252 citations · 1.3k across the 10 of their papers we have counts for
5 papers · 1 filter
Balsa: Learning a Query Optimizer Without Expert Demonstrations
Zongheng Yang, Wei-Lin Chiang, Sifei Luan +3
Query optimizers are a performance-critical component in every database system. Due to their complexity, optimizers take experts months to write and years to refine. In this work,…
NeuroCard: One Cardinality Estimator for All Tables
Zongheng Yang, Amog Kamsetty, Sifei Luan +4
Query optimizers rely on accurate cardinality estimates to produce good execution plans. Despite decades of research, existing cardinality estimators are inaccurate for complex que…
Qd-tree: Learning Data Layouts for Big Data Analytics
Zongheng Yang, Badrish Chandramouli, Chi Wang +6
Corporations today collect data at an unprecedented and accelerating scale, making the need to run queries on large datasets increasingly important. Technologies such as columnar b…
Deep Unsupervised Cardinality Estimation
Zongheng Yang, Eric Liang, Amog Kamsetty +7
Cardinality estimation has long been grounded in statistical tools for density estimation. To capture the rich multivariate distributions of relational tables, we propose the use o…
Learning to Optimize Join Queries With Deep Reinforcement Learning
Sanjay Krishnan, Zongheng Yang, Ken Goldberg +2
Exhaustive enumeration of all possible join orders is often avoided, and most optimizers leverage heuristics to prune the search space. The design and implementation of heuristics…