【极数系列】Flink配置参数如何获取？（06）

gitee码云地址

直接下载解压可用 https://gitee.com/shawsongyue/aurora.git
模块：aurora_flink
主类：GetParamsStreamingJob

简介概述

​ 1.几乎所有的批和流的 Flink 应用程序，都依赖于外部配置参数。这些配置参数可以用于指定输入和输出源（如路径或地址）、系统参数（并行度，运行时配置）和特定的应用程序参数（通常使用在用户自定义函数）。

​ 2.为解决以上问题，Flink 提供一个名为 Parametertool 的简单公共类，其中包含了一些基本的工具。请注意，这里说的 Parametertool 并不是必须使用的。Commons CLI 和 argparse4j 等其他框架也可以非常好地兼容 Flink。

​ 3.**ParameterTool**定义了一组静态方法，用于读取配置信息。该工具类内部使用了 Map` 类型，这样使得它可以很容易地与你的配置集成在一起。

01 配置值来自.properties文件

1.通过路径读取

//定义文件路径
String propertiesFilePath = "E:\\project\\aurora_dev\\aurora_flink\\src\\main\\resources\\application.properties";

//方式一:直接使用内置工具类
ParameterTool parameter_01 = ParameterTool.fromPropertiesFile(propertiesFilePath);
String jobName_01 = parameter_01.get("jobName");
logger.info("方式一:读取配置文件中指定的key值={}",jobName_01);

2.通过文件流读取

//定义文件路径
String propertiesFilePath = "E:\\project\\aurora_dev\\aurora_flink\\src\\main\\resources\\application.properties";

//方式二：使用文件
File propertiesFile = new File(propertiesFilePath);
ParameterTool parameter_02 = ParameterTool.fromPropertiesFile(propertiesFile);
String jobName_02 = parameter_02.get("jobName");
logger.info("方式二:读取配置文件中指定的key值={}",jobName_02);

3.通过IO流读取

//定义文件路径
String propertiesFilePath = "E:\\project\\aurora_dev\\aurora_flink\\src\\main\\resources\\application.properties";

//方式三：使用IO流
InputStream propertiesFileInputStream = new FileInputStream(new File(propertiesFilePath));
ParameterTool parameter_03 = ParameterTool.fromPropertiesFile(propertiesFileInputStream);
String jobName_03 = parameter_03.get("jobName");
logger.info("方式三:读取配置文件中指定的key值={}",jobName_03);

02 配置值来自命令行

tips：在idea的命令行传参，格式：–jobName program_job_aurora

ParameterTool parameter_04 = ParameterTool.fromArgs(args);
String jobName_04 = parameter_04.get("jobName");
logger.info("方式四:命令行传参key值={}",jobName_04);

03 配置来自系统属性

tips：在idea的的jvm系统参数设置，格式：-Dinput=hdfs:///mydata

//方式五：获取jvm参数值
ParameterTool parameter_05 = ParameterTool.fromSystemProperties();
String jobName_05 = parameter_05.get("input");
logger.info("方式五:获取jvm参数key值={}",jobName_05);

04 注册以及使用全局变量

注意：Flink全局变量仅支持在富函数中使用，即Rich开头的类使用

//定义文件路径
String propertiesFilePath = "E:\\project\\aurora_dev\\aurora_flink\\src\\main\\resources\\application.properties";

//直接使用内置工具类获取参数
ParameterTool parameter_01 = ParameterTool.fromPropertiesFile(propertiesFilePath);

//方式六：注册全局参数
        final StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
        env.getConfig().setGlobalJobParameters(parameter_01);
        //在任意富函数中均可以获取,注意！注意！注意！只有富文本函数才可以使用
        //1.创建富函数
        RichFlatMapFunction<String, String> richFlatMap = new RichFlatMapFunction<>() {
            @Override
            public void flatMap(String s, Collector<String> collector) throws Exception {
                //获取运行环境
                ParameterTool parameters = (ParameterTool) getRuntimeContext().getExecutionConfig().getGlobalJobParameters();
                //获取对应的值
                String jobName = parameters.getRequired("jobName");
                logger.info("方式六:获取全局注册参数key值={}",jobName_05);
            }
        };
        //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.执行富文本处理
        dataStreamSource.flatMap(richFlatMap);
        //5.启动程序
        env.execute();

05 Flink获取参数值Demo

1.项目结构

2.pom.xml文件如下

<?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>

3.配置文件

（1）application.properties

jobName=job_aurora
jobMemory=1024
taskName=task_aurora

（2）log4j2.properties

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:\\tmprootLogger.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

4.项目主类

package com.aurora;


import org.apache.flink.api.common.functions.RichFlatMapFunction;
import org.apache.flink.api.java.ExecutionEnvironment;
import org.apache.flink.api.java.utils.ParameterTool;
import org.apache.flink.streaming.api.datastream.DataStreamSource;
import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
import org.apache.flink.util.Collector;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;

import java.io.File;
import java.io.FileInputStream;
import java.io.IOException;
import java.io.InputStream;
import java.util.ArrayList;

/**
 * @description flink获取外部参数作业
 *
 * @author 浅夏的猫
 * @datetime 15:54 2024/1/28
*/
public class GetParamsStreamingJob {

    private static final Logger logger = LoggerFactory.getLogger(GetParamsStreamingJob.class);

    public static void main(String[] args) throws Exception {

        //定义文件路径
        String propertiesFilePath = "E:\\project\\aurora_dev\\aurora_flink\\src\\main\\resources\\application.properties";

        //方式一:直接使用内置工具类
        ParameterTool parameter_01 = ParameterTool.fromPropertiesFile(propertiesFilePath);
        String jobName_01 = parameter_01.get("jobName");
        logger.info("方式一:读取配置文件中指定的key值={}",jobName_01);

        //方式二：使用文件
        File propertiesFile = new File(propertiesFilePath);
        ParameterTool parameter_02 = ParameterTool.fromPropertiesFile(propertiesFile);
        String jobName_02 = parameter_02.get("jobName");
        logger.info("方式二:读取配置文件中指定的key值={}",jobName_02);

        //方式三：使用IO流
        InputStream propertiesFileInputStream = new FileInputStream(new File(propertiesFilePath));
        ParameterTool parameter_03 = ParameterTool.fromPropertiesFile(propertiesFileInputStream);
        String jobName_03 = parameter_03.get("jobName");
        logger.info("方式三:读取配置文件中指定的key值={}",jobName_03);

        //方式四：命令行传参格式：--jobName program_job_aurora
        ParameterTool parameter_04 = ParameterTool.fromArgs(args);
        String jobName_04 = parameter_04.get("jobName");
        logger.info("方式四:命令行传参key值={}",jobName_04);

        //方式五：获取jvm参数值
        ParameterTool parameter_05 = ParameterTool.fromSystemProperties();
        String jobName_05 = parameter_05.get("input");
        logger.info("方式五:获取jvm参数key值={}",jobName_05);

        //方式六：注册全局参数
        final StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
        env.getConfig().setGlobalJobParameters(parameter_01);
        //在任意富函数中均可以获取,注意！注意！注意！只有富文本函数才可以使用
        //1.创建富函数
        RichFlatMapFunction<String, String> richFlatMap = new RichFlatMapFunction<>() {
            @Override
            public void flatMap(String s, Collector<String> collector) throws Exception {
                //获取运行环境
                ParameterTool parameters = (ParameterTool) getRuntimeContext().getExecutionConfig().getGlobalJobParameters();
                //获取对应的值
                String jobName = parameters.getRequired("jobName");
                logger.info("方式六:获取全局注册参数key值={}",jobName_05);
            }
        };
        //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.执行富文本处理
        dataStreamSource.flatMap(richFlatMap);
        //5.启动程序
        env.execute();
    }

}

5.运行查看相关日志

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