IDEA环境下的开发

环境准备

  1. 安装jdk

https://www.oracle.com/java/technologies/downloads/#java17

根据本机环境下载软件包进行安装即可：

image-20220123193406254

安装完成后，执行java -version确认成功：

❯ java -version
java version "17.0.2" 2022-01-18 LTS
Java(TM) SE Runtime Environment (build 17.0.2+8-LTS-86)
Java HotSpot(TM) 64-Bit Server VM (build 17.0.2+8-LTS-86, mixed mode, sharing)

  1. 安装IDEA

    社区版本下载地址： https://www.jetbrains.com/idea/download/#section=mac

    image-20220123193620792

创建java项目

安装好IDEA后，打开并创建新项目。选择maven项目（因为后面要用到kafka-client依赖）：

image-20201206210855737

根据个人情况配置项目：

image-20201206211121584

配置依赖包

创建完成后，在根目录找到pom.xml文件：

image-20220123194035001

我们需要要在这个xml中添加依赖，在 https://mvnrepository.com/artifact/org.apache.kafka 搜索kafka的maven的依赖：

image-20220123194220595

打开后，根据Kafka的版本选择依赖：

image-20220123194331605

将上面这段复制下来，同slf4j一起添加到pom.xml(slf4j是kafka-client依赖的包)。pom.xml内容最终如下：

<?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>kafka-learn</artifactId>
    <version>1.0</version>
    <properties>
        <maven.compiler.source>17</maven.compiler.source>
        <maven.compiler.target>17</maven.compiler.target>
    </properties>

<!--    在这里添加依赖-->
    <dependencies>
        <!-- https://mvnrepository.com/artifact/org.apache.kafka/kafka-clients -->
        <dependency>
            <groupId>org.apache.kafka</groupId>
            <artifactId>kafka-clients</artifactId>
            <version>2.7.1</version>
        </dependency>
        <!-- https://mvnrepository.com/artifact/org.slf4j/slf4j-simple -->
        <dependency>
            <groupId>org.slf4j</groupId>
            <artifactId>slf4j-simple</artifactId>
            <version>1.7.25</version>
        </dependency>
    </dependencies>
</project>

打开maven面板，点击刷新按钮引入依赖：

image-20220123194702418

测试java代码

在src目录下新建包名(例如com.kpingfan.kafka)和java文件(ProducerDemo.java):

image-20220123195010107

ProducerDemo.java内容：

package com.kpingfan.kafka;

import org.apache.kafka.clients.producer.KafkaProducer;
import org.apache.kafka.clients.producer.ProducerConfig;
import org.apache.kafka.clients.producer.ProducerRecord;
import org.apache.kafka.common.serialization.StringSerializer;

import java.util.Properties;

public class ProducerDemo {
    public static void main(String[] args) {
        String bootstrapServers = "b-1.mskdemo.mxqzz7.c4.kafka.ap-southeast-1.amazonaws.com:9092,b-5.mskdemo.mxqzz7.c4.kafka.ap-southeast-1.amazonaws.com:9092,b-6.mskdemo.mxqzz7.c4.kafka.ap-southeast-1.amazonaws.com:9092";   // 根据Kafka broker地址做替换

        // create Producer properties
        // 详细参数见：https://kafka.apache.org/documentation/#producerconfigs
        Properties properties = new Properties();
        properties.setProperty(ProducerConfig.BOOTSTRAP_SERVERS_CONFIG, bootstrapServers);
        properties.setProperty(ProducerConfig.KEY_SERIALIZER_CLASS_CONFIG, StringSerializer.class.getName());
        properties.setProperty(ProducerConfig.VALUE_SERIALIZER_CLASS_CONFIG, StringSerializer.class.getName());

        // create the producer
        KafkaProducer<String, String> producer = new KafkaProducer<String, String>(properties);

        // create a producer record
        ProducerRecord<String, String> record =
                new ProducerRecord<String, String>("first-topic", "hello world");  // 根据topic名称做替换

        // send data - asynchronous
        producer.send(record);
        // flush data
        producer.flush();
        // flush and close producer
        producer.close();
    }
}

运行main函数：

image-20220123195253251

由于本机与Kafka Broker地址不通，所以此消息不会发送成功（可以在本地电脑搭建Kafka并进行测试）。但在控制台能看到相应的提示，这证明代码本身的依赖是满足的

image-20220123195350802