数据库存取 meaning in English
da database access
database access
Examples
- The website is running on the intranet and it works well . this dissertation provides a new method to manage the parts " drawings , which is applicable to not only dryland machines " parts drawings but also all kinds of machines " parts drawings
本研究为工程图纸的电子化管理提出了一种新的方案，并利用了web技术实现了dwf格式电子图纸数据库存取和矢量图形网上浏览，在降低用户软件要求的基础上，实现图纸的管理应用。 - To persistence the objects there are two common approach . one approach is that structured query language ( sql ) codeis embedded in the source code of your classes . the other approach is that sql statements for your business classes are encapsulated in one or more " data classes . " the disadvantage is that it directly couples your business classes with the schema of your relational database , implying that a simple change such as renaming a column or porting to another database results in a rework of your source code
实现在关系数据库存取对象,常用的做法有：一种方法是在对象中直接编写sql代码来存取对象，另一种方法是将sql代码在专门的数据类（或存储过程）中编写，但着两种方式都使得对象模型与关系数据库模式的耦合度大，不容易维护，因为关系数据库模式的微小改动，都将导致应用程序的重新编译。 - An efficient algorithm qais is proposed that uses the efficient method to reduce database access activity , and present a novel algorithm aiu based on this algorithm , it is fit for mining association rules and incremental updating . it is especially effective in vldb , mining long patterns , and high support . the perfermance of qais / aiu is verified on the basis of synthetic data , experiments show that the proposed algorithm can mine association rules more efficiently by not generating candidate itemsets and reducing the redundancy of frequent itemsets while generating association rules
然而目前大多数挖掘关联规则的算法往往必需多次扫描事务数据库才能达到要求的目标，这样重复性的数据库存取动作将会导致过多的执行时问浪费在i o动作上，另外在频繁集生成规则时现有的算法没有考虑到规则的大量冗余，为了解决这个问题本文提出了一个不需要生成候选集同时有效的去除生成规则时产生大量冗余的算法qais ，来提高关联规则生成的速度，并且在此算法基础上提出了新颖的关联规则增量更新算法aiu ，通过应用合成数据验证了qais aiu算法的有效性，由试验结果来看这个方法确实能更有效且准确地获得事务数据库的关联规则，尤其适合挖掘超大数据库中高支持度下长模式的挖掘。 - General kinds of apriori - like algorithm always produce huge number of candidate itemset , and it ' s a grave burden to mining efficiency . at the same time apriori - like algorithm needs repeated confirming of the database fetch in every stage circulation . that is also a great burden for the system
一般的类aprioir算法会产生非常庞大的候选项集，对挖掘的效率是一个沉重的负担，并且类apriori在每一阶段循环都需要进行重复数据库存取确认，这对系统而言也是一个很大的负担。