Book Image

Serverless Analytics with Amazon Athena

By : Anthony Virtuoso, Mert Turkay Hocanin, Aaron Wishnick
Book Image

Serverless Analytics with Amazon Athena

By: Anthony Virtuoso, Mert Turkay Hocanin, Aaron Wishnick

Overview of this book

Amazon Athena is an interactive query service that makes it easy to analyze data in Amazon S3 using SQL, without needing to manage any infrastructure. This book begins with an overview of the serverless analytics experience offered by Athena and teaches you how to build and tune an S3 Data Lake using Athena, including how to structure your tables using open-source file formats like Parquet. You’ll learn how to build, secure, and connect to a data lake with Athena and Lake Formation. Next, you’ll cover key tasks such as ad hoc data analysis, working with ETL pipelines, monitoring and alerting KPI breaches using CloudWatch Metrics, running customizable connectors with AWS Lambda, and more. Moving on, you’ll work through easy integrations, troubleshooting and tuning common Athena issues, and the most common reasons for query failure. You will also review tips to help diagnose and correct failing queries in your pursuit of operational excellence. Finally, you’ll explore advanced concepts such as Athena Query Federation and Athena ML to generate powerful insights without needing to touch a single server. By the end of this book, you’ll be able to build and use a data lake with Amazon Athena to add data-driven features to your app and perform the kind of ad hoc data analysis that often precedes many of today’s ML modeling exercises.
Table of Contents (20 chapters)
1
Section 1: Fundamentals Of Amazon Athena
5
Section 2: Building and Connecting to Your Data Lake
9
Section 3: Using Amazon Athena
14
Chapter 11: Operational Excellence – Monitoring, Optimization, and Troubleshooting
15
Section 4: Advanced Topics

Building an ad hoc analytics strategy

As we've seen in our examples, by putting the information in the hands of subject-matter experts, you can make better, faster decisions. Thus, it should be a focal point of any ad hoc analytics strategy to improve the accessibility of data, putting it in the hands of the individuals best suited to interpret the insights it contains. Our first step in forming such a strategy is to remember that while this book will present solutions based on the Athena ecosystem, it is rarely a good idea to lock yourself into any single product or analytics engine. The underlying technologies, pricing models, and supporting tooling will make trade-offs that necessarily favor one use case over others. If something sounds too good to be true, such as a product claiming to be the only analytics system you need, it's probably mediocre at a wide range of things and unlikely to be the best in class for anything. This is part of the philosophy behind AWS&apos...