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Название: AWS Cookbook: Building Practical Solutions with AWS (Third Early Release)
Автор: John Culkin, Mike Zazon
Издательство: O’Reilly Media, Inc.
Год: 2021-04-14
Страниц: 206
Язык: английский
Формат: epub
Размер: 10.2 MB

This practical guide provides over 100 self-contained recipes to help you creatively solve issues you may encounter in your AWS cloud endeavors. If you're comfortable with rudimentary scripting and general cloud concepts, this cookbook will give you what you need to both address foundational tasks and create high-level capabilities. This book is for developers, engineers, and architects of all levels, from beginner to expert. The recipes in this book aim to bridge the gap between “Hello World” proofs of concept and enterprise grade applications by using applied examples with guided walk-throughs of common scenarios that you can directly apply to your current or future work. These skillful and experience-building tasks will immediately deliver value regardless of your AWS experience level.

Название: The Railroad Photography of Lucius Beebe and Charles Clegg
Издательство: Indiana University Press
Год: 2019
Формат: True PDF
Страниц: 214
Размер: 54 Mb
Язык: English

The Railroad Photography of Lucius Beebe and Charles Clegg

Название: Data Algorithms with Spark: Recipes and Design Patterns for Scaling Up using PySpark (Fourth Early Release)
Автор: Mahmoud Parsian
Издательство: O’Reilly Media, Inc.
Год: 2021-09-10
Страниц: 390
Язык: английский
Формат: epub
Размер: 10.1 MB

Apache Spark's speed, ease of use, sophisticated analytics, and multilanguage support makes practical knowledge of this cluster-computing framework a required skill for data engineers and data scientists. With this hands-on guide, anyone looking for an introduction to Spark will learn practical algorithms and examples using PySpark. Spark’s “native” language is Scala, but you can use language APIs to run Spark code from other programming languages (for example, Java, R, and Python). In this book, I teach you how to use PySpark to solve big data problems in Spark. In this book, you will learn how to solve your big data problems in Spark by expressing your solution in PySpark. You will lean how to read your data and represent it as an RDD and DataFrame. RDD is a fundamental data abstraction of Spark. DataFrame (a distributed table of rows with named columns) in Spark allows developers to impose a structure onto a distributed collection of data, allowing higher-level abstraction.