Spark Streaming之统计socket单词数

青旅半醒 2023-02-25 07:15 4阅读 0赞

### 一、统计socket单词数 ###

侦听TCP套接字的数据服务器接收到的文本数据中的单词数。

### 二、maven配置 ###

<?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.mk</groupId>
      <artifactId>spark-test</artifactId>
      <version>1.0</version>
    
      <name>spark-test</name>
      <url>http://spark.mk.com</url>
    
      <properties>
        <project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>
        <maven.compiler.source>1.8</maven.compiler.source>
        <maven.compiler.target>1.8</maven.compiler.target>
        <scala.version>2.11.1</scala.version>
        <spark.version>2.4.4</spark.version>
        <hadoop.version>2.6.0</hadoop.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-streaming_2.11</artifactId>
          <version>${spark.version}</version>
        </dependency>
    
    
        <dependency>
          <groupId>junit</groupId>
          <artifactId>junit</artifactId>
          <version>4.11</version>
          <scope>test</scope>
        </dependency>
        <dependency>
          <groupId>org.projectlombok</groupId>
          <artifactId>lombok</artifactId>
          <version>1.18.10</version>
        </dependency>
    </dependencies>
    
      <build>
        <pluginManagement>
          <plugins>
    
            <plugin>
              <artifactId>maven-clean-plugin</artifactId>
              <version>3.1.0</version>
            </plugin>
    
            <plugin>
              <artifactId>maven-resources-plugin</artifactId>
              <version>3.0.2</version>
            </plugin>
            <plugin>
              <artifactId>maven-compiler-plugin</artifactId>
              <version>3.8.0</version>
            </plugin>
            <plugin>
              <artifactId>maven-surefire-plugin</artifactId>
              <version>2.22.1</version>
            </plugin>
            <plugin>
              <artifactId>maven-jar-plugin</artifactId>
              <version>3.0.2</version>
            </plugin>
    
    
    
          </plugins>
        </pluginManagement>
      </build>
    </project>

### 三、编程代码  ###

public class SocketApp implements SparkConfInfo {
    
        public static void main(String[] args) throws InterruptedException {
    
            JavaStreamingContext streamingContext = new SocketApp().getStreamingContext("SocketApp", 5);
            JavaReceiverInputDStream<String> lines = streamingContext.socketTextStream("localhost", 8891);
            JavaDStream<String> words = lines.flatMap(x -> Arrays.asList(x.split("\\s+")).stream()
                    .filter(v->v.length()>0).iterator());
            JavaPairDStream<String, Integer> pairs = words.mapToPair(s -> new Tuple2<>(s, 1));
            JavaPairDStream<String, Integer> wordCounts = pairs.reduceByKey(Integer::sum);
            wordCounts.foreachRDD(v->{
                v.foreach(s-> System.out.println(s._1+":" + s._2));
                System.out.println("---------------------------");
            });
            streamingContext.start();
            streamingContext.awaitTermination();
        }
    }
    
    
    public interface SparkConfInfo {
    
        default JavaStreamingContext getStreamingContext(String appName, int second){
            SparkConf sparkConf = getSparkConf();
            sparkConf.setAppName(appName);
            JavaStreamingContext jssc = new JavaStreamingContext(sparkConf, Durations.seconds(second));
            return jssc;
        }
    
        default SparkSession getSparkSession(String appName){
            SparkConf sparkConf = getSparkConf();
    
            SparkSession session = SparkSession.builder().appName(appName).config(sparkConf).config(sparkConf).getOrCreate();
            return session;
        }
    
        default SparkConf getSparkConf() {
            SparkConf sparkConf = new SparkConf();
            if(System.getProperty("os.name").toLowerCase().contains("win")) {
                sparkConf.setMaster("local[4]");
                System.out.println("使用本地模拟是spark");
            }else
            {
                sparkConf.setMaster("spark://hadoop01:7077,hadoop02:7077,hadoop03:7077");
                sparkConf.set("spark.driver.host","192.168.150.1");//本地ip，必须与spark集群能够相互访问，如：同一个局域网
                sparkConf.setJars(new String[] {".\\out\\artifacts\\spark_test\\spark-test.jar"});//项目构建生成的路径
            }
            return sparkConf;
        }
    }

输入内容

Tom        Lucy
    Tom        Jack
    Jone        Lucy
    Jone        Jack
    Lucy        Mary
    Lucy        Ben
    Jack        Alice
    Jack        Jesse
    Terry        Alice
    Terry        Jesse
    Philip        Terry
    Philip        Alma
    Mark        Terry
    Mark        Alma

输出结果

Mark:2
    Tom:2
    Jesse:2
    Philip:2
    Alice:2
    Jone:2
    Terry:4
    Alma:2
    Ben:1
    Lucy:4
    Mary:1
    Jack:4
    ---------------------------