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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

The different options of the Storm topology

This section covers the following operations that a user can perform on the Storm cluster:

Deactivate
Activate
Rebalance
Kill
Dynamic log level settings

Deactivate

Storm supports the deactivating a topology. In the deactivated state, spouts will not emit any new tuples into the pipeline, but the processing of the already emitted tuples will continue. The following is the command to deactivate the running topology:

$> bin/storm deactivate topologyName

Deactivate SampleStormClusterTopology using the following command:

bin/storm deactivate SampleStormClusterTopology

The following information is displayed:

0 [main] INFO backtype.storm.thrift - Connecting to Nimbus at localhost:6627 76 [main] INFO backtype.storm.command.deactivate - Deactivated topology: SampleStormClusterTopology

Activate

Storm also the supports activating a topology. When a topology is activated, spouts will again start emitting tuples. The following is the command to activate the topology:

...

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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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