106 citations · 429 across the 28 of their papers we have counts for
30 papers
Query Performance Tuning with Optimal Exploration of Optimizer Cost Model Parameter Space
Wentao Wu, Xiaoying Wang, Vivek Narasayya +1
Modern query optimizers use analytical cost models to estimate the cost of a given query plan. Such cost models are typically functions of a set of "cost units" that specify unit C…
Mandol: An Agglomerative Agent Memory System for Long-Term Conversations
Yuhan Zhang, Zhiyuan Guo, Ziheng Zeng +3
Long-term conversational agents need to remember and query cross-session, multi-typed information with complex correlations. Existing agent memory systems rely on heterogeneous vec…
Evaluating the Practical Effectiveness of LLM-Driven Index Tuning on Microsoft SQL Server
Xiaoying Wang, Wentao Wu, Vivek Narasayya +1
Indexes are crucial for database performance. Index tuning, i.e., selecting appropriate indexes for a database workload, is an important problem. The state-of-the-art index tuning…
UTune: Towards Uncertainty-Aware Online Index Tuning
Chenning Wu, Sifan Chen, Wentao Wu +4
There have been a flurry of recent proposals on learned benefit estimators for index tuning. Although these learned estimators show promising improvement over what-if query optimiz…
Esc: An Early-stopping Checker for Budget-aware Index Tuning
Xiaoying Wang, Wentao Wu, Vivek Narasayya +1
Index tuning is a time-consuming process. One major performance bottleneck in existing index tuning systems is the large amount of "what-if" query optimizer calls that estimate the…
Wii: Dynamic Budget Reallocation In Index Tuning
Xiaoying Wang, Wentao Wu, Chi Wang +2
Index tuning aims to find the optimal index configuration for an input workload. It is often a time-consuming and resource-intensive process, largely attributed to the huge amount…