I have a project which uses Spring Boot related project. I want to use the Transactional feature of Kafka consumer and producer in the project. I need to produce a lot of messages in Kafka as efficient as possible. So I need a multi-thread consuming and producing for this requirement. How can I use Spring boot for developing a multi-thread consumer and producer?
See the concurrency listener Boot property.
spring.kafka.listener.concurrency
The topic must have at least as many partitions as the concurrency.
https://docs.spring.io/spring-kafka/docs/2.6.1/reference/html/#message-listener-container
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I have a node application that consumes Kafka messages, makes some long operations, and finally, sends the result to another microservice through Kafka message.
what is the best approach to improve my application scalability so it can process more Kafka messages per second? and why?
Using the clustering module of node js to create multiple instances that connect to Kafka using the same consumer group. (I think it should enhance the scalability by cores count)
Using a thread pool of the worker threads node js module. and distribute the Kafka consumed messages across the worker threads.
any other suggestions?
I was checking Spring batch remote partitioning for loading data from RDBMS sources as well as multi partitioned Kafka topic. Problem with me is, I can not have rabbitMQ or JMS as the middle wear between master and worker nodes, I can only have Kafka as channel between the master and worker.
On all the documentation I can see that it supports JMS and AMQP.
Can anyone tell me how we can use remote partitioning with Kafka as middle wear .... if anyone has working example also, it will be a great help?
spring-integration-kafka provides similar endpoints to those used for JMS and RabbitMQ so it shouldn't be difficult to apply the concepts in that documentation to kafka.
The spring-integration-kafka latest version is 3.3.1 (it is moving to the core spring-integration project in 5.4.0).
I have a clustered application built around spring tooling, using kafka as the message layer for the fabric. At a high level, its architecture is a master process that parcels out work to slave processes running on separate hardware/vm's.
Master
|_______________
| | |
slave1 slave2 slave3
What I expect to happen is, if I throw 100 messages at Kafka, each of the slaves (three in this example) will pick up a proportionate number of messages and execute a proportionate amount of the work (about 1/3rd in this example).
What really happens is a slave picks up all of the messages and executes all of the work. It is indeterminate which slave will pick up the messages, but it is guaranteed one a slave starts picking up messages, the others will not until the slave has finished its work.
To me, it looks like the read from Kafka is pulling all of the messages from the queue, rather than one at a time. This leads me to believe I missed a configuration either on Kafka or in the Spring kafka.
I think you miss a conceptual understanding what is Apache Kafka and how it works.
There is no queues, first of all. Messages are settled in the topic. Everybody subscribed can get the same message. However there is a concept of consumer group. So, independently of the number of subscrbibers, only one of them will read a single message if the consumer group is the same.
There is another feature in Kafka called partitions. With that you can distribute your messages into different partitions or they will be assigned automatically: evenly by default. This partitions feature has another angle to use. When we have several subscribers for the same topic in the same consumer group, the partitions are distributed between them. So, you may reconsider your logic in favor of built-in features in Apache Kafka.
There is nothing to do from the Spring Kafka perspective, though. You only need properly configure your topic for reasonable number of partitions and provide the same consumer group for all your "slaves".
There is a topic with 8 partitions in a Kafka cluster.
I implemented application to consume the topic with KafkaMessageDrivenChannelAdapter which concurrent is 8 and offsetManager is KafkaTopicOffsetManager.
When I start one application instance everything is right. But when I start two application instances, I find the meesge is consumed twice. Do you know why and how to solve it? I need change to highLevelConsumer?
You have to distribute the partitions across instances with that adapter.
We are working on upgrading to kafka 0.9 java clients which supports consumer groups.
The first milestone for the core project is available.
We need to work on releasing a milestone of spring-integration-kafka 2.0 that uses this new client.
Kafka says that the offset is managed by consumers and there should be as many consumers as many partitions for the same group.
Spring integration says that the number of consumer streams in high level consumer is the number of partitions for the same group.
So, can the spring kafka consumer code run on multiple servers for the same group? If yes, how do the offsets know not to be in conflict between servers?
According to the kafka doc, if group (http://kafka.apache.org/documentation.html#introduction) was implemented, each message is consumed by exactly one consumer in the group. Each consumer can run on one machine. Two consumer can run on the same machine, also. In this case, each consumer can be one process.
One group can contain multiple consumers. Partitions can be distributed among all the consumers in one group by some algorithms. The number of consumers can be larger or less than the number of the partitions.
Offset can be managed by aid of zookeeper. but not all functions have been implemented in some clients until now.
As for your use case, in fact, kafka maybe "at-least-once delivery system". Kafka can be at-most-once delivery by disabling retries on the producer OR committing its offset before processing a batch of messages. It is very difficult to implement "exactly-once delivery system", which requires co-operation. But kafka provides offset. So it may be possible.For more details, please see http://kafka.apache.org/documentation.html#semantics, http://ben.kirw.in/2014/11/28/kafka-patterns/, https://dzone.com/articles/kafka-clients-at-most-once-at-least-once-exactly-o and so on.
Based on my personal experience, I spent lots of time to make sure that my kafka system to be exactly-once delivery system. but when the server is down, some messages can be consumed twice. But my testing was done on standalone kafka server, always kafka cluter is used in production. So, I think it may can be considered as exactly-once system.