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.

Disaggregated Coordinator Production Rollout – Swapnil Tailor, Meta

We would like to talk about disaggregated coordinator production rollout with some stats. Also we can inform community about changes needed to support deployment of disaggregated coordinator.

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.

Disaggregated Coordinator – Swapnil Tailor, Facebook

In the existing Presto architecture, single coordinator has become a bottleneck in a number of ways for cluster scalability. – With an increasing number of workers, the coordinator has the potential of slow down due to a high number of tasks. – In high QPS use cases, we have found workers can become starved of splits by excessive CPU being spend on task updates in coordinator. – Also with single coordinator, we have an upper limit on the worker pool because of above-mentioned reasons. To overcome with this challenges, we are coming up with a new architecture which supports multiple coordinators in a single cluster.

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.