spark streaming简单示例

<?xml version="1.0" encoding="UTF-8"?>
<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">
    <modelVersion>4.0.</modelVersion>
    <parent>
        <artifactId>bigdata</artifactId>
        <groupId>qinfeng.zheng</groupId>
        <version>1.0-SNAPSHOT</version>
    </parent>
    <groupId>qinfeng.zheng</groupId>
    <artifactId>spark-streaming</artifactId>
    <version>1.0-SNAPSHOT</version>

    <dependencies>
        <dependency>
            <groupId>org.scala-lang</groupId>
            <artifactId>scala-library</artifactId>
        </dependency>
        <dependency>
            <groupId>org.apache.spark</groupId>
            <artifactId>spark-core_2.</artifactId>
        </dependency>
        <dependency>
            <groupId>org.apache.hadoop</groupId>
            <artifactId>hadoop-client</artifactId>
        </dependency>
        <dependency>
            <groupId>org.apache.spark</groupId>
            <artifactId>spark-streaming_2.</artifactId>
        </dependency>

        <dependency>
            <groupId>org.apache.spark</groupId>
            <artifactId>spark-streaming-kafka_2.</artifactId>
        </dependency>

    </dependencies>

    <build>
        <sourceDirectory>src/main/scala</sourceDirectory>
        <plugins>
            <plugin>
                <groupId>net.alchim31.maven</groupId>
                <artifactId>scala-maven-plugin</artifactId>
                <version>3.2.</version>
                <executions>
                    <execution>
                        <goals>
                            <goal>compile</goal>
                            <goal>testCompile</goal>
                        </goals>
                        <configuration>
                            <args>
                                <arg>-make:transitive</arg>
                                <arg>-dependencyfile</arg>
                                <arg>${project.build.directory}/.scala_dependencies</arg>
                            </args>
                        </configuration>
                    </execution>
                </executions>
            </plugin>
            <plugin>
                <groupId>org.apache.maven.plugins</groupId>
                <artifactId>maven-surefire-plugin</artifactId>
                <version>2.18.</version>
                <configuration>
                    <useFile>false</useFile>
                    <disableXmlReport>true</disableXmlReport>
                    <includes>
                        <include>**/*Test.*</include>
                        <include>**/*Suite.*</include>
                    </includes>
                </configuration>
            </plugin>

            <plugin>
                <groupId>org.apache.maven.plugins</groupId>
                <artifactId>maven-shade-plugin</artifactId>
                <version>2.3</version>
                <executions>
                    <execution>
                        <phase>package</phase>
                        <goals>
                            <goal>shade</goal>
                        </goals>
                        <configuration>
                            <filters>
                                <filter>
                                    <artifact>*:*</artifact>
                                    <excludes>
                                        <exclude>META-INF/*.SF</exclude>
                                        <exclude>META-INF/*.DSA</exclude>
                                        <exclude>META-INF/*.RSA</exclude>
                                    </excludes>
                                </filter>
                            </filters>
                            <transformers>
                                <transformer
                                        implementation="org.apache.maven.plugins.shade.resource.ManifestResourceTransformer">
                                    <mainClass>qinfeng.zheng.java.KafkaReceiverWordCount</mainClass>
                                </transformer>
                            </transformers>
                        </configuration>
                    </execution>
                </executions>
            </plugin>
        </plugins>
    </build>
</project>

import org.apache.spark.SparkConf
import org.apache.spark.streaming.dstream.DStream
import org.apache.spark.streaming.{Seconds, StreamingContext}

/**
  * 创建时间: 10:57 2018/7/8
  * 修改时间:
  * 编码人员: ZhengQf
  * 版   本: 0.0.1
  * 功能描述: 流式读取hdfs://hdp01:9000/wc/目录下面的文件内容,计算wordcount
  *         最好打成jar上传到linux服务器上运行.windows平台有时不会打印内容
  */
object HDFSWordCount {
  def main(args: Array[String]): Unit = {
    //    System.setProperty("HADOOP_USER_NAME","root")
    val conf = new SparkConf().setAppName("HDFSWordCount").setMaster("local")
    //     val sc = new SparkContext(conf)
    //     val rdd = sc.textFile("hdfs://hdp01:9000/wc/wc.txt")
    //     rdd.foreach(print)
    val scc = new StreamingContext(conf, Seconds(10));
    //同一个文件名的文件不会重复读取,即便是修改了文件内容也不会重复读取
    val lines = scc.textFileStream("D:\\tmp\\wc")   //读取本地文件
    //读取hdfs上的文件,在window读取hdfs可能存在问题
//    val lines = scc.textFileStream("hdfs://hdp01:9000/wc/")

    val words: DStream[String] = lines.flatMap(_.split(" "))
    val wordPairs: DStream[(String, Int)] = words.map((_, 1))
    val wc: DStream[(String, Int)] = wordPairs.reduceByKey(_ + _)
    //wc.saveAsTextFiles("./stream/") //指定计算结果的存储路径
    wc.print() //print  action算子
    scc.start()
    scc.awaitTermination()
    scc.stop()
  }

}