Presto at Varsity Tutors: Using Federated Queries to Power External Reporting – John Cross

Presto at Varsity Tutors: Using Federated Queries to Power External Reporting – John Cross

Varsity Tutors is a learning platform that enables online academic, professional, and enrichment learning. A growing part of their offering partners with school districts to provide customized support for teachers and students. Varsity Tutors for Schools provides external reporting capabilities including student assessments, progress reports, and more. To provide these timely reports, Varsity Tutors (an AWS shop) uses Presto scripts to perform federated queries across MySQL, Postgres, and Redshift and writes data back to S3. They use Ahana Cloud as their managed service for Presto. In this session, John will discuss what technologies they evaluated, why they chose Presto, and their current data architecture including how they handle security for cross-account writes and how they perform upserts into the final reporting database.

Presto on Spark – Facebook – Virtual Meetup

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: 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.