A pay-as-you-go framework for query execution feedback

Author:

Chaudhuri Surajit1,Narasayya Vivek2,Ramamurthy Ravi3

Affiliation:

1. Microsoft Research, One Microsoft Way, Redmond, WA

2. Microsoft Research One Microsoft Way Red mond, WA

3. Microsoft Research One Microsoft Way Redmond, WA

Publisher

VLDB Endowment

Subject

General Earth and Planetary Sciences,Water Science and Technology,Geography, Planning and Development

Cited by 16 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Automating localized learning for cardinality estimation based on XGBoost;Knowledge and Information Systems;2024-06-01

2. Towards Exploratory Query Optimization for Template-Based SQL Workloads;2024 IEEE 40th International Conference on Data Engineering (ICDE);2024-05-13

3. Better Distributed Graph Query Planning With Scouting Queries;Proceedings of the 6th Joint Workshop on Graph Data Management Experiences & Systems (GRADES) and Network Data Analytics (NDA);2023-06-18

4. Robust Cardinality: a novel approach for cardinality prediction in SQL queries;Journal of the Brazilian Computer Society;2021-09-01

5. Efficiently approximating selectivity functions using low overhead regression models;Proceedings of the VLDB Endowment;2020-08

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