快速導覽

先決條件：您必須安裝並執行 Apache Kafka。然後您必須將 Spring for Apache Kafka (spring-kafka) JAR 及其所有相依性放在您的類別路徑中。最簡單的方法是在您的建置工具中宣告相依性。

如果您未使用 Spring Boot，請在您的專案中宣告 spring-kafka jar 作為相依性。

Maven
Gradle

<dependency>
  <groupId>org.springframework.kafka</groupId>
  <artifactId>spring-kafka</artifactId>
  <version>3.2.4</version>
</dependency>

compile 'org.springframework.kafka:spring-kafka:3.2.4'

當使用 Spring Boot 時（且您未使用 start.spring.io 建立您的專案），請省略版本，Boot 將自動引入與您的 Boot 版本相容的正確版本

Maven
Gradle

<dependency>
  <groupId>org.springframework.kafka</groupId>
  <artifactId>spring-kafka</artifactId>
</dependency>

implementation 'org.springframework.kafka:spring-kafka'

但是，最快速的入門方法是使用 start.spring.io（或 Spring Tool Suits 和 Intellij IDEA 中的精靈）並建立一個專案，選擇 'Spring for Apache Kafka' 作為相依性。

相容性

此快速導覽適用於以下版本

Apache Kafka Clients 3.7.x
Spring Framework 6.1.x
最低 Java 版本：17

開始使用

最簡單的入門方法是使用 start.spring.io（或 Spring Tool Suits 和 Intellij IDEA 中的精靈）並建立一個專案，選擇 'Spring for Apache Kafka' 作為相依性。請參閱 Spring Boot 文件，以取得關於其基礎架構 Bean 的意見導向自動組態的更多資訊。

這是一個最小的消費者應用程式。

Spring Boot 消費者應用程式

應用程式

Java
Kotlin

@SpringBootApplication
public class Application {

    public static void main(String[] args) {
        SpringApplication.run(Application.class, args);
    }

    @Bean
    public NewTopic topic() {
        return TopicBuilder.name("topic1")
                .partitions(10)
                .replicas(1)
                .build();
    }

    @KafkaListener(id = "myId", topics = "topic1")
    public void listen(String in) {
        System.out.println(in);
    }

}

@SpringBootApplication
class Application {

    @Bean
    fun topic() = NewTopic("topic1", 10, 1)

    @KafkaListener(id = "myId", topics = ["topic1"])
    fun listen(value: String?) {
        println(value)
    }

}

fun main(args: Array<String>) = runApplication<Application>(*args)

application.properties

spring.kafka.consumer.auto-offset-reset=earliest

NewTopic Bean 會導致主題在 Broker 上建立；如果主題已存在，則不需要它。

Spring Boot 生產者應用程式

應用程式

Java
Kotlin

@SpringBootApplication
public class Application {

    public static void main(String[] args) {
        SpringApplication.run(Application.class, args);
    }

    @Bean
    public NewTopic topic() {
        return TopicBuilder.name("topic1")
                .partitions(10)
                .replicas(1)
                .build();
    }

    @Bean
    public ApplicationRunner runner(KafkaTemplate<String, String> template) {
        return args -> {
            template.send("topic1", "test");
        };
    }

}

@SpringBootApplication
class Application {

    @Bean
    fun topic() = NewTopic("topic1", 10, 1)

    @Bean
    fun runner(template: KafkaTemplate<String?, String?>) =
        ApplicationRunner { template.send("topic1", "test") }

    companion object {
        @JvmStatic
        fun main(args: Array<String>) = runApplication<Application>(*args)
    }

}

使用 Java 組態（無 Spring Boot）

Spring for Apache Kafka 設計為在 Spring 應用程式環境中使用。例如，如果您在 Spring 環境之外自行建立監聽器容器，除非您滿足容器實作的所有 ...Aware 介面，否則並非所有功能都能運作。

以下是一個不使用 Spring Boot 的應用程式範例；它同時具有 Consumer 和 Producer。

不使用 Spring Boot

Java
Kotlin

public class Sender {

    public static void main(String[] args) {
        AnnotationConfigApplicationContext context = new AnnotationConfigApplicationContext(Config.class);
        context.getBean(Sender.class).send("test", 42);
    }

    private final KafkaTemplate<Integer, String> template;

    public Sender(KafkaTemplate<Integer, String> template) {
        this.template = template;
    }

    public void send(String toSend, int key) {
        this.template.send("topic1", key, toSend);
    }

}

public class Listener {

    @KafkaListener(id = "listen1", topics = "topic1")
    public void listen1(String in) {
        System.out.println(in);
    }

}

@Configuration
@EnableKafka
public class Config {

    @Bean
    ConcurrentKafkaListenerContainerFactory<Integer, String>
                        kafkaListenerContainerFactory(ConsumerFactory<Integer, String> consumerFactory) {
        ConcurrentKafkaListenerContainerFactory<Integer, String> factory =
                                new ConcurrentKafkaListenerContainerFactory<>();
        factory.setConsumerFactory(consumerFactory);
        return factory;
    }

    @Bean
    public ConsumerFactory<Integer, String> consumerFactory() {
        return new DefaultKafkaConsumerFactory<>(consumerProps());
    }

    private Map<String, Object> consumerProps() {
        Map<String, Object> props = new HashMap<>();
        props.put(ConsumerConfig.BOOTSTRAP_SERVERS_CONFIG, "localhost:9092");
        props.put(ConsumerConfig.GROUP_ID_CONFIG, "group");
        props.put(ConsumerConfig.KEY_DESERIALIZER_CLASS_CONFIG, IntegerDeserializer.class);
        props.put(ConsumerConfig.VALUE_DESERIALIZER_CLASS_CONFIG, StringDeserializer.class);
        props.put(ConsumerConfig.AUTO_OFFSET_RESET_CONFIG, "earliest");
        // ...
        return props;
    }

    @Bean
    public Sender sender(KafkaTemplate<Integer, String> template) {
        return new Sender(template);
    }

    @Bean
    public Listener listener() {
        return new Listener();
    }

    @Bean
    public ProducerFactory<Integer, String> producerFactory() {
        return new DefaultKafkaProducerFactory<>(senderProps());
    }

    private Map<String, Object> senderProps() {
        Map<String, Object> props = new HashMap<>();
        props.put(ProducerConfig.BOOTSTRAP_SERVERS_CONFIG, "localhost:9092");
        props.put(ProducerConfig.LINGER_MS_CONFIG, 10);
        props.put(ProducerConfig.KEY_SERIALIZER_CLASS_CONFIG, IntegerSerializer.class);
        props.put(ProducerConfig.VALUE_SERIALIZER_CLASS_CONFIG, StringSerializer.class);
        //...
        return props;
    }

    @Bean
    public KafkaTemplate<Integer, String> kafkaTemplate(ProducerFactory<Integer, String> producerFactory) {
        return new KafkaTemplate<>(producerFactory);
    }

}

class Sender(private val template: KafkaTemplate<Int, String>) {

    fun send(toSend: String, key: Int) {
        template.send("topic1", key, toSend)
    }

}

class Listener {

    @KafkaListener(id = "listen1", topics = ["topic1"])
    fun listen1(`in`: String) {
        println(`in`)
    }

}

@Configuration
@EnableKafka
class Config {

    @Bean
    fun kafkaListenerContainerFactory(consumerFactory: ConsumerFactory<Int, String>) =
        ConcurrentKafkaListenerContainerFactory<Int, String>().also { it.consumerFactory = consumerFactory }


    @Bean
    fun consumerFactory() = DefaultKafkaConsumerFactory<Int, String>(consumerProps)

    val consumerProps = mapOf(
        ConsumerConfig.BOOTSTRAP_SERVERS_CONFIG to "localhost:9092",
        ConsumerConfig.GROUP_ID_CONFIG to "group",
        ConsumerConfig.KEY_DESERIALIZER_CLASS_CONFIG to IntegerDeserializer::class.java,
        ConsumerConfig.VALUE_DESERIALIZER_CLASS_CONFIG to StringDeserializer::class.java,
        ConsumerConfig.AUTO_OFFSET_RESET_CONFIG to "earliest"
    )

    @Bean
    fun sender(template: KafkaTemplate<Int, String>) = Sender(template)

    @Bean
    fun listener() = Listener()

    @Bean
    fun producerFactory() = DefaultKafkaProducerFactory<Int, String>(senderProps)

    val senderProps = mapOf(
        ProducerConfig.BOOTSTRAP_SERVERS_CONFIG to "localhost:9092",
        ProducerConfig.LINGER_MS_CONFIG to 10,
        ProducerConfig.KEY_SERIALIZER_CLASS_CONFIG to IntegerSerializer::class.java,
        ProducerConfig.VALUE_SERIALIZER_CLASS_CONFIG to StringSerializer::class.java
    )

    @Bean
    fun kafkaTemplate(producerFactory: ProducerFactory<Int, String>) = KafkaTemplate(producerFactory)

}

如您所見，當不使用 Spring Boot 時，您必須定義幾個基礎架構 Bean。