17 citations · 75 across the 10 of their papers we have counts for
7 papers · 1 filter
Extract-Transform-Load for Video Streams
Ferdinand Kossmann, Ziniu Wu, Eugenie Lai +4
Social media, self-driving cars, and traffic cameras produce video streams at large scales and cheap cost. However, storing and querying video at such scales is prohibitively expen…
Lero: A Learning-to-Rank Query Optimizer
Rong Zhu, Wei Chen, Bolin Ding +4
A recent line of works apply machine learning techniques to assist or rebuild cost-based query optimizers in DBMS. While exhibiting superiority in some benchmarks, their deficienci…
FactorJoin: A New Cardinality Estimation Framework for Join Queries
Ziniu Wu, Parimarjan Negi, Mohammad Alizadeh +2
Cardinality estimation is one of the most fundamental and challenging problems in query optimization. Neither classical nor learning-based methods yield satisfactory performance wh…
Cardinality Estimation in DBMS: A Comprehensive Benchmark Evaluation
Yuxing Han, Ziniu Wu, Peizhi Wu +11
Cardinality estimation (CardEst) plays a significant role in generating high-quality query plans for a query optimizer in DBMS. In the last decade, an increasing number of advanced…
A Unified Transferable Model for ML-Enhanced DBMS
Ziniu Wu, Pei Yu, Peilun Yang +6
Recently, the database management system (DBMS) community has witnessed the power of machine learning (ML) solutions for DBMS tasks. Despite their promising performance, these exis…
BayesCard: Revitilizing Bayesian Frameworks for Cardinality Estimation
Ziniu Wu, Amir Shaikhha, Rong Zhu +3
Cardinality estimation (CardEst) is an essential component in query optimizers and a fundamental problem in DBMS. A desired CardEst method should attain good algorithm performance,…
FLAT: Fast, Lightweight and Accurate Method for Cardinality Estimation
Rong Zhu, Ziniu Wu, Yuxing Han +5
Query optimizers rely on accurate cardinality estimation (CardEst) to produce good execution plans. The core problem of CardEst is how to model the rich joint distribution of attri…