基于SpringBoot 使用 Flink 收发Kafka消息 - IT评测·应用市场-qidao123.com

---
version: '2'
services:
zookeeper:
image: confluentinc/cp-zookeeper:7.3.0
hostname: zookeeper
container_name: zookeeper
ports:
- "2181:2181"
environment:
ZOOKEEPER_CLIENT_PORT: 2181
ZOOKEEPER_TICK_TIME: 2000
broker:
image: confluentinc/cp-kafka:7.3.0
hostname: broker
container_name: broker
depends_on:
- zookeeper
ports:
- "29092:29092"
environment:
KAFKA_BROKER_ID: 1
KAFKA_ZOOKEEPER_CONNECT: 'zookeeper:2181'
KAFKA_LISTENER_SECURITY_PROTOCOL_MAP: PLAINTEXT:PLAINTEXT,PLAINTEXT_HOST:PLAINTEXT
KAFKA_ADVERTISED_LISTENERS: PLAINTEXT://broker:9092,PLAINTEXT_HOST://localhost:29092
KAFKA_OFFSETS_TOPIC_REPLICATION_FACTOR: 1
KAFKA_GROUP_INITIAL_REBALANCE_DELAY_MS: 0

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<properties>
<jdk.version>1.8</jdk.version>
<maven.compiler.source>8</maven.compiler.source>
<maven.compiler.target>8</maven.compiler.target>
<project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>
<spring-boot.version>2.7.7</spring-boot.version>
<flink.version>1.16.0</flink.version>
</properties>
<dependencyManagement>
<dependencies>
<dependency>
<groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-dependencies</artifactId>
<version>${spring-boot.version}</version>
<type>pom</type>
<scope>import</scope>
</dependency>
</dependencies>
</dependencyManagement>
<dependencies>
<dependency>
<groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-starter</artifactId>
</dependency>
<dependency>
<groupId>org.projectlombok</groupId>
<artifactId>lombok</artifactId>
<optional>true</optional>
</dependency>
<dependency>
<groupId>org.apache.flink</groupId>
<artifactId>flink-java</artifactId>
<version>${flink.version}</version>
<scope>provided</scope>
</dependency>
<dependency>
<groupId>org.apache.flink</groupId>
<artifactId>flink-clients</artifactId>
<version>${flink.version}</version>
<scope>provided</scope>
</dependency>
<dependency>
<groupId>org.apache.flink</groupId>
<artifactId>flink-streaming-java</artifactId>
<version>${flink.version}</version>
<scope>provided</scope>
</dependency>
<dependency>
<groupId>org.apache.flink</groupId>
<artifactId>flink-connector-kafka</artifactId>
<version>${flink.version}</version>
<scope>provided</scope>
</dependency>
</dependencies>

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@Component
@Slf4j
public class KafkaRunner implements ApplicationRunner
{
@Override
public void run(ApplicationArguments args) throws Exception {
try{
/****************************************************************************
* Setup Flink environment.
****************************************************************************/
// Set up the streaming execution environment
final StreamExecutionEnvironment streamEnv
= StreamExecutionEnvironment.getExecutionEnvironment();
/****************************************************************************
* Read Kafka Topic Stream into a DataStream.
****************************************************************************/
//Set connection properties to Kafka Cluster
Properties properties = new Properties();
properties.setProperty("bootstrap.servers", "localhost:29092");
properties.setProperty("group.id", "flink.learn.realtime");
//Setup a Kafka Consumer on Flnk
FlinkKafkaConsumer<String> kafkaConsumer =
new FlinkKafkaConsumer<>
("flink.kafka.streaming.source", //topic
new SimpleStringSchema(), //Schema for data
properties); //connection properties
//Setup to receive only new messages
kafkaConsumer.setStartFromLatest();
//Create the data stream
DataStream<String> auditTrailStr = streamEnv
.addSource(kafkaConsumer);
//Convert each record to an Object
DataStream<Tuple2<String, Integer>> userCounts
= auditTrailStr
.map(new MapFunction<String,Tuple2<String,Integer>>() {
@Override
public Tuple2<String,Integer> map(String auditStr) {
System.out.println("--- Received Record : " + auditStr);
AuditTrail at = new AuditTrail(auditStr);
return new Tuple2<String,Integer>(at.getUser(),at.getDuration());
}
})
.keyBy(0) //By user name
.reduce((x,y) -> new Tuple2<String,Integer>( x.f0, x.f1 + y.f1));
//Print User and Durations.
userCounts.print();
/****************************************************************************
* Setup data source and execute the Flink pipeline
****************************************************************************/
//Start the Kafka Stream generator on a separate thread
System.out.println("Starting Kafka Data Generator...");
Thread kafkaThread = new Thread(new KafkaStreamDataGenerator());
kafkaThread.start();
// execute the streaming pipeline
streamEnv.execute("Flink Windowing Example");
}
catch(Exception e) {
e.printStackTrace();
}
}
}

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Thread kafkaThread = new Thread(new KafkaStreamDataGenerator());
kafkaThread.start();

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