This workshop guided you through the process of creating and managing Amazon S3 Tables using both the AWS Management Console and CLI. Here’s a summary of the steps covered:
Created S3 Table Buckets for structured data storage.
Integrated Apache Spark with the S3 Tables Catalog for querying and processing large datasets.
Inserted and queried sample data in Iceberg Tables through Spark-Shell.
With Amazon S3 Tables, you can unlock the full potential of big data and take advantage of the AWS ecosystem’s capabilities.
Benefits of Amazon S3 Tables:
Optimized Query Performance: With partitioning and efficient data processing, S3 Tables reduce query time, even for large datasets.
Automated Management: S3 Tables handle metadata, data versioning, and schema updates automatically.
Seamless Integration: Work seamlessly with AWS analytics services such as AWS Glue, Amazon Athena, and Amazon EMR.
Notes:
Currently, Amazon S3 Tables is available in select AWS regions (such as US East (N. Virginia) and US West (Oregon)). Check the official AWS documentation for more details on availability.