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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AnalyticDB-V: A Hybrid Analytical Engine Towards Query Fusion for Structured and Unstructured Data

2020年8月1日·
Chuangxian Wei
,
Bin Wu
,
Sheng Wang
,
Renjie Lou
,
Chaoqun Zhan
,
Feifei Li
,
Yuanzhe Cai
PDF DOI
类型
会议文章
发表于
Proceedings of the VLDB Endowment, 13(12), 2020
publication
最近更新于 2026年11月2日
← Weighted Distinct Sampling: Cardinality Estimation for SPJ Queries 2021年6月1日
Wander Join and XDB: Online Aggregation via Random Walks 2019年1月1日 →
语言:
中文
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