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Amazon Redshift Cookbook

You're reading from Amazon Redshift Cookbook Recipes for building modern data warehousing solutions

Product type Paperback

Published in Apr 2025

Publisher Packt

ISBN-13 9781836206910

Length 470 pages

Edition 2nd Edition

Concepts

Data Science

Authors (3):

Shruti Worlikar

Harshida Patel

Anusha Challa

View More author details

Table of Contents (17) Chapters

Preface

1. Getting Started with Amazon Redshift

2. Data Management FREE CHAPTER

3. Loading and Unloading Data

4. Zero-ETL Ingestions

5. Scalable Data Orchestration for Automation

6. Platform Authorization and Security

7. Data Authorization and Security

8. Performance Optimization

9. Cost Optimization

10. Lakehouse Architecture

11. Data Sharing with Amazon Redshift

12. Generative AI and ML with Amazon Redshift

13. Unlock Your Exclusive Benefits

Unlock this Book’s Free Benefits in 3 Easy Steps

14. Other Books You May Enjoy

15. Index

Appendix

Configuring Workload Management (WLM) for provisioned cluster

Amazon Redshift workload management (WLM) enables you to set up query priorities in a data warehouse. WLM helps you create query queues that can be defined based on different parameters, such as memory allotment, priority, user groups, query groups, and query monitoring rules. Users generally use WLM to set priorities for different query types, such as long-running versus short-running, ETL versus reporting, and so on. In this recipe, we will demonstrate how to configure WLM within a Redshift data warehouse. Hence, you can manage multiple workloads running on the same data warehouse and each of them can be assigned different priorities based on business needs.

Note

Amazon Redshift serverless automatically manages WLM. You do not need to configure WLM on a serverless endpoint.

Getting ready

To complete this recipe, you will need the following setup:

An IAM user with access to Amazon...

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Authors (3)

Shruti Worlikar

Shruti Worlikar

Shruti Worlikar is a cloud professional with technical expertise in data 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 master's degree in telecommunications and network management from Syracuse University in 2011. Her work history includes work at JPMorgan Chase, MicroStrategy, and Amazon Web Services (AWS). She is currently working in the role of Sr. 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 Northern Virginia, with her husband and two kids.

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Harshida Patel

Harshida Patel

Harshida Patel is a principal 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 in 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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Anusha Challa

Anusha Challa

Anusha Challa is a seasoned professional with over 15 years of expertise in architecting data and analytics solutions across on-premises and cloud environments. She has provided guidance to hundreds of Amazon Redshift customers, empowering them to design scalable and robust end-to-end data warehouse architectures. Anusha speaks at various AWS events, such as re:Invent and AWS Summits, where she shares best practices for using Amazon Redshift and other AWS analytics services. She has a bachelor's degree in computer science and a master's degree with a specialization in Machine Learning. Based in Chicago, Anusha enjoys reading books and traveling during her free time.

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