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Mastering Apache Storm

You're reading from Mastering Apache Storm

Product type Book

Published in Aug 2017

Publisher

ISBN-13 9781787125636

Pages 284 pages

Edition 1st Edition

Languages

Concepts

Data Processing

Author (1):

Ankit Jain

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

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

Chapter 9. Storm and Hadoop Integration

So far, we have seen how Storm can be used for developing real-time stream processing applications. In general, these real-time applications are seldom used in isolation; they are more often than not used in combination with other batch processing operations.

The most common platform for developing batch jobs is Apache Hadoop. In this chapter, we will see how applications built with Apache Storm can be deployed over existing Hadoop clusters with the help of a Storm-YARN framework for optimized use and management of resources. We will also cover how we can write the process data into HDFS by creating an HDFS bolt in Storm.

In this chapter, we will cover the following topics:

Overview of Apache Hadoop and its various components
Setting up a Hadoop cluster
Write Storm topology to persist data into HDFS
Overview of Storm-YARN
Deploying Storm-YARN on Hadoop
Running a storm application on Storm-YARN.

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Authors (1)

Ankit 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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