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Practical Real-time Data Processing and Analytics

You're reading from   Practical Real-time Data Processing and Analytics Distributed Computing and Event Processing using Apache Spark, Flink, Storm, and Kafka

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Product type Paperback
Published in Sep 2017
Publisher Packt
ISBN-13 9781787281202
Length 360 pages
Edition 1st Edition
Languages
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Authors (2):
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Shilpi Saxena Shilpi Saxena
Author Profile Icon Shilpi Saxena
Shilpi Saxena
Saurabh Gupta Saurabh Gupta
Author Profile Icon Saurabh Gupta
Saurabh Gupta
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Table of Contents (14) Chapters Close

Preface 1. Introducing Real-Time Analytics FREE CHAPTER 2. Real Time Applications – The Basic Ingredients 3. Understanding and Tailing Data Streams 4. Setting up the Infrastructure for Storm 5. Configuring Apache Spark and Flink 6. Integrating Storm with a Data Source 7. From Storm to Sink 8. Storm Trident 9. Working with Spark 10. Working with Spark Operations 11. Spark Streaming 12. Working with Apache Flink 13. Case Study

Setting up infrastructure for data ingestion

There are multiple tools and frameworks available on the market for data ingestion. We will discuss the following in the scope of this book:

  • Apache Kafka
  • Apache NiFi
  • Logstash
  • Fluentd
  • Apache Flume

Apache Kafka

Kafka is message broker which can be connected to any real-time framework available on the market. In this book, we will use Kafka often for all types of examples. We will use Kafka as a data source which keeps data from files in queues for further processing. Download Kafka from https://www.apache.org/dyn/closer.cgi?path=/kafka/0.10.1.1/kafka_2.11-0.10.1.1.tgz to your local machine. Once the kafka_2.11-0.10.1.1.tgz file is downloaded, extract the files using the following...

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