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

Understanding the ad hoc analytics hype

If you are lucky, you may not be aware of the buzzword levels of hype surrounding ad hoc analytics. Fortunately, there are strong fundamentals behind the increasing level of interest and importance placed on having good tooling for ad hoc analytics. In a moment, we'll attempt to form a proper definition of ad hoc analytics, but not before we run a time travel query of our own to set the stage for what we now know as ad hoc analytics.

As a society, we've been collecting data since the advent of commerce. In the era before modern big data technologies, the business intelligence landscape was a very different place. Most data capture and entry was a manual affair, frequently driven by government accounting and auditing requirements. Particularly savvy companies were tracking their own, non-accounting-related Key Performance Indicators (KPIs), but these exercises were often short-lived and targeted at achieving specific outcomes. It...