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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

Storm Deployment, Topology Development, and Topology Options

In this chapter, we are going to start with deployment of Storm on multiple node (three Storm and three ZooKeeper) clusters. This chapter is very important because it focuses on how we can set up the production Storm cluster and why we need the high availability of both the Storm Supervisor, Nimbus, and ZooKeeper (as Storm uses ZooKeeper for storing the metadata of the cluster, topology, and so on)?

The following are the key points that we are going to cover in this chapter:

  • Deployment of the Storm cluster
  • Program and deploy the word count example
  • Different options of the Storm UI--kill, active, inactive, and rebalance
  • Walkthrough of the Storm UI
  • Dynamic log level settings
  • Validating the Nimbus high availability
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