<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/maven-v4_0_0.xsd">
<modelVersion>4.0.0</modelVersion>
<groupId>com.sid.spark</groupId>
<artifactId>spark-train</artifactId>
<version>1.0</version>
<inceptionYear>2008</inceptionYear>
<properties>
<scala.version>2.11.8</scala.version>
<kafka.version>0.9.0.0</kafka.version>
<spark.version>2.2.0</spark.version>
<hadoop.version>2.9.0</hadoop.version>
<hbase.version>1.4.4</hbase.version>
</properties>
<repositories>
<repository>
<id>scala-tools.org</id>
<name>Scala-Tools Maven2 Repository</name>
<url>http://scala-tools.org/repo-releases</url>
</repository>
</repositories>
<pluginRepositories>
<pluginRepository>
<id>scala-tools.org</id>
<name>Scala-Tools Maven2 Repository</name>
<url>http://scala-tools.org/repo-releases</url>
</pluginRepository>
</pluginRepositories>
<dependencies>
<dependency>
<groupId>org.scala-lang</groupId>
<artifactId>scala-library</artifactId>
<version>${scala.version}</version>
</dependency>
<dependency>
<groupId>org.apache.kafka</groupId>
<artifactId>kafka_2.11</artifactId>
<version>${kafka.version}</version>
</dependency>
<dependency>
<groupId>org.apache.hadoop</groupId>
<artifactId>hadoop-client</artifactId>
<version>${hadoop.version}</version>
<exclusions>
<exclusion>
<artifactId>servlet-api</artifactId>
<groupId>javax.servlet</groupId>
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</dependency>
<!--<dependency>-->
<!--<groupId>org.apache.hbase</groupId>-->
<!--<artifactId>hbase-clinet</artifactId>-->
<!--<version>${hbase.version}</version>-->
<!--</dependency>-->
<!--<dependency>-->
<!--<groupId>org.apache.hbase</groupId>-->
<!--<artifactId>hbase-server</artifactId>-->
<!--<version>${hbase.version}</version>-->
<!--</dependency>-->
<dependency>
<groupId>org.apache.spark</groupId>
<artifactId>spark-streaming_2.11</artifactId>
<version>${spark.version}</version>
</dependency>
<dependency>
<groupId>org.apache.spark</groupId>
<artifactId>spark-sql_2.11</artifactId>
<version>${spark.version}</version>
</dependency>
<dependency>
<groupId>org.apache.spark</groupId>
<artifactId>spark-streaming-flume_2.11</artifactId>
<version>${spark.version}</version>
</dependency>
<dependency>
<groupId>org.apache.spark</groupId>
<artifactId>spark-streaming-flume-sink_2.11</artifactId>
<version>${spark.version}</version>
</dependency>
<dependency>
<groupId>org.apache.spark</groupId>
<artifactId>spark-streaming-kafka-0-8_2.11</artifactId>
<version>2.2.0</version>
</dependency>
<dependency>
<groupId>net.jpountz.lz4</groupId>
<artifactId>lz4</artifactId>
<version>1.3.0</version>
</dependency>
<dependency>
<groupId>mysql</groupId>
<artifactId>mysql-connector-java</artifactId>
<version>5.1.31</version>
</dependency>
<dependency>
<groupId>org.apache.commons</groupId>
<artifactId>commons-lang3</artifactId>
<version>3.5</version>
</dependency>
</dependencies>
<build>
<sourceDirectory>src/main/scala</sourceDirectory>
<!--<testSourceDirectory>src/test/scala</testSourceDirectory>-->
<plugins>
<plugin>
<groupId>org.scala-tools</groupId>
<artifactId>maven-scala-plugin</artifactId>
<executions>
<execution>
<goals>
<goal>compile</goal>
<goal>testCompile</goal>
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<configuration>
<scalaVersion>${scala.version}</scalaVersion>
<args>
<arg>-target:jvm-1.5</arg>
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<plugin>
<groupId>org.apache.maven.plugins</groupId>
<artifactId>maven-eclipse-plugin</artifactId>
<configuration>
<downloadSources>true</downloadSources>
<buildcommands>
<buildcommand>ch.epfl.lamp.sdt.core.scalabuilder</buildcommand>
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<additionalProjectnatures>
<projectnature>ch.epfl.lamp.sdt.core.scalanature</projectnature>
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<classpathContainers>
<classpathContainer>org.eclipse.jdt.launching.JRE_CONTAINER</classpathContainer>
<classpathContainer>ch.epfl.lamp.sdt.launching.SCALA_CONTAINER</classpathContainer>
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</build>
<reporting>
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<plugin>
<groupId>org.scala-tools</groupId>
<artifactId>maven-scala-plugin</artifactId>
<configuration>
<scalaVersion>${scala.version}</scalaVersion>
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</reporting>
</project>
package com.zoujc.sparkstreaming
import kafka.serializer.StringDecoder
import org.apache.spark.SparkConf
import org.apache.spark.streaming.kafka.KafkaUtils
import org.apache.spark.streaming.{Seconds, StreamingContext}
/**
* Spark Streaming 基于 Direct 对接Kafka
*/
object KafkaDirect {
def main(args: Array[String]): Unit = {
if (args.length != 2) {
System.err.println("Usage: KafkaDirect <brokers> <topics>")
System.exit(1)
}
val Array(brokers, topics) = args
val sparkConf = new SparkConf().setAppName("KafkaReceiver").setMaster("local[3]")
val ssc = new StreamingContext(sparkConf, Seconds(5))
/*
@param ssc StreamingContext object
@param kafkaParams Kafka <a href="http://kafka.apache.org/documentation.html#configuration">
configuration parameters</a>. Requires "metadata.broker.list" or "bootstrap.servers"
to be set with Kafka broker(s) (NOT zookeeper servers), specified in
host1:port1,host2:port2 form.
If not starting from a checkpoint, "auto.offset.reset" may be set to "largest" or "smallest"
to determine where the stream starts (defaults to "largest")
@param topics Names of the topics to consume
@tparam K type of Kafka message key
@tparam V type of Kafka message value
@tparam KD type of Kafka message key decoder
@tparam VD type of Kafka message value decoder
@return DStream of (Kafka message key, Kafka message value) */
val topicsSet = topics.split(",").toSet
val kafkaParams = Map[String, String]("metadata.broker.list" -> brokers)
val messages = KafkaUtils.createDirectStream[String, String, StringDecoder, StringDecoder](ssc, kafkaParams, topicsSet)
messages.print()
messages.map(_._2).flatMap(_.split(" ")).map((_, 1)).reduceByKey(_ + _).print()
ssc.start()
ssc.awaitTermination()
}
}