AWS Certified Data Analytics Specialty 2021 – Hands-On - Athena Performance

The video tutorial focuses on optimizing Athena's performance by using columnar data formats like ORC or Parquet, organizing data into a small number of large files, and leveraging partitions. It explains how to preprocess data using tools like Glue and ETL transforms, and how to add partitions to existing datasets using the MSCK REPAIR TABLE command. These strategies help improve query performance and efficiency when working with Athena.

What is the impact of using a small number of large files compared to a large number of small files in Athena?

What command can be used in Athena to add metadata for partitions to an existing database?