DESCRIPTION Many of the technologies discussed in the book—Spark, Storm, Kafka, Impala, RabbitMQ, etc.—are covered individually in other books. Throughout this book, readers will get a clear picture of how these technologies work individually and together, gain insight on how to choose the correct technologies, and discover how to fuse them together to architect a robust system. Streaming Data introduces the concepts and requirements of streaming and real-time data systems. Readers will develop a foundation to understand the challenges and solutions of building in-the-moment data systems before committing to specific technologies. Using lots of diagrams, this book systematically builds up the blueprint for an inthe- moment system concept by concept. This book focuses on the big ideas of streaming and real time data systems rather than the implementation details. KEY FEATURES • Lots of diagrams to explain concepts • Collecting and analyzing data in real time • Uses running examples • Explains how to combine emerging technologies AUDIENCE No experience with streaming or real-time data systems required. Perfect for developers or architects, this book is also written to be accessible to technical managers and business decision makers. Competancy in the Java programming language is recomended. ABOUT THE TECHNOLOGY Applications built to deal with streaming data present fundamentally different challenges than those that work with stored data. For example, live location data paired with a social media profile might allow a vendor to recommend a product or service to a user at just the right instant, and the split-nanosecond reaction of a pacemaker or anti-lock brakes can save lives. Emerging techniques and technologies that enable you to take immediate action on streaming data make it possible to design and build in-the-moment decision systems, dynamic reporting dashboards, live recommendation systems, and other real-time applications.
