search
HomeJavajavaTutorialHow to use Java to develop a stream processing and batch processing application based on Apache Flink

如何使用Java开发一个基于Apache Flink的流处理和批处理应用

How to use Java to develop a stream processing and batch processing application based on Apache Flink

Introduction:
Apache Flink is a powerful, open source stream processing and batch processing application Batch processing framework with high throughput, high reliability and low latency. This article will introduce how to use Java to develop a stream processing and batch processing application based on Apache Flink, and give detailed code examples.

1. Environment preparation

  1. Install JDK: Make sure your computer has the Java Development Kit (JDK) installed. You can download JDK from Oracle's official website and install it according to the official guide.
  2. Download Apache Flink: You can download the latest version of Flink from the official Apache Flink website. Unzip the downloaded zip file to a suitable location.
  3. Install IDE: You can choose an IDE that suits you for development. It is recommended to use Eclipse or IntelliJ IDEA.

2. Project creation

  1. Create a new Java project in the IDE and name it "flink-demo".
  2. Copy the downloaded and decompressed Apache Flink file to the root directory of the project.

3. Introduce dependencies

  1. Add the following dependencies in the project’s build.gradle file:

    dependencies {
     compileOnly project(":flink-dist")
     compile group: 'org.apache.flink', name: 'flink-core', version: '1.12.2'
     compile group: 'org.apache.flink', name: 'flink-streaming-java', version: '1.12.2'
     compile group: 'org.apache.flink', name: 'flink-clients', version: '1.12.2'
    }
  2. In the IDE , right-click the project root directory and select "Refresh Gradle Project" to update the project's dependencies.

4. Implement Flink stream processing application

  1. Create a new package in the src/main/java directory and name it "com.flinkdemo.stream".
  2. Create a Java class named "StreamProcessingJob" and implement the stream processing logic in it.

    package com.flinkdemo.stream;
    
    import org.apache.flink.streaming.api.datastream.DataStream;
    import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
    
    public class StreamProcessingJob {
    
     public static void main(String[] args) throws Exception {
         // 创建一个执行环境
         final StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
    
         // 从socket接收数据流
         DataStream<String> text = env.socketTextStream("localhost", 9999);
    
         // 打印接收到的数据
         text.print();
    
         // 启动执行环境
         env.execute("Stream Processing Job");
     }
    }
  3. In the IDE, right-click the StreamProcessingJob class and select "Run As" -> "Java Application" to start the application.

5. Implement Flink batch processing application

  1. Create a new package in the src/main/java directory and name it "com.flinkdemo.batch".
  2. Create a Java class named "BatchProcessingJob" and implement the batch processing logic in it.

    package com.flinkdemo.batch;
    
    import org.apache.flink.api.java.ExecutionEnvironment;
    import org.apache.flink.api.java.DataSet;
    import org.apache.flink.api.java.tuple.Tuple2;
    
    public class BatchProcessingJob {
    
     public static void main(String[] args) throws Exception {
         // 创建一个执行环境
         final ExecutionEnvironment env = ExecutionEnvironment.getExecutionEnvironment();
    
         // 从集合创建DataSet
         DataSet<Tuple2<String, Integer>> dataSet = env.fromElements(
                 new Tuple2<>("A", 1),
                 new Tuple2<>("A", 2),
                 new Tuple2<>("B", 3),
                 new Tuple2<>("B", 4),
                 new Tuple2<>("C", 5)
         );
    
         // 根据key进行分组,并计算每组的元素个数
         DataSet<Tuple2<String, Integer>> result = dataSet
                 .groupBy(0)
                 .sum(1);
    
         // 打印结果
         result.print();
    
         // 执行任务
         env.execute("Batch Processing Job");
     }
    }
  3. In the IDE, right-click the BatchProcessingJob class and select "Run As" -> "Java Application" to start the application.

Conclusion:
Through the introduction of this article, you have learned how to use Java to develop a stream processing and batch processing application based on Apache Flink. You can add more logic to your streaming and batch processing applications according to your needs, and explore more of Flink's features and functionality. I wish you good results in your Flink development journey!

The above is the detailed content of How to use Java to develop a stream processing and batch processing application based on Apache Flink. For more information, please follow other related articles on the PHP Chinese website!

Statement
The content of this article is voluntarily contributed by netizens, and the copyright belongs to the original author. This site does not assume corresponding legal responsibility. If you find any content suspected of plagiarism or infringement, please contact admin@php.cn
How do I use Maven or Gradle for advanced Java project management, build automation, and dependency resolution?How do I use Maven or Gradle for advanced Java project management, build automation, and dependency resolution?Mar 17, 2025 pm 05:46 PM

The article discusses using Maven and Gradle for Java project management, build automation, and dependency resolution, comparing their approaches and optimization strategies.

How do I create and use custom Java libraries (JAR files) with proper versioning and dependency management?How do I create and use custom Java libraries (JAR files) with proper versioning and dependency management?Mar 17, 2025 pm 05:45 PM

The article discusses creating and using custom Java libraries (JAR files) with proper versioning and dependency management, using tools like Maven and Gradle.

How do I implement multi-level caching in Java applications using libraries like Caffeine or Guava Cache?How do I implement multi-level caching in Java applications using libraries like Caffeine or Guava Cache?Mar 17, 2025 pm 05:44 PM

The article discusses implementing multi-level caching in Java using Caffeine and Guava Cache to enhance application performance. It covers setup, integration, and performance benefits, along with configuration and eviction policy management best pra

How can I use JPA (Java Persistence API) for object-relational mapping with advanced features like caching and lazy loading?How can I use JPA (Java Persistence API) for object-relational mapping with advanced features like caching and lazy loading?Mar 17, 2025 pm 05:43 PM

The article discusses using JPA for object-relational mapping with advanced features like caching and lazy loading. It covers setup, entity mapping, and best practices for optimizing performance while highlighting potential pitfalls.[159 characters]

How does Java's classloading mechanism work, including different classloaders and their delegation models?How does Java's classloading mechanism work, including different classloaders and their delegation models?Mar 17, 2025 pm 05:35 PM

Java's classloading involves loading, linking, and initializing classes using a hierarchical system with Bootstrap, Extension, and Application classloaders. The parent delegation model ensures core classes are loaded first, affecting custom class loa

See all articles

Hot AI Tools

Undresser.AI Undress

Undresser.AI Undress

AI-powered app for creating realistic nude photos

AI Clothes Remover

AI Clothes Remover

Online AI tool for removing clothes from photos.

Undress AI Tool

Undress AI Tool

Undress images for free

Clothoff.io

Clothoff.io

AI clothes remover

AI Hentai Generator

AI Hentai Generator

Generate AI Hentai for free.

Hot Article

R.E.P.O. Energy Crystals Explained and What They Do (Yellow Crystal)
3 weeks agoBy尊渡假赌尊渡假赌尊渡假赌
R.E.P.O. Best Graphic Settings
3 weeks agoBy尊渡假赌尊渡假赌尊渡假赌
R.E.P.O. How to Fix Audio if You Can't Hear Anyone
4 weeks agoBy尊渡假赌尊渡假赌尊渡假赌
WWE 2K25: How To Unlock Everything In MyRise
1 months agoBy尊渡假赌尊渡假赌尊渡假赌

Hot Tools

MantisBT

MantisBT

Mantis is an easy-to-deploy web-based defect tracking tool designed to aid in product defect tracking. It requires PHP, MySQL and a web server. Check out our demo and hosting services.

Atom editor mac version download

Atom editor mac version download

The most popular open source editor

SublimeText3 Linux new version

SublimeText3 Linux new version

SublimeText3 Linux latest version

DVWA

DVWA

Damn Vulnerable Web App (DVWA) is a PHP/MySQL web application that is very vulnerable. Its main goals are to be an aid for security professionals to test their skills and tools in a legal environment, to help web developers better understand the process of securing web applications, and to help teachers/students teach/learn in a classroom environment Web application security. The goal of DVWA is to practice some of the most common web vulnerabilities through a simple and straightforward interface, with varying degrees of difficulty. Please note that this software

mPDF

mPDF

mPDF is a PHP library that can generate PDF files from UTF-8 encoded HTML. The original author, Ian Back, wrote mPDF to output PDF files "on the fly" from his website and handle different languages. It is slower than original scripts like HTML2FPDF and produces larger files when using Unicode fonts, but supports CSS styles etc. and has a lot of enhancements. Supports almost all languages, including RTL (Arabic and Hebrew) and CJK (Chinese, Japanese and Korean). Supports nested block-level elements (such as P, DIV),