Java版Flink使用指南——自定义无界流生成器

news2024/12/24 10:09:32

大纲

新建工程
- 自定义无界流
使用
打包、提交、运行

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

public abstract class RichSourceFunction<OUT> extends AbstractRichFunction
        implements 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;

    @Override
    public void run(SourceContext<Long> ctx) throws Exception {
        long count = 0L;
        while (isRunning) {
            Thread.sleep(1000); // Simulate delay
            ctx.collect(count++); // Emit data
        }
    }

    @Override
    public 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");
	}
}