同时给出了查询代价视图选择问题的代价模型和实视图选择的过程。
In the meantime, the cost model of the query cost view selection problem and the process of materialized views selection are presented.
有的在向前或向后遍历时产生了大量的冗余数据，从而造成查询代价较大。
Some traverse forward or backward generated a lot of redundant data, resulting in greater price inquiries.
这些常见的查询与总数没有任何关系，但每次却都要返回总数，这就需要付出代价。
Neither of these common queries care about total, but they're paying the cost of fetching it each time.
简介：向DB 2数据库添加索引通常是改善查询性能的最好方法，但添加索引也是有代价的。
Summary: Adding an index to a DB2 database is often the best way to improve query performance, but the addition can have trade-offs.
例如，基于一个非常复杂的、只返回5行的查询(例如一个GROUPBY查询)的视图在远程数据源上计算起来代价较高。
For example, a view based on a very complex query that returns only five rows (for example, a GROUP BY query) is costly to evaluate at the remote source.
查询优化是查询处理研究的一个主要问题，为此着重分析研究了查询优化所涉及的代价估计、查询规划和搜索空间等相关问题。
Query optimization is the main problem of query processing research, thus in particular discusses cost estimated, query plan, search Spaces and so on related problems.
查询优化主要针对连接等一些具有较高执行代价的操作进行研究。
The query optimization mainly researches into some operations that have higher executing cost.
区域划分能够优化位置数据库的拓扑结构，有效地降低查询和更新代价。
Zone partition can effectively optimize the topology of location databases and efficiently reduce the cost of location paging and location update.
在分布式查询优化中，应同时考虑本地处理代价和传输代价。
In the distributed query optimization, both local processing cost and transmission cost should be thought over simultaneously.
在服务器层设计一个查询优化器，并研究了查询重写和代价估计优化方法以及缓存机制。
In the integration server layer, design a query optimizer and research query rewrite, cost estimation model and caches mechanism.
在分布式数据查询处理中，连接操作是最常用的、费时的而且代价较高的一种操作，也是影响查询效率的关键因素。
In processing of distribute data query, the join operation is the kind of the most in common use, time-consuming, higher price, and also is the key factor of the query efficiency for affect.
在分布式数据查询处理中，连接操作是最常用的、费时的而且代价较高的一种操作，也是影响查询效率的关键因素。
In processing of the distribute data query, the join operation is the kind of the most in common use, time-consuming and a higher price, also is the key factor of the query efficiency for affect.
实验结果表明，这种查询空间精练策略能够有效的提高索引的性能，降低相似性查询的IO代价和CPU代价。
Experimental results show that reducing query space can improve the indexing performance effectively and reduce the cost for IO and CPU.
数据库查询优化包括两方面，基于代价的查询优化和基于响应时光的查询优化，可以有效地提高庞杂查询的效力。
There are two methods of database query optimization: cost-based and response time-based query optimization, all of which can improve the efficiency of complex query.
查询语句的优化就是对于给定的查询，选择代价最小的操作序列，使查询过程既节省时间，又节省空间。
The optimization of query sentences is to select operation sequence with minimal costs in terms of given query so as to make query a time-saving and space-saving process.
提出了一种增强预测范围聚集查询epra算法，采用更精确的剪枝搜索准则，减少了查询所需要访问的节点代价。
Also developed for the PRA tree is an enhanced predictive range aggregate (EPRA) query algorithm which USES a more precise branch and bound searching strategy, reducing the disk I?
在分布式数据库查询处理中，连接操作是最常用的、费时的且代价较高的一种操作，也是影响查询效率的关键因素。
For distribute database query, join operation is the kind of the most common use with time-consuming and higher price and also it is the key confluence factor of the query efficiency.
虚拟函数唯一一个明显的代价是在调用虚拟函数之前附加了一个存储查询。
The only significant cost of virtual functions is one additional memory lookup before a virtual function can be called.
实验证明，该方法能够自适应地划分合理的日志区空间，有效提高查询性能，减少各种非聚集索引的更新代价。
The experimental results prove that it can make a proper log region allocation, efficiently improve search performance, and reduce non-clustered index update cost.
在分布式数据库系统中，由于数据的物理分布使得分布式查询处理增加了许多新的复杂性，不同的查询处理策略，其查询处理代价和复杂度是大不一样的。
When adding distributed data into the database system, distributed query process is more difficult and complicated. The cost of query process is different due to different query process tactics.
在分布式数据库系统中，由于数据的物理分布使得分布式查询处理增加了许多新的复杂性，不同的查询处理策略，其查询处理代价和复杂度是大不一样的。
When adding distributed data into the database system, distributed query process is more difficult and complicated. The cost of query process is different due to different query process tactics.
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