Description
Book SynopsisDESCRIPTION
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.
