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

Triggering ETL queries with S3 notifications

Due to its low cost, high reliability, and seemingly infinite scalability, Amazon S3 is often at the center of many cloud architectures. In 2014, this led the S3 team to add the ability to trigger events for operations on your objects. These events can be filtered by bucket, prefix, and operation type with possible destinations, including Simple Queue Service (SQS), Simple Notification Service (SNS), and Lambda. You may also be interested to know that S3 does not charge for this feature. You'll only pay for the associated SQS, SNS, or Lambda usage for processing the events.

As we said earlier, we want our ETL process to react to the arrival of new data without the need to wait or poll. This reduces latency and increases data freshness for time-sensitive workloads such as our trade summary reports. The integration between S3 events and AWS Lambda also automatically handles re-driving failed events, simplifying our error handling...