confluent kafka consumer java example

confluent kafka consumer java example

Apache, Apache Kafka, Kafka, and associated open source project names are trademarks of the Apache Software Foundation, Confluent vs. Kafka: Why you need Confluent, Kora, The Apache Kafka Engine, Built for the Cloud, Watch demo: Kafka streaming in 10 minutes, Take the Confluent Cost Savings Challenge, Everything You Always Wanted to Know About Kafkas Rebalance Protocol But Were Afraid to Ask, The Magical Rebalance Protocol of Apache Kafka, read about the Confluent Parallel Consumer, Stop processing and close the consumer (optionally, retry a few times beforehand), Send records to the dead letter queue and continue to the next record (optionally, retry a few times beforehand), Retry until the record is processed successfully (this might take forever), Offset might be committed before a record is processed, Message processing order cant be guaranteed since messages from the same partition could be processed in parallel, Stop the task, waiting only for the record currently being processed to finish, Ensure that records from the same partitions are processed only by one thread at a time, Commit offsets only after records are processed. If the consumer in the example above suddenly crashed, then the group member taking over the partition would begin consumption from offset 1. This method does not use the consumer's group management functionality (where no need of group.id) In the older version of the rebalancing protocol, called eager rebalancing, all partitions assigned to a consumer are revoked, even if they are going to be assigned to the same consumer again. } Next youll create an implementation of the ConsumerRecordsHandler interface named FileWritingRecordsHandler, but before you do that, lets take a peek under the hood to understand how the helper class works. This appears to require all topics use the same serializer. Understanding Kafka consumer internals is important in implementing a successful multi-threaded solution that overcomes these limitations, in which analyzing the thread per consumer model and taking a look under the hood of the Kafka consumer is a good first step. We then saw how an already consuming consumer could seek its offset to read messages from the beginning. The rest of this blog post describes how it works. In fact weve moved the, One word of caution: at the time of this writing, the new consumer is still considered beta in terms of stability. If your application stops polling (whether because the processing code has thrown an exception or a downstream system has crashed), then no heartbeats will be sent, the session timeout will expire, and the group will be rebalanced. Reduced Dependencies: the new consumer is written in pure Java. There has to be a Producer of records for the Consumer to feed on. Apache Kafka, and its ecosystems, Use the Cloud quick start to get up and running with Confluent Cloud using a basic cluster, Stream data between Kafka and other systems, Use clients to produce and consume messages, 3. You should always close the consumer when you are finished with it. What is the best way to set up multiple operating systems on a retro PC? executor.awaitTermination(5000, TimeUnit.MILLISECONDS); This example submits the three runnable consumers to an executor. You can see that the consumer group is using all six partitions in your topic, and you can see offsets and consumer lag: Now if you click on hobbit on . A topic partition is an object formed by the topic name and the partition number. Create a production configuration file. The more frequently you commit offsets, the less duplicates you will see in a crash. In order to provide that information to the main consumer thread, the getCurrentOffset() method is added to the Task class. props.put("session.timeout.ms", "60000"); The consumers poll loop is designed to handle this problem. 0.9.0.0-cp1 Even though we have a test for the KafkaConsumerApplication, its What are the Star Trek episodes where the Captain lowers their shields as sign of trust? It can be completed in two ways: Now, lets focus again on the main consumer thread. How to use multi-thread consumer in kafka 0.9.0? props.put(group.id, groupId); for (ConsumerRecord record : records) Note that weve provided a callback to commitAsync, which is invoked by the consumer when the commit finishes (either successfully or not). This means that there are no longer problems with excessive delays between poll method calls, and as a result, group rebalancing is very fast. For example, with a single Kafka broker and Zookeeper both running on localhost, you might do the following from the root of the Kafka distribution: # bin/kafka-topics.sh --create --topic consumer-tutorial --replication-factor 1 --partitions 3 --zookeeper localhost:2181, # bin/kafka-verifiable-producer.sh --topic consumer-tutorial --max-messages 200000 --broker-list localhost:9092. The maximum delay allowed between poll method calls is defined by the max.poll.interval.ms config, which is five minutes by default. (Specifically for when trying to categorize an adult). For a step-by-step guide on building a Java client application for Kafka, see Getting Started with Apache Kafka and Java. To use the consumers commit API, you should first disable automatic commit by setting enable.auto.commit to false in the consumers configuration. I am using Confluent.Kafka .NET client version 1.3.0. how to replay messages in kafka topic based on timestamp? I know we can spawn multiple threads (per topic) to consume from each topic, but in my case if the number of topics increases, then the number of threads consuming from the topics increases, which I do not want, since the topics are not going to get data too frequently, so the threads will sit ideal. public void onComplete(Map offsets, , which is invoked by the consumer when the commit finishes (either successfully or not). To consume messages from the beginning of a Kafka topic, we create an instance of KafkaConsumer with a randomly generated consumer group id. Map data = new HashMap<>(); data.put("partition", record.partition()); System.out.println(this.id + ": " + data); To test this example, you will need a Kafka broker running release 0.9.0.0 and a topic with some string data to consume. If another identical consumer was subscribed to the same set of topics, would they get records in the exact same order? Does the policy change for AI-generated content affect users who (want to) Configure kafka-net to stop sending latest messages. Browse other questions tagged, Where developers & technologists share private knowledge with coworkers, Reach developers & technologists worldwide, You can always set the offset value manually. You can view your costs in real time, In the most extreme case, you could commit offsets after every message is processed, as in the following example: try { As of Kafka 0.9 and above, offsets are stored in a Kafka topic instead of zookeeper, Self-healing code is the future of software development, How to keep your new tool from gathering dust, We are graduating the updated button styling for vote arrows, Statement from SO: June 5, 2023 Moderator Action. The example below shows a basic poll loop which prints the offset and value of fetched records as they arrive: The poll API returns fetched records based on the current position. } finally { Will it be possible for a single consumer to subscribe to 7 partitions across different topics? public void run() { Save 25% or More on Your Kafka Costs | Take the Confluent Cost Savings Challenge. In my opinion, these are a clear indicator of how the business is . Note: Make sure that the Server URL and PORT are in compliance with the values in //config/server.properties. Foundation. In this tutorial, you'll build a small application that uses a KafkaConsumer to read records from Kafka. The following examples therefore include the full poll loop with the commit details in bold. Introduction In this tutorial, you will run a Java client application that produces messages to and consumes messages from an Apache Kafka cluster. Let's take a look at each of these steps in detail. There is a lot to optimize. Even with this option, the consumer may be kicked out of the group if processing a single record takes too long. The example below shows the basic usage: consumer.commitAsync(new OffsetCommitCallback() {. Using a terminal window, run the following command to start a Confluent CLI producer: Each line represents input data for the KafkaConsumer application. public ConsumerLoop(int id, In each iteration of the poll loop, the main thread checks which tasks are finished and resumes corresponding partitions. } finally { Compile and run the Kafka Consumer program, 12. Each thread is given a separate id so that you can see which thread is receiving data. The example below shows how to assign all the partitions from a topic using the. If no heartbeat is received when the timer expires, the coordinator marks the member dead and signals the rest of the group that they should rejoin so that partitions can be reassigned. List partitions = new ArrayList<>(); ) consumer.close(); This is all handled automatically when you begin consuming data. e.printStackTrace; personal data will be processed in accordance with our Privacy Policy. The lag of a partition is the difference between the log end offset and the last committed offset. The first phase of this was rewriting the Producer API in 0.8.1. As we proceed through this tutorial, well introduce more of the configuration. As always, the complete code for all the examples is availableover on GitHub. It is not safe for multithreaded use without external synchronization and it is probably not a good idea to try. Right into Your Inbox. Finally, polling the same consumer again for messages now reads all the messages from the beginning of the partition: In this article, we've learned how to read messages from the beginning of a Kafka topic using the Kafka Consumer API. } finally { } finally { When this flag is set to false from another thread (e.g. Lastly, let's publish a few dummy messages to the Kafka topic baeldung. 3. With the created map we get the offset of each partition on the specified datetime with offsetsForTimes method. I can explain how it works and you may figure the solution on your own. Use the following command to create the topic: Create the following Gradle build file, named build.gradle for the project: And be sure to run the following command to obtain the Gradle wrapper: Then create a development configuration file at configuration/dev.properties: Lets do a quick overview of some of the more important properties here: The key.deserializer and value.deserializer properties provide a class implementing the Deserializer interface for converting byte arrays into the expected object type of the key and value respectively. In the next example, well put all of this together to build a simple Runnable task which initializes the consumer, subscribes to a list of topics, and executes the poll loop indefinitely until shutdown externally. A multi-consumer approach can also be used for vertical scaling, but this requires additional management of consumer instances and accompanying consuming threads in the application code. We are creating two consumers who will listen to two topics we created in the 3rd section (topic configuration). Whenever a consumer consumes a message,its offset is commited with zookeeper to keep a future track to process each message only once. I would like to start consuming messages from a given time onwards. things like real-time query performance, focus on most used tables coding, and a host of super useful plugins as well: Slow MySQL query performance is all too common. } You should therefore set the session timeout large enough to make this unlikely. I don't have time now to check the code, but i will do it. Using asynchronous commits will generally give you higher throughput since your application can begin processing the next batch of messages before the commit returns. within minutes: The Kubernetes ecosystem is huge and quite complex, so Kafka provides a convenient Java client library that we can use to perform various operations on the Kafka cluster. try { To test this example, you will need a Kafka broker running release 0.9.0.0 and a topic with some string data to consume. This is usually achieved by scaling: using multiple consumers within the same group, each processing data from a subset of topic partitions and running in a single thread. This is done by the handleFetchedRecords() method. We can simply use mock consumer to process some data youll feed into it. You can shutdown the process using Ctrl-C from the command line or through your IDE. and wait for them to shutdown. Create a new Java Project called KafkaExamples, in your favorite IDE. Operating Kafka at scale can consume your cloud spend and engineering time. Verify they are destroyed to avoid unexpected charges. The parameter passed to poll controls the maximum amount of time that the consumer will block while it awaits records at the current position. } catch (CommitFailedException e) { consumers.add(consumer); And operating everyday tasks like scaling or deploying new clusters can be complex and require dedicated engineers. The kafka-streams-examples GitHub repo is a curated repo with examples that demonstrate the use of Kafka Streams DSL, the low-level Processor API, Java 8 lambda expressions, reading and writing Avro data, and implementing unit tests with TopologyTestDriver and end-to-end integration tests using embedded Kafka clusters. Exception exception) { I'm leaving you and example for now, i will check it later. Make sure to verify the number of partitions given in any Kafka topic. When implementing a multi-threaded consumer architecture, it is important to note that the Kafka consumer is not thread safe. Offsets are committed by your app and stored in a special offsets kafka topic called __consumer_offsets. Additionally, to reset the existing consumer to read from the beginning of the topic, we use the KafkaConsumer.seekToBeginning(Collection partitions) method. When using the thread per consumer model, you can deal with this problem by tuning the following config values: When the record processing time varies, it might be hard to tweak these configs perfectly, so it is recommended to use separate threads for processing. while (running) { Is there any way to have a single consumer to consume from all topics? The first step is to disable auto commit in the consumer configuration: Offsets are committed manually from the main thread loop, but only Task instances know which record from the corresponding partition was last processed and, consequently, which offsets can be committed. The tradeoff is that you may only find out later that the commit failed. The high watermark is the offset of the last message that was successfully copied to all of the logs replicas. After subscribing to a topic, you need to start the event loop to get a partition assignment and begin fetching data. ConsumerRecords records = consumer.poll(Long.MAX_VALUE); A more reasonable approach might be to commit after every N messages where N can be tuned for better performance. Multi-threaded access must be properly synchronized, which can be tricky. Thanks in Advance, When I run the above code in asp.net core, I am getting below error , %4|1632063373.082|ASSIGN|rdkafka#consumer-1| [thrd:main]: Group "1": application *assign() call failed: Changes to the current assignment must be made using incremental_assign() or incremental_unassign() when rebalance protocol type is COOPERATIVE Unhandled exception. In this case, its hard coded to five seconds. If you run into any problems, tell us about it on the Kafka mailing list. Also note that, if you are changing the Topic name, make sure you use the same topic name for the Kafka Producer Example and Kafka Consumer Example Java Applications. Using a new environment keeps your learning resources separate from your other Confluent Cloud resources. Confluent.Kafka.KafkaException: Local: Erroneous state, Thanks for the response, but two things: 1- part of my question was how to get the offset of the first message whose timestamp is after a given time (again, my approach above won't work if the given time is prior to the timestamp of the last committed message). For each group, one of the brokers is selected as the group coordinator. Thanks for contributing an answer to Stack Overflow! This prevents the consumer from reading unreplicated data which could later be lost. How to configure Apache Kafka to sending data at specified time? } Save 25% or More on Your Kafka Costs | Take the Confluent Cost Savings Challenge. The next step creates and submits the record processing tasks. What is the proper way to prepare a cup of English tea? Did anybody use PCBs as macro-scale mask-ROMS? If i'm not wrong, in assign method you can specify the initial offset. For example, we had a "high-level" consumer API which supported consumer groups and handled failover, but didn't support many of the more complex usage scenarios. Once the consumer begins processing, it commits offsets regularly according to the needs of the application. Setting enable.auto.commit configuration to true enables the Kafka consumer to handle committing offsets automatically for you. Because records are fetched and processed by the same thread, they are processed in the same order as they were written to the partition. To do this it uses an API style similar to the poll or select call in unix: once topics are registered, all future coordination, rebalancing, and data fetching is driven through a single poll call meant to be invoked in an event loop. Let's create a Kafka topic named baeldung by referring to our Kafka Topic Creation guide. A wide range of resources to get you started, Build a client app, explore use cases, and build on our demos and resources, Confluent proudly supports the global community of streaming platforms, real-time data streams, Apache Kafka, and its ecosystems. Can see which confluent kafka consumer java example is given a separate id so that you may only find out later that the failed. All topics topics use the same set of topics, would they get records in the 3rd section topic! Will listen to two topics we created confluent kafka consumer java example the exact same order am using Confluent.Kafka.NET client version 1.3.0. to. '', `` 60000 '' ) ; this example submits the record processing tasks values in / kafka_directory... Focus again on the specified datetime with offsetsForTimes method how it works a Kafka topic baeldung with.! Offsetsfortimes method } finally { Compile and run the Kafka consumer to process each message only once require topics! Of messages before the commit returns want to ) Configure kafka-net to stop sending latest messages, the duplicates. Watermark is the best way to prepare a cup of English tea '' ) ; example! Best way to have a single consumer to handle committing offsets automatically for you to Configure Apache Kafka sending. Randomly generated consumer group id operating systems confluent kafka consumer java example a retro PC Producer of for! My opinion, these are a clear indicator of how the business is is set to false another! The high watermark is the difference between the log end offset and confluent kafka consumer java example... Client version 1.3.0. how to assign all the partitions from a topic using the the three runnable to. First disable automatic commit by setting enable.auto.commit configuration to true enables the Kafka consumer is written in pure Java needs! Message that was successfully copied to all of the application to 7 partitions different. We create an instance of KafkaConsumer with a randomly generated consumer group id an instance of with... Begins processing, it commits offsets regularly according to the main consumer.! If the consumer may be kicked out of the application the Producer API in 0.8.1 public void run )..., well introduce more of the brokers is selected as the group coordinator: now, i do... Unreplicated data which could later be lost of records for the consumer to process some data youll feed into.. To replay messages in Kafka topic named baeldung by referring to our Kafka topic, you need to the. ( ) { i 'm not wrong, in your favorite IDE is done by max.poll.interval.ms... The max.poll.interval.ms config, which can be completed in two ways: now lets. Could later be lost this appears to require all topics include the full poll loop designed! Your app and stored in a special offsets Kafka topic called __consumer_offsets once consumer. When trying to categorize an adult ) configuration ) two consumers who will listen to topics! Thread is receiving data Task class Confluent cloud resources can specify the initial offset a single takes! Availableover on GitHub < kafka_directory > /config/server.properties to consume from all topics use the same set of topics, they! Between poll method calls is defined by the max.poll.interval.ms config, which is five minutes by default to! It is important to note that the commit failed across different topics include full! Processed in accordance with our Privacy policy with it the three runnable consumers to executor! With this option, the less duplicates you will run a Java client application for Kafka see! For each group, one of the last message that was successfully to! Use the consumers commit API, you will run a Java client application that uses a KafkaConsumer to records! The last committed offset important to note that the Kafka consumer to handle committing offsets automatically for you i explain! Flag is set to false from another thread ( e.g small application that uses a KafkaConsumer to read messages the! Kafka consumer program, 12 you will see in a special offsets Kafka topic even with this,. To the Kafka mailing list successfully copied to all of the group if processing a single to! Rest of this was rewriting the Producer API in 0.8.1 make this unlikely a environment! Topic name and the last committed offset i would like to start the event loop to get a assignment! This was rewriting the Producer API in 0.8.1 this blog post describes how works. I 'm leaving you and example for now, lets focus again on the main consumer thread on! Other Confluent cloud resources Specifically for when trying to categorize an adult.! I do n't have time now to check the code, but i will it! Using asynchronous commits will generally give you higher throughput since your application can begin processing the next step and! Throughput since your application can begin processing the next step creates and submits the record processing tasks a!, one of the last committed offset with offsetsForTimes method to have a consumer! Your IDE my opinion, these are a clear indicator of how the business is, which can completed! Section ( topic configuration ) with the created map we get the offset of each partition on the datetime..., let 's publish a few dummy messages to the Kafka consumer is written in pure Java ( running {. Same order up multiple operating systems on a retro PC compliance with the created map get! Given in any Kafka topic processed in accordance with our Privacy policy should first disable automatic by!, tell us about it on the Kafka consumer is not safe for multithreaded use without external synchronization it...: make sure to verify the number of partitions given in any Kafka topic named by... In detail use mock consumer to feed on explain how it works and you may figure the solution your. Offsets, the less duplicates you will run a Java client application that produces messages to the consumer! In / < kafka_directory > /config/server.properties if the consumer may be kicked out of the is... Be completed in two ways: now, i will check it.! To false in the exact same order, see Getting Started with Apache Kafka cluster an object formed the! Same set of topics, would they get records in the exact same order to feed.... Data at specified time? or through your IDE single consumer to feed on implementing a multi-threaded consumer,. Processing a single consumer to handle committing offsets automatically for you the of! A clear indicator of how the business is needs of the configuration the following examples therefore include the full loop! Set up multiple operating systems on a retro PC building a Java client application that uses a to! At scale can consume your cloud spend and engineering time seek its offset commited! ( 5000, TimeUnit.MILLISECONDS ) ; this example submits the record processing.! Topic configuration ) difference between confluent kafka consumer java example log end offset and the last committed offset dummy messages to and consumes from. The proper way to have a single consumer to process each message only once dummy! To require all topics a new environment keeps your learning resources separate your. Operating Kafka at scale can consume your cloud spend and engineering time group, one of application... When trying to categorize an adult ) commited with zookeeper to keep a track! Two ways: now, lets focus again on the main consumer.! Config, which is five minutes by default accordance with our Privacy policy its offset to records... | Take the Confluent Cost Savings Challenge has to be a Producer records. Three runnable consumers to an executor all of the logs replicas kafka_directory > /config/server.properties not thread.. Take a look at each of these steps in detail will check it.. Large enough to make this unlikely the specified datetime with offsetsForTimes method / < kafka_directory > /config/server.properties a! At specified time? you are finished with it your own is defined the. And stored in a special offsets Kafka topic baeldung time onwards well introduce more of the.. Example below shows the basic usage: consumer.commitAsync ( new OffsetCommitCallback ( ) { that you specify. Server URL and PORT are in compliance with the values in / kafka_directory. Phase of this blog post describes how it works and you may only find out later that the consumer! A cup of English tea this example submits the three runnable consumers to an executor can be in... Idea to try are creating two consumers who will listen to two topics we created the! Of a Kafka topic single record takes too long above suddenly crashed, then the group taking! An already consuming consumer could seek its offset is commited with zookeeper to keep future! Can shutdown the process using Ctrl-C from the beginning of a Kafka topic Creation guide any topic. Multi-Threaded access must be properly synchronized, which can be tricky when implementing a multi-threaded consumer architecture, is. Can explain how it works in 0.8.1 use mock consumer to consume from... Can begin processing the next batch of messages before confluent kafka consumer java example commit failed code, but i will check it.. Created in the 3rd section ( topic configuration ) and stored in a special offsets topic! Configure kafka-net to confluent kafka consumer java example sending latest messages Confluent.Kafka.NET client version 1.3.0. how to messages! Lastly, let 's create a Kafka topic called __consumer_offsets through your IDE Started. A multi-threaded consumer architecture, it commits offsets regularly according to the Kafka to. Suddenly crashed, then the group coordinator of English tea the high watermark the. Referring to our Kafka topic named baeldung by referring to our Kafka topic could seek its offset to messages! Can see which thread is given a separate id so that you shutdown. Special offsets Kafka topic named baeldung by referring to our Kafka topic named baeldung by referring to Kafka! Called KafkaExamples, in your favorite IDE with Apache Kafka and Java Kafka Costs | Take Confluent. The policy change for AI-generated content affect users who ( want to ) Configure kafka-net to stop sending latest.!

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