - * Uses eclipse paho as MqttClient http://www.eclipse.org/paho/ - * @param brokerUrl Url of remote mqtt publisher - * @param topic topic name to subscribe to - * @param storageLevel RDD storage level. - */ - -private[streaming] -class MQTTInputDStream[T: ClassTag]( - @transient ssc_ : StreamingContext, - brokerUrl: String, - topic: String, - storageLevel: StorageLevel - ) extends NetworkInputDStream[T](ssc_) with Logging { - - def getReceiver(): NetworkReceiver[T] = { - new MQTTReceiver(brokerUrl, topic, storageLevel) - .asInstanceOf[NetworkReceiver[T]] - } -} - -private[streaming] -class MQTTReceiver(brokerUrl: String, - topic: String, - storageLevel: StorageLevel - ) extends NetworkReceiver[Any] { - lazy protected val blockGenerator = new BlockGenerator(storageLevel) - - def onStop() { - blockGenerator.stop() - } - - def onStart() { - - blockGenerator.start() - - // Set up persistence for messages - var peristance: MqttClientPersistence = new MemoryPersistence() - - // Initializing Mqtt Client specifying brokerUrl, clientID and MqttClientPersistance - var client: MqttClient = new MqttClient(brokerUrl, "MQTTSub", peristance) - - // Connect to MqttBroker - client.connect() - - // Subscribe to Mqtt topic - client.subscribe(topic) - - // Callback automatically triggers as and when new message arrives on specified topic - var callback: MqttCallback = new MqttCallback() { - - // Handles Mqtt message - override def messageArrived(arg0: String, arg1: MqttMessage) { - blockGenerator += new String(arg1.getPayload()) - } - - override def deliveryComplete(arg0: IMqttDeliveryToken) { - } - - override def connectionLost(arg0: Throwable) { - logInfo("Connection lost " + arg0) - } - } - - // Set up callback for MqttClient - client.setCallback(callback) - } -} diff --git a/streaming/src/main/scala/org/apache/spark/streaming/dstream/NetworkInputDStream.scala b/streaming/src/main/scala/org/apache/spark/streaming/dstream/NetworkInputDStream.scala index 27d474c0a0..d41f726f83 100644 --- a/streaming/src/main/scala/org/apache/spark/streaming/dstream/NetworkInputDStream.scala +++ b/streaming/src/main/scala/org/apache/spark/streaming/dstream/NetworkInputDStream.scala @@ -175,7 +175,7 @@ abstract class NetworkReceiver[T: ClassTag]() extends Serializable with Logging private class NetworkReceiverActor extends Actor { logInfo("Attempting to register with tracker") val ip = env.conf.get("spark.driver.host", "localhost") - val port = env.conf.get("spark.driver.port", "7077").toInt + val port = env.conf.getInt("spark.driver.port", 7077) val url = "akka.tcp://spark@%s:%s/user/NetworkInputTracker".format(ip, port) val tracker = env.actorSystem.actorSelection(url) val timeout = 5.seconds @@ -212,7 +212,7 @@ abstract class NetworkReceiver[T: ClassTag]() extends Serializable with Logging case class Block(id: BlockId, buffer: ArrayBuffer[T], metadata: Any = null) val clock = new SystemClock() - val blockInterval = env.conf.get("spark.streaming.blockInterval", "200").toLong + val blockInterval = env.conf.getLong("spark.streaming.blockInterval", 200) val blockIntervalTimer = new RecurringTimer(clock, blockInterval, updateCurrentBuffer) val blockStorageLevel = storageLevel val blocksForPushing = new ArrayBlockingQueue[Block](1000) diff --git a/streaming/src/main/scala/org/apache/spark/streaming/dstream/TwitterInputDStream.scala b/streaming/src/main/scala/org/apache/spark/streaming/dstream/TwitterInputDStream.scala deleted file mode 100644 index 387e15b0e6..0000000000 --- a/streaming/src/main/scala/org/apache/spark/streaming/dstream/TwitterInputDStream.scala +++ /dev/null @@ -1,99 +0,0 @@ -/* - * 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.dstream - -import org.apache.spark._ -import org.apache.spark.streaming._ -import storage.StorageLevel -import twitter4j._ -import twitter4j.auth.Authorization -import java.util.prefs.Preferences -import twitter4j.conf.ConfigurationBuilder -import twitter4j.conf.PropertyConfiguration -import twitter4j.auth.OAuthAuthorization -import twitter4j.auth.AccessToken - -/* A stream of Twitter statuses, potentially filtered by one or more keywords. -* -* @constructor create a new Twitter stream using the supplied Twitter4J authentication credentials. -* An optional set of string filters can be used to restrict the set of tweets. The Twitter API is -* such that this may return a sampled subset of all tweets during each interval. -* -* If no Authorization object is provided, initializes OAuth authorization using the system -* properties twitter4j.oauth.consumerKey, .consumerSecret, .accessToken and .accessTokenSecret. -*/ -private[streaming] -class TwitterInputDStream( - @transient ssc_ : StreamingContext, - twitterAuth: Option[Authorization], - filters: Seq[String], - storageLevel: StorageLevel - ) extends NetworkInputDStream[Status](ssc_) { - - private def createOAuthAuthorization(): Authorization = { - new OAuthAuthorization(new ConfigurationBuilder().build()) - } - - private val authorization = twitterAuth.getOrElse(createOAuthAuthorization()) - - override def getReceiver(): NetworkReceiver[Status] = { - new TwitterReceiver(authorization, filters, storageLevel) - } -} - -private[streaming] -class TwitterReceiver( - twitterAuth: Authorization, - filters: Seq[String], - storageLevel: StorageLevel - ) extends NetworkReceiver[Status] { - - var twitterStream: TwitterStream = _ - lazy val blockGenerator = new BlockGenerator(storageLevel) - - protected override def onStart() { - blockGenerator.start() - twitterStream = new TwitterStreamFactory().getInstance(twitterAuth) - twitterStream.addListener(new StatusListener { - def onStatus(status: Status) = { - blockGenerator += status - } - // Unimplemented - def onDeletionNotice(statusDeletionNotice: StatusDeletionNotice) {} - def onTrackLimitationNotice(i: Int) {} - def onScrubGeo(l: Long, l1: Long) {} - def onStallWarning(stallWarning: StallWarning) {} - def onException(e: Exception) { stopOnError(e) } - }) - - val query: FilterQuery = new FilterQuery - if (filters.size > 0) { - query.track(filters.toArray) - twitterStream.filter(query) - } else { - twitterStream.sample() - } - logInfo("Twitter receiver started") - } - - protected override def onStop() { - blockGenerator.stop() - twitterStream.shutdown() - logInfo("Twitter receiver stopped") - } -} diff --git a/streaming/src/main/scala/org/apache/spark/streaming/receivers/ZeroMQReceiver.scala b/streaming/src/main/scala/org/apache/spark/streaming/receivers/ZeroMQReceiver.scala deleted file mode 100644 index f164d516b0..0000000000 --- a/streaming/src/main/scala/org/apache/spark/streaming/receivers/ZeroMQReceiver.scala +++ /dev/null @@ -1,53 +0,0 @@ -/* - * 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.receivers - -import scala.reflect.ClassTag - -import akka.actor.Actor -import akka.util.ByteString -import akka.zeromq._ - -import org.apache.spark.Logging - -/** - * A receiver to subscribe to ZeroMQ stream. - */ -private[streaming] class ZeroMQReceiver[T: ClassTag](publisherUrl: String, - subscribe: Subscribe, - bytesToObjects: Seq[ByteString] ⇒ Iterator[T]) - extends Actor with Receiver with Logging { - - override def preStart() = ZeroMQExtension(context.system).newSocket(SocketType.Sub, Listener(self), - Connect(publisherUrl), subscribe) - - def receive: Receive = { - - case Connecting ⇒ logInfo("connecting ...") - - case m: ZMQMessage ⇒ - logDebug("Received message for:" + m.frame(0)) - - //We ignore first frame for processing as it is the topic - val bytes = m.frames.tail - pushBlock(bytesToObjects(bytes)) - - case Closed ⇒ logInfo("received closed ") - - } -} diff --git a/streaming/src/main/scala/org/apache/spark/streaming/scheduler/Job.scala b/streaming/src/main/scala/org/apache/spark/streaming/scheduler/Job.scala index 7341bfbc99..c8ee93bf5b 100644 --- a/streaming/src/main/scala/org/apache/spark/streaming/scheduler/Job.scala +++ b/streaming/src/main/scala/org/apache/spark/streaming/scheduler/Job.scala @@ -38,4 +38,4 @@ class Job(val time: Time, func: () => _) { } override def toString = id -}
\ No newline at end of file +} diff --git a/streaming/src/main/scala/org/apache/spark/streaming/scheduler/JobGenerator.scala b/streaming/src/main/scala/org/apache/spark/streaming/scheduler/JobGenerator.scala index 5f8be93a98..3c624e8199 100644 --- a/streaming/src/main/scala/org/apache/spark/streaming/scheduler/JobGenerator.scala +++ b/streaming/src/main/scala/org/apache/spark/streaming/scheduler/JobGenerator.scala @@ -104,7 +104,7 @@ class JobGenerator(jobScheduler: JobScheduler) extends Logging { // or if the property is defined set it to that time if (clock.isInstanceOf[ManualClock]) { val lastTime = ssc.initialCheckpoint.checkpointTime.milliseconds - val jumpTime = ssc.sc.conf.get("spark.streaming.manualClock.jump", "0").toLong + val jumpTime = ssc.sc.conf.getLong("spark.streaming.manualClock.jump", 0) clock.asInstanceOf[ManualClock].setTime(lastTime + jumpTime) } diff --git a/streaming/src/main/scala/org/apache/spark/streaming/scheduler/JobScheduler.scala b/streaming/src/main/scala/org/apache/spark/streaming/scheduler/JobScheduler.scala index 9304fc1a93..30c070c274 100644 --- a/streaming/src/main/scala/org/apache/spark/streaming/scheduler/JobScheduler.scala +++ b/streaming/src/main/scala/org/apache/spark/streaming/scheduler/JobScheduler.scala @@ -31,7 +31,7 @@ private[streaming] class JobScheduler(val ssc: StreamingContext) extends Logging { val jobSets = new ConcurrentHashMap[Time, JobSet] - val numConcurrentJobs = ssc.conf.get("spark.streaming.concurrentJobs", "1").toInt + val numConcurrentJobs = ssc.conf.getInt("spark.streaming.concurrentJobs", 1) val executor = Executors.newFixedThreadPool(numConcurrentJobs) val generator = new JobGenerator(this) val listenerBus = new StreamingListenerBus() diff --git a/streaming/src/main/scala/org/apache/spark/streaming/scheduler/NetworkInputTracker.scala b/streaming/src/main/scala/org/apache/spark/streaming/scheduler/NetworkInputTracker.scala index abff55d77c..75f7244643 100644 --- a/streaming/src/main/scala/org/apache/spark/streaming/scheduler/NetworkInputTracker.scala +++ b/streaming/src/main/scala/org/apache/spark/streaming/scheduler/NetworkInputTracker.scala @@ -160,7 +160,9 @@ class NetworkInputTracker( } // Run the dummy Spark job to ensure that all slaves have registered. // This avoids all the receivers to be scheduled on the same node. - ssc.sparkContext.makeRDD(1 to 50, 50).map(x => (x, 1)).reduceByKey(_ + _, 20).collect() + if (!ssc.sparkContext.isLocal) { + ssc.sparkContext.makeRDD(1 to 50, 50).map(x => (x, 1)).reduceByKey(_ + _, 20).collect() + } // Distribute the receivers and start them ssc.sparkContext.runJob(tempRDD, startReceiver) diff --git a/streaming/src/test/java/org/apache/spark/streaming/JavaAPISuite.java b/streaming/src/test/java/org/apache/spark/streaming/JavaAPISuite.java index 354f04f9a5..be93799a2a 100644 --- a/streaming/src/test/java/org/apache/spark/streaming/JavaAPISuite.java +++ b/streaming/src/test/java/org/apache/spark/streaming/JavaAPISuite.java @@ -25,17 +25,19 @@ import com.google.common.io.Files; import kafka.serializer.StringDecoder; -import org.apache.hadoop.mapreduce.lib.input.SequenceFileInputFormat; -import org.apache.spark.SparkConf; -import org.apache.spark.streaming.api.java.JavaDStreamLike; +import scala.Tuple2; + import org.junit.After; import org.junit.Assert; -import org.junit.Before; import org.junit.Test; +import java.io.*; +import java.util.*; -import scala.Tuple2; -import twitter4j.Status; +import com.google.common.base.Optional; +import com.google.common.collect.Lists; +import com.google.common.io.Files; +import org.apache.spark.SparkConf; import org.apache.spark.HashPartitioner; import org.apache.spark.api.java.JavaPairRDD; import org.apache.spark.api.java.JavaRDD; @@ -45,42 +47,11 @@ import org.apache.spark.storage.StorageLevel; 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 org.apache.spark.streaming.dstream.SparkFlumeEvent; -import org.apache.spark.streaming.JavaTestUtils; -import org.apache.spark.streaming.JavaCheckpointTestUtils; - -import java.io.*; -import java.util.*; - -import akka.actor.Props; -import akka.zeromq.Subscribe; - // The test suite itself is Serializable so that anonymous Function implementations can be // serialized, as an alternative to converting these anonymous classes to static inner classes; // see http://stackoverflow.com/questions/758570/. -public class JavaAPISuite implements Serializable { - private transient JavaStreamingContext ssc; - - @Before - public void setUp() { - SparkConf conf = new SparkConf() - .setMaster("local[2]") - .setAppName("test") - .set("spark.streaming.clock", "org.apache.spark.streaming.util.ManualClock"); - ssc = new JavaStreamingContext(conf, new Duration(1000)); - ssc.checkpoint("checkpoint"); - } - - @After - public void tearDown() { - ssc.stop(); - ssc = null; - - // To avoid Akka rebinding to the same port, since it doesn't unbind immediately on shutdown - System.clearProperty("spark.driver.port"); - } - +public class JavaAPISuite extends LocalJavaStreamingContext implements Serializable { @Test public void testCount() { List<List<Integer>> inputData = Arrays.asList( @@ -1610,26 +1581,6 @@ public class JavaAPISuite implements Serializable { // Java arguments and assign it to a JavaDStream without producing type errors. Testing of the // InputStream functionality is deferred to the existing Scala tests. @Test - public void testKafkaStream() { - HashMap<String, Integer> topics = Maps.newHashMap(); - JavaPairDStream<String, String> test1 = ssc.kafkaStream("localhost:12345", "group", topics); - JavaPairDStream<String, String> test2 = ssc.kafkaStream("localhost:12345", "group", topics, - StorageLevel.MEMORY_AND_DISK()); - - HashMap<String, String> kafkaParams = Maps.newHashMap(); - kafkaParams.put("zookeeper.connect","localhost:12345"); - kafkaParams.put("group.id","consumer-group"); - JavaPairDStream<String, String> test3 = ssc.kafkaStream( - String.class, - String.class, - StringDecoder.class, - StringDecoder.class, - kafkaParams, - topics, - StorageLevel.MEMORY_AND_DISK()); - } - - @Test public void testSocketTextStream() { JavaDStream<String> test = ssc.socketTextStream("localhost", 12345); } @@ -1667,36 +1618,4 @@ public class JavaAPISuite implements Serializable { public void testRawSocketStream() { JavaDStream<String> test = ssc.rawSocketStream("localhost", 12345); } - - @Test - public void testFlumeStream() { - JavaDStream<SparkFlumeEvent> test = ssc.flumeStream("localhost", 12345, StorageLevel.MEMORY_ONLY()); - } - - @Test - public void testFileStream() { - JavaPairDStream<String, String> foo = - ssc.<String, String, SequenceFileInputFormat<String,String>>fileStream("/tmp/foo"); - } - - @Test - public void testTwitterStream() { - String[] filters = new String[] { "good", "bad", "ugly" }; - JavaDStream<Status> test = ssc.twitterStream(filters, StorageLevel.MEMORY_ONLY()); - } - - @Test - public void testActorStream() { - JavaDStream<String> test = ssc.actorStream((Props)null, "TestActor", StorageLevel.MEMORY_ONLY()); - } - - @Test - public void testZeroMQStream() { - JavaDStream<String> test = ssc.zeroMQStream("url", (Subscribe) null, new Function<byte[][], Iterable<String>>() { - @Override - public Iterable<String> call(byte[][] b) throws Exception { - return null; - } - }); - } } diff --git a/streaming/src/test/java/org/apache/spark/streaming/LocalJavaStreamingContext.java b/streaming/src/test/java/org/apache/spark/streaming/LocalJavaStreamingContext.java new file mode 100644 index 0000000000..34bee56885 --- /dev/null +++ b/streaming/src/test/java/org/apache/spark/streaming/LocalJavaStreamingContext.java @@ -0,0 +1,46 @@ +/* + * 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; + +import org.apache.spark.streaming.api.java.JavaStreamingContext; +import org.junit.After; +import org.junit.Before; + +public abstract class LocalJavaStreamingContext { + + protected transient JavaStreamingContext ssc; + + @Before + public void setUp() { + System.clearProperty("spark.driver.port"); + System.clearProperty("spark.hostPort"); + System.setProperty("spark.streaming.clock", "org.apache.spark.streaming.util.ManualClock"); + ssc = new JavaStreamingContext("local[2]", "test", new Duration(1000)); + ssc.checkpoint("checkpoint"); + } + + @After + public void tearDown() { + ssc.stop(); + ssc = null; + + // To avoid Akka rebinding to the same port, since it doesn't unbind immediately on shutdown + System.clearProperty("spark.driver.port"); + System.clearProperty("spark.hostPort"); + } +} diff --git a/streaming/src/test/scala/org/apache/spark/streaming/InputStreamsSuite.scala b/streaming/src/test/scala/org/apache/spark/streaming/InputStreamsSuite.scala index 5185954521..a8e053278a 100644 --- a/streaming/src/test/scala/org/apache/spark/streaming/InputStreamsSuite.scala +++ b/streaming/src/test/scala/org/apache/spark/streaming/InputStreamsSuite.scala @@ -23,7 +23,7 @@ import akka.actor.IOManager import akka.actor.Props import akka.util.ByteString -import org.apache.spark.streaming.dstream.{FileInputDStream, NetworkReceiver, SparkFlumeEvent} +import org.apache.spark.streaming.dstream.{NetworkReceiver} import java.net.{InetSocketAddress, SocketException, Socket, ServerSocket} import java.io.{File, BufferedWriter, OutputStreamWriter} import java.util.concurrent.{Executors, TimeUnit, ArrayBlockingQueue} @@ -31,18 +31,11 @@ import collection.mutable.{SynchronizedBuffer, ArrayBuffer} import util.ManualClock import org.apache.spark.storage.StorageLevel import org.apache.spark.streaming.receivers.Receiver -import org.apache.spark.{SparkContext, Logging} +import org.apache.spark.Logging import scala.util.Random import org.apache.commons.io.FileUtils import org.scalatest.BeforeAndAfter -import org.apache.flume.source.avro.AvroSourceProtocol -import org.apache.flume.source.avro.AvroFlumeEvent -import org.apache.flume.source.avro.Status -import org.apache.avro.ipc.{specific, NettyTransceiver} -import org.apache.avro.ipc.specific.SpecificRequestor -import java.nio.ByteBuffer import collection.JavaConversions._ -import java.nio.charset.Charset import com.google.common.io.Files import java.util.concurrent.atomic.AtomicInteger @@ -56,7 +49,7 @@ class InputStreamsSuite extends TestSuiteBase with BeforeAndAfter { testServer.start() // Set up the streaming context and input streams - val ssc = new StreamingContext(new SparkContext(conf), batchDuration) + val ssc = new StreamingContext(conf, batchDuration) val networkStream = ssc.socketTextStream("localhost", testServer.port, StorageLevel.MEMORY_AND_DISK) val outputBuffer = new ArrayBuffer[Seq[String]] with SynchronizedBuffer[Seq[String]] val outputStream = new TestOutputStream(networkStream, outputBuffer) @@ -99,62 +92,13 @@ class InputStreamsSuite extends TestSuiteBase with BeforeAndAfter { } - test("flume input stream") { - // Set up the streaming context and input streams - val ssc = new StreamingContext(new SparkContext(conf), batchDuration) - val flumeStream = ssc.flumeStream("localhost", testPort, StorageLevel.MEMORY_AND_DISK) - val outputBuffer = new ArrayBuffer[Seq[SparkFlumeEvent]] - with SynchronizedBuffer[Seq[SparkFlumeEvent]] - val outputStream = new TestOutputStream(flumeStream, outputBuffer) - ssc.registerOutputStream(outputStream) - ssc.start() - - val clock = ssc.scheduler.clock.asInstanceOf[ManualClock] - val input = Seq(1, 2, 3, 4, 5) - Thread.sleep(1000) - val transceiver = new NettyTransceiver(new InetSocketAddress("localhost", testPort)) - val client = SpecificRequestor.getClient( - classOf[AvroSourceProtocol], transceiver) - - for (i <- 0 until input.size) { - val event = new AvroFlumeEvent - event.setBody(ByteBuffer.wrap(input(i).toString.getBytes())) - event.setHeaders(Map[CharSequence, CharSequence]("test" -> "header")) - client.append(event) - Thread.sleep(500) - clock.addToTime(batchDuration.milliseconds) - } - - val startTime = System.currentTimeMillis() - while (outputBuffer.size < input.size && System.currentTimeMillis() - startTime < maxWaitTimeMillis) { - logInfo("output.size = " + outputBuffer.size + ", input.size = " + input.size) - Thread.sleep(100) - } - Thread.sleep(1000) - val timeTaken = System.currentTimeMillis() - startTime - assert(timeTaken < maxWaitTimeMillis, "Operation timed out after " + timeTaken + " ms") - logInfo("Stopping context") - ssc.stop() - - val decoder = Charset.forName("UTF-8").newDecoder() - - assert(outputBuffer.size === input.length) - for (i <- 0 until outputBuffer.size) { - assert(outputBuffer(i).size === 1) - val str = decoder.decode(outputBuffer(i).head.event.getBody) - assert(str.toString === input(i).toString) - assert(outputBuffer(i).head.event.getHeaders.get("test") === "header") - } - } - - test("file input stream") { // Disable manual clock as FileInputDStream does not work with manual clock conf.set("spark.streaming.clock", "org.apache.spark.streaming.util.SystemClock") // Set up the streaming context and input streams val testDir = Files.createTempDir() - val ssc = new StreamingContext(new SparkContext(conf), batchDuration) + val ssc = new StreamingContext(conf, batchDuration) val fileStream = ssc.textFileStream(testDir.toString) val outputBuffer = new ArrayBuffer[Seq[String]] with SynchronizedBuffer[Seq[String]] def output = outputBuffer.flatMap(x => x) @@ -206,7 +150,7 @@ class InputStreamsSuite extends TestSuiteBase with BeforeAndAfter { testServer.start() // Set up the streaming context and input streams - val ssc = new StreamingContext(new SparkContext(conf), batchDuration) + val ssc = new StreamingContext(conf, batchDuration) val networkStream = ssc.actorStream[String](Props(new TestActor(port)), "TestActor", StorageLevel.MEMORY_AND_DISK) //Had to pass the local value of port to prevent from closing over entire scope val outputBuffer = new ArrayBuffer[Seq[String]] with SynchronizedBuffer[Seq[String]] @@ -249,20 +193,6 @@ class InputStreamsSuite extends TestSuiteBase with BeforeAndAfter { } } - test("kafka input stream") { - val ssc = new StreamingContext(new SparkContext(conf), batchDuration) - val topics = Map("my-topic" -> 1) - val test1 = ssc.kafkaStream("localhost:12345", "group", topics) - val test2 = ssc.kafkaStream("localhost:12345", "group", topics, StorageLevel.MEMORY_AND_DISK) - - // Test specifying decoder - val kafkaParams = Map("zookeeper.connect"->"localhost:12345","group.id"->"consumer-group") - val test3 = ssc.kafkaStream[ - String, - String, - kafka.serializer.StringDecoder, - kafka.serializer.StringDecoder](kafkaParams, topics, StorageLevel.MEMORY_AND_DISK) - } test("multi-thread receiver") { // set up the test receiver @@ -273,7 +203,7 @@ class InputStreamsSuite extends TestSuiteBase with BeforeAndAfter { MultiThreadTestReceiver.haveAllThreadsFinished = false // set up the network stream using the test receiver - val ssc = new StreamingContext(new SparkContext(conf), batchDuration) + val ssc = new StreamingContext(conf, batchDuration) val networkStream = ssc.networkStream[Int](testReceiver) val countStream = networkStream.count val outputBuffer = new ArrayBuffer[Seq[Long]] with SynchronizedBuffer[Seq[Long]] diff --git a/streaming/src/test/scala/org/apache/spark/streaming/TestSuiteBase.scala b/streaming/src/test/scala/org/apache/spark/streaming/TestSuiteBase.scala index 33464bc3a1..b20d02f996 100644 --- a/streaming/src/test/scala/org/apache/spark/streaming/TestSuiteBase.scala +++ b/streaming/src/test/scala/org/apache/spark/streaming/TestSuiteBase.scala @@ -142,16 +142,12 @@ trait TestSuiteBase extends FunSuite with BeforeAndAfter with Logging { // Default before function for any streaming test suite. Override this // if you want to add your stuff to "before" (i.e., don't call before { } ) def beforeFunction() { - //if (useManualClock) { - // System.setProperty( - // "spark.streaming.clock", - // "org.apache.spark.streaming.util.ManualClock" - // ) - //} else { - // System.clearProperty("spark.streaming.clock") - //} if (useManualClock) { + logInfo("Using manual clock") conf.set("spark.streaming.clock", "org.apache.spark.streaming.util.ManualClock") + } else { + logInfo("Using real clock") + conf.set("spark.streaming.clock", "org.apache.spark.streaming.util.SystemClock") } } @@ -175,9 +171,8 @@ trait TestSuiteBase extends FunSuite with BeforeAndAfter with Logging { operation: DStream[U] => DStream[V], numPartitions: Int = numInputPartitions ): StreamingContext = { - val sc = new SparkContext(conf) // Create StreamingContext - val ssc = new StreamingContext(sc, batchDuration) + val ssc = new StreamingContext(conf, batchDuration) if (checkpointDir != null) { ssc.checkpoint(checkpointDir) } @@ -201,9 +196,8 @@ trait TestSuiteBase extends FunSuite with BeforeAndAfter with Logging { input2: Seq[Seq[V]], operation: (DStream[U], DStream[V]) => DStream[W] ): StreamingContext = { - val sc = new SparkContext(conf) // Create StreamingContext - val ssc = new StreamingContext(sc, batchDuration) + val ssc = new StreamingContext(conf, batchDuration) if (checkpointDir != null) { ssc.checkpoint(checkpointDir) } @@ -279,7 +273,7 @@ trait TestSuiteBase extends FunSuite with BeforeAndAfter with Logging { val startTime = System.currentTimeMillis() while (output.size < numExpectedOutput && System.currentTimeMillis() - startTime < maxWaitTimeMillis) { logInfo("output.size = " + output.size + ", numExpectedOutput = " + numExpectedOutput) - Thread.sleep(100) + Thread.sleep(10) } val timeTaken = System.currentTimeMillis() - startTime |