Java版Flink使用指南——自定义无界流生成器

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

自定义无界流

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

public abstract class RichSourceFunction<OUT> extends AbstractRichFunctionimplements SourceFunction<OUT> {private static final long 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。

package org.example.generator;import org.apache.flink.streaming.api.functions.source.RichSourceFunction;public class UnBoundedStreamGenerator extends RichSourceFunction<Long> {private volatile boolean isRunning = true;@Overridepublic void run(SourceContext<Long> ctx) throws Exception {long count = 0L;while (isRunning) {Thread.sleep(1000); // Simulate delayctx.collect(count++); // Emit data}}@Overridepublic void cancel() {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。

/** 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* with the License.  You may obtain a copy of the License at**     http://www.apache.org/licenses/LICENSE-2.0** Unless required by applicable law or agreed to in writing, software* distributed under the License is distributed on an "AS IS" BASIS,* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.* See the License for the specific language governing permissions and* limitations under the License.*/package org.example;import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
import org.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').*/
public class DataStreamJob {public static void main(String[] args) throws Exception {// Sets up the execution environment, which is the main entry point// to building Flink applications.final StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();env.addSource(new UnBoundedStreamGenerator()).name("Custom Stream Source").setParallelism(1) .print(); // For demonstration, print the stream to stdout// Execute program, beginning computation.env.execute("Flink Java API Skeleton");}
}

打包、提交、运行

使用下面命令查看日志输出

tail -f log/*

然后我们在后台点击Cancel Job

可以看到输出

工程代码

https://github.com/f304646673/FlinkDemo