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Amazon Redshift Cookbook

You're reading from Amazon Redshift Cookbook

Product type Book

Published in Jul 2021

Publisher Packt

ISBN-13 9781800569683

Pages 384 pages

Edition 1st Edition

Languages

Concepts

Authors (3):

Shruti Worlikar

Thiyagarajan Arumugam

Harshida Patel

View More author details

Table of Contents (13) Chapters

Preface

1. Chapter 1: Getting Started with Amazon Redshift

2. Chapter 2: Data Management

3. Chapter 3: Loading and Unloading Data

4. Chapter 4: Data Pipelines

5. Chapter 5: Scalable Data Orchestration for Automation

6. Chapter 6: Data Authorization and Security

7. Chapter 7: Performance Optimization

8. Chapter 8: Cost Optimization

9. Chapter 9: Lake House Architecture

10. Chapter 10: Extending Redshift's Capabilities

11. Other Books You May Enjoy

Appendix

Unloading data to Amazon S3

Amazon Redshift can create a copy of the data on Amazon S3 using the UNLOAD command. The UNLOAD command splits the data across multiple files based on the node slices across the Redshift cluster.

This recipe will show you how to use UNLOAD data from an Amazon Redshift cluster in an Amazon S3 bucket.

Getting ready

To complete this recipe, you will need to do the following:

Gain access to the AWS Console.
Deploy an Amazon Redshift deployed in AWS region eu-west-1. Load the data, as referenced in the Loading data from Amazon S3 recipe.
Create Amazon Redshift cluster master user credentials.
Gain access to any SQL interface, such as a SQL client or the Amazon Redshift Query Editor.
Create an Amazon S3 bucket in eu-west-1. We will reference it as [Your-Amazon_S3_Bucket].
Attach an IAM role to an Amazon Redshift cluster that can access Amazon S3.

How to do it…

To unload the data from Amazon Redshift into...

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Authors (3)

Shruti Worlikar

Shruti Worlikar is a cloud professional with technical expertise in data lakes and analytics across cloud platforms. Her background has led her to become an expert in on-premises-to-cloud migrations and building cloud-based scalable analytics applications. Shruti earned her bachelor's degree in electronics and telecommunications from Mumbai University in 2009 and later earned her masters' degree in telecommunications and network management from Syracuse University in 2011. Her work history includes work at J.P. Morgan Chase, MicroStrategy, and Amazon Web Services (AWS). She is currently working in the role of Manager, Analytics Specialist SA at AWS, helping customers to solve real-world analytics business challenges with cloud solutions and working with service teams to deliver real value. Shruti is the DC Chapter Director for the non-profit Women in Big Data (WiBD) and engages with chapter members to build technical and business skills to support their career advancements. Originally from Mumbai, India, Shruti currently resides in Aldie, VA, with her husband and two kids.

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Thiyagarajan Arumugam

Thiyagarajan Arumugam (Thiyagu) is a principal big data solution architect at AWS, architecting and building solutions at scale using big data to enable data-driven decisions. Prior to AWS, Thiyagu as a data engineer built big data solutions at Amazon, operating some of the largest data warehouses and migrating to and managing them. He has worked on automated data pipelines and built data lake-based platforms to manage data at scale for the customers of his data science and business analyst teams. Thiyagu is a certified AWS Solution Architect (Professional), earned his master's degree in mechanical engineering at the Indian Institute of Technology, Delhi, and is the author of several blog posts at AWS on big data. Thiyagu enjoys everything outdoors – running, cycling, ultimate frisbee – and is currently learning to play the Indian classical drum the mrudangam. Thiyagu currently resides in Austin, TX, with his wife and two kids.

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Harshida Patel

Harshida Patel is a senior analytics specialist solution architect at AWS, enabling customers to build scalable data lake and data warehousing applications using AWS analytical services. She has presented Amazon Redshift deep-dive sessions at re:Invent. Harshida has a bachelor's degree in electronics engineering and a master's in electrical and telecommunication engineering. She has over 15 years of experience architecting and building end-to-end data pipelines in the data management space. In the past, Harshida has worked in the insurance and telecommunication industries. She enjoys traveling and spending quality time with friends and family, and she lives in Virginia with her husband and son.

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