AWS Clean Rooms launches advanced configurations to optimize SQL performance

AWS Clean Rooms Advanced Configurations

AWS Clean Rooms now supports advanced configurations to enhance the performance of Spark SQL queries. This update allows you to customize Spark properties and compute sizes for SQL queries at runtime, providing greater flexibility to meet your performance, scale, and cost requirements.

You can configure Spark properties such as shuffle partition settings for parallel processing and autoBroadcastJoinThreshold for optimizing join operations. Additionally, you can cache an existing table’s data containing results from a SQL query or create and cache a new table to improve performance and reduce costs for complex queries using large datasets.

For example, advertisers running lift analysis on their campaigns can specify a custom number of workers for an instance type and configure Spark properties to optimize costs without editing their SQL query.

What to do

• Configure Spark properties for better control over SQL query behavior and tuning.
• Cache existing table data or create new tables to improve performance and reduce costs.
• Specify custom instance types and Spark properties to optimize costs.

Source: AWS release notes

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