摘要
针对大数据查询效率低下的问题,提出了一种有效的搜索方法。将共享的历史查询结果作为中间结果集,在新的查询请求到达时,首先与历史查询进行匹配,若能实现匹配,则直接将匹配部分的历史查询结果直接作为新查询请求结果的一部分。这减少了大量的对历史查询的重复计算,节省了搜索时间,提高了查询效率。实验对比分析表明,新的基于大数据的查询方法能较好地提高查询效率。
This paper proposed an efficient search method to the problem of low efficiency for large dada queries. Using shared history query results as a set of intermediate results, when a new query request arrives, the first match for histor- ical inquiry is directly added to the matching portion of the historical results for directly as part of the new query result of the request if achieving matching. It can reduce the large number of double counting query history, save search time and improve query efficiency. By experimental comparison and analysis show that data based query methods can improve query efficiency.
出处
《计算机科学》
CSCD
北大核心
2013年第6期183-186,共4页
Computer Science
基金
国家973计划项目(2011CB302302)资助
关键词
大数据
搜索
查询网
云数据库
Big data, Search, Query network, Cloud database
