Building Large-scale Query Operators and Window Functions for Prestissimo using Velox – Aditi Pandit
In this talk, Aditi Pandit, Principal Software Engineer at Ahana and Presto/Velox contributor, will throw the covers back on some of the most interesting portions of working in Prestissimo and Velox. The talk will be based on the experience of implementing the windowing functions in Velox. It will cover the nitty gritty on the vectorized operator, memory management and spilling. This talk is perfect for anyone who is using Presto in production and wants to understand more about the internals, or someone who is new to Presto and is looking for a deep technical understanding of the architecture.
How Blinkit is Building an Open Data Lakehouse with Presto on AWS – Satyam Krishna & Akshay Agarwal
Blinkit, India’s leading instant delivery service, uses Presto on AWS to help them deliver on their promise of “everything delivered in 10 minutes”. In this session, Satyam and Akshay will discuss why they moved to Presto on S3 from their cloud data warehouse for more flexibility and better price performance. They’ll also share more on their open data lakehouse architecture which includes Presto as their SQL engine for ad hoc reporting, Ahana as SaaS for Presto, Apache Hudi and Iceberg to help manage transactions, and AWS S3 as their data lake.
Update on Intel’s Participation in the Presto and Velox Communities – David Cohen, Intel
In this talk I will provide a brief update on Intel’s involvement in the Presto and Velox projects.
PrestoDB, the Velox Library, and the Coming Age of Heterogeneous Hardware – Dave Cohen, Intel
This talk will quickly review the market shift to use heterogeneous hardware, the need for new language runtime and library level abstractions to hide the complexity of this hardware, and position the PrestoDB SQL query engine with the Velox and Cachelib libraries embodiments of these abstractions.
Prestissimo – Presto-on-Velox for Faster More Efficient Queries – Orri Erling, Meta
We built a drop-in replacement for the Presto worker using C++ and Velox and saw a dramatic improvements in CPU efficiency and latency for interactive queries. We embraced adaptive execution provided by Velox to efficiently evaluate filters pushed down into scan and automatically enable array-based aggregations and joins. We make extensive use of dictionary encodings to achieve zero-copy execution throughout the engine. We allow for vectorization friendly function implementations, provide ASCII-only fast paths and many other tricks. We’d like to share our learnings, early results and future plans. We are looking forward to invite the community to join our efforts in building the next generation of Presto together.