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Mqtt streaming support in Python
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‎external/mqtt-assembly/pom.xml

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<?xml version="1.0" encoding="UTF-8"?>
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<!--
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~ Licensed to the Apache Software Foundation (ASF) under one or more
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~ contributor license agreements. See the NOTICE file distributed with
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~ this work for additional information regarding copyright ownership.
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~ The ASF licenses this file to You under the Apache License, Version 2.0
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~ (the "License"); you may not use this file except in compliance with
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~ the License. You may obtain a copy of the License at
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~
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~ http://www.apache.org/licenses/LICENSE-2.0
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~
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~ Unless required by applicable law or agreed to in writing, software
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~ distributed under the License is distributed on an "AS IS" BASIS,
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~ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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~ See the License for the specific language governing permissions and
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~ limitations under the License.
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-->
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<project xmlns="http://maven.apache.org/POM/4.0.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd">
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<modelVersion>4.0.0</modelVersion>
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<parent>
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<groupId>org.apache.spark</groupId>
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<artifactId>spark-parent</artifactId>
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<version>1.3.0-SNAPSHOT</version>
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<relativePath>../../pom.xml</relativePath>
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</parent>
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<groupId>org.apache.spark</groupId>
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<artifactId>spark-streaming-mqtt-assembly_2.10</artifactId>
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<packaging>jar</packaging>
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<name>Spark Project External Kafka Assembly</name>
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<url>http://spark.apache.org/</url>
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<properties>
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<sbt.project.name>streaming-mqtt-assembly</sbt.project.name>
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<spark.jar.dir>scala-${scala.binary.version}</spark.jar.dir>
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<spark.jar.basename>spark-streaming-mqtt-assembly-${project.version}.jar</spark.jar.basename>
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<spark.jar>${project.build.directory}/${spark.jar.dir}/${spark.jar.basename}</spark.jar>
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</properties>
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<dependencies>
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<dependency>
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<groupId>org.apache.spark</groupId>
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<artifactId>spark-streaming-mqtt_${scala.binary.version}</artifactId>
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<version>${project.version}</version>
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</dependency>
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<dependency>
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<groupId>org.apache.spark</groupId>
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<artifactId>spark-streaming_${scala.binary.version}</artifactId>
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<version>${project.version}</version>
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<scope>provided</scope>
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</dependency>
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</dependencies>
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<build>
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<outputDirectory>target/scala-${scala.binary.version}/classes</outputDirectory>
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<testOutputDirectory>target/scala-${scala.binary.version}/test-classes</testOutputDirectory>
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<plugins>
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<plugin>
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<groupId>org.apache.maven.plugins</groupId>
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<artifactId>maven-shade-plugin</artifactId>
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<configuration>
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<shadedArtifactAttached>false</shadedArtifactAttached>
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<outputFile>${spark.jar}</outputFile>
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<artifactSet>
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<includes>
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<include>*:*</include>
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</includes>
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</artifactSet>
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<filters>
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<filter>
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<artifact>*:*</artifact>
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<excludes>
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<exclude>META-INF/*.SF</exclude>
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<exclude>META-INF/*.DSA</exclude>
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<exclude>META-INF/*.RSA</exclude>
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</excludes>
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</filter>
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</filters>
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</configuration>
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<executions>
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<execution>
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<phase>package</phase>
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<goals>
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<goal>shade</goal>
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</goals>
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<configuration>
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<transformers>
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<transformer implementation="org.apache.maven.plugins.shade.resource.ServicesResourceTransformer"/>
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<transformer implementation="org.apache.maven.plugins.shade.resource.AppendingTransformer">
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<resource>reference.conf</resource>
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</transformer>
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<transformer implementation="org.apache.maven.plugins.shade.resource.DontIncludeResourceTransformer">
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<resource>log4j.properties</resource>
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</transformer>
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<transformer implementation="org.apache.maven.plugins.shade.resource.ApacheLicenseResourceTransformer"/>
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<transformer implementation="org.apache.maven.plugins.shade.resource.ApacheNoticeResourceTransformer"/>
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</transformers>
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</configuration>
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</execution>
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</executions>
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</plugin>
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</plugins>
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</build>
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</project>

‎pom.xml

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<module>external/flume-sink</module>
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<module>external/flume-assembly</module>
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<module>external/mqtt</module>
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<module>external/mqtt-assembly</module>
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<module>external/zeromq</module>
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<module>examples</module>
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<module>repl</module>

‎project/SparkBuild.scala

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sparkKinesisAsl) = Seq("yarn", "yarn-stable", "java8-tests", "ganglia-lgpl",
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"kinesis-asl").map(ProjectRef(buildLocation, _))
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val assemblyProjects@Seq(assembly, examples, networkYarn, streamingFlumeAssembly, streamingKafkaAssembly) =
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Seq("assembly", "examples", "network-yarn", "streaming-flume-assembly", "streaming-kafka-assembly")
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val assemblyProjects@Seq(assembly, examples, networkYarn, streamingFlumeAssembly, streamingKafkaAssembly, streamingMqttAssembly) =
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Seq("assembly", "examples", "network-yarn", "streaming-flume-assembly", "streaming-kafka-assembly", "streaming-mqtt-assembly")
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.map(ProjectRef(buildLocation, _))
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val tools = ProjectRef(buildLocation, "tools")
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.getOrElse(SbtPomKeys.effectivePom.value.getProperties.get("hadoop.version").asInstanceOf[String])
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},
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jarName in assembly <<= (version, moduleName, hadoopVersion) map { (v, mName, hv) =>
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if (mName.contains("streaming-flume-assembly") || mName.contains("streaming-kafka-assembly")) {
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if (mName.contains("streaming-flume-assembly") || mName.contains("streaming-kafka-assembly") || mName.contains("streaming-mqtt-assembly")) {
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// This must match the same name used in maven (see external/kafka-assembly/pom.xml)
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s"${mName}-${v}.jar"
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} else {

‎python/pyspark/streaming/mqtt.py

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#
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# Licensed to the Apache Software Foundation (ASF) under one or more
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# contributor license agreements. See the NOTICE file distributed with
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# this work for additional information regarding copyright ownership.
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# The ASF licenses this file to You under the Apache License, Version 2.0
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# (the "License"); you may not use this file except in compliance with
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# the License. You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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#
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from py4j.java_collections import MapConverter
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from py4j.java_gateway import java_import, Py4JError
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from pyspark.storagelevel import StorageLevel
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from pyspark.serializers import PairDeserializer, NoOpSerializer
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from pyspark.streaming import DStream
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__all__ = ['MQTTUtils']
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class MQTTUtils(object):
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@staticmethod
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def createStream(ssc, brokerUrl, topic
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storageLevel=StorageLevel.MEMORY_AND_DISK_SER_2):
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"""
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Create an input stream that pulls messages from a Mqtt Broker.
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:param ssc: StreamingContext object
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:param brokerUrl: Url of remote mqtt publisher
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:param topic: topic name to subscribe to
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:param storageLevel: RDD storage level.
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:return: A DStream object
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"""
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java_import(ssc._jvm, "org.apache.spark.streaming.mqtt.MQTTUtils")
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jlevel = ssc._sc._getJavaStorageLevel(storageLevel)
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try:
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jstream = ssc._jvm.MQTTUtils.createStream(ssc._jssc, brokerUrl, topic, jlevel)
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except Py4JError, e:
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# TODO: use --jar once it also work on driver
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if not e.message or 'call a package' in e.message:
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print "No Mqtt package, please put the assembly jar into classpath:"
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print " $ bin/spark-submit --driver-class-path external/mqtt-assembly/target/" + \
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"scala-*/spark-streaming-mqtt-assembly-*.jar"
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raise e
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ser = PairDeserializer(NoOpSerializer(), NoOpSerializer())
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stream = DStream(jstream, ssc, ser)
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return stream

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