Athena_Query.vpy #Import the JDBC Driver jar file from your libs folder into your current Vortex Folder The remainder of the script properly formats the result set so that it can be displayed in Vortex. The script will first ask the user to input this information as well as a few other parameters such as what Athena database you would like to connect to and your SQL query, and then create a connection to Athena to properly query the data. You will need to have your Amazon Public and Private Access keys handy, and an s3 location where your output result set can be stored.
The body of your AthenaQuery.vpy file should be copy and pasted from below. Vortex script extensions must be saved in your \vortex\scripts folder to work properly. Create a new document called Athena Query and save it as a. Move this newly downloaded Athena jar file to a ‘libs’ folder in your Vortex Folder. If you do not have Java installed on your system you can do so here. You may have to upgrade your JDK to the newest version as well. Make sure you have downloaded the JDBC Driver here. Before we get started here are a few prerequisites. This guide will show you how to create a connection to Athena from Vortex and pull in your desired data through an sql query. This makes it easy for anyone with SQL skills to quickly analyze large-scale datasets.
With Athena, there’s no need for complex ETL jobs to prepare your data for analysis. Most results are delivered within seconds. Simply point to your data in Amazon S3, define the schema, and start querying using standard SQL. Athena is serverless, so there is no infrastructure to manage, and you pay only for the queries that you run. This tutorial was created by Jackson Pullman Getting StartedĪmazon Athena is an interactive query service that makes it easy to analyze data in Amazon S3 using standard SQL.
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