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KafKa partitioner class, assign message to partition within topic using key


KafKa partitioner class, assign message to partition within topic using key

By : dcsonos
Date : November 27 2020, 01:01 AM
To fix this issue Each topic in Kafka is split into many partitions. Partition allows for parallel consumption increasing throughput.
Producer publishes the message to a topic using the Kafka producer client library which balances the messages across the available partitions using a Partitioner. The broker to which the producer connects to takes care of sending the message to the broker which is the leader of that partition using the partition owner information in zookeeper. Consumers use Kafka’s High-level consumer library (which handles broker leader changes, managing offset info in zookeeper and figuring out partition owner info etc implicitly) to consume messages from partitions in streams; each stream may be mapped to a few partitions depending on how the consumer chooses to create the message streams.
code :


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Apache Kafka Topic Partition Message Handling

Apache Kafka Topic Partition Message Handling


By : Lynda Abedi
Date : March 29 2020, 07:55 AM
it helps some times I'll answer your questions by walking you through partition replication, because you need to learn about replication to understand the answer.
A single broker is considered the "leader" for a given partition. All produces and consumes occur with the leader. Replicas of the partition are replicated to a configurable amount of other brokers. The leader handles replicating a produce to the other replicas. Other replicas that are caught up to the leader are called "in-sync replicas." You can configure what "caught up" means.
kafka how to implement exactly-once message delivery logic with topic/partition/offset

kafka how to implement exactly-once message delivery logic with topic/partition/offset


By : Ivo
Date : March 29 2020, 07:55 AM
I hope this helps you . You have to write out the last offset processed atomically, along with the results of the processing, outside of Kafka. This can be to a database or file, just don't do two writes, make it a single atomic write of both data and offset. If your consumer crashes and it or another instance restarts or takes over, you need to make sure that first it reads the last offset stored with the last processing results and seek() to that position before you poll() for more messages. This is how many of the existing Kafka Sink Connectors can achieve EOS consumption today.
How to create concurrent message listener for Kafka topic with 1 partition

How to create concurrent message listener for Kafka topic with 1 partition


By : uimarshall
Date : March 29 2020, 07:55 AM
hop of those help? No, there definitely will be only one target listener. One partition - one process to consumer per consumer group. That is an Apache Kafka nature. That is not Spring Kafka problem.
You can parallel messages from that partition lately from your listener method using TaskExecutor. But that is already your application - the Framework won't do anything for you on the matter. Just because the nature of the target Kafka system.
How to re-send (read) an old kafka message from given topic and partition at specific offset using spring-kafka?

How to re-send (read) an old kafka message from given topic and partition at specific offset using spring-kafka?


By : Ratan Kumar
Date : March 29 2020, 07:55 AM
will be helpful for those in need There is an easier solution.
Use the DefaultConsumerFactory to create a KafkaConsumer (or simply create one) Use a different group.id Set the max.poll.records property to 1 consumer.assign(...) the desired topic/partition seek(...) to the required offset poll(...) until you get the record close() the consumer
Will send(Topic, Key, Message) method of KafkaTemplate calls Partition method if I provide custom Partitioner?

Will send(Topic, Key, Message) method of KafkaTemplate calls Partition method if I provide custom Partitioner?


By : user3157378
Date : March 29 2020, 07:55 AM
To fix the issue you can do Well, KafkaTemplate is fully based on the Apache Kafka Client Producer. The final code looks like:
code :
producer.send(producerRecord, buildCallback(producerRecord, producer, future));
 /**
     * computes partition for given record.
     * if the record has partition returns the value otherwise
     * calls configured partitioner class to compute the partition.
     */
    private int partition(ProducerRecord<K, V> record, byte[] serializedKey, byte[] serializedValue, Cluster cluster) {
        Integer partition = record.partition();
        return partition != null ?
                partition :
                partitioner.partition(
                        record.topic(), record.key(), serializedKey, record.value(), serializedValue, cluster);
    }
/**
 * Send the data to the provided topic with the provided key and partition.
 * @param topic the topic.
 * @param partition the partition.
 * @param timestamp the timestamp of the record.
 * @param key the key.
 * @param data the data.
 * @return a Future for the {@link SendResult}.
 * @since 1.3
 */
ListenableFuture<SendResult<K, V>> send(String topic, Integer partition, Long timestamp, K key, V data);
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