6 papers
DistJoin: A Decoupled Join Cardinality Estimator based on Adaptive Neural Predicate Modulation
Kaixin Zhang, Hongzhi Wang, Ziqi Li +4
Research on learned cardinality estimation has made significant progress in recent years. However, existing methods still face distinct challenges that hinder their practical deplo…
ForeSight: A Predictive-Scheduling Deterministic Database
Junfang Huang, Yu Yan, Hongzhi Wang +2
Deterministic databases enable scalable replicated systems by executing transactions in a predetermined order. However, existing designs fail to capture transaction dependencies, l…
Algorithmic Complexity Attacks on All Learned Cardinality Estimators: A Data-centric Approach
Yingze Li, Xianglong Liu, Dong Wang +4
Learned cardinality estimators show promise in query cardinality prediction, yet they universally exhibit fragility to training data drifts, posing risks for real-world deployment.…
CONCERTO: Complex Query Execution Mechanism-Aware Learned Cost Estimation
Kaixin Zhang, Hongzhi Wang, Kunkai Gu +4
With the growing demand for massive data analysis, many DBMSs have adopted complex underlying query execution mechanisms, including vectorized operators, parallel execution, and dy…
Brame: Hierarchical Data Management Framework for Cloud-Edge-Device Collaboration
Xianglong Liu, Hongzhi Wang, Yingze Li +3
In the realm of big data, cloud-edge-device collaboration is prevalent in industrial scenarios. However, a systematic exploration of the theory and methodologies related to data ma…
Updateable Data-Driven Cardinality Estimator with Bounded Q-error
Yingze Li, Xianglong Liu, Hongzhi Wang +2
Modern Cardinality Estimators struggle with data updates. This research tackles this challenge within single-table. We introduce ICE, an Index-based Cardinality Estimator, the firs…