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Mastering Apache Storm

You're reading from  Mastering Apache Storm

Product type Book
Published in Aug 2017
Publisher
ISBN-13 9781787125636
Pages 284 pages
Edition 1st Edition
Languages
Author (1):
Ankit Jain Ankit Jain
Profile icon Ankit Jain

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 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

Parallelism of a topology


Parallelism means the distribution of jobs on multiple nodes/instances where each instance can work independently and can contribute to the processing of data. Let's first look at the processes/components that are responsible for the parallelism of a Storm cluster.

Worker process

A Storm topology is executed across multiple supervisor nodes in the Storm cluster. Each of the nodes in the cluster can run one or more JVMs called worker processes, which are responsible for processing a part of the topology.

A worker process is specific to one of the specific topologies and can execute multiple components of that topology. If multiple topologies are being run at the same time, none of them will share any of the workers, thus providing some degree of isolation between topologies.

Executor

Within each worker process, there can be multiple threads executing parts of the topology. Each of these threads is called an executor. An executor can execute only one of the components...

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