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

Product type Paperback

Published in Aug 2017

Publisher Packt

ISBN-13 9781787283985

Length 278 pages

Edition 1st Edition

Tools

Kafka

Concepts

Data Analysis

Authors (2):

Chanchal Singh

Manish Kumar

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Table of Contents (14) Chapters

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

Understanding Kafka Connect and Kafka Stream

Kafka Connect is a tool that provides the ability to move data into and out of the Kafka system. Thousands of use cases use the same kind of source and target system while using Kafka. Kafka Connect is comprised of Connectors for those common source or target systems.

Kafka Connect consists of a set of Connectors, and the Connectors are of two types:

Import Connectors: Import Connectors are used to bring data from the source system into Kafka topics. These Connectors accept configuration through property files and bring data into a Kafka topic in any way you wish. You don't need to write your own producer to do such jobs. A few of the popular Connectors are JDBC Connector, file Connector, and so on.
Export Connectors: Unlike Import Connectors, Export Connectors are used to copy data from Kafka topics to the target system. This...

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Authors (2)

Singh

Contacted on 12/01/18 by Davis Anto

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Kumar

Ashish Kumar is a seasoned data science professional, a publisher author and a thought leader in the field of data science and machine learning. An IIT Madras graduate and a Young India Fellow, he has around 7 years of experience in implementing and deploying data science and machine learning solutions for challenging industry problems in both hands-on and leadership roles. Natural Language Procession, IoT Analytics, R Shiny product development, Ensemble ML methods etc. are his core areas of expertise. He is fluent in Python and R and teaches a popular ML course at Simplilearn. When not crunching data, Ashish sneaks off to the next hip beach around and enjoys the company of his Kindle. He also trains and mentors data science aspirants and fledgling start-ups.

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