引言
gitee地址：https://gitee.com/shawsongyue/aurora.git
源码直接下载可运行，模块：aurora_flink
Flink 版本：1.18.0
Jdk 版本：11
1.创建mavenx项目
2.包结构
3.引入pom依赖
tips：transformer处写主启动类
<?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.xsy</groupId>
<artifactId>aurora_flink</artifactId>
<version>1.0-SNAPSHOT</version>
<!--属性设置-->
<properties>
<!--java_JDK版本-->
<java.version>11</java.version>
<!--maven打包插件-->
<maven.plugin.version>3.8.1</maven.plugin.version>
<!--编译编码UTF-8-->
<project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>
<!--输出报告编码UTF-8-->
<project.reporting.outputEncoding>UTF-8</project.reporting.outputEncoding>
<!--json数据格式处理工具-->
<fastjson.version>1.2.75</fastjson.version>
<!--log4j版本-->
<log4j.version>2.17.1</log4j.version>
<!--flink版本-->
<flink.version>1.18.0</flink.version>
<!--scala版本-->
<scala.binary.version>2.11</scala.binary.version>
<!--log4j依赖-->
<log4j.version>2.17.1</log4j.version>
</properties>
<!--通用依赖-->
<dependencies>
<!-- json -->
<dependency>
<groupId>com.alibaba</groupId>
<artifactId>fastjson</artifactId>
<version>${fastjson.version}</version>
</dependency>
<!-- https://mvnrepository.com/artifact/org.apache.flink/flink-java -->
<dependency>
<groupId>org.apache.flink</groupId>
<artifactId>flink-java</artifactId>
<version>${flink.version}</version>
</dependency>
<dependency>
<groupId>org.apache.flink</groupId>
<artifactId>flink-streaming-scala_2.12</artifactId>
<version>${flink.version}</version>
</dependency>
<!-- https://mvnrepository.com/artifact/org.apache.flink/flink-clients -->
<dependency>
<groupId>org.apache.flink</groupId>
<artifactId>flink-clients</artifactId>
<version>${flink.version}</version>
</dependency>
<!--================================集成外部依赖==========================================-->
<!--集成日志框架 start-->
<dependency>
<groupId>org.apache.logging.log4j</groupId>
<artifactId>log4j-slf4j-impl</artifactId>
<version>${log4j.version}</version>
</dependency>
<dependency>
<groupId>org.apache.logging.log4j</groupId>
<artifactId>log4j-api</artifactId>
<version>${log4j.version}</version>
</dependency>
<dependency>
<groupId>org.apache.logging.log4j</groupId>
<artifactId>log4j-core</artifactId>
<version>${log4j.version}</version>
</dependency>
<!--集成日志框架 end-->
</dependencies>
<!--编译打包-->
<build>
<finalName>${project.name}</finalName>
<!--资源文件打包-->
<resources>
<resource>
<directory>src/main/resources</directory>
</resource>
<resource>
<directory>src/main/java</directory>
<includes>
<include>**/*.xml</include>
</includes>
</resource>
</resources>
<plugins>
<plugin>
<groupId>org.apache.maven.plugins</groupId>
<artifactId>maven-shade-plugin</artifactId>
<version>3.1.1</version>
<executions>
<execution>
<phase>package</phase>
<goals>
<goal>shade</goal>
</goals>
<configuration>
<artifactSet>
<excludes>
<exclude>org.apache.flink:force-shading</exclude>
<exclude>org.google.code.flindbugs:jar305</exclude>
<exclude>org.slf4j:*</exclude>
<excluder>org.apache.logging.log4j:*</excluder>
</excludes>
</artifactSet>
<filters>
<filter>
<artifact>*:*</artifact>
<excludes>
<exclude>META-INF/*.SF</exclude>
<exclude>META-INF/*.DSA</exclude>
<exclude>META-INF/*.RSA</exclude>
</excludes>
</filter>
</filters>
<transformers>
<transformer implementation="org.apache.maven.plugins.shade.resource.ManifestResourceTransformer">
<mainClass>org.xsy.sevenhee.flink.TestStreamJob</mainClass>
</transformer>
</transformers>
</configuration>
</execution>
</executions>
</plugin>
</plugins>
<!--插件统一管理-->
<pluginManagement>
<plugins>
<!--maven打包插件-->
<plugin>
<groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-maven-plugin</artifactId>
<version>${spring.boot.version}</version>
<configuration>
<fork>true</fork>
<finalName>${project.build.finalName}</finalName>
</configuration>
<executions>
<execution>
<goals>
<goal>repackage</goal>
</goals>
</execution>
</executions>
</plugin>
<!--编译打包插件-->
<plugin>
<artifactId>maven-compiler-plugin</artifactId>
<version>${maven.plugin.version}</version>
<configuration>
<source>${java.version}</source>
<target>${java.version}</target>
<encoding>UTF-8</encoding>
<compilerArgs>
<arg>-parameters</arg>
</compilerArgs>
</configuration>
</plugin>
</plugins>
</pluginManagement>
</build>
<!--配置Maven项目中需要使用的远程仓库-->
<repositories>
<repository>
<id>aliyun-repos</id>
<url>https://maven.aliyun.com/nexus/content/groups/public/</url>
<snapshots>
<enabled>false</enabled>
</snapshots>
</repository>
</repositories>
<!--用来配置maven插件的远程仓库-->
<pluginRepositories>
<pluginRepository>
<id>aliyun-plugin</id>
<url>https://maven.aliyun.com/nexus/content/groups/public/</url>
<snapshots>
<enabled>false</enabled>
</snapshots>
</pluginRepository>
</pluginRepositories>
</project>
4.增加log4j2.properties配置
tips：resource目录下增加该配置，主要用于日志打印
rootLogger.level=INFO
rootLogger.appenderRef.console.ref=ConsoleAppender
appender.console.name=ConsoleAppender
appender.console.type=CONSOLE
appender.console.layout.type=PatternLayout
appender.console.layout.pattern=%d{HH:mm:ss,SSS} %-5p %-60c %x - %m%n
log.file=D:\\tmp
5.创建主启动类
tips：编写了一个简单的有界数据流处理demo程序
- step1：创建flink程序运行所需环境
- step2：创建数据集
- step3：把有限数据集转换为数据源
- step4：简单通过flatmap处理数据
- step5：输出最终结果
- step6：启动任务
package com.aurora;
import org.apache.flink.api.common.functions.FlatMapFunction;
import org.apache.flink.streaming.api.datastream.DataStreamSource;
import org.apache.flink.streaming.api.datastream.SingleOutputStreamOperator;
import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
import org.apache.flink.streaming.api.functions.sink.SinkFunction;
import org.apache.flink.util.Collector;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
import java.util.ArrayList;
import java.util.Random;
import java.util.UUID;
/**
* @author 浅夏的猫
* @description 主启动类
* @date 22:46 2024/1/13
*/
public class Application {
private static final Logger logger = LoggerFactory.getLogger(Application.class);
public static void main(String[] args) throws Exception {
//1.创建flink程序运行所需环境
StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
//2.创建数据集
ArrayList<String> list = new ArrayList<>();
list.add("001");
list.add("002");
list.add("003");
//3.把有限数据集转换为数据源
DataStreamSource<String> dataStreamSource = env.fromCollection(list).setParallelism(1);
//4.简单通过flatmap处理数据，
SingleOutputStreamOperator<String> flatMap = dataStreamSource.flatMap(new FlatMapFunction<String, String>() {
@Override
public void flatMap(String record, Collector<String> collector) throws Exception {
//数据追加随机数
String uuidRecord=record+ UUID.randomUUID().toString();
//当前环节处理完需要传递数据给下个环节
collector.collect(uuidRecord);
}
});
//5.输出最终结果
flatMap.addSink(new SinkFunction<String>() {
@Override
public void invoke(String value) throws Exception {
logger.info("当前正在处理的数据:{}",value);
}
}).setParallelism(1);
//6.启动任务
env.execute();
}
}
6.构建打jar包
7.flinkUI页面部署
1.点击add new上传对应的应用包
2.主类填写com.aurora.Application
3.检查任务running状态，大概几秒钟跑完
文章来源：https://www.toymoban.com/news/detail-820044.html
文章来源地址https://www.toymoban.com/news/detail-820044.html
到了这里，关于【极数系列】Flink项目入门搭建（03）的文章就介绍完了。如果您还想了解更多内容，请在右上角搜索TOY模板网以前的文章或继续浏览下面的相关文章，希望大家以后多多支持TOY模板网！
