Java版Flink使用指南——自定义无界流生成器

大纲

在《Java版Flink使用指南——从RabbitMQ中队列中接入消息流》一文中，我们让外部组件RabbitMQ充当了无界流的数据源，使得Flink进行了流式处理。在《Java版Flink使用指南——将消息写入到RabbitMQ的队列中》一文中，我们使用了Flink自带的数据生成器，生成了有限数据，从而让Flink以批处理形式运行了该任务。
本文我们将自定义一个无界流生成器，以方便后续测试。

新建工程

我们新建一个名字叫UnboundedStreamGenerator的工程。
Archetype：org.apache.flink:flink-quickstart-java
版本：1.19.1
在这里插入图片描述

自定义无界流

新建src/main/java/org/example/generator/UnBoundedStreamGenerator.java
然后UnBoundedStreamGenerator实现RichSourceFunction接口

publicabstractclassRichSourceFunction<OUT>extendsAbstractRichFunctionimplementsSourceFunction<OUT>{privatestaticfinallong serialVersionUID =1L;}

主要实现SourceFunction接口的run和cancel方法。run方法用来获取获取，cancel方法用于终止任务。

packageorg.example.generator;importorg.apache.flink.streaming.api.functions.source.RichSourceFunction;publicclassUnBoundedStreamGeneratorextendsRichSourceFunction<Long>{privatevolatileboolean isRunning =true;@Overridepublicvoidrun(SourceContext<Long> ctx)throwsException{long count =0L;while(isRunning){Thread.sleep(1000);// Simulate delay
            ctx.collect(count++);// Emit data}}@Overridepublicvoidcancel(){
        isRunning =false;System.out.println("UnBoundedStreamGenerator canceled");}}

在run方法中，我们每隔一秒产生一条数据，且这个数字自增。

使用

我们使用addSource方法，将该无界流生成器添加成数据源。然后将其输出到日志。

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 * Licensed to the Apache Software Foundation (ASF) under one
 * or more contributor license agreements.  See the NOTICE file
 * distributed with this work for additional information
 * regarding copyright ownership.  The ASF licenses this file
 * to you under the Apache License, Version 2.0 (the
 * "License"); you may not use this file except in compliance
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 * See the License for the specific language governing permissions and
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 */packageorg.example;importorg.apache.flink.streaming.api.environment.StreamExecutionEnvironment;importorg.example.generator.UnBoundedStreamGenerator;/**
 * Skeleton for a Flink DataStream Job.
 *
 * <p>For a tutorial how to write a Flink application, check the
 * tutorials and examples on the <a href="https://flink.apache.org">Flink Website</a>.
 *
 * <p>To package your application into a JAR file for execution, run
 * 'mvn clean package' on the command line.
 *
 * <p>If you change the name of the main class (with the public static void main(String[] args))
 * method, change the respective entry in the POM.xml file (simply search for 'mainClass').
 */publicclassDataStreamJob{publicstaticvoidmain(String[] args)throwsException{// Sets up the execution environment, which is the main entry point// to building Flink applications.finalStreamExecutionEnvironment env =StreamExecutionEnvironment.getExecutionEnvironment();
        env.addSource(newUnBoundedStreamGenerator()).name("Custom Stream Source").setParallelism(1).print();// For demonstration, print the stream to stdout// Execute program, beginning computation.
        env.execute("Flink Java API Skeleton");}}