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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

Default scheduler

The Storm default scheduler assigns component executors as evenly as possible between all the workers (supervisor slots) assigned to a given topology.

Let's consider a sample topology with one spout and one bolt, with both components having two executors. The following diagram shows the assignment of executors if we have submitted the topology by allocating two workers (supervisor slots):

As shown in the preceding diagram, each worker node contains one executor for a spout and one executor for a bolt. The even distribution of executors between workers is only possible if the number of executors in each component is divisible by the number of workers assigned to a topology.

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