Keynote Panel: Presto at Scale – Shradha Ambekar, Gurmeet Singh, Neerad Somanchi & Rupa Gangatirkar

Keynote Panel: Presto at Scale – Shradha Ambekar, Gurmeet Singh, Neerad Somanchi & Rupa Gangatirkar

Over the last decade Presto has become one of the most widely adopted open source SQL query engines. In use at companies large and small, Presto’s performance, reliability, and efficiency at scale have become critical to many companies’ data infrastructures. In this panel we’ll hear from three of the largest companies running Presto at scale – Meta, Uber, and Intuit. They’ll share more about their learnings, some of their impressive performance metrics with Presto, and what they envision going forward for Presto at their respective companies.

The Future of Presto’s Query Optimizer – Bill McKenna, Ahana

The Future of Presto’s Query Optimizer – Bill McKenna, Ahana

In this talk, you will hear from the query optimizer OG himself, Bill McKenna (Principal software engineer at Ahana, Architect for the query optimizer that became the code base of the Amazon Redshift query optimizer, and co-author of The Volcano Optimizer Generator: Extensibility and Efficient Search) go into detail about the state of modern query optimizers, and how Presto stacks up against them and where it will go in the near future. If database theory is your jam, you won’t want to miss this deeply technical presentation from one of the pioneers in the field.

Presto On Spark: Scaling not Failing with Spark – Ariel Weisberg, Meta & Shradha Ambekar, Intuit

Presto On Spark: Scaling not Failing with Spark – Ariel Weisberg, Meta & Shradha Ambekar, Intuit

Presto on Spark is an integration between Presto and Spark that leverages Presto’s compiler/evaluation as a library and Spark’s large scale processing capabilities. It enables a unified SQL experience between interactive and batch use cases. A unified option for batch data processing and ad hoc is very important for creating the experience of queries that scale instead of fail without requiring rewrites between different SQL dialects. In this session, we’ll talk about Presto On Spark architecture, why it matters and its implementation/usage at Intuit.