Spark入门（十八）之多表关联

喜欢ヅ旅行 2023-02-24 11:22 12阅读 0赞

### 一、多表关联 ###

输入是两个文件，一个代表工厂表，包含工厂名列和地址编号列；另一个代表地址表，包含地址名列和地址编号列。要求从输入数据中找出工厂名和地址名的对应关系，输出"工厂名——地址名"表

### 二、maven设置 ###

<?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>junit</groupId>
          <artifactId>junit</artifactId>
          <version>4.11</version>
          <scope>test</scope>
        </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 MultiTableJoinApp implements SparkConfInfo {
    
        public static void main(String[] args) {
    
            String factoryFilePath = "E:\\spark\\factory.txt";
            SparkSession sparkSession = new MultiTableJoinApp().getSparkConf("MultiTableJoinApp");
            JavaPairRDD<String, String> addressFactoryRdd = sparkSession.sparkContext()
                    .textFile(factoryFilePath, 4)
                    .toJavaRDD()
                    .flatMap(v -> Arrays.asList(v.split("\n")).iterator())
                    .mapToPair(v -> {
    
                        if(v.matches("\\s+factoryname\\s+addressed\\s+")){
                            return null;
                        }
                        String[] data = v.trim().split("\\s{2,}");
                        if (data.length != 2) {
                            return null;
                        }
                        return new Tuple2<>(data[1],data[0]);
                    }).filter(v -> v != null);
    
            String addressFilePath = "E:\\spark\\address.txt";
            JavaPairRDD<String, String> addressNameRdd = sparkSession.sparkContext()
                    .textFile(addressFilePath, 4)
                    .toJavaRDD()
                    .flatMap(v -> Arrays.asList(v.split("\n")).iterator())
                    .mapToPair(v -> {
                        if(v.matches("\\s+addressID\\s+addressname\\s+")){
                            return null;
                        }
                        String[] data = v.trim().split("\\s{2,}");
                        if (data.length != 2) {
                            return null;
                        }
    
    
                        return new Tuple2<>(data[0],data[1]);
                    }).filter(v -> v != null);
    
            JavaPairRDD<String, Tuple2<String, String> >  joinRdd = addressFactoryRdd.join(addressNameRdd);
            List<Tuple2<String, String>> childGrand = joinRdd.mapToPair(v->new Tuple2<>(v._2._1, v._2._2))
                   .sortByKey(true)
                    .collect();
    
            System.out.println("factoryname\t\taddressname");
            childGrand.forEach(v -> System.out.println(v._1 + "\t\t" + v._2));
    
            sparkSession.stop();
        }
    }
    
    
    
    public interface SparkConfInfo {
    
        default SparkSession getSparkConf(String appName){
            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
            }
    
            SparkSession session = SparkSession.builder().appName(appName).config(sparkConf).config(sparkConf).getOrCreate();
            return session;
        }
    }

factory.txt文件内容

factoryname        addressed 
    Beijing Red Star        1
    Shenzhen Thunder        3
    Guangzhou Honda        2
    Beijing Rising        1
    Guangzhou Development Bank        2
    Tencent        3
    Back of Beijing        1

address.txt文件内容

addressID        addressname 
    1        Beijing
    2        Guangzhou
    3        Shenzhen
    4        Xian

输出

factoryname		addressname
    Back of Beijing		Beijing
    Beijing Red Star		Beijing
    Beijing Rising		Beijing
    Guangzhou Development Bank		Guangzhou
    Guangzhou Honda		Guangzhou
    Shenzhen Thunder		Shenzhen
    Tencent		Shenzhen

### 四、join方法 ###

<W> JavaPairRDD<K, Tuple2<V, W>> join(JavaPairRDD<K, W> other)

关联表返回相同可以的键值对