Videos Archive - PrestoDB

Shared Foundations Of Composable Data Systems – Biswapesh Chattopadhyay, Google

Data processing systems have evolved significantly over the last decade, driven by various factors such as the advent of cloud computing, increasingly complexity of applications such as ML, HTAP, Streaming, Observability and Graph processing. However, historically, these frameworks have evolved independently, leading to significant fragmentation of the stack. In this talk, I will talk about how this has evolved in the open source and at Meta, and how we are solving this problem through the Shared Foundations effort, leading to composable systems. This has resulted in significantly better performance, more features, higher engineering velocity and a more consistent user experience.

Presto & the Foundations of Open Lake House: Trends & Opportunities – Biswapesh Chattopadhyay, Meta

Building open and shared foundational tech to build a lake house architecture can provide the best-of-breed user experience across the Analytics and ML domains and potentially beyond. In this talk, Biswa will share examples drawn from the evolution of the data stack at Meta over the last few years including efforts towards dialect unification (Sapphire aka Presto-on-Spark and Xstream-IE streaming engine efforts), eval unification (using Velox as the base), eliminating the need for data duplication for interactive analytics by building smart caching (RaptorX), building a best-of-breed file format that works across Analytics and ML (Alpha), and building an open source ML data pre-proc engine (TorchArrow) which shares the core dialect and eval components with Presto.

Presto on Kafka at Scale – Yang Yang & Yupeng Fu, Uber

Presto is a popular distributed SQL query engine for running interactive analytic queries. Presto provides a Connector API that allows plugins to dozens of data sources, and thus positions itself as a single point of access to a wide variety of data. At Uber, we significantly improved Presto’s Kafka connector to meet Uber’s scale. For example, the new connector allows dynamic Kafka cluster and topic discovery so users can directly query existing Kafka topics without any registration and onboarding process; dynamic schema discovery allows fetching the latest schema without any Presto restart or deployment; smart time range suggestions to users based on Kafka metadata analysis to avoid large-range scans and thus keep the query interactive.

Open Source Data Lake Analytics: Trends and Opportunities – Biswapesh Chattopadhyay, Meta

Open source data analytics is undergoing an interesting transformation as the industry rapidly evolves around it. Accelerating migration to the cloud, the rise of immensely well funded proprietary vendors, fast evolving needs of the users all contribute to this. This talk goes into detail about the trends and opportunities in the OSS data analytics space, and a call to action on how this space can stay relevant.