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.
What You Will Learn
- Install Storm and learn about the prerequisites
- Get to know the components of a Storm topology and how to control the flow of data between them
- Ingest Twitter data directly into Storm
- Use Storm with MongoDB and Redis
- Build topologies and run them in Storm
- Use an interactive graphical debugger to debug your topology as it’s running in Storm
- Test your topology components outside of Storm
- Configure your topology using YAML