Book Image

Mastering Apache Storm

By : Ankit Jain
Book Image

Mastering Apache Storm

By: Ankit Jain

Overview of this book

Apache Storm is a real-time Big Data processing framework that processes large amounts of data reliably, guaranteeing that every message will be processed. Storm allows you to scale your data as it grows, making it an excellent platform to solve your big data problems. This extensive guide will help you understand right from the basics to the advanced topics of Storm. The book begins with a detailed introduction to real-time processing and where Storm fits in to solve these problems. You’ll get an understanding of deploying Storm on clusters by writing a basic Storm Hello World example. Next we’ll introduce you to Trident and you’ll get a clear understanding of how you can develop and deploy a trident topology. We cover topics such as monitoring, Storm Parallelism, scheduler and log processing, in a very easy to understand manner. You will also learn how to integrate Storm with other well-known Big Data technologies such as HBase, Redis, Kafka, and Hadoop to realize the full potential of Storm. With real-world examples and clear explanations, this book will ensure you will have a thorough mastery of Apache Storm. You will be able to use this knowledge to develop efficient, distributed real-time applications to cater to your business needs.
Table of Contents (19 chapters)
Title Page
Credits
About the Author
About the Reviewers
www.PacktPub.com
Customer Feedback
Preface

Trident groupBy operation


The groupBy operation doesn't involve any repartitioning. The groupBy operation converts the input stream into a grouped stream. The main function of the groupBy operation is to modify the behavior of subsequent aggregate functions.

groupBy before partitionAggregate

If the groupBy operation is used before a partitionAggregate, then the partitionAggregate will run the aggregate on each group created within the partition.

groupBy before aggregate

If the groupBy operation is used before an aggregate, then input tuples is first repartition and then perform the aggregate operation on each group.