| 摘要: |
| 传统的数据库系统围绕单次查询的模型构建，独立地执行并发查询.由于该模型的限制，传统数据库无法一次对多个查询进行优化.多查询共享技术旨在共享查询之间的公共部分，从而达到提高系统整体响应时间和吞吐量的目的.将多查询执行模式分为两类，介绍了各自的原型系统——基于全局查询计划的多查询原型系统和以运算符为中心的多查询原型系统，并且讨论了两种系统的优势以及所适用场景.在之后的内容中，将多查询共享技术按照查询的各个阶段分为查询编译阶段中的多查询共享技术以及查询执行阶段中的多查询共享技术两大类.以这两个方向为线索，梳理了多查询计划的表示方法、多查询表达式合并、多查询共享算法、多查询优化等各种方向的研究成果.在此基础上，还介绍了共享查询技术在关系数据库和非关系数据库中的应用.最后，分析了共享查询技术面临的机遇和挑战. |
| 关键词: 多查询 共享查询 查询优化 数据库 高并发 |
| DOI：10.13328/j.cnki.jos.006203 |
| 分类号:TP311 |
| 基金项目:国家重点研发计划（2019YFB2102600）；国家自然科学基金（61572194，61672233） |
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| Review of Research on Multi-query Sharing Technology |
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WEI Jian-Hao, XIA Ye-Feng, GONG Xue-Qing
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Software Engineering Institute, East China Normal University, Shanghai 200062, China
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| Abstract: |
| Traditional database systems are built around a model of query-at-a-time, and concurrent queries in the context are executed independently. Due to the limitations of this model, traditional databases cannot optimize multiple queries at a time. Multi-query sharing technology is designed to share the common part between queries to improve the overall response time and throughput of the system. This study divides the multi-query execution mode into two categories and introduces their respective prototype systems:the multi-query prototype system based on the global query plan and on demand simultaneous pipelining. Also, the advantages of the two systems and the applicable scenarios are discussed. In the following content, the multi-query sharing technology is divided into multiple query sharing technologies in the query compilation phase and query execution phase according to the various stages of the query. There are two major types of multi-query sharing technologies. Taking these two directions as clues, the research results in various directions such as the multi-query plan representation method, multi-query expression combination, multi-query sharing algorithm, and multi-query optimization are reviewed here. On this basis, the applications of shared query technology in relational database and non-relational database are also introduced. Finally, it analyzes the opportunities and challenges faced by shared query technology. |
| Key words: multi-query query sharing query optimization database high concurrency |
