By Nishant Garg
Message publishing is a mechanism of connecting heterogeneous purposes including messages which are routed among them, for instance by utilizing a message dealer like Apache Kafka. Such suggestions take care of real-time volumes of knowledge and course it to a number of shoppers with no letting details manufacturers be aware of who the ultimate shoppers are.
Apache Kafka is a realistic, hands-on consultant supplying you with a chain of step by step functional implementations, as a way to assist you reap the benefits of the genuine energy in the back of Kafka, and provides you a powerful grounding for utilizing it on your publisher-subscriber dependent architectures.
Apache Kafka takes you thru a couple of transparent, useful implementations to help you to exploit the ability of Apache Kafka, speedy and painlessly. you are going to research every little thing you want to be aware of for constructing Kafka clusters. This ebook explains how Kafka easy blocks like manufacturers, agents, and shoppers really paintings and healthy jointly. you'll then discover extra settings and configuration adjustments to accomplish ever extra advanced objectives. eventually you are going to find out how Kafka works with different instruments like Hadoop, hurricane, and so on.
You will examine every thing you want to be aware of to paintings with Apache Kafka within the correct structure, in addition to how you can leverage its strength of dealing with thousands of megabytes of messages in keeping with moment from a number of consumers.
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Additional info for Apache Kafka
On the consumer side, all the pulling of messages is done from the lead replica. • Asynchronous replication: The only difference in this mode is that as soon as a lead replica writes the message to its local log, it sends the acknowledgement to the message client and does not wait for the acknowledgements from follower replicas. But as a down side, this mode does not ensure the message delivery in case of broker failure. org/confluence/display/KAFKA/ Kafka+Replication. Summary In this chapter, we have learned the design concepts used for building a solid foundation for Kafka.
For testing purposes, all the commands will remain identical to the ones we used in the single node – multiple brokers cluster. The following diagram shows the cluster scenario where multiple brokers are configured on multiple nodes (Node 1 and Node 2 in this case), and the producers and consumers are getting connected in different combinations: Single Node - Single Kafka Broker ZooKeeper Node 1 Producers Broker 1 Consumers Broker 2 Producers Consumers Node 2 Broker 1 Producers Consumers Broker 2 [ 25 ] Setting up the Kafka Cluster Kafka broker property list The following is the list of few important properties that can be configured for the Kafka broker.
Java consumer API Kafka provides two types of API for Java consumers: • The high-level consumer API • The simple consumer API The high-level consumer API provides an abstraction over the lowlevel implementation of the consumer API, whereas the simple consumer API provides more control to the consumer by allowing it to override its default low-level implementation. High-level consumer API The high-level consumer API is used when only data is needed and the handling of message offsets is not required.
Apache Kafka by Nishant Garg