摘要: 在大型强子对撞机(LHC)上紧凑型缪子螺线管探测器(CMS)实验的复杂数据环境下,有多个关系型数据源记录了关于数据组织和分布的信息。为实现数据查询系统的精确关键词查询功能,通过分析数据库模式图的方法,将关键词查询语言动态翻译成SQL语言,设计并实现一个跨数据库平台的关键词查询系统。针对动态翻译过程中存在的二义性问题,提出基于查询实体的模式图分析算法,以及基于最小权重树查找的动态连接算法。实验结果表明,该动态连接算法能为关键词查询正确生成所需数据库表的连接方式,使关键词查询系统具有较高的查询效率,以满足用户实时、精确查询的需求。
关键词:
关键词查询,
查询语言,
关系数据库,
结构化查询语言,
二义性问题
Abstract: Under complex data environment of Compact Muon Solenoid(CMS) experiment on the Large Hadron Collider(LHC), there are a number of relational data sources providing organization and distribution information for indexing the complex CMS data. To provide accurate keywords query function for data query system, this paper presents a keywords query system which can support different databases. By analyzing the database schema graph, this system can dynamically translate keywords Query Language(QL) into Structured Query Language(SQL) language. During this translation, the key issue is how to solve the ambiguity problem, therefore two algorithms are provided: a schema graph analysis algorithm based on query entities and a dynamic join algorithm based on a minimal weight tree generation. Experimental result shows that the dynamic join algorithm can calculate the connection mode of the database table for keywords query, make the keywords query system have high query efficiency, and meet the needs of users in real time, accurate query.
Key words:
keywords query,
Query Language(QL),
relational database,
Structured Query Language(SQL),
ambiguity problem
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