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Mastering Apache Storm

You're reading from Mastering Apache Storm Real-time big data streaming using Kafka, Hbase and Redis

Product type Paperback

Published in Aug 2017

Publisher

ISBN-13 9781787125636

Length 284 pages

Edition 1st Edition

Languages

Java

Tools

Apache Storm

Concepts

Big Data

Author (1):

Jain

View More author details

Table of Contents (19) Chapters

Title Page

Credits

About the Author

About the Reviewers

www.PacktPub.com

Customer Feedback

Preface

1. Real-Time Processing and Storm Introduction FREE CHAPTER

2. Storm Deployment, Topology Development, and Topology Options

3. Storm Parallelism and Data Partitioning

4. Trident Introduction

5. Trident Topology and Uses

6. Storm Scheduler

7. Monitoring of Storm Cluster

8. Integration of Storm and Kafka

9. Storm and Hadoop Integration

10. Storm Integration with Redis, Elasticsearch, and HBase

11. Apache Log Processing with Storm

12. Twitter Tweet Collection and Machine Learning

Introduction to Hadoop

Apache Hadoop is an open source platform for developing and deploying big data applications. It was initially developed at Yahoo! based on the MapReduce and Google File System papers published by Google. Over the past few years, Hadoop has become the flagship big data platform.

In this section, we will discuss the key components of a Hadoop cluster.

Hadoop Common

This is the base library on which other Hadoop modules are based. It provides an abstraction for OS and filesystem operations so that Hadoop can be deployed on a variety of platforms.

Hadoop Distributed File System

Commonly known as HDFS, the Hadoop Distributed File System is a scalable, distributed, fault-tolerant filesystem. HDFS acts as the storage layer of the Hadoop ecosystem. It allows the sharing and storage of data and application code among the various nodes in a Hadoop cluster.

The following are the key assumptions taken while designing HDFS:

It should be deployable on a cluster of commodity hardware.
Hardware...

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Authors (1)

Jain

Jain

Ankit Jain holds a bachelor's degree in computer science and engineering. He has 6 years, experience in designing and architecting solutions for the big data domain and has been involved with several complex engagements. His technical strengths include Hadoop, Storm, S4, HBase, Hive, Sqoop, Flume, Elasticsearch, machine learning, Kafka, Spring, Java, and J2EE. He also shares his thoughts on his personal blog. You can follow him on Twitter at @mynameisanky. He spends most of his time reading books and playing with different technologies. When not at work, he spends time with his family and friends watching movies and playing games.

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