Streaming Data: Understanding the real-time pipeline

Psaltis, Andrew

ISBN 10: 1617292281 / ISBN 13: 9781617292286

Edité par Manning, 2017

A propos de cet article

This is a Brand-new US Edition. This Item may be shipped from US or any other country as we have multiple locations worldwide.

N° de réf. du vendeur ABNR-29178

Détails bibliographiques

• Titre: Streaming Data: Understanding the real-time pipeline
• Éditeur: Manning
• Date de parution: 2017
• Langue: anglais
• ISBN à 10 chiffres: 1617292281
• ISBN à 13 chiffres: 9781617292286
• Reliure: Couverture souple
• État de l'article: New

A propos de ce titre

Synopsis

Cert article n est plus en solde !

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.

À propos de l?auteur

Andrew Psaltis is a software engineer and architect focused full time on building massively scalable real-time analytics systems using Spark, Kafka, Storm, Hadoop, and WebSockets.