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Pro Apache Phoenix, Akhtar


Варианты приобретения
Цена: 25150.00T
Кол-во:
Наличие: Поставка под заказ.  Есть в наличии на складе поставщика.
Склад Америка: 236 шт.  
При оформлении заказа до: 2025-12-15
Ориентировочная дата поставки: Январь
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Автор: Akhtar
Название:  Pro Apache Phoenix
ISBN: 9781484223697
Издательство: Springer
Классификация:
ISBN-10: 1484223691
Обложка/Формат: Paperback
Страницы: 140
Вес: 0.26 кг.
Дата издания: 2017
Язык: English
Иллюстрации: 13 black & white illustrations, 95 colour illustrations, biography
Размер: 197 x 134 x 7
Читательская аудитория: Professional & vocational
Основная тема: Professional Computing
Подзаголовок: An SQL Driver for HBase
Ссылка на Издательство: Link
Рейтинг:
Поставляется из: Германии
Описание:
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 techniques
Who This Book Is For
Data engineers, Big Data administrators, and architects.

Дополнительное описание:
Chapter 1:Introduction to Big Data Analytics.- Chapter 2:Using Phoenix for HBase.- Chapter 3:Performing CRUD operations using phoenix.- Chapter 4:Advance Querying.- Chapter 5:Transactions.- Chapter 6:Advance Phoenix concepts.- Chapter 7:Performance T


Beginning Apache Pig

Автор: Vaddeman
Название: Beginning Apache Pig
ISBN: 1484223365 ISBN-13(EAN): 9781484223369
Издательство: Springer
Рейтинг:
Цена: 25150.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:

Learn to use Apache Pig to develop lightweight big data applications easily and quickly. This book shows you many optimization techniques and covers every context where Pig is used in big data analytics. Beginning Apache Pig shows you how Pig is easy to learn and requires relatively little time to develop big data applications.
The book is divided into four parts: the complete features of Apache Pig; integration with other tools; how to solve complex business problems; and optimization of tools.
You'll discover topics such as MapReduce and why it cannot meet every business need; the features of Pig Latin such as data types for each load, store, joins, groups, and ordering; how Pig workflows can be created; submitting Pig jobs using Hue; and working with Oozie. You'll also see how to extend the framework by writing UDFs and custom load, store, and filter functions. Finally you'll cover different optimization techniques such as gathering statistics about a Pig script, joining strategies, parallelism, and the role of data formats in good performance.
What You Will Learn
• Use all the features of Apache Pig
• Integrate Apache Pig with other tools
• Extend Apache Pig
• Optimize Pig Latin code
• Solve different use cases for Pig Latin
Who This Book Is For
All levels of IT professionals: architects, big data enthusiasts, engineers, developers, and big data administrators


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