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.
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.
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.
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.