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  • Book Overview & Buying Amazon Redshift Cookbook
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Amazon Redshift Cookbook

Amazon Redshift Cookbook

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

Amazon Redshift Cookbook

4.8 (9)
By: Shruti Worlikar, Thiyagarajan Arumugam, Harshida 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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Event-driven applications using AWS Lambda

AWS Lambda helps you to build event-driven microservices. This serverless process can be invoked using a variety of events such as when a file arrives, when a notification is received, and so on. This helps build a decoupled data workflow that can be invoked as soon as the upstream dependencies are met, instead of a schedule-based workflow.

For example, let's say we have a website that is continuously sending the clickstream logs every 15 minutes into Amazon S3. Instead of accumulating all the log files and processing them at midnight in a typical ETL process, Amazon S3 can send an event to a Lambda function when an object is created and processed immediately. This provides several advantages, such as processing in smaller batch sizes to meet a service-level agreement (SLA) and also to have the data current within the data warehouse.

There are several ways to invoke an AWS Lambda function using an event—you can find more...

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Amazon Redshift Cookbook
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