Storm Applied is a practical guide to using Apache Storm for the real-world tasks associated with processing and analyzing real-time data streams. This immediately useful book starts by building a solid foundation of Storm essentials so that you learn how to think about designing Storm solutions the right way from day one. But it quickly dives into real-world case studies that will bring the novice up to speed with productionizing Storm.
About the Technology
It's hard to make sense out of data, when it's coming at you fast. Like Hadoop, Storm processes large amounts of data but it does it reliably and in real time, guaranteeing that every message will be, processed. Storm allows you to scale with your data as it grows, making it an excellent platform to solve your big data problems.
Storm Applied is an example-driven guide to processing and analyzing real-time data streams. This immediately useful book starts by teaching you how to design Storm solutions the right way. Then, it quickly dives into real-world case studies that show you how to scale a high-throughput stream processor, ensure smooth operation within a production cluster, and more. Along the way, you'll learn to use Trident for stateful stream processing, along with other tools from the Storm ecosystem.
This book moves through the basics quickly. While prior experience with Storm is not, assumed, some experience with big data and real-time systems is helpful.
What's Inside • Mapping real problems to Storm components • Performance tuning and scaling • Practical troubleshooting and debugging • Exactly-once processing with Trident
Table of Contents • Introducing Storm • Core Storm concepts • Topology design • Creating robust topologies • Moving from local to remote topologies • Tuning in Storm • Resource contention • Storm internals • Trident
