Spark入门（十七）之单表关联

我不是女神ヾ 2023-02-24 11:22 60阅读 0赞

###  一、单表关联 ###

给出child-parent（孩子——父母）表，要求输出grandchild-grandparent（孙子——祖父母）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 SingleTableJoinApp implements SparkConfInfo {
    
        public static void main(String[] args) {
    
            String filePath = "E:\\spark\\childParent.txt";
            SparkSession sparkSession = new SingleTableJoinApp().getSparkConf("childParent");
            JavaPairRDD<String, String> childParent = sparkSession.sparkContext()
                    .textFile(filePath, 4)
                    .toJavaRDD()
                    .flatMap(v -> Arrays.asList(v.split("\n")).iterator())
                    .mapToPair(v -> {
                        if(v.matches("\\s+child\\s+parent\\s+")){
                            return null;
                        }
                        String[] data = v.split("\\s+");
                        if (data.length != 2) {
                            return null;
                        }
    
    
                        return new Tuple2<>(data[0],data[1]);
                    }).filter(v -> v != null).cache();
    
            JavaPairRDD<String, String> parentChild = childParent.mapToPair(v->new Tuple2(v._2, v._1));
            JavaPairRDD<String, Tuple2<String, String> >  joinRdd = parentChild.join(childParent);
            List<Tuple2<String, String>> childGrand = joinRdd.mapToPair(v->new Tuple2<>(v._2._1, v._2._2))
                   .sortByKey(true)
                    .collect();
            System.out.println("child\t\tgrand");
            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;
        }
    }

childParent.txt文件内容

child        parent
    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

child		grand
    Jone		Mary
    Jone		Ben
    Jone		Alice
    Jone		Jesse
    Mark		Alice
    Mark		Jesse
    Philip		Alice
    Philip		Jesse
    Tom		Mary
    Tom		Ben
    Tom		Alice
    Tom		Jesse

### 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