Spark-Core开发及提交

Spark开发

spark-core开发

使用IDEA开发spark程序

创建scala项目

配置maven依赖

<?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">
    <parent>
        <artifactId>SparkDemo</artifactId>
        <groupId>com.realsee.aidata</groupId>
        <version>1.0.0</version>
    </parent>
    <modelVersion>4.0.0</modelVersion>

    <artifactId>spark-core</artifactId>

    <dependencies>
        <dependency>
            <groupId>org.apache.spark</groupId>
            <artifactId>spark-core_2.12</artifactId>
            <version>3.0.1</version>
        </dependency>
    </dependencies>

    <build>
        <plugins>
            <!-- 该插件用于将 Scala 代码编译成 class 文件 -->
            <plugin>
                <groupId>net.alchim31.maven</groupId>
                <artifactId>scala-maven-plugin</artifactId>
                <version>3.2.2</version>
                <executions>
                    <execution>
                        <!-- 声明绑定到 maven 的 compile 阶段 -->
                        <goals>
                            <goal>testCompile</goal>
                        </goals>
                    </execution>
                </executions>
            </plugin>
            <plugin>
                <groupId>org.apache.maven.plugins</groupId>
                <artifactId>maven-assembly-plugin</artifactId>
                <version>3.1.0</version>
                <configuration>
                    <descriptorRefs>
                        <descriptorRef>jar-with-dependencies</descriptorRef>
                    </descriptorRefs>
                </configuration>
                <executions>
                    <execution>
                        <id>make-assembly</id>
                        <phase>package</phase>
                        <goals>
                            <goal>single</goal>
                        </goals>
                    </execution>
                </executions>
            </plugin>
        </plugins>
    </build>
</project>

scala代码开发

package com.realsee.aidata

import org.apache.log4j.Logger
import org.apache.spark.rdd.RDD
import org.apache.spark.{SparkConf, SparkContext}

/**
 * @author weizhaolin
 * @date 2022/7/29 16:45
 */
object Demo {

    val logger = Logger.getLogger("Demo")

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

        // 创建连接
        // 此处不配置AppName、Master等，配置写在spark-submit.sh里
        val sparkConf = new SparkConf()
        val sc: SparkContext = new SparkContext(sparkConf)

        // args接收spark-submit.sh里传入的参数
        // 以下写具体逻辑代码
        println(args(0))
        val rdd: RDD[Int] = sc.makeRDD(List(1, 2, 3, 4))
        rdd.collect().foreach(println)

        // 关闭连接
        sc.stop()
    }

}

使用maven打包

打包完成后，会在Project根目录下的out文件夹下，生成xxx.jar（本案例即spark-core.jar）

spark提交脚本开发

#!/bin/bash

if [ $# -ne 1 ]; then
    echo "缺少参数flag:(dev or online or dev)"
    echo "正确运行示例：sh $0 flag"
    exit 1
fi

PT=$1
echo ''start spark-core.sh $PT''

spark-submit \
    --class com.realsee.aidata.demo \
    --name weizhaolin \
    --master yarn \
    --deploy-mode cluster \
    --executor-memory 10g \
    --num-executors 20 \
    --executor-cores 2 \
    --driver-memory 6g \
    --conf spark.default.parallelism=100 \
    --conf spark.storage.memoryfraction=0.6 \
    --conf spark.sql.shuffle.partitions=1000 \
    --conf spark.shuffle.memoryfraction=0.3 \
    --conf spark.yarn.executor.memoryoverhead=2048 \
    spark-core.jar \
    $PT

if [ $? -ne 0 ]; then
   echo "spark submit failed"
   exit 1
fi

–class：scala类名

–name：app名称

–master：运行环境，yarn模式

–num-executors：executors数量

–executor-cores：每个executors核数

spark-sql开发

敬请期待… …