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.
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.
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.
Updates from the New PrestoDB C++ Execution Engine – Deepak Majeti, Ahana & Dave Cohen, Intel
This talk will provide an overview of an ongoing effort to enable the new PrestoDB C++ execution engine, code-named Prestissimo, and its use of the Velox library with the ability to run the TPC-H benchmark with good performance.
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.
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.