Quick Stats – Runtime ANALYZE for Better Query Plans – Anant Aneja, Ahana

Quick Stats – Runtime ANALYZE for Better Query Plans – Anant Aneja, Ahana

An optimizer’s plans are only as good as the estimates available for the tables its querying. For queries over recently ingested data that is not yet ANALYZE-d to update table or partition stats, the Presto optimizer flies blind; it is unable to make good query plans and resorts to syntactic join orders. To solve this problem, we propose building ‘Quick Stats’ : By utilizing file level metadata available in open data lake formats such as Delta & Hudi, and by examining stats from Parquet & ORC footers, we can build a representative stats sample at a per partition level. These stats can be cached for use be newer queries, and can also be persisted back to the metastore. New strategies for tuning these stats, such as sampling, can be added to improve their precision.

Top 10 Reasons to Use & Contribute to Presto – Steven Mih, Ahana

Top 10 Reasons to Use & Contribute to Presto – Steven Mih, Ahana

Presto is complicated with many intricacies. Ahana Cloud is the only managed service for Presto on AWS that simplifies Presto, bringing its power to platform teams of any size or skill set. In this session we’ll give you a quick overview of Ahana Cloud, including managing multiple Presto clusters seamlessly, querying a range of data sources, as well as just-released capabilities.