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Mastering Apache Storm

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

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Product type Paperback
Published in Aug 2017
Publisher
ISBN-13 9781787125636
Length 284 pages
Edition 1st Edition
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Author (1):
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Ankit Jain Ankit Jain
Author Profile Icon Ankit Jain
Ankit Jain
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Table of Contents (13) Chapters Close

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

Integration of Storm with Hadoop

The probability that the organizations developing and operating big data applications already have a Hadoop cluster deployed is very high. Also, there is a high possibility that they also have real-time stream processing applications deployed to go along with the batch applications running on Hadoop.

It would be great if we can leverage the already deployed YARN cluster to also run the Storm topologies. This will reduce the operational cost of maintenance by giving you only one cluster to manage instead of two.

Storm-YARN is a project developed by Yahoo! that enables the deployment of Storm topologies over YARN clusters. It enables the deployment of Storm processes on nodes managed by YARN.

The following diagram illustrates how the Storm processes are deployed on YARN:

Figure 6: Storm processes on YARN

In the next section, we will see how to set...

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