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Amazon Redshift Cookbook

Amazon Redshift Cookbook

By : Shruti Worlikar, Arumugam, Patel
4.8 (9)
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Amazon Redshift Cookbook

Amazon Redshift Cookbook

4.8 (9)
By: Shruti Worlikar, Arumugam, Patel

Overview of this book

Amazon Redshift is a fully managed, petabyte-scale AWS cloud data warehousing service. It enables you to build new data warehouse workloads on AWS and migrate on-premises traditional data warehousing platforms to Redshift. This book on Amazon Redshift starts by focusing on Redshift architecture, showing you how to perform database administration tasks on Redshift. You'll then learn how to optimize your data warehouse to quickly execute complex analytic queries against very large datasets. Because of the massive amount of data involved in data warehousing, designing your database for analytical processing lets you take full advantage of Redshift's columnar architecture and managed services. As you advance, you’ll discover how to deploy fully automated and highly scalable extract, transform, and load (ETL) processes, which help minimize the operational efforts that you have to invest in managing regular ETL pipelines and ensure the timely and accurate refreshing of your data warehouse. Finally, you'll gain a clear understanding of Redshift use cases, data ingestion, data management, security, and scaling so that you can build a scalable data warehouse platform. By the end of this Redshift book, you'll be able to implement a Redshift-based data analytics solution and have understood the best practice solutions to commonly faced problems.
Table of Contents (13 chapters)
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Data sharing across multiple Amazon Redshift clusters

Amazon Redshift RA3 clusters decouple storage and compute, and provide the ability to scale either of them independently. The decoupled storage allows for data to be read by different consumer clusters that allow workload isolation. The data producer cluster controls access to the data that is shared. This feature opens up the possibility to set up a flexible multi-tenant system—for example, within an organization, data produced by a business unit can be shared with any of the different teams such as marketing, finance, data science, and so on that can be independently consumed using their own Amazon Redshift clusters.

Getting ready

To complete this recipe, you will need the following:

  • An IAM user with access to Amazon Redshift
  • Two separate two-node Amazon Redshift ra3.xlplus clusters deployed in the eu-west-1 AWS Region:

    a. The first cluster should be deployed with the retail sample dataset from Chapter...

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