Book Image

Building Python Real-Time Applications with Storm

By : Kartik Bhatnagar, Barry Hart
Book Image

Building Python Real-Time Applications with Storm

By: Kartik Bhatnagar, Barry Hart

Overview of this book

Big data is a trending concept that everyone wants to learn about. With its ability to process all kinds of data in real time, Storm is an important addition to your big data “bag of tricks.” At the same time, Python is one of the fastest-growing programming languages today. It has become a top choice for both data science and everyday application development. Together, Storm and Python enable you to build and deploy real-time big data applications quickly and easily. You will begin with some basic command tutorials to set up storm and learn about its configurations in detail. You will then go through the requirement scenarios to create a Storm cluster. Next, you’ll be provided with an overview of Petrel, followed by an example of Twitter topology and persistence using Redis and MongoDB. Finally, you will build a production-quality Storm topology using development best practices.
Table of Contents (14 chapters)

Chapter 2. The Storm Anatomy

This chapter gives a detailed view of the internal structure and processes of the Storm technology. We will cover the following topics in this chapter:

  • Storm processes

  • Storm-topology-specific terminologies

  • Interprocess communication

  • Fault tolerance in Storm

  • Guaranteed tuple processing

  • Parallelism in Storm—scaling a distributed computation

As we advance through the chapter, you will understand Storm's processes and their role in detail. In this chapter, various Storm-specific terminologies will be explained. You will learn how Storm achieves fault tolerance for different types of failure. We will see what guaranteed message processing is and, most importantly, how to configure parallelism in Storm to achieve fast and reliable processing.