Because the user base also grew, data changes became slower and slower.
因为用户量也在增长，数据修改变得越来越慢。
This approach makes it easier to assess the impact of architecture and data changes.
这种方法使得评估架构和数据更改的影响变得更加容易。
Antipatterns: Manually applying database and data changes in each target environment.
反模式：在每个目标环境中手动应用数据库和数据更改。
Using this model, data changes on a page can be automatically reflected on another page.
通过使用这个模型，在一个页面上进行的数据修改可以自动地反映在另一个页面上。
Asynchronous updates let data changes propagate to the clients in a Web 2.0 environment.
异步更新允许将数据更改传播到Web 2.0环境中的各个客户端。
A complementary method is to invalidate the cached entry when the underlying data changes.
一种补充方法是，当底层数据改变时，让缓存的数据项失效。
Mark your transaction as read-only if it doesn't involve data changes as mentioned in Section 4.3.1.
如果不涉及数据变更，将事务标记为只读的，就像4.3.1节提到的那样。
In each scenario, data changes are synchronized automatically, transaction by transaction, or on demand.
在每一种场景中，数据修改都将被自动同步，可以逐一执行同步，也可以按需同步。
The service layer does have one method involving data changes on both databases. Here is the pseudo-code.
服务层上有一个方法设计在两个数据库上执行数据变更。
Do not expect the output of any of the session bean methods to reflect data changes from running other methods.
请不要期望任何会话bean方法的输出能反映因运行其它方法而造成的数据变化。
Er can be configured so that if data changes are made on any server, the other participants become updated too.
可以对ER进行配置，因此如果在任何服务器上修改了数据，那么也将更新其他参与节点。
First, we'd like to show how we were able to protect the JTable's UI code from being altered by any data changes.
首先，我们展示如何保护JTable的UI代码不因任何数据变化而遭到更改。
Only data changes are required to be replicated, so read transaction are unaffected by the implementation of HADR.
由于只需复制被更改的数据，所以读事务不受 HADR实现的影响。
There is also an experimental facility to receive 'push' notifications the instant that data changes on the server.
还有一个实验工具，在服务器上的数据发生变化时能立即接收“推”过来的通知。
Whether a complex data structure is overkill for a plain resume depends on your needs and how often the data changes.
一个复杂数据结构对于一份简单的简历是否过度，要取决于您的需求和数据更改的频率。
Storing a single profile item is useful, but most data changes over time, particularly when you talk about energy usage.
存储单个配置项目很有用，但大多数数据随时间改变，特别是当您谈论能源用途时。
Some database changes require changes in data as well as schema, and some of those data changes require logical changes.
有些数据库变化要求数据和模式一起变化，有些数据变化要求逻辑变化。
And yet a third possibility is that there is simply a tremendous amount of data changes taking place throughout the day.
而第三种可能性是这一天中的确进行了大量数据更改。
So when the interested data changes, the Grid infrastructure (on the server) will send a notification message to the client.
所以当感兴趣的数据发生变化时，Grid基础结构(在服务器上)会向客户机发送一个通知消息。
It is also possible that over time, as your data changes, old partitioning keys become less optimal than they were previously.
随着时间的推移，因数据的改变，旧的分区键有可能会不如之前那么好。
Consumers of XML data returned from data-mining queries are often interested only in the data changes made since a previous query.
从数据挖掘查询返回的XML数据的消费者通常只对自上次查询以来发生的数据变化感兴趣。
When data changes or the values need to be computed, the summaries can be used without necessarily rerunning all of the computations.
当数据更改或值需要被计算时，可以使用各级汇总，而不必重新运行所有计算。
You can synchronize changes in data and schema. You can also address data changes that involve logical operations on your model objects.
可以同步数据和模式中的变化，也可以解决涉及对模型对象进行逻辑操作的数据变化。
In fact, the line of reasoning should simply be how frequently your data changes with respect to how frequently you perform your lookups.
事实上，正确的思路应该是：执行查找的频率与数据变化的频率有关。
It may also improve performance, as not every item in the repeat will need to have its associated controls redrawn when the data changes.
它也可以改善性能，因为当数据更改时，并非repeat中的每一条目都需要刷新其关联控件。
If the nature of the data changes over time, the KB accuracy can be verified periodically, using Classification Workbench reporting tools.
如果数据的性质会随时间变化，那么可以定期使用ClassificationWorkbench报告工具检查知识库的精确性。
Raw data providers are not sufficient for data that is always changing, because the components do not receive notification of data changes.
原始数据提供程序不能满足经常改变的数据的需求，因为组件不能收到数据变更通知。
HADR protects against data loss by replicating data changes from a source database, called the primary, to a target database, called the standby.
HADR把数据修改从源数据库(称为主数据库)复制到目标数据库(称为备用数据库)，从而防止数据丢失。
Grails also supports intercepting Auto reload Events that can be used to monitor resources for any data changes and then reload the changes when they occur.
Grails还支持对自动重新加载事件的拦截，这可用来监控资源的改变，当发生变化时会重新加载资源。
The flow-scoped persistence-context object manages data loaded during the flow as persistent entities, and data changes cached as the entities' dirty states.
流作用域的持久化上下文对象将流期间加载的数据作为持久化实体来管理并将数据变更缓存为实体的脏状态。
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