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Learning Apache Storm for Big Data Processing

Learning Apache Storm for Big Data Processing

By : Prashant Nair
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Learning Apache Storm for Big Data Processing

Learning Apache Storm for Big Data Processing

By: Prashant Nair

Overview of this book

Apache Storm is a distributed real-time processing engine. Created by Nathanmarz for Backtype and later open sourced under Apache License 2, it's a scalable and a fault-tolerant engine used to process a massive number of unbounded streams. In this course you will see how simple yet efficient Apache Storm is when it comes to real-time processing. In the course, you will learn about data processing types followed by Apache Storm and its features. You'll learn the core concepts of Apache Storm such as spouts, bolts, topology, and stream grouping, and set up Apache Storm in single-node and multi-node configurations. Also you'll explore how fault-tolerant Apache Storm is. Taking this course will kick-start your experience with Apache Storm; you'll create a scalable, fault-tolerant, real-time processing application while setting a strong base for the fundamentals of the real-time processing paradigm and Apache Storm. All the code and supporting files for the course can be found here- https://github.com/PacktPublishing/Learning-Apache-Storm-for-Big-Data-Processing
Table of Contents (9 chapters)
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8
Integrating Hadoop with Apache Storm
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Chapter: 3
Setting Up Your Apache Storm Development Environment
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Learning Apache Storm for Big Data Processing
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