Serverless Analytics with Amazon Athena: Query structured,unstructured,or semi-structured data in seconds without setting up any infrastructure
Author: Anthony Virtuoso ,Mert Turkay Hocanin ,Aaron Wishnick,Rahul Pathak (Foreword)
Publisher finelybook 出版社: Packt Publishing (November 19,2021)
Language 语言: English
Print Length 页数: 438 pages
ISBN-10: 1800562349
ISBN-13: 9781800562349
Book Description
Get more from your data with Amazon Athena’s ease-of-use,interactive performance,and pay-per-query pricing
Key Features
Explore the promising capabilities of Amazon Athena and Athena’s Query Federation SDK
Use Athena to prepare data for common machine learning activities
Cover best practices for setting up connectivity between your application and Athena and security considerations
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 Author: 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.
Author: 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.
What you will learn
Secure and manage the cost of querying your data
Use Athena ML and User Defined Functions (UDFs) to add advanced features to your reports
Write your own Athena Connector to integrate with a custom data source
Discover your datasets on S3 using AWS Glue Crawlers
Integrate Amazon Athena into your applications
Setup Identity and Access Management (IAM) policies to limit access to tables and databases in Glue Data Catalog
Add an Amazon SageMaker Notebook to your Athena queries
Get to grips with using Athena for ETL pipelines
