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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):

Ankit Jain

View More author details

Table of Contents (13) Chapters

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

Monitoring of Storm Cluster

In the previous chapters, we learned how we can deploy topologies on remote Storm clusters, how we can configure the parallelism of a topology, the different types of stream grouping, and so on. In this chapter, we will focus on how we can monitor and collect the statistics of topologies running on Storm clusters.

In this chapter, we will be covering the following topics:

Collecting Storm metrics through the Nimbus thrift port
Integration of Storm with Ganglia
Installation of Graphite

The rest of the chapter is locked

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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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