Apache Flink：使用Apache Kafka作为Sink的简单demo(数据结果存放地方)

Posted 2021-07-24 你是小KS

1. 声明

当前内容主要为测试和使用Flink，将数据读取处理后放入到kafka的topic中

主要内容：

1. 使用Flink读取文本内容
2. 过滤读取的内容
3. 将读取的内容放入kafka中

2.基本demo

1.pom依赖

	<properties>
		<project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>
		<flink.version>1.13.0</flink.version>
		<target.java.version>1.8</target.java.version>
		<scala.binary.version>2.11</scala.binary.version>
		<maven.compiler.source>${target.java.version}</maven.compiler.source>
		<maven.compiler.target>${target.java.version}</maven.compiler.target>
		<log4j.version>2.12.1</log4j.version>
	</properties>

	<dependencies>
		<dependency>
			<groupId>org.apache.flink</groupId>
			<artifactId>flink-walkthrough-common_${scala.binary.version}</artifactId>
			<version>${flink.version}</version>
		</dependency>

		<!-- This dependency is provided, because it should not be packaged into 
			the JAR file. -->
		<dependency>
			<groupId>org.apache.flink</groupId>
			<artifactId>flink-streaming-java_${scala.binary.version}</artifactId>
			<version>${flink.version}</version>
			<!-- <scope>provided</scope> -->
		</dependency>
		<dependency>
			<groupId>org.apache.flink</groupId>
			<artifactId>flink-clients_${scala.binary.version}</artifactId>
			<version>${flink.version}</version>
			<!-- <scope>provided</scope> -->
		</dependency>
		<!-- 直接导入需要的flink到kafka的连接器 -->
		<dependency>
			<groupId>org.apache.flink</groupId>
			<artifactId>flink-connector-kafka_2.12</artifactId>
			<version>1.13.0</version>
		</dependency>
		<dependency>
			<groupId>org.apache.logging.log4j</groupId>
			<artifactId>log4j-slf4j-impl</artifactId>
			<version>${log4j.version}</version>
			<scope>runtime</scope>
		</dependency>
		<dependency>
			<groupId>org.apache.logging.log4j</groupId>
			<artifactId>log4j-api</artifactId>
			<version>${log4j.version}</version>
			<scope>runtime</scope>
		</dependency>
		<dependency>
			<groupId>org.apache.logging.log4j</groupId>
			<artifactId>log4j-core</artifactId>
			<version>${log4j.version}</version>
			<scope>runtime</scope>
		</dependency>
	</dependencies>

2.开启一个命令行消费者

3.开始编写demo

import java.util.Properties;
import org.apache.flink.api.common.JobExecutionResult;
import org.apache.flink.api.common.functions.FilterFunction;
import org.apache.flink.api.common.serialization.SimpleStringSchema;
import org.apache.flink.streaming.api.datastream.DataStream;
import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
import org.apache.flink.streaming.connectors.kafka.FlinkKafkaProducer;

/**
 * 
 * @author hy
 * @createTime 2021-05-23 10:38:40
 * @description 当前内容主要将Apache Flink中处理的内容放入当前的Apache Kafka中(将Kafka作为数据输出的地点)
 *
 */
public class LocalRunningToKafkaSaveTest {
	public static void main(String[] args) {
		// 采用本地模式
		StreamExecutionEnvironment env = StreamExecutionEnvironment.createLocalEnvironment();

		// 设定数据来源为集合数据
		String topic = "test-events"; // 设置监听的主题
		Properties props = new Properties();
		props.setProperty("bootstrap.servers", "192.168.1.101:9092");
		props.setProperty("group.id", "test");
		String filePath = "D:\\\\eclipse-workspace\\\\Apache-Flink-Start\\\\resources\\\\abc.txt";
		DataStream<String> txtStream = env.readTextFile(filePath);

		// 这里可以进行处理操作(但是结果需要赋值)
		txtStream = txtStream.filter(new FilterFunction<String>() {
			@Override
			public boolean filter(String value) throws Exception {
				// TODO Auto-generated method stub
				// 返回数据中不带有19的数据
				if(!value.contains("19")) {
					return true;
				}
				return false;
			}
		});
		
		System.out.println("处理后的数据=====>");
		txtStream.print();
		System.out.println("<=====处理后的数据");
		
		// 将读取的文本类型的数据注入到kafka的这个topic中
		FlinkKafkaProducer<String> producer=new FlinkKafkaProducer<String>(topic, new SimpleStringSchema(),props);
		txtStream.addSink(producer);
		System.out.println("将当前的数据处理后放入kafka的test-events这个topic成功！");
		try {
			// 最后开始执行
			JobExecutionResult result = env.execute("Fraud Detection");
			if (result.isJobExecutionResult()) {
				System.out.println("执行完毕......");
			}
			System.out.println();
		} catch (Exception e) {
			// TODO Auto-generated catch block
			e.printStackTrace();
		}
	}

}

小心这里的filter,以及使用的Sink为FlinkKafkaProducer(一个消息生产者)

3. 测试结果

命令行消费者结果：

4. 总结

1.由于本人没有找到一个清空topic的消息的，只要是订阅了的，以前发布的消息都会发送，并且接受到，只有执行删除topic的指令，然后在创建才有用

./bin/kafka-topics.sh --delete --topic test-events --bootstrap-server 192.168.1.101:9092