Description: Serverless Analytics with Amazon Athena by Anthony Virtuoso, Mert Turkay Hocanin, Aaron Wishnick, Rahul Pathak Serverless Analytics with Amazon Athena covers all the offerings of Athena to help you run interactive queries and analyze large data stored in Amazon S3 using standard SQL. Throughout this book, youll learn how to add data-driven insights or ad hoc queries to an application in a cost-effective manner, without needing to manage any infrastructure. FORMAT Paperback LANGUAGE English CONDITION Brand New Publisher Description Get more from your data with Amazon Athenas ease-of-use, interactive performance, and pay-per-query pricingKey FeaturesExplore the promising capabilities of Amazon Athena and Athenas Query Federation SDKUse Athena to prepare data for common machine learning activitiesCover best practices for setting up connectivity between your application and Athena and security considerationsBook DescriptionAmazon 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. Youll learn how to build, secure, and connect to a data lake with Athena and Lake Formation. Next, youll 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, youll 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, youll 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, youll 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 todays ML modeling exercises.What you will learnSecure and manage the cost of querying your dataUse Athena ML and User Defined Functions (UDFs) to add advanced features to your reportsWrite your own Athena Connector to integrate with a custom data sourceDiscover your datasets on S3 using AWS Glue CrawlersIntegrate Amazon Athena into your applicationsSetup Identity and Access Management (IAM) policies to limit access to tables and databases in Glue Data CatalogAdd an Amazon SageMaker Notebook to your Athena queriesGet to grips with using Athena for ETL pipelinesWho this book is forBusiness intelligence (BI) analysts, application developers, and system administrators who are looking to generate insights from an ever-growing sea of data while controlling costs and limiting operational burden, will find this book helpful. Basic SQL knowledge is expected to make the most out of this book. Author Biography Anthony Virtuoso works as a Principal Engineer at Amazon and holds multiple patents in distributed systems, software defined networks, and security. In his eight years at Amazon, he has helped launch several Amazon Web Services, the most recent of which was Amazon Managed Blockchain. As one of the original authors of Athena Query Federation, youll often find him lurking on the Athena Federation GitHub repository answering questions and shipping bug fixes. When not at work, Anthony obsesses over a different set of customers, namely his wife and two little boys, aged 2 and 5. His kids enjoy doing science experiments with dad, like 3D printing toys, building with Lego, or searching the local pond for tardigrades.Mert Turkay Hocanin is a Principal Big Data Architect at Amazon Web Services within the AWS Glue and AWS Lake Formation services and has previously worked for several other services including Amazon Athena, Amazon EMR, Amazon Managed Blockchain. During his time at AWS, he worked with several Fortune 500 companies on some of the largest data lakes in the world and was involved with the launching of three Amazon Web Services. Prior to being a Big Data Architect, he was a Senior Software Developer within Amazons retail systems organization building one of the earliest data lakes in the company in 2013. When he is not helping customers build data lakes, he enjoys spending time with his wife-Subrina, son-Tristan, and exploring New York City.Aaron Wishnick works as a Senior Software Engineer at Amazon, where he has been for 7 years. During that time he has worked on Amazons payment systems, financial intelligence systems, as well as working for AWS on Athena and AWS Proton. When not at work, Aaron and his fiance, Alyssa, are on a quest to determine just how much dog fur is too much, with their husky and malamute, Mina and Wally.| Table of Contents Table of ContentsYour First Query Introduction to Amazon AthenaKey Features, Query Types, and FunctionsMetastores, Data Sources, and Data LakesSecuring Your DataAWS Glue and AWS Lake FormationAd Hoc AnalyticsQuerying Unstructured and Semi-Structured DataServerless ETL PipelinesBuilding Applications with Amazon AthenaOperational Excellence - Maintenance, Optimization, and TroubleshootingAthena Query FederationAthena UDFs and MLLake Formation – Advanced Topics Details ISBN1800562349 Author Rahul Pathak Short Title Serverless Analytics with Amazon Athena Pages 438 Language English Year 2021 ISBN-10 1800562349 ISBN-13 9781800562349 Format Paperback Publisher Packt Publishing Limited Imprint Packt Publishing Limited Place of Publication Birmingham Country of Publication United Kingdom AU Release Date 2021-10-15 NZ Release Date 2021-10-15 Publication Date 2021-10-15 Subtitle Query structured, unstructured, or semi-structured data in seconds without setting up any infrastructure DEWEY 004 Audience General UK Release Date 2021-10-15 We've got this At The Nile, if you're looking for it, we've got it. 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