What is Presto on Spark?

1. Reporting and dashboarding This includes serving custom reporting for both internal and external developers for business insights and also many organizations using Presto for interactive A/B testing analytics. A defining characteristic of this use case is a requirement for low latency. It requires tens to hundreds of milliseconds at very high QPS, and not…

Scaling with Presto on Spark

Overview Presto was originally designed to run interactive queries against data warehouses, but now it has evolved into a unified SQL engine on top of open data lake analytics for both interactive and batch workloads. Popular workloads on data lakes include: 1. Reporting and dashboarding This includes serving custom reporting for both internal and external…

Running Presto in a Hybrid Cloud Architecture

Migrating SQL workloads from a fully on-premise environment to cloud infrastructure has numerous benefits, including alleviating resource contention and reducing costs by paying for computation resources on an on-demand basis. In the case of Presto running on data stored in HDFS, the separation of compute in the cloud and storage on-premises is apparent since Presto’s…