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)

About the Reviewers

Oscar Campos has been working with Python since early 2007. He is the author of the famous Anaconda Python IDE package for Sublime Text 3, available as free software at http://github.com/DamnWidget/anaconda.

He currently works as a senior software engineer on EXADS, programming high-concurrency backend system applications in Golang.

Oscar has also reviewed PySide GUI Application Development, Packt Publishing.

Pavan Narayanan is a blogger at DataScience Hacks (https://datasciencehacks.wordpress.com), experienced in developing mathematical programming and data analytics solutions. He has utilized Apache Storm for developing real-time analytics prototype and his interests are exploring problem solving techniques, from industrial mathematics to machine learning. He can be reached at .

Pavan has also reviewed Apache Mahout Essentials, Learning Apache Mahout Classification, and Mastering Machine Learning with R, all by Packt Publishing.