This little tool has moved very large databases from source to DB2.
这个小工具曾经成功地把数据从非常大的源数据库转移到DB2。
This method can be scaled up to very large databases by parallel projection and compress technique.
该方法能通过并行投影和压缩技术扩展到大数据库中进行挖掘规则。
The need to extract information automatically from very large databases has grown significantly in recent years.
近年来，从大型数据库自动提取知识的需求急剧增长。
As the volume of image database grows, it is urged to work over high effective index technique to support fast similarity search in very large databases.
图像数据库容量的增长，迫切需要研究高效的索引技术来支持快速相似性检索的要求。
They can apply the data mining techniques for very large databases that they learn to research in the medical and biotechnology industries, along with many others.
他们能够将数据挖掘技术应用到医学和生物学领域中的大型数据库中。
DB2 V9 introduced a table partitioning feature that can increase the potential size of a single table, and significantly reduce the maintenance effort required to manage very large databases.
DB 2V 9引入了一个表分区特性，它能够增加一个表的可能大小，同时能够显著减少管理大型数据库所需要的维护。
But if your relational databases contain millions of records, you could have a very large and potentially very slow Notes database.
但是如果关系数据库包含数百万条记录，相应的Notes数据库就可能变得非常大并且可能会非常慢。
Have applications that require very high speed access to large quantities of data, for which traditional databases simply aren't fast enough?
具有这样的应用程序：需要对大量数据进行高速访问，对于此要求，传统的数据库速度根本无法满足需要？
64-bit Linux allows for file sizes up to 4 exabytes (2 to the power of 63), a very significant advantage to servers accessing large databases.
位的Linux允许文件大小最大达到4EB(2的63次幂)，其重要的优点之一就是可以处理对大型数据库的访问。
With the growth of data in volume and dimensionality, it has become a very challenging problem to build a high-efficient classifier for large databases.
随着数据集的数据量和维数的增加，建立高效的、适用于大型数据集的分类法已成为数据挖掘的一个挑战性问题。
Data Mining is a domain which tries to extract knowledge and interesting information from very large-scale databases. This knowledge is hidden, unknown, but potentially useful.
数据挖掘是从大型数据库的数据中提取人们感兴趣的知识，这些知识是隐含的、事先未知的潜在有用信息。
This can be very important for large databases that contain may polygons, most of which will not be in the field-of-view at any one time such as a terrain database.
包含着很多多边形，但是这些多边形大多永远被排除在视野以外，对于一个大型数据库，就像地形数据库来说是很重要的。
Data Mining is a domain that tries to extract knowledge and interesting information from very large-scale databases. This knowledge is hidden, unknown, but potentially useful.
数据挖掘是从大型数据库的数据中提取人们感兴趣的知识，这些知识是隐含的、事先未知的潜在有用的信息。
That is to say, for very large spatial databases, QR-tree processes more superiority than R-tree.
也就是说，对于大型空间数据库索引来说，QR -树与R -树相比整体性能上具有较明显的优势。
That is to say, for very large spatial databases, QR-tree processes more superiority than R-tree.
也就是说，对于大型空间数据库索引来说，QR -树与R -树相比整体性能上具有较明显的优势。
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