Using Amazon S3 Tables with Kestra

The blog post provides a detailed guide on orchestrating data loading into Amazon S3 Tables using Kestra, emphasizing the automation of transforming and querying structured data. Amazon's S3 Tables, supported by Apache Iceberg, allow data to be easily accessed by analytics engines like EMR and Athena, eliminating the manual setup and conversion typically required for querying structured data in object storage. The article outlines a step-by-step process to create a workflow in Kestra, demonstrating tasks such as downloading and converting CSV files to Parquet format, uploading them to S3, and creating Iceberg-backed S3 Tables. It further explains configuring the necessary AWS services, including creating IAM roles, setting up EC2 key pairs, and using EMR to submit Spark jobs for data processing. The tutorial culminates in querying the data using Amazon Athena, showcasing the efficiency of using Kestra for end-to-end data orchestration with S3 Tables.