Streaming Data (Paperback)

Andrew Psaltis

ISBN 10: 1617292281 / ISBN 13: 9781617292286

Published by Manning Publications, New York, 2017

About this Item

Paperback. DESCRIPTION Many of the technologies discussed in the bookSpark, 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. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

Seller Inventory # 9781617292286

Bibliographic Details

• Title: Streaming Data (Paperback)
• Publisher: Manning Publications, New York
• Publication Date: 2017
• Language: English
• ISBN 10: 1617292281
• ISBN 13: 9781617292286
• Binding: Paperback
• Condition: new

About this title

Synopsis

Summary

Streaming Data introduces the concepts and requirements of streaming and real-time data systems. The book is an idea-rich tutorial that teaches you to think about how to efficiently interact with fast-flowing data.

Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.

About the Technology

As humans, we're constantly filtering and deciphering the information streaming toward us. In the same way, streaming data applications can accomplish amazing tasks like reading live location data to recommend nearby services, tracking faults with machinery in real time, and sending digital receipts before your customers leave the shop. Recent advances in streaming data technology and techniques make it possible for any developer to build these applications if they have the right mindset. This book will let you join them.

About the Book

Streaming Data is an idea-rich tutorial that teaches you to think about efficiently interacting with fast-flowing data. Through relevant examples and illustrated use cases, you'll explore designs for applications that read, analyze, share, and store streaming data. Along the way, you'll discover the roles of key technologies like Spark, Storm, Kafka, Flink, RabbitMQ, and more. This book offers the perfect balance between big-picture thinking and implementation details.

What's Inside

• The right way to collect real-time data
• Architecting a streaming pipeline
• Analyzing the data
• Which technologies to use and when

About the Reader

Written for developers familiar with relational database concepts. No experience with streaming or real-time applications required.

About the Author

Andrew Psaltis is a software engineer focused on massively scalable real-time analytics.

Table of Contents

PART 1 - A NEW HOLISTIC APPROACH

1. Introducing streaming data
2. Getting data from clients: data ingestion
3. Transporting the data from collection tier: decoupling the data pipeline
4. Analyzing streaming data
5. Algorithms for data analysis
6. Storing the analyzed or collected data
7. Making the data available
8. Consumer device capabilities and limitations accessing the data

PART 2 - TAKING IT REAL WORLD

9. Analyzing Meetup RSVPs in real time

About the Author

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.