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Streaming Data: Understanding the real-time pipeline, Andrew Psaltis

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Streaming Data: Understanding the real-time pipeline, Andrew Psaltis - фото 1 - id-p2186816638

Характеристики и описание

Друкчорно-білий
ЯзыкEnglish
ОбложкаМягкая
Папірбілий, офсет
Рік2017
Состояниенова книга
Сторінок216

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.

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

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

PART 2 - TAKING IT REAL WORLD

Analyzing Meetup RSVPs in real time

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