Speeding Up Presto in ByteDance – Shengxuan Liu, Bytedance & Beinan Wang, Alluxio

Speeding Up Presto in ByteDance – Shengxuan Liu, Bytedance & Beinan Wang, Alluxio

Shengxuan Liu from ByteDance and Beinan Wang from Alluxio will present the practical problems and interesting findings during the launch of Presto Router and Alluxio Local Cache. Their talk covers how ByteDance’s Presto team implements the cache invalidation and dashboard for Alluxio’s Local Cache. Shengxuan will also share his experience using a customized cache strategy to improve the cache efficiency and system reliability.

Shared Foundations Of Composable Data Systems – Biswapesh Chattopadhyay, Google

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.

Scaling Cache for Presto Iceberg Connector – Beinan Wang, Alluxio & Chunxu Tang

Scaling Cache for Presto Iceberg Connector – Beinan Wang, Alluxio & Chunxu Tang

While using the Presto Iceberg connector, the in-heap cache in Presto is likely overloaded. In this talk, Beinan and Chunxu will share the design, implementation, and optimization of the off-heap cache to address the scalability challenges. You will learn how to cache Iceberg data and metadata for the Presto Iceberg connector, followed by future work on improving table scans using Apache Arrow.

Speed Up Presto at Uber with Alluxio Caching – Chen Liang, Uber & Beinan Wang, Alluxio

Speed Up Presto at Uber with Alluxio Caching – Chen Liang, Uber & Beinan Wang, Alluxio

At Uber, Presto is heavily used as one of the primary data analytics tools, and Presto’s query performance has profound production impact at Uber. As part of the Presto optimization effort, we turned to explore Alluxio as a caching solution. Alluxio is an open source data orchestration platform often used by many compute frameworks as the caching layer. Alluxio caching is currently enabled on ~2000 nodes across 6 clusters at Uber. In this presentation, we will talk about our journey at Uber of integrating Alluxio cache into Presto. We will discuss the Uber specific challenges we encountered and how we addressed them. We will also present the performance improvements we have seen. Besides, we will also discuss our plan and next steps, and potential future collaboration opportunities with the community.

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

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 Query Analysis for Data Layout Formatting and Query Result Caching – Gurmeet Singh, Uber

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.

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

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.

After RaptorX: Improve Performance Understanding and Workload Analysis in Presto – Ke Wang & Bin Fan

After RaptorX: Improve Performance Understanding and Workload Analysis in Presto – Ke Wang & Bin Fan

RaptorX, an umbrella project presented in PrestoCon Day in March, enabled the Presto interactive fleet in Facebook to reduce latency by 10x, based on a set of architectural improvements and optimizations with hierarchical caching. This presentation provides an update on the follow-up enhancement. Bin Fan from Alluxio will talk about the exploration of a probabilistic algorithm in Alluxio caching to estimate cache working set and the implementation of shadow cache Ke Wang from Facebook will talk about how shadow cache is used to understand the system bottleneck for better resource allocation and query routing decisions. She will also cover a recent improvement in collecting and aggregating per-query runtime statistics on the Presto engine to better understand the time breakdown, resource usage breakdown and cache hit rate on a per-query basis, which can help identify areas of improvement.

RaptorX: Building a 10X Faster Presto – James Sun, Facebook, Inc

RaptorX: Building a 10X Faster Presto – James Sun, Facebook, Inc

RaptorX is an internal project name aiming to boost query latency significantly beyond what vanilla Presto is capable of. For this session, we introduce the hierarchical cache work including Alluxio data cache, fragment result cache, etc. Cache is the key building block for RaptorX. With the support of the cache, we are able to boost query performance by 10X. This new architecture can beat performance oriented connectors like Raptor with the added benefit of continuing to work with disaggregated storage.