This version is still in development and is not considered stable yet. For the latest stable version, please use Spring Boot 3.3.4! |
This version is still in development and is not considered stable yet. For the latest stable version, please use Spring Boot 3.3.4! |
Apache Kafka is supported by providing auto-configuration of the spring-kafka
project.
Kafka configuration is controlled by external configuration properties in spring.kafka.*
.
For example, you might declare the following section in application.properties
:
-
Properties
-
YAML
spring.kafka.bootstrap-servers=localhost:9092
spring.kafka.consumer.group-id=myGroup
spring:
kafka:
bootstrap-servers: "localhost:9092"
consumer:
group-id: "myGroup"
To create a topic on startup, add a bean of type NewTopic .
If the topic already exists, the bean is ignored.
|
See KafkaProperties
for more supported options.
To create a topic on startup, add a bean of type NewTopic .
If the topic already exists, the bean is ignored.
|
Sending a Message
Spring’s KafkaTemplate
is auto-configured, and you can autowire it directly in your own beans, as shown in the following example:
-
Java
-
Kotlin
import org.springframework.kafka.core.KafkaTemplate;
import org.springframework.stereotype.Component;
@Component
public class MyBean {
private final KafkaTemplate<String, String> kafkaTemplate;
public MyBean(KafkaTemplate<String, String> kafkaTemplate) {
this.kafkaTemplate = kafkaTemplate;
}
// ...
public void someMethod() {
this.kafkaTemplate.send("someTopic", "Hello");
}
}
import org.springframework.kafka.core.KafkaTemplate
import org.springframework.stereotype.Component
@Component
class MyBean(private val kafkaTemplate: KafkaTemplate<String, String>) {
// ...
fun someMethod() {
kafkaTemplate.send("someTopic", "Hello")
}
}
If the property spring.kafka.producer.transaction-id-prefix is defined, a KafkaTransactionManager is automatically configured.
Also, if a RecordMessageConverter bean is defined, it is automatically associated to the auto-configured KafkaTemplate .
|
If the property spring.kafka.producer.transaction-id-prefix is defined, a KafkaTransactionManager is automatically configured.
Also, if a RecordMessageConverter bean is defined, it is automatically associated to the auto-configured KafkaTemplate .
|
Receiving a Message
When the Apache Kafka infrastructure is present, any bean can be annotated with @KafkaListener
to create a listener endpoint.
If no KafkaListenerContainerFactory
has been defined, a default one is automatically configured with keys defined in spring.kafka.listener.*
.
The following component creates a listener endpoint on the someTopic
topic:
-
Java
-
Kotlin
import org.springframework.kafka.annotation.KafkaListener;
import org.springframework.stereotype.Component;
@Component
public class MyBean {
@KafkaListener(topics = "someTopic")
public void processMessage(String content) {
// ...
}
}
import org.springframework.kafka.annotation.KafkaListener
import org.springframework.stereotype.Component
@Component
class MyBean {
@KafkaListener(topics = ["someTopic"])
fun processMessage(content: String?) {
// ...
}
}
If a KafkaTransactionManager
bean is defined, it is automatically associated to the container factory.
Similarly, if a RecordFilterStrategy
, CommonErrorHandler
, AfterRollbackProcessor
or ConsumerAwareRebalanceListener
bean is defined, it is automatically associated to the default factory.
Depending on the listener type, a RecordMessageConverter
or BatchMessageConverter
bean is associated to the default factory.
If only a RecordMessageConverter
bean is present for a batch listener, it is wrapped in a BatchMessageConverter
.
A custom ChainedKafkaTransactionManager must be marked @Primary as it usually references the auto-configured KafkaTransactionManager bean.
|
A custom ChainedKafkaTransactionManager must be marked @Primary as it usually references the auto-configured KafkaTransactionManager bean.
|
Kafka Streams
Spring for Apache Kafka provides a factory bean to create a StreamsBuilder
object and manage the lifecycle of its streams.
Spring Boot auto-configures the required KafkaStreamsConfiguration
bean as long as kafka-streams
is on the classpath and Kafka Streams is enabled by the @EnableKafkaStreams
annotation.
Enabling Kafka Streams means that the application id and bootstrap servers must be set.
The former can be configured using spring.kafka.streams.application-id
, defaulting to spring.application.name
if not set.
The latter can be set globally or specifically overridden only for streams.
Several additional properties are available using dedicated properties; other arbitrary Kafka properties can be set using the spring.kafka.streams.properties
namespace.
See also Additional Kafka Properties for more information.
To use the factory bean, wire StreamsBuilder
into your @Bean
as shown in the following example:
-
Java
-
Kotlin
import org.apache.kafka.common.serialization.Serdes;
import org.apache.kafka.streams.KeyValue;
import org.apache.kafka.streams.StreamsBuilder;
import org.apache.kafka.streams.kstream.KStream;
import org.apache.kafka.streams.kstream.Produced;
import org.springframework.context.annotation.Bean;
import org.springframework.context.annotation.Configuration;
import org.springframework.kafka.annotation.EnableKafkaStreams;
import org.springframework.kafka.support.serializer.JsonSerde;
@Configuration(proxyBeanMethods = false)
@EnableKafkaStreams
public class MyKafkaStreamsConfiguration {
@Bean
public KStream<Integer, String> kStream(StreamsBuilder streamsBuilder) {
KStream<Integer, String> stream = streamsBuilder.stream("ks1In");
stream.map(this::uppercaseValue).to("ks1Out", Produced.with(Serdes.Integer(), new JsonSerde<>()));
return stream;
}
private KeyValue<Integer, String> uppercaseValue(Integer key, String value) {
return new KeyValue<>(key, value.toUpperCase());
}
}
import org.apache.kafka.common.serialization.Serdes
import org.apache.kafka.streams.KeyValue
import org.apache.kafka.streams.StreamsBuilder
import org.apache.kafka.streams.kstream.KStream
import org.apache.kafka.streams.kstream.Produced
import org.springframework.context.annotation.Bean
import org.springframework.context.annotation.Configuration
import org.springframework.kafka.annotation.EnableKafkaStreams
import org.springframework.kafka.support.serializer.JsonSerde
@Configuration(proxyBeanMethods = false)
@EnableKafkaStreams
class MyKafkaStreamsConfiguration {
@Bean
fun kStream(streamsBuilder: StreamsBuilder): KStream<Int, String> {
val stream = streamsBuilder.stream<Int, String>("ks1In")
stream.map(this::uppercaseValue).to("ks1Out", Produced.with(Serdes.Integer(), JsonSerde()))
return stream
}
private fun uppercaseValue(key: Int, value: String): KeyValue<Int?, String?> {
return KeyValue(key, value.uppercase())
}
}
By default, the streams managed by the StreamBuilder
object are started automatically.
You can customize this behavior using the spring.kafka.streams.auto-startup
property.
Additional Kafka Properties
The properties supported by auto configuration are shown in the Integration Properties section of the Appendix. Note that, for the most part, these properties (hyphenated or camelCase) map directly to the Apache Kafka dotted properties. See the Apache Kafka documentation for details.
Properties that don’t include a client type (producer
, consumer
, admin
, or streams
) in their name are considered to be common and apply to all clients.
Most of these common properties can be overridden for one or more of the client types, if needed.
Apache Kafka designates properties with an importance of HIGH, MEDIUM, or LOW. Spring Boot auto-configuration supports all HIGH importance properties, some selected MEDIUM and LOW properties, and any properties that do not have a default value.
Only a subset of the properties supported by Kafka are available directly through the KafkaProperties
class.
If you wish to configure the individual client types with additional properties that are not directly supported, use the following properties:
-
Properties
-
YAML
spring.kafka.properties[prop.one]=first
spring.kafka.admin.properties[prop.two]=second
spring.kafka.consumer.properties[prop.three]=third
spring.kafka.producer.properties[prop.four]=fourth
spring.kafka.streams.properties[prop.five]=fifth
spring:
kafka:
properties:
"[prop.one]": "first"
admin:
properties:
"[prop.two]": "second"
consumer:
properties:
"[prop.three]": "third"
producer:
properties:
"[prop.four]": "fourth"
streams:
properties:
"[prop.five]": "fifth"
This sets the common prop.one
Kafka property to first
(applies to producers, consumers, admins, and streams), the prop.two
admin property to second
, the prop.three
consumer property to third
, the prop.four
producer property to fourth
and the prop.five
streams property to fifth
.
You can also configure the Spring Kafka JsonDeserializer
as follows:
-
Properties
-
YAML
spring.kafka.consumer.value-deserializer=org.springframework.kafka.support.serializer.JsonDeserializer
spring.kafka.consumer.properties[spring.json.value.default.type]=com.example.Invoice
spring.kafka.consumer.properties[spring.json.trusted.packages]=com.example.main,com.example.another
spring:
kafka:
consumer:
value-deserializer: "org.springframework.kafka.support.serializer.JsonDeserializer"
properties:
"[spring.json.value.default.type]": "com.example.Invoice"
"[spring.json.trusted.packages]": "com.example.main,com.example.another"
Similarly, you can disable the JsonSerializer
default behavior of sending type information in headers:
-
Properties
-
YAML
spring.kafka.producer.value-serializer=org.springframework.kafka.support.serializer.JsonSerializer
spring.kafka.producer.properties[spring.json.add.type.headers]=false
spring:
kafka:
producer:
value-serializer: "org.springframework.kafka.support.serializer.JsonSerializer"
properties:
"[spring.json.add.type.headers]": false
Properties set in this way override any configuration item that Spring Boot explicitly supports. |
Properties set in this way override any configuration item that Spring Boot explicitly supports. |
Testing with Embedded Kafka
Spring for Apache Kafka provides a convenient way to test projects with an embedded Apache Kafka broker.
To use this feature, annotate a test class with @EmbeddedKafka
from the spring-kafka-test
module.
For more information, please see the Spring for Apache Kafka reference manual.
To make Spring Boot auto-configuration work with the aforementioned embedded Apache Kafka broker, you need to remap a system property for embedded broker addresses (populated by the EmbeddedKafkaBroker
) into the Spring Boot configuration property for Apache Kafka.
There are several ways to do that:
-
Provide a system property to map embedded broker addresses into
spring.kafka.bootstrap-servers
in the test class:
-
Java
-
Kotlin
static {
System.setProperty(EmbeddedKafkaBroker.BROKER_LIST_PROPERTY, "spring.kafka.bootstrap-servers");
}
init {
System.setProperty(EmbeddedKafkaBroker.BROKER_LIST_PROPERTY, "spring.kafka.bootstrap-servers")
}
-
Configure a property name on the
@EmbeddedKafka
annotation:
-
Java
-
Kotlin
import org.springframework.boot.test.context.SpringBootTest;
import org.springframework.kafka.test.context.EmbeddedKafka;
@SpringBootTest
@EmbeddedKafka(topics = "someTopic", bootstrapServersProperty = "spring.kafka.bootstrap-servers")
class MyTest {
// ...
}
import org.springframework.boot.test.context.SpringBootTest
import org.springframework.kafka.test.context.EmbeddedKafka
@SpringBootTest
@EmbeddedKafka(topics = ["someTopic"], bootstrapServersProperty = "spring.kafka.bootstrap-servers")
class MyTest {
// ...
}
-
Use a placeholder in configuration properties:
-
Properties
-
YAML
spring.kafka.bootstrap-servers=${spring.embedded.kafka.brokers}
spring:
kafka:
bootstrap-servers: "${spring.embedded.kafka.brokers}"