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)
Section 1: Fundamentals Of Amazon Athena
Section 2: Building and Connecting to Your Data Lake
Section 3: Using Amazon Athena
Chapter 11: Operational Excellence – Monitoring, Optimization, and Troubleshooting
Section 4: Advanced Topics

Best practices for connecting to Athena

In this section, we're going to go over some things to consider when connecting to and calling Athena, including idempotency tokens and query tracking.

Idempotency tokens

I know this statement may come as a huge surprise to you, but perfect software does not exist. It's going to fail. There's a reason why there are so many different options out there for monitoring the operational status of an application. And among the infinitesimal category of possible failure scenarios, they can be narrowed down to two large categories – safe to retry and not safe to retry. It's that second category we will be focusing on in this section. More specifically there is a subcategory of not safe to retry that can quickly be summarized as ¯\_(ツ)_/¯ – you have no clue whether it is safe to retry; you know something happened, but exactly what happened is a complete mystery.

Thankfully Athena (and many other...