Streaming Data. Questo articolo non è disponibile.
Lingua: inglese
Editore: Manning, 2017
- Brossura
- Usato
Condizione: Usato - Molto buono
EUR 25,36
Descrizione dell’articolo da parte del venditore
Gut/Very good: Buch bzw. Schutzumschlag mit wenigen Gebrauchsspuren an Einband, Schutzumschlag oder Seiten. / Describes a book or dust jacket that does show some signs of wear on either the binding, dust jacket or pages.
Codice articolo M01617292281-V
- Titolo
- Streaming Data
- Autore
- Psaltis, Andrew G.
- Editore
- Manning
- Anno di pubblicazione
- 2017
- Condizione
- very good
- Rilegatura
- Brossura
- Lingua
- inglese
- ISBN 10
- 1617292281
- ISBN 13
- 9781617292286
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
- Introducing streaming data
- Getting data from clients: data ingestion
- Transporting the data from collection tier: decoupling the data pipeline
- Analyzing streaming data
- Algorithms for data analysis
- Storing the analyzed or collected data
- Making the data available
- Consumer device capabilities and limitations accessing the data
- Analyzing Meetup RSVPs in real time
PART 1 - A NEW HOLISTIC APPROACH
PART 2 - TAKING IT REAL WORLD
"Riassunto" può appartenere a un’altra edizione di questo titolo.
Informazioni sull’autore
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.
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.
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