What this book covers

Chapter 1, Getting Acquainted with Storm, provides detailed information about Storm's use cases, different installation modes, and configuration in Storm.

Chapter 2, The Storm Anatomy, tells you about Storm-specific terminologies, processes, fault tolerance in Storm, tuning parallelism in Storm, and guaranteed tuple processing, with detailed explanations about each of these.

Chapter 3, Introducing Petrel, introduces a framework called Petrel for building Storm topologies in Python. This chapter walks through the installation of Petrel and includes a simple example.

Chapter 4, Example Topology – Twitter, provides an in-depth example of a topology that computes statistics on Twitter data in real time. The example introduces the use of tick tuples, which are useful for topologies that need to compute statistics or do other things on a schedule. In this chapter, you also see how topologies can access configuration data.

Chapter 5, Persistence Using Redis and MongoDB, updates the sample Twitter topology for the use of Redis, a popular key-value store. It shows you how to simplify the complex Python calculation logic with built-in Redis operations. The chapter concludes with an example of storing Twitter data in MongoDB, a popular NoSQL database, and using its aggregation capabilities to generate reports.

Chapter 6, Petrel in Practice, teaches practical skills that will make developers more productive using Storm. You learn how to use Petrel to create automated tests for your spout and bolt components that run outside of Storm. You also see how to use a graphical debugger to debug a topology running inside Storm.

Appendix, Managing Storm Using Supervisord, is a practical demonstration of monitoring and control of Storm using a supervisor over the cluster.