1) query combining
查询合并
1.
In this paper,a query complete-including method is proposed based on data stream sharing,and then it is optimized to a query combining method with its cost model.
基于在查询间共享数据流的思想,提出了基于查询包含和查询合并的数据流共享策略,并建立了相应的收益模型,最后通过实验分析对比了两种策略的运行效果。
2) Fusion query
合并查询
3) multi-query merging
多查询合并
4) Sub-query combination
子查询合并
5) Progressive combine query
渐进式合并查询
6) parallel query
并行查询
1.
Taking account of operators needs of CPU and disk I/O into account, we focus our research on processor allocation of parallel query on Shared Nothing execution environment.
并行查询中的处理机分配是并行数据库系统中查询优化的重要组成部分。
2.
In order to improve the performance and accuracy of user querying(refer to multi-heterogeneous data sources) in grid environment,the paper presents a parallel querying solution based on multi-ontology.
为了提高网格集成环境中用户查询(涉及多异构数据源)的效率和精确性,提出了基于多本体的并行查询处理方法,给出了全局查询的生成算法和基于查询树的全局查询分解算法。
补充资料：查询
1.查问;调查。
说明：补充资料仅用于学习参考，请勿用于其它任何用途。
参考词条