Failures are simply logged after retries are exhausted. If there are multiple such beans, they will be applied according to their Ordered.order property. If you are using producers in a multi-threaded environment, the BiFunction should return multiple producers (perhaps thread-bound using a ThreadLocal). When not using the spring test context, the EmbdeddedKafkaCondition creates a broker; the condition includes a parameter resolver so you can access the broker in your test method. The following example creates a set of mappings: If you use Spring Boot, you can provide these properties in the application.properties (or yaml) file. This can happen when, for example, the configured user is denied access to read a certain topic or credentials are incorrect. The exceptions that are considered fatal, by default, are: since these exceptions are unlikely to be resolved on a retried delivery. The time to process a batch of records plus this value must be less than the max.poll.interval.ms consumer property. The DLT handler method can also be provided through the RetryTopicConfigurationBuilder.dltHandlerMethod(String, String) method, passing as arguments the bean name and method name that should process the DLTs messages. See Micrometer Observation Documentation for details of the default observations that are recorded. Using a FixedBackOff with FixedBackOff.UNLIMITED_ATTEMPTS causes (effectively) infinite retries. This quick tour works with the following versions: The simplest way to get started is to use start.spring.io (or the wizards in Spring Tool Suits and Intellij IDEA) and create a project, selecting 'Spring for Apache Kafka' as a dependency. See Listener Info Header and Abstract Listener Container Properties for more information. See Configuring Global Settings and Features for more details. The containerProperties.groupId, if present, otherwise the group.id property from the consumer factory. See Monitoring for more information. This version requires the 3.3.1 kafka-clients. By default the topics are autocreated with one partition and a replication factor of -1 (meaning use the broker default). A ConsumerStoppedEvent is now emitted when a consumer stops. This interface provides methods to look up the next topic in the chain or the DLT for a topic if configured, as well as useful properties such as the topics name, delay and type. Starting with version 2.2, you can now override the container factorys concurrency and autoStartup properties by using properties on the annotation itself. A common use case is to start a listener after another listener has consumed all the records in a topic. ConsumerFailedToStartEvent - published if no ConsumerStartingEvent is published within the consumerStartTimeout container property. For a batch listener, the listener must throw a BatchListenerFailedException indicating which records in the batch failed. Spring Kafka and number of topic consumers - Stack If this property is not provided, the container configures a logging listener that logs rebalance events at the INFO level. The bean name for user-configured containers or the id attribute of @KafkaListener s. A value to populate in the KafkaHeaders.LISTENER_INFO header. You should not use this technique in such a situation, or you should use something to call. Introduced in version 2.5.3, you can configure a KafkaStreamsMicrometerListener to automatically register micrometer meters for the KafkaStreams object managed by the factory bean: For serializing and deserializing data when reading or writing to topics or state stores in JSON format, Spring for Apache Kafka provides a JsonSerde implementation that uses JSON, delegating to the JsonSerializer and JsonDeserializer described in Serialization, Deserialization, and Message Conversion. When using group management, onPartitionsAssigned is called when partitions are assigned. The following listing shows the signatures of those methods: The EmbeddedKafkaBroker class has a utility method that lets you consume for all the topics it created. You can also provide a custom implementation of Spring Retrys SleepingBackOffPolicy interface: You can set the global timeout for the retrying process. If you provide a custom producer factory, it must support transactions. Property placeholders are resolved for the brokerPropertiesLocation URL and for any property placeholders found in the resource. The KafkaTransactionManager is an implementation of Spring Frameworks PlatformTransactionManager. The following simple Spring Boot application provides an example of how to use the same template to send to different topics, each using a different value serializer. Prerequisites: You must install and run Apache Kafka. It is now called after a timeout (as well as when records arrive); the second parameter is true in the case of a call after a timeout. Note that SimpleThreadScope does not destroy beans that have a destruction interface (such as DisposableBean), so you should destroy() the instance yourself. When so configured, the RequestReplyFuture will be completed exceptionally and you can catch the ExecutionException, with the DeserializationException in its cause property. In addition, these properties can be provided: spring.kafka.embedded.count - the number of Kafka brokers to manage; spring.kafka.embedded.ports - ports (comma-separated value) for every Kafka broker to start, 0 if random port is a preferred; the number of values must be equal to the count mentioned above; spring.kafka.embedded.topics - topics (comma-separated value) to create in the started Kafka cluster; spring.kafka.embedded.partitions - number of partitions to provision for the created topics; spring.kafka.embedded.broker.properties.location - the location of the file for additional Kafka broker configuration properties; the value of this property must follow the Spring resource abstraction pattern. By default, no interval is configured - authentication and authorization errors are considered fatal, which causes the container to stop. KafkaHeaders.DLT_ORIGINAL_TOPIC: The original topic. Spring for Apache Kafka also provides JsonSerializer and JsonDeserializer implementations that are based on the This map should be ordered (e.g. The single constructor is similar to the KafkaListenerContainer constructor. See transactionIdPrefix for more information. See Starting @KafkaListener s in Sequence for more information. Starting with version 2.6.7, in addition to detecting DeserializationException s, the template will call the replyErrorChecker function, if provided. The following error handler configuration will do exactly that: Starting with version 2.7, the recoverer checks that the partition selected by the destination resolver actually exists. The default executor creates threads named -C-n; with the KafkaMessageListenerContainer, the name is the bean name; with the ConcurrentMessageListenerContainer the name is the bean name suffixed with -n where n is incremented for each child container. The framework provides the DeadLetterPublishingRecoverer which sends the failed record to a dead-letter topic. The property can also be a String of comma-delimited map entries, as shown below. A positive value is an absolute offset by default. In the former the record is forwarded back to the DLT topic so it doesnt block other DLT records' processing. This first part of the reference documentation is a high-level overview of Spring for Apache Kafka and the underlying concepts and some code snippets that can help you get up and running as quickly as possible. The maximum time in ms to block the stop() method until all consumers stop and before publishing the container stopped event. In addition (also since 2.1.5), ConsumerPausedEvent and ConsumerResumedEvent instances are published with the container as the source property and the TopicPartition instances involved in the partitions property. The following examples show how to do so: The registry only maintains the life cycle of containers it manages; containers declared as beans are not managed by the registry and can be obtained from the application context. The following example shows how to use it: This mechanism requires an @EnableKafka annotation on one of your @Configuration classes and a listener container factory, which is used to configure the underlying ConcurrentMessageListenerContainer. See Batch Listeners for more information about consuming batches. It is provided with a reference to the producer factory in its constructor. You can inject the MessageConverter into a KafkaTemplate instance directly and by using AbstractKafkaListenerContainerFactory bean definition for the @KafkaListener.containerFactory() property. See Forwarding Listener Results using @SendTo for more information about sending replies. A LinkedHashMap is recommended so that the keys are examined in order. The first argument is the current list of records; the second is true if this call is due to a timeout. See Handling Exceptions for more information. The @KafkaListener annotation has a new property splitIterables; default true. Following is an example using the same MyProducerInterceptor from above, but changed to not use the internal config property. The template provides constant static variables for these "topic" names: The real ConsumerRecord s in the Collection contain the actual topic(s) from which the replies are received. See Using KafkaTemplate for more information. The processor does not change the key or value; it simply adds headers. For the @RetryableTopic annotation you can provide the factorys bean name, and using the RetryTopicConfiguration bean you can either provide the bean name or the instance itself. ContainerProperties has a property called consumerRebalanceListener, which takes an implementation of the Kafka clients ConsumerRebalanceListener interface. See Publishing Dead-letter Records for more information about this recoverer. Starting with version 2.2, the stream configuration is now provided as a, The preceding example provides no mechanism for shutting down the broker(s) when all tests are complete. This event might signal that the configured task executor has insufficient threads to support the containers it is used in and their concurrency. Support for creating native images is provided. JsonDeserializer.USE_TYPE_INFO_HEADERS (default true): You can set it to false to ignore headers set by the serializer. Using a batch listener would help - you just need to hold up the consumer thread in the listener until all the individual records have completed processing. When null, such exceptions are considered fatal and the container will stop. See Managing Dead Letter Record Headers for more information. To use it from a Spring application, the kafka-streams jar must be present on classpath. If you wish to commit the Kafka transaction first, and only commit the DB transaction if the Kafka transaction is successful, use nested @Transactional methods: The serializer and deserializer support a number of cusomizations using properties, see JSON for more information. A similar listener is provided for the StreamsBuilderFactoryBean - see KafkaStreams Micrometer Support. If the topic is configured to use LOG_APPEND_TIME, the user-specified timestamp is ignored and the broker adds in the local broker time. The same technique can be used when specifying initial offsets: The initial offset will be applied to all 6 partitions. Customizing the JsonSerializer and JsonDeserializer, Appendix A: Override Spring Boot Dependencies, Appendix B: Micrometer Observation Documentation, D.3.2. Then, to use the template, you can invoke one of its methods. Starting with version 2.5, the DefaultKafkaProducerFactory and DefaultKafkaConsumerFactory can be configured with a Listener to receive notifications whenever a producer or consumer is created or closed. Since 2.8.3 theres a global list of fatal exceptions which will cause the record to be sent to the DLT without any retries. The first is called immediately. The 0.11.0.0 client library provides an AdminClient, which you can use to create topics. Spring for Apache Kafka This header is used on the inbound side to provide appropriate conversion of each header value to the original type. When a message in the retry topic is not due for consumption, a KafkaBackOffException is thrown. The following listing shows the definition of the ProducerListener interface: By default, the template is configured with a LoggingProducerListener, which logs errors and does nothing when the send is successful. You can use the KafkaTemplate to execute a series of operations within a local transaction. Set this property to true and the container will correct such mis-reported offsets. See Examples of Kafka Transactions with Other Transaction Managers for an example application that chains JDBC and Kafka transactions. See the Apache Kafka documentation for all possible options. You can use property placeholders or SpEL expressions within most annotation properties, as the following example shows: Starting with version 2.1.2, the SpEL expressions support a special token: __listener. To configure the @KafkaListener to handle null payloads, you must use the @Payload annotation with required = false. Starting with version 2.2, a new container property called missingTopicsFatal has been added (default: false since 2.3.4). See Seeking to a Specific Offset for more information. With the last two methods, each record is retrieved individually and the results assembled into a ConsumerRecords object. Starting with version 2.1.3, you can configure stateful retry. You can specify a global error handler to be used for all listeners in the container factory. (See @EmbeddedKafka Annotation for information about using @EmbeddedKafka with JUnit 5). Starting with version 2.5.5, you can apply an initial offset to all assigned partitions: The * wildcard represents all partitions in the partitions attribute. You can revert to the previous behavior by setting the removeTypeHeaders property to false, either directly on the deserializer or with the configuration property described earlier. Starting with version 2.2, the type information headers (if added by the serializer) are removed by the deserializer. If you wish to use a different version of kafka-clients or kafka-streams, and use the embedded kafka broker for testing, you need to override their version used by Spring Boot dependency management; set the kafka.version property. If your broker is earlier that version 2.4, you will now need to explicitly set the property. The DelegatingByTopicSerializer and DelegatingByTopicDeserializer are now provided. If it is a tombstone message for a compacted log, you usually also need the key so that your application can determine which key was deleted. The consumer will be paused (no new records delivered) until all the offsets for the previous poll have been committed. The following example shows how to do so: This section covers how to send messages. The provider gives a way to customize the metadata. consumer errors). The header mappers also convert to String when creating MessageHeaders from the consumer record and never map this header on an outbound record. You can now configure an adviceChain in the container properties. See Serialization, Deserialization, and Message Conversion for more information. New Delegating Serializer/Deserializer, D.8.9. See ProducerFactory.transactionCapable(). Auto creation of topics will only occur if the configuration is processed before the application context is refreshed, as in the above example. When used as the parameter to a @KafkaListener method, the interface type is automatically passed to the converter as normal. The following example shows how to seek to the last record processed, in each partition, each time the container goes idle. Key Features of Apache Kafka What is Spring Boot? See KafkaTemplate Transactional and non-Transactional Publishing for more information. In addition, the recoverer verifies that the partition selected by the destination resolver actually exists before publishing to it. KafkaHeaders.DLT_ORIGINAL_OFFSET: The original offset. To configure this feature, set the idleEventInterval on the container. See Transactions for more information. See Container Error Handlers for more information. While the container is idle, an event is published every idleEventInterval milliseconds. Convenient constants (EmbeddedKafkaBroker.SPRING_EMBEDDED_KAFKA_BROKERS and EmbeddedKafkaBroker.SPRING_EMBEDDED_ZOOKEEPER_CONNECT) are provided for this property. The following example shows how to do so: Starting with version 2.1.1, the org.springframework.core.convert.ConversionService used by the default o.s.messaging.handler.annotation.support.MessageHandlerMethodFactory to resolve parameters for the invocation of a listener method is supplied with all beans that implement any of the following interfaces: org.springframework.core.convert.converter.Converter, org.springframework.core.convert.converter.GenericConverter. When true prevents the container from starting if the confifgured topic(s) are not present on the broker. The DB transaction is committed first; if the Kafka transaction fails to commit, the record will be redelivered so the DB update should be idempotent. An example of obtaining one of the Kafka metrics, Detecting Idle and Non-Responsive Consumers, 4.1.15. Starting with version 2.2, you can use the same factory to create any ConcurrentMessageListenerContainer. Use KEY_SERIALIZATION_TOPIC_CONFIG when using this for keys. See Listener Container Properties for more information. Similar to the Kafka Streams API, you must define the KStream instances before you start the KafkaStreams. The container will defer the commit until the missing offset is acknowledged. See Exactly Once Semantics and KIP-447 for more information. The FallbackBatchErrorHandler takes a the following approach. In the latter the consumer ends the execution without forwarding the message. An actual sleep interval is selected as the minimum from the provided option and difference between the max.poll.interval.ms consumer config and the current records batch processing time. You can add additional tags using the templates micrometerTags property. To add tags to timers/traces, configure a custom KafkaTemplateObservationConvention or KafkaListenerObservationConvention to the template or listener container, respectively. The main chapter covers the core classes to develop a Kafka application with Spring. Starting with version 2.4.2 you are able to add your own HandlerMethodArgumentResolver and resolve custom method parameters. KafkaHeaders.DLT_KEY_EXCEPTION_STACKTRACE: The Exception stack trace (key deserialization errors only). For example, if you create the listener container yourself outside of a Spring context, not all functions will work unless you satisfy all of the, If the broker supports it (1.0.0 or higher), the admin increases the number of partitions if it is found that an existing topic has fewer partitions than the, In version 3.0, the methods that previously returned, In version 3.0, the futures returned by these methods (and their, When using manual partition assignment (no group management), the duration for the wait must be greater than the containers, If you have multiple client instances and you do not configure them as discussed in the preceding paragraph, each instance needs a dedicated reply topic. If you implement your own listener directly, you can simply use the container factory to create a raw container for that listener: Containers for methods annotated with @KafkaListener can be created dynamically by declaring the bean as prototype: The following Spring application events are published by listener containers and their consumers: ConsumerStartingEvent - published when a consumer thread is first started, before it starts polling. There are two mechanisms to add more headers. You can now specify kafka consumer properties directly on the annotation; these will override any properties with the same name defined in the consumer factory (since version 2.2.4). If your broker version is earlier than 2.4, you will need to set an explicit value.
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