Amazon iconAmazonSep 10, 2026

Accelerating Spark queries with Iceberg materialized views

Accelerate slow, repetitive Apache Spark analytical queries on Apache Iceberg tables without rewriting any SQL.

Accelerating Spark queries with Iceberg materialized views

Share this story

Send the public story page.

Useful takeaways from this story.

Accelerate slow, repetitive Apache Spark analytical queries on Apache Iceberg tables without rewriting any SQL.

This post shows how automatic query rewrite in Amazon EMR and AWS Glue uses Iceberg materialized views in the AWS Glue Data Catalog to transparently substitute matching query plans, and how to design...

Building the complete brief

The page is ready to read now. The fuller skim-friendly version will appear here automatically.

The useful part

Accelerate slow, repetitive Apache Spark analytical queries on Apache Iceberg tables without rewriting any SQL. This post shows how automatic query rewrite in Amazon EMR and AWS Glue uses Iceberg materialized views in the AWS Glue Data Catalog to transparently substitute matching query plans, and how to design materialized views for the best speedup.

How it works

  • This post shows how automatic query rewrite in Amazon EMR and AWS Glue uses Iceberg materialized views in the AWS Glue Data Catalog to transparently substitute matching query plans, and how to design...

Keep reading in the app

Open the app view to save this story, compare related coverage, and continue from the same source.

Open in app