Query Performance Prediction for Concurrent Queries using Graph Embedding
Summary: First graph-embedding-based model for concurrent query performance prediction. Queries mapped to a plan graph; edges encode lock conflicts and buffering correlations; graph embeddings + predictor forecast runtime; dynamic workloads handled via graph update/compaction; real-world tests beat state-of-the-art. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Xuanhe Zhou (Tsinghua University)
- 2. Ji Sun (Tsinghua University)
- 3. Guoliang Li (Tsinghua University)
- 4. Jianhua Feng (Tsinghua University)
BibTeX Citation
@article{zhou_vldb20,
title = {{Query Performance Prediction for Concurrent Queries using Graph Embedding}},
author = {Zhou, Xuanhe and Sun, Ji and Li, Guoliang and Feng, Jianhua},
journal = {PVLDB},
series = {{VLDB} '20},
volume = {13},
number = {9},
pages = {1416--1428},
doi = {10.14778/3397230.3397238},
url = {https://doi.org/10.14778/3397230.3397238},
year = {2020}
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