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
About the Author
About the Reviewers
Customer Feedback

Utilizing the 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 the subsequent aggregate function. The following diagram shows how the groupBy operation groups the tuples of a single partition:

The behavior of groupBy is dependent on a position where it is used. The following behavior is possible:

  • If the groupBy operation is used before a partitionAggregate, then the partitionAggregate will run the aggregate on each group created within the partition.
  • If the groupBy operation is used before an aggregate, the tuples of the same batch are first repartitioned into a single partition, then groupBy is applied to each single partition, and at the end it will perform the aggregate operation on each group.