Videos Archive - PrestoDB

Predicting Resource Usages of Future Queries Based on 10M Presto Queries at Twitter

Here, Chunxu and Beinan would like to share what they have learned in developing a highly-scalable query predictor service through applying machine learning algorithms to ~10 million historical Presto queries to classify queries based on their CPU times and peak memory bytes. At Twitter, this service is helping to improve the performance of Presto clusters and provide expected execution statistics on Business Intelligence dashboards.

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.

A Tour of Presto Iceberg Connector – Beinan Wang, Alluxio & Chunxu Tang, Twitter

Apache Iceberg is an open table format for huge analytic datasets. The Presto Iceberg connector consolidates the SQL engine and the table format, to empower high-performant data analytics. Here, Beinan and Chunxu would like to discuss and share the architectural design of the Presto Iceberg connector, advanced Iceberg feature support (such as native iceberg connector, row-level deletion, and iceberg v2 support), and the future roadmap.

Presto and Apache Iceberg – Chunxu Tang, Twitter

Apache Iceberg is an open table format for huge analytic datasets. At Twitter, engineers are working on the Presto-Iceberg connector, aiming to bring high-performance data analytics on Iceberg to the Presto ecosystem. Here, Chunxu would like to share what they have learned during the development, hoping to shed light on the future work of interactive queries.

Level 101 for Presto: What is PrestoDB?

In Level 101, you’ll get an overview of Presto, including: A high level overview of Presto & most common use cases The problems it solves and why you should use it A live, hands-on demo on getting Presto running on Docker Real world example: How Twitter uses Presto at scale

Level 102 for Presto: Getting Started with PrestoDB

In this tech talk, we’ll build on what we learned in Level 101 and show you how easy it is to get started with PrestoDB. We’ll also dive deeper into key features and connectors.

Level 103 for Presto: Deep Dive into the PrestoDB architecture at Twitter

In this tech talk, we’ll take a look at the PrestoDB architecture in more technical depth. Next, we’ll have the Presto engineers at Twitter share their PrestoDB use case and architecture which includes several large Presto clusters with over 2,000 nodes.