Spark学习:用spark实现ETL

一、RDBMS To RDBMS
1、pom.xml

<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>Spark</groupId>
    <artifactId>Spark</artifactId>
    <version>0.0.1-SNAPSHOT</version>
    <dependencies>
        <dependency>
            <groupId>org.apache.spark</groupId>
            <artifactId>spark-core_2.12</artifactId>
            <version>3.2.0</version>
        </dependency>
        <dependency>
            <groupId>org.apache.spark</groupId>
            <artifactId>spark-sql_2.12</artifactId>
            <version>3.2.0</version>
        </dependency>
    </dependencies>
    <build>
        <plugins>
            <plugin>
                <groupId>net.alchim31.maven</groupId>
                <artifactId>scala-maven-plugin</artifactId>
                <version>3.2.2</version>
                <executions>
                    <execution>
                        <id>compile-scala</id>
                        <phase>compile</phase>
                        <goals>
                            <goal>add-source</goal>
                            <goal>compile</goal>
                        </goals>
                    </execution>
                    <execution>
                        <id>test-compile-scala</id>
                        <phase>test-compile</phase>
                        <goals>
                            <goal>add-source</goal>
                            <goal>testCompile</goal>
                        </goals>
                    </execution>
                </executions>
                <configuration>
                    <scalaVersion>2.12.15</scalaVersion>
                </configuration>
            </plugin>

            <plugin>
                <groupId>org.apache.maven.plugins</groupId>
                <artifactId>maven-compiler-plugin</artifactId>
                <version>3.2</version>
                <configuration>
                    <source>1.8</source>
                    <target>1.8</target>
                </configuration>
            </plugin>

            <plugin>
                <artifactId>maven-assembly-plugin</artifactId>
                <configuration>
                    <descriptorRefs>
                        <descriptorRef>jar-with-dependencies</descriptorRef>
                    </descriptorRefs>
                    <archive>
                        <manifest>
                            <mainClass></mainClass>
                        </manifest>
                    </archive>
                </configuration>
                <executions>
                    <execution>
                        <id>make-assembly</id>
                        <phase>package</phase>
                        <goals>
                            <goal>single</goal>
                        </goals>
                    </execution>
                </executions>
            </plugin>

            <plugin>
                <groupId>org.codehaus.mojo</groupId>
                <artifactId>exec-maven-plugin</artifactId>
                <version>1.6.0</version>
                <executions>
                    <execution>
                        <goals>
                            <goal>exec</goal>
                        </goals>
                    </execution>
                </executions>
                <configuration>
                    <executable>java</executable>
                    <includeProjectDependencies>true</includeProjectDependencies>
                    <includePluginDependencies>false</includePluginDependencies>
                    <classpathScope>compile</classpathScope>
                    <mainClass>cn.spark.study.App</mainClass>
                </configuration>
            </plugin>
        </plugins>
    </build>
</project>

2、Main

package bigData

import org.apache.spark.sql.SparkSession

import java.util.Properties

object DataSync {
    

  def main(args:Array[String]):Unit = {
    

    val app = s"${
      this.getClass.getSimpleName}".filter(!_.equals('$'))

    val spark: SparkSession = SparkSession.builder
      .appName(app)
      .master("local[*]")
      .config("spark.shuffle.consolidateFiles", "true")
      .config("spark.serializer", "org.apache.spark.serializer.KryoSerializer")
      .config("spark.streaming.kafka.maxRatePerPartition", "500")
      .config("spark.streaming.stopGracefullyOnShutdown", "true")
      .config("spark.network.timeout", "600")
      .config("spark.streaming.kafka.consumer.poll.ms", "60000")
      .config("spark.core.connection.ack.wait.timeout", "900")
      .config("spark.rpc.message.maxSize", "50")
      .config("spark.akka.timeout", "900")
      .getOrCreate()

    //数据源
    val source_url = s"jdbc:oracle:thin:@192.168.0.101:1521/orcl"
    val source_prop = new Properties()
    source_prop.put("user","scott")
    source_prop.put("password","scott")
    source_prop.put("driver","oracle.jdbc.driver.OracleDriver")

    //目标库
    val target_url  = s"jdbc:oracle:thin:@192.168.0.101:1521/orcl"
    val target_prop = new Properties()
    target_prop.put("user","scott")
    target_prop.put("password","scott")
    target_prop.put("driver","oracle.jdbc.driver.OracleDriver")

    import spark.implicits._
    spark.read.jdbc(source_url,"EMP",source_prop).write.jdbc(target_url,"EMP_TEST",target_prop)
  }
}

3、运行结果

不过要注意,代码中没有做表已经存在的判断,第二次运行会报错