In this chapter, you learned some skills that will help make you more productive building your own topologies. As you develop spouts or bolts, you can test them individually before assembling them into a complete topology and deploying on Storm. If you encounter a tricky problem that occurs only while running in Storm, you can use Winpdb in addition to (or instead of) log messages. When your code is working, you can get insights into which components take most of the time, so you can focus on improving performance in those areas. With these skills, you are now ready to go out and build your own topologies. Good luck!
Building Python Real-Time Applications with Storm
By :
Building Python Real-Time Applications with Storm
By:
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)
Building Python Real-Time Applications with Storm
Credits
About the Authors
About the Reviewers
www.PacktPub.com
Preface
Free Chapter
Getting Acquainted with Storm
The Storm Anatomy
Introducing Petrel
Example Topology – Twitter
Persistence Using Redis and MongoDB
Petrel in Practice
Managing Storm Using Supervisord
Index
Customer Reviews