Therefore, it would be wasteful to query a database on every request to get the latest list of categories.
因此，对于每个请求都通过查询数据库获取最新的分类列表是很浪费的。
The virtual database coordinates the execution of the queries on the physical databases and post-processes the results of the individual query in memory to prepare a consolidated result.
此虚拟数据库会协调这些查询在物理数据库上的执行，并会在内存内置后处理各个查询的结果用以准备一个合并结果。
If you need to wait on a blocking action — say, the results from a remote database query — it is not clear exactly how long you will need to wait for results to be available.
如果您需要等待一个阻塞操作—比如，对于来自远程数据库查询的结果—您不会确切地知道在可以使用结果之前究竟要等待多长时间。
And they only appear when the database administrator runs a query profiler on your system when it has performance problems.
并且它们只有在数据库管理员在系统具有性能问题时在系统上运行查询剖析器时才会出现。
Instead, the optimizer gathers up-to-date statistics on every database table referenced in a query.
相反，优化器将对查询中引用的每个数据库表收集最新的统计数据。
Suppose a database that resides on a storage area network (SAN) storage array exhibits poor performance every time a certain query is run against it.
假设位于一个存储区域网络(SAN)存储阵列上的数据库在每次对它运行某个查询时具有糟糕的性能。
Database search is great to retrieve structured and exactly matched data, but it requires highly specialized knowledge on query construction and data model familiarity.
用数据库搜索来检索结构化且严格匹配的数据十分管用，但这需要对查询结构和数据模型十分熟悉和了解才行。
JPQL is a full-featured query language with syntax similar to SQL, but it operates on entities rather than database tables.
JPQL是一种语法上类似于SQL的完备查询语言，但是它是在实体上，而不是在数据库表上进行操作。
Additionally, more and more data is being marked-up using XML; this puts pressure on database companies to add XML storage, persistence, and query capabilities to their products.
何况越来越多的数据正使用XML标记，这就迫使数据库公司在产品中增加XML存储、持久性和查询的能力。
The business delegate may in turn rely on a DAO object that in turn relies on a database query or an or mapping query that sorts the CDs very efficiently.
业务代理又可能会依赖于一个dao对象，而后者又依赖于一个数据库查询或OR映射查询，这样可以对CD进行有效的查询。
The discussion focused on a couple of big issues of database design without getting into the details of query optimization and application considerations.
本文着重讨论了数据库设计的两个比较大的问题，而没有深入研究查询优化和应用程序考虑事项的细节。
You can make the SQL query on the predefined BPC database view.
您可以在预定义的BPC数据库视图上执行SQL查询。
The database structure needs to hold the survey results and then enable you to query and report on the data that has been stored.
数据库结构需要能够保存问卷调查的结果，然后允许您对所存储的数据进行查询和报告。
This activity sends a query to the database and returns none, one or more account datasets depending on the query.
该活动会向数据库发送一条查询，该查询会返回零个、一个或多个账户数据集合。
The design of a data warehouse database is focused on query performance.
数据仓库数据库设计的重点在于查询性能。
Now imagine a database with enough of these records that a query for images taken on 2009-11-16 returns 5,000 images.
现在假设一个数据库具有足够的记录，查询拍摄于2009-11-16的图像将返回5,000个图像。
The customer ID is also extracted from the message and is used to query the database for information on the items purchased by the customer.
再次从消息中提取出客户ID，并用它在数据库中查询这位客户购买的商品的相关信息。
They're considerably slower than a join on a relational database, but, as a result, it is much harder to create a query that overwhelms the data store.
这要比关系数据库上的连接慢得多，因此很难创建一个让数据存储超负荷的查询。
Future articles will build on this foundation to query, update, and delete data from an Apache Derby database.
后续文章将在此基础上查询、更新和删除ApacheDerby数据库中的数据。
Query optimization focuses on CPUbound execution paths, while a fully cached database will still be preoccupied with optimizing page fetches to mass storage that are no longer an issue.
查询优化集中于cpu密集型(CPUbound)执行路径，而全缓存数据库将仍然集中于优化取页到大容量存储器的操作，而这已不再是问题。
Consider the following query on the EMPLOYEE table in the SAMPLE database.
考虑对SAMPLE数据库的employee表执行如下查询。
For example, early attempts at storing XML data in varchar2 fields of a relational database resulted in poor query performance when an XQuery engine was simply layered on top.
比如，最初曾经尝试将XML数据保存在关系数据库的varchar2字段中，然后简单地增加一个XQuery引擎层，结果查询性能很差。
You can confirm that the database has in fact been updated by performing a select query on the cachetbl as you can see in Figure 1.
通过对cachetbl执行一个选择查询，可以确认数据库实际上已经更新，如图1所示。
You choose the database and write the query that is to be fired on a server, and click Submit.
选择数据库并编写要在服务器上执行的查询，然后单击submit。
The same applies to the result set entries when a user queries items on the Business Process Choreographer database view using one of the query API methods (see Resources).
当用户使用queryAPI方法之一在业务流程编排数据库视图中查询项时，结果集项的情况也是如此(请参阅参考资料)。
Those objects on the server can then deal with its native data types as arguments, query a database from those arguments, and return its native data types as values.
而该服务器上的那些对象随后就可以作为参数处理原生数据类型、从这些参数查询数据库并作为值返回其原生数据类型。
On the server, you use code to query a database or retrieve data from a service.
在服务器端，主要是使用代码来查询数据库或从服务检索数据。
In the first installment of this two-part column, I focused on the pros and cons of reducing query times by adding indexes to a DB2 database.
在这个两部分系列的第一期中，我重点介绍了通过将索引添加到DB 2数据库来减少查询次数的优势和缺点。
For sparse lookup, a database query is generated based on each input record and the query is sent to the target database to get the result.
对于稀疏查找来说，它将根据每条输入记录来生成数据库查询，并且查询将被发送给目标数据库以获取结果。
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