Pro Apache Phoenix e-bog
230,54 DKK
(inkl. moms 288,18 DKK)
Leverage Phoenix as an ANSI SQL engine built on top of the highly distributed and scalable NoSQL framework HBase. Learn the basics and best practices that are being adopted in Phoenix to enable a high write and read throughput in a big data space. This book includes real-world cases such as Internet of Things devices that send continuous streams to Phoenix, and the book explains how key fe...
E-bog
230,54 DKK
Forlag
Apress
Udgivet
29 december 2016
Genrer
Open source and other operating systems
Sprog
English
Format
epub
Beskyttelse
LCP
ISBN
9781484223703
Leverage Phoenix as an ANSI SQL engine built on top of the highly distributed and scalable NoSQL framework HBase. Learn the basics and best practices that are being adopted in Phoenix to enable a high write and read throughput in a big data space. This book includes real-world cases such as Internet of Things devices that send continuous streams to Phoenix, and the book explains how key features such as joins, indexes, transactions, and functions help you understand the simple, flexible, and powerful API that Phoenix provides. Examples are provided using real-time data and data-driven businesses that show you how to collect, analyze, and act in seconds. Pro Apache Phoenix covers the nuances of setting up a distributed HBase cluster with Phoenix libraries, running performance benchmarks, configuring parameters for production scenarios, and viewing the results. The book also shows how Phoenix plays well with other key frameworks in the Hadoop ecosystem such as Apache Spark, Pig, Flume, and Sqoop.You will learn how to:Handle a petabyte data store by applying familiar SQL techniquesStore, analyze, and manipulate data in a NoSQL Hadoop echo system with HBaseApply best practices while working with a scalable data store on Hadoop and HBaseIntegrate popular frameworks (Apache Spark, Pig, Flume) to simplify big data analysisDemonstrate real-time use cases and big data modeling techniquesWho This Book Is ForData engineers, Big Data administrators, and architects.