Bin Wu
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    • PolarStore: High-Performance Data Compression for Large-Scale Cloud-Native Databases
    • Andromeda: Debugging Database Performance Issues with Retrieval-Augmented Large Language Models
    • Anser: Adaptive Information Sharing Framework of AnalyticDB
    • Lindorm TSDB: A Cloud-Native Time-Series Database for Large-Scale Monitoring Systems
    • Active Sampling for Sparse Table by Bayesian Optimization with Adaptive Resolution
    • ShapleyIQ: Influence Quantification by Shapley Values for Performance Debugging of Microservices
    • CatSQL: Towards Real World Natural Language to SQL Applications
    • OneShotSTL: One-Shot Seasonal-Trend Decomposition for Online Time Series Anomaly Detection and Forecasting
    • Learning-Based Query Optimization for Multi-Probe Approximate Nearest Neighbor Search
    • Releasing Private Data for Numerical Queries
    • Cquirrel: Continuous Query Processing over Acyclic Relational Schemas
    • Weighted Distinct Sampling: Cardinality Estimation for SPJ Queries
    • AnalyticDB-V: A Hybrid Analytical Engine Towards Query Fusion for Structured and Unstructured Data
    • Wander Join and XDB: Online Aggregation via Random Walks
    • Deep Meta-Learning: Learning to Learn in the Concept Space
    • Wander Join and XDB: Online Aggregation via Random Walks
    • Counting Triangles in Large Graphs by Random Sampling
    • Wander Join: Online Aggregation for Joins
    • Wander Join: Online Aggregation via Random Walks
    • Correlative Multi-Label Multi-Instance Image Annotation
    • Multi-Kernel Multi-Label Learning with Max-Margin Concept Network
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PolarStore: High-Performance Data Compression for Large-Scale Cloud-Native Databases

2026年2月1日·
Qingda Hu
,
Xinjun Jimmy Yang
,
Feifei Li
,
Junru Li
,
Ya Lin
,
Yuqi Zhou
,
Yicong Zhu
,
Junwei Zhang
,
Rongbiao Xie
,
Ling Zhou
,
Bin Wu
,
Wenchao Zhou
PDF
类型
会议文章
发表于
24th USENIX Conference on File and Storage Technologies (FAST 2026)
publication
最近更新于 2026年11月2日
Andromeda: Debugging Database Performance Issues with Retrieval-Augmented Large Language Models 2025年6月1日 →
语言:
中文
English

© 2026 Bin Wu。本作品采用 CC BY NC ND 4.0 许可。

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