| 本文已被：浏览 7768次 下载 8037次 |
码上扫一扫！ |
|
|
| 网格环境下基于流水线的多重相似查询优化 |
|
胡华1,2, 庄毅2, 胡海洋1,2, 赵格华3
|
|
1.杭州电子科技大学 计算机学院,浙江 杭州 310018;2.浙江工商大学 计算机与信息工程学院,浙江 杭州 310018;3.香港中文大学 计算机科学与工程系,香港
|
|
| 摘要: |
| 提出一种网格环境下基于流水线技术的分布式多重相似查询的优化算法(pipeline-based distributed similarity query processing,简称pGMSQ).首先,当用户提交若干个查询请求时,采用基于代价的动态层次聚类策略(dynamic query clustering,简称DQC)对其进行合并.然后在数据结点层,采用索引支持的向量集缩减方法快速过滤无关向量.最后,在执行结点层对候选向量执行求精操作返回结果向量.由于本查询采用了流水线技术,实验结果表明,该方法在提高查询性能的同时也提高了系统的吞吐量. |
| 关键词: 网格 多重查询优化 高维索引 数据分片 |
| DOI： |
| 分类号: |
| 基金项目:Supported by the National Natural Science Foundation of China under Grant Nos.60873022, 60903053 (国家自然科学基金); the Zhejiang Provincal Natural Science Foundation of China under Grant Nos.Y1080148, Y1090165 (浙江省自然科学基金); the Key Program of Science and Technology of Zhejiang Province of China under Grant No.2008C13082 (浙江省科技厅重大科技项目); the Key Project of Special Foundation for Young Scholars in Zhejiang Gongshang University of China under Grant No.Q09-7 (浙江工商大学青年人才基金重点资助项目); the Open Fund Provided by State Key Laboratory for Novel Software Technology of Nanjing University of China (南京大学计算机软件新技术国家重点实验室开放基金) |
|
| Pipeline-Based Multi-Query Optimization for Similarity Queries in Grid Environment |
|
HU Hua,ZHUANG Yi,HU Hai-Yang,Dickson CHIU
|
| Abstract: |
| This paper proposes a multi-query optimization algorithm for pipeline-based distributed similarity query processing (pGMSQ) in grid environment. First, when a number of query requests are simultaneously submitted by users, a cost-based dynamic query clustering (DQC) is invoked to quickly and effectively identify the correlation among the query spheres (requests). Then, index-support vector set reduction is performed at data node level in parallel. Finally, refinement of the candidate vectors is conducted to get the answer set at the execution node level. By adopting pipeline-based technique, this algorithm is experimentally proved to be efficient and effective in minimizing the response time by decreasing network transfer cost and increasing the throughput. |
| Key words: grid multi-query optimization high-dimensional indexing data partition |
