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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

Building Storm Applications with Kafka

In the previous chapter, we learned about Apache Spark, a near real-time processing engine which can process data in micro batches. But when it comes to very low latency applications, where seconds of delay may cause big trouble, Spark may not be a good fit for you. You would need a framework which can handle millions of records per second and you would want to process record by record, instead of processing in batches, for lower latency. In this chapter, we will learn about the real-time processing engine, Apache Storm. Storm was first designed and developed by Twitter, which later became an open source Apache project.

In this chapter, we will learn about:

  • Introduction to Apache Storm
  • Apache Storm architecture
  • Brief overview of Apache Heron
  • Integrating Apache Storm with Apache Kafka (Java/Scala example)
  • Use case (log processing)
...
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