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Building Data Streaming Applications with Apache Kafka

You're reading from   Building Data Streaming Applications with Apache Kafka Design, develop and streamline applications using Apache Kafka, Storm, Heron and Spark

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Product type Paperback
Published in Aug 2017
Publisher Packt
ISBN-13 9781787283985
Length 278 pages
Edition 1st Edition
Tools
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Authors (2):
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Chanchal Singh Chanchal Singh
Author Profile Icon Chanchal Singh
Chanchal Singh
Manish Kumar Manish Kumar
Author Profile Icon Manish Kumar
Manish Kumar
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Table of Contents (14) Chapters Close

Preface 1. Introduction to Messaging Systems FREE CHAPTER 2. Introducing Kafka the Distributed Messaging Platform 3. Deep Dive into Kafka Producers 4. Deep Dive into Kafka Consumers 5. Building Spark Streaming Applications with Kafka 6. Building Storm Applications with Kafka 7. Using Kafka with Confluent Platform 8. Building ETL Pipelines Using Kafka 9. Building Streaming Applications Using Kafka Streams 10. Kafka Cluster Deployment 11. Using Kafka in Big Data Applications 12. Securing Kafka 13. Streaming Application Design Considerations

Replication and replicated logs

Replication is one of the most important factors in achieving reliability for Kafka systems. Replicas of message logs for each topic partition are maintained across different servers in a Kafka cluster. This can be configured for each topic separately. What it essentially means is that for one topic, you can have the replication factor as 3 and for another, you can use 5. All the reads and writes happen through the leader; if the leader fails, one of the followers will be elected as leader.

Generally, followers keep a copy of the leader's log, which means that the leader does not make the message as committed until it receives acknowledgment from all the followers. There are different ways that the log replication algorithm has been implemented; it should ensure that, if leader tells the producer that the message is committed, it must be available...

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