Presto Query Analysis for Data Layout Formatting and Query Result Caching – Gurmeet Singh, Uber

Presto Query Analysis for Data Layout Formatting and Query Result Caching – Gurmeet Singh, Uber

In this talk, I will be talking about a microservice that we have built at Uber to be able to analyze Presto queries. The Presto Query Engine does not provide endpoints for query analysis purposes. One has to either execute the query or gather insights from the query explain plan. In this talk, I will talk about 1. The work that we had to do to do the query analysis in a microservice using Presto as a library. 2. Doing predicate analysis on the queries to come up with data formatting recommendations in order to improve query performance. 3. Using the analysis service for query result cache invalidation. The analysis figures out whether the results from a previous run of the query are still valid and can be reused.

Presto on Elastic Capacity – Neerad Somanchi & Abhisek Saikia, Meta

Presto on Elastic Capacity – Neerad Somanchi & Abhisek Saikia, Meta

Presto on elastic capacity – Elasticity of a shared fleet is one of the fundamental pillars of the IaaS (Infrastructure-as-a-Service) world. The ability of services to efficiently use both guaranteed and non-guaranteed (opportunistic) capacity is important in such a setting. Presto is great when it runs on guaranteed capacity (i.e, capacity that is fixed and stable). But what if we want Presto to leverage elastic (opportunistic) capacity, i.e, capacity that is shifting, but in a predictable manner (think Amazon EC2 Spot Blocks)? In this lightning presentation, Neerad Somanchi and Abhisek Saikia will talk about how a recent feature developed for Presto can help it efficiently utilize such elastic compute.