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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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Toc

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

Trident repartitioning operations

By performing repartitioning operations, a user can partition tuples across multiple tasks. The repartitioning operation doesn't make any changes to the content of the tuples. Also, the tuples will only pass over the network for the repartitioning operation. Here are the different types of repartitioning operation.

Utilizing shuffle operation

This repartitioning operation partitions the tuples in a uniform, random way across multiple tasks. This repartitioning operation is generally used when we want to distribute the processing load uniformly across the tasks. The following diagram shows how the input tuples are repartitioned using the shuffle operation:

Here is a piece of code...

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