SparkStreaming案例：模拟百度热搜排行榜

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pom文件

<?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>4.0.0</modelVersion>
    
        <groupId>com.cll</groupId>
        <artifactId>day01</artifactId>
        <version>1.0-SNAPSHOT</version>
    
        
        <repositories>
            <repository>
                <id>aliyun</id>
                <url>http://maven.aliyun.com/nexus/content/groups/public/</url>
            </repository>
            <repository>
                <id>cloudera</id>
                <url>https://repository.cloudera.com/artifactory/cloudera-repos/</url>
            </repository>
            <repository>
                <id>jboss</id>
                <url>http://repository.jboss.com/nexus/content/groups/public</url>
            </repository>
        </repositories>
        <properties>
            <maven.compiler.source>1.8</maven.compiler.source>
            <maven.compiler.target>1.8</maven.compiler.target>
            <encoding>UTF-8</encoding>
            <scala.version>2.11.8</scala.version>
            <scala.compat.version>2.11</scala.compat.version>
            <hadoop.version>2.7.4</hadoop.version>
            <spark.version>2.2.0</spark.version>
        </properties>
        <dependencies>
            <dependency>
                <groupId>org.scala-lang</groupId>
                <artifactId>scala-library</artifactId>
                <version>${scala.version}</version>
            </dependency>
            <dependency>
                <groupId>org.apache.spark</groupId>
                <artifactId>spark-core_2.11</artifactId>
                <version>${spark.version}</version>
            </dependency>
            <dependency>
                <groupId>org.apache.spark</groupId>
                <artifactId>spark-sql_2.11</artifactId>
                <version>${spark.version}</version>
            </dependency>
            <dependency>
                <groupId>org.apache.spark</groupId>
                <artifactId>spark-hive_2.11</artifactId>
                <version>${spark.version}</version>
            </dependency>
            <dependency>
                <groupId>org.apache.spark</groupId>
                <artifactId>spark-hive-thriftserver_2.11</artifactId>
                <version>${spark.version}</version>
            </dependency>
            <dependency>
                <groupId>org.apache.spark</groupId>
                <artifactId>spark-streaming_2.11</artifactId>
                <version>${spark.version}</version>
            </dependency>
            
            <dependency>
                <groupId>org.apache.spark</groupId>
                <artifactId>spark-streaming-kafka-0-10_2.11</artifactId>
                <version>${spark.version}</version>
            </dependency>
            <dependency>
                <groupId>org.apache.spark</groupId>
                <artifactId>spark-sql-kafka-0-10_2.11</artifactId>
                <version>${spark.version}</version>
            </dependency>
    
            
    
            <dependency>
                <groupId>org.apache.hadoop</groupId>
                <artifactId>hadoop-client</artifactId>
                <version>2.7.4</version>
            </dependency>
            <dependency>
                <groupId>org.apache.hbase</groupId>
                <artifactId>hbase-client</artifactId>
                <version>1.3.1</version>
            </dependency>
            <dependency>
                <groupId>org.apache.hbase</groupId>
                <artifactId>hbase-server</artifactId>
                <version>1.3.1</version>
            </dependency>
            <dependency>
                <groupId>com.typesafe</groupId>
                <artifactId>config</artifactId>
                <version>1.3.3</version>
            </dependency>
            <dependency>
                <groupId>mysql</groupId>
                <artifactId>mysql-connector-java</artifactId>
                <version>5.1.38</version>
            </dependency>
        </dependencies>
    
        <build>
            <sourceDirectory>src/main/scala</sourceDirectory>
            <testSourceDirectory>src/test/scala</testSourceDirectory>
            <plugins>
                
                <plugin>
                    <groupId>org.apache.maven.plugins</groupId>
                    <artifactId>maven-compiler-plugin</artifactId>
                    <version>3.5.1</version>
                </plugin>
                
                <plugin>
                    <groupId>net.alchim31.maven</groupId>
                    <artifactId>scala-maven-plugin</artifactId>
                    <version>3.2.2</version>
                    <executions>
                        <execution>
                            <goals>
                                <goal>compile</goal>
                                <goal>testCompile</goal>
                            </goals>
                            <configuration>
                                <args>
                                    <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>2.18.1</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></mainClass>
                                    </transformer>
                                </transformers>
                            </configuration>
                        </execution>
                    </executions>
                </plugin>
            </plugins>
        </build>
    </project>

代码：

object wordcount4 {
      /*
       演示SparkStreaming的应用
      * 模拟百度热搜排行榜
      * 统计最近10s的热搜词，每隔5s计算一次----涉及到窗口，需要使用reduceBykeyAndWindow进行统计
      * */
      def main(args: Array[String]): Unit = {
          //创建streamingContext
        val conf: SparkConf = new SparkConf().setAppName("wc").setMaster("local[*]")
        val sc = new SparkContext(conf)
        val ssc = new StreamingContext(sc, Seconds(5))
        sc.setLogLevel("WARN")
        //Seconds(5)表示每个批次间隔5s
    
        //读取数据
        val Dstream: ReceiverInputDStream[String] = ssc.socketTextStream("node03",9999)
        val wordOne = Dstream.flatMap(_.split(" ")).map((_,1))
    
        //统计窗口内的数据
        val resDstream: DStream[(String, Int)] = wordOne.reduceByKeyAndWindow((a:Int, b:Int)=>a+b,Seconds(10),Seconds(5))
    
        //对统计出来的数据进行排序
        //!!!对dstream的操作，显示转化成为对rdd的操作，在操作中进行排序，因为dstream本身没有排序方法
        val sortedDStream = resDstream.transform(rdd => {
          //根据数量进行排序
          val sortedRDD: RDD[(String, Int)] = rdd.sortBy(_._2, false)
          val top3Arr: Array[(String, Int)] = sortedRDD.take(3)
          println("========top3===========")
          top3Arr.foreach(println)
          println("========top3===========")
          sortedRDD
        })
    
    
        //输出结果
        //注意：尽管上面的代码已经有输出打印，但是不是DStream的ouput输出操作，所以下面的output代码不能省略
        sortedDStream.print()
        //开启
        ssc.start()
        ssc.awaitTermination()
    
      }
    
    }