Videos Archive - PrestoDB

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.

Executing Any External Code in Any Language with Presto – A Universal Connector – Ravishankar Nair

Connector based architecture is one of the powerful features in Presto for extensibility. While we have a solid pack of many connectors, the ability to reuse an existing external snippet to fetch data and access through Presto will make it enormously helpful. For example, consider accessing mainframe code through Presto using simple SQL which is quite cumbersome to handle by creating a connector paradigm. Ravishankar explores how he implemented this feature using a protocol server and a protocol connector which eventually helped him to achieve a patent on the concept.

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.