在学习flink 的过程中，伊始的flink 版本是1.17.2 报题目的错误 ，百思不得其解，尝试更替了1.19.1 然后就成功了 ，期间未做任何的修改 。

ui 默认地址 ： http://localhost:8081 

pom 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>org.example</groupId>
    <artifactId>TT</artifactId>
    <version>1.0-SNAPSHOT</version>

    <properties>
        <maven.compiler.source>8</maven.compiler.source>
        <maven.compiler.target>8</maven.compiler.target>
        <project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>
    </properties>
    <dependencies>

        <dependency>
            <groupId>org.apache.flink</groupId>
            <artifactId>flink-streaming-java</artifactId>
            <version>1.19.1</version>
        </dependency>
        <dependency>
            <groupId>org.apache.flink</groupId>
            <artifactId>flink-clients</artifactId>
            <version>1.19.1</version>
        </dependency>

        <dependency>
            <groupId>org.apache.flink</groupId>
            <artifactId>flink-connector-datagen</artifactId>
            <version>1.19.1</version>
        </dependency>

        <dependency>
            <groupId>org.apache.flink</groupId>
            <artifactId>flink-table-api-java-bridge</artifactId>
            <version>1.19.1</version>
        </dependency>

        <!--在本地的集成开发环境里运行Table API和SQL的支持-->
        <dependency>
            <groupId>org.apache.flink</groupId>
            <artifactId>flink-table-planner-loader</artifactId>
            <version>1.19.1</version>
        </dependency>

        <dependency>
            <groupId>org.apache.flink</groupId>
            <artifactId>flink-table-runtime</artifactId>
            <version>1.19.1</version>
        </dependency>
        <dependency>
            <groupId>org.apache.flink</groupId>
            <artifactId>flink-runtime-web</artifactId>
            <version>1.19.1</version>

        </dependency>

        <dependency>
            <groupId>org.slf4j</groupId>
            <artifactId>slf4j-log4j12</artifactId>
            <version>1.7.25</version>
        </dependency>


        <dependency>
            <groupId>org.apache.flink</groupId>
            <artifactId>flink-java</artifactId>
            <version>1.19.1</version>
        </dependency>

    </dependencies>



</project>

Java 类 ，flink 环境的初始化有很多种，这个只是本地环境的一种 ：

package com.org.flinkBase;

import org.apache.flink.api.common.functions.MapFunction;
import org.apache.flink.configuration.Configuration;
import org.apache.flink.streaming.api.datastream.DataStream;
import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
import org.apache.flink.streaming.api.functions.ProcessFunction;
import org.apache.flink.util.Collector;

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

        Configuration conf = new Configuration();
        //conf.setString(RestOptions.BIND_PORT,"8081-8089");
        StreamExecutionEnvironment env = StreamExecutionEnvironment.createLocalEnvironmentWithWebUI(conf);

        // 产生一个初始数据流，这里我们使用一个简单的集合作为数据源
        DataStream<String> initialStream = env.fromElements("Hello", "Flink", "World","Hello", "Flink", "World");

        // 定义一个 Map 算子，将流中的每个字符串转换为大写
        DataStream<String> transformedStream = initialStream.map(new MapFunction<String, String>() {
            @Override
            public String map(String value) throws Exception {
                return value.toUpperCase();
            }
        });

        // 使用 ProcessFunction 增加处理时间
        transformedStream
                .keyBy((String value) -> value) // 这里使用每个字符串本身作为 key，只是为了演示
                .process(new ProcessFunction<String, String>() {
                    @Override
                    public void processElement(String value, Context ctx, Collector<String> out) throws Exception {
                        // 模拟处理时间，例如，延迟5秒
                        Thread.sleep(85000);
                        out.collect(value);
                    }
                })
                .print(); // 输出转换后的数据流


        env.execute("Java Flink Job with Map Operator");


    }

}

Ui  结果：

感悟：

柳暗花明又一村，死磕到底的勇气，不断试错，新时代的爱迪生，努力寻找答案