Videos Archive - PrestoDB

5 Reasons Why AI Is the Future of SQL – Jared Zhao, AskEdith

SQL remains ubiquitous for data retrieval and analytics, yet can be tedious to write, and is downright unusable for business users. The 2-5 business day turnaround time for data projects is both disruptive and frustrating for business users. Data teams are becoming increasingly overwhelmed, and organizations are pushing to empower their “citizen data analysts.” With the advent of AI English-to-SQL platforms like AskEdith, now anyone can work with and query Presto using plain English questions. AskEdith integrates natively with web interfaces like Ahana for a seamless analytics experience.

Presto on Spark – Facebook – Virtual Meetup

At Facebook, we have spent the past several years in independently building and scaling both Presto and Spark to Facebook scale batch workloads. It is now increasingly evident that there is significant value in coupling Presto’s state-of-art low-latency evaluation with Spark’s robust and fault tolerant execution engine. In this talk, we’ll take a deep dive in Presto and Spark architecture with a focus on key differentiators (e.g., disaggregated shuffle) that are required to further scale Presto.

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.