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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

Concepts

Data Processing

Author (1):

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

Writing Trident functions, filters, and projections

This section covers the definition of Trident functions, filters, and projections. Trident functions, filters, and projections are used to modify/filter the input tuples based on certain criteria. This section also covers how we can write Trident functions, filters, and projections.

Trident function

Trident functions contain logic to modify the original tuple. A Trident function gets a set of fields of the tuple as input and emits one or more tuples as output. The fields of the output tuples are merged with the fields of the input tuple to form the complete tuple, which will pass to the next action in the topology. If the Trident function emits no tuples corresponding to the input tuple, then that tuple is removed from the stream.

We can write a custom Trident function by extending the storm.trident.operation.BaseFunction class and implementing the execute(TridentTuple tuple, TridentCollector collector) method.

Let's write the sample Trident...

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Authors (1)

Ankit Jain

Ankit Jain holds a bachelor's degree in computer science and engineering. He has 6 years, experience in designing and architecting solutions for the big data domain and has been involved with several complex engagements. His technical strengths include Hadoop, Storm, S4, HBase, Hive, Sqoop, Flume, Elasticsearch, machine learning, Kafka, Spring, Java, and J2EE. He also shares his thoughts on his personal blog. You can follow him on Twitter at @mynameisanky. He spends most of his time reading books and playing with different technologies. When not at work, he spends time with his family and friends watching movies and playing games.

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