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Ryan Marcus
BasketballPtsRebAstCurrent Season0.00.30.0About Me. I'm Ryan Marcus, an assistant professor of computer science at the University of Pennsylvania. I'm using machine learning to build the next generation of data management tools that automatically adapt to new hardware and user workloads, invent novel processing strategies, and understand user intention.
Ryan Marcus. Assistant Professor of Computer Science University of Pennsylvania Philadelphia, PA. rcmarcus@seas.upenn.edu. RESEARCH INTERESTS. Machine learning for systems, especially databases and clouds. Machine programming, parallel and distributed systems, high performance computing, programming languages & compilers. EDUCATION.
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Ryan Marcus. University of Pennsylvania. Verified email at seas.upenn.edu - Homepage. Computer science Databases ML for Systems Machine Programming. Title. Sort. Sort by citations Sort by year Sort by title. Cited by.
- Applying Bao to Distributed Systems
- How Bao Works
- From Single-Node to Distributed
- Discussion
This post was also published on the MIT DSAIL blog. A good portion of my postdoc at MIT has been spent developing Bao, a system for learned query optimization with an eye towards practicality. Bao was recently published at SIGMOD 2021, where we were thrilled to receive a best paper award. In our paper, we show how Bao can be applied to the open-sou...
Previous approaches1 to learned query optimization attempted to replace large parts of traditional query optimizers. In contrast, Bao sits on top of a traditional query optimizer (called the underlying optimizer) and learns to steer the underlying optimizer in the right direction. The image above illustrates the process Bao uses to steer the underl...
In the original Bao paper, we evaluated Bao on a single-node database system (e.g., Oracle and PostgreSQL). However, many data warehouse databases are, in fact, distributed. Luckily, Bao is largely agnostic to the underlying execution engine or storage layout: as long as you have a set of hints, Bao can pick and choose from them and learn from its ...
Looking over the results, we find ourself returning to the same set of takeaways: 1. Don’t spend too much time comparing results between systems. The experiments are ran on different clouds, using different hardware, at different times of day. While we followed best practice guidelines to tune the systems, an expert might still do better, in partic...
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Aug 10, 2020 · A postdoc from MIT's CSAIL team, Ryan Marcus, led the development of Bao, a learning-based query optimizer for PostgreSQL that can run queries faster and smaller than traditional systems. Bao is part of a project by Kraska and colleagues to create instance-optimized systems that adapt to the data and workload they store.
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