花时间确定如何让查询缓存为你工作是值得的。
It is worth the time to figure out how to get query caching working for you.
MySQL可以使用其查询缓存为查询阶段提速。
需要指出的是关于性能的主要设计要素是查询缓存。
It's pointed out that a major design element for performance is the query cache.
它首先使查询缓存无效。
不过，问题是查询缓存在默认情况下是禁用的。
The catch, though, is that the query cache is disabled by default.
在数据查询方面提出了高速查询缓存优化策略。
In aspect of data querying, it proposed optimized strategy of fast query cache.
在启用查询缓存之后，重要的是要理解它是否得到了有效的使用。
After you enable the query cache, it's important to understand whether it's being used effectively.
例如，它不需要会话缓存，也不和任何二级缓存或查询缓存有交互。
For example, it doesn't have session cache, and nor does it interact with any second-level or query cache.
经过解析的人员查询缓存在BPEDB中，但是公司中的人员可能会有变动。
Resolved staff queries are cached in the BPEDB, but the staff in a company can change.
MySQL有一个特性称为查询缓存，它将（后面会用到的）查询结果保存在内存中。
MySQL has a feature called the query cache that stores the result of a query in memory, should it be needed again.
任何一个查询的首次执行都包含了构建一个查询缓存的性能损耗，以利于提高后续查询的执行速度。
Initial execution of any query includes the costs of building up a query cache to enable faster execution of subsequent queries.
由于您正在本地缓存来自Twitter的搜索结果，您肯定不希望浏览器再执行间接的查询缓存。
Since you are locally caching search results from Twitter, you certainly do not want the browser to do any more indirect caching of queries.
通过添加代码来同时在单个进程中管理多个用户的查询缓存，不需要挂起进程，而可以进行切换来为另一个用户执行工作。
By adding code to manage query caches for multiple users at the same time in a single process, the process need not be suspended, but can be switched to perform work for another user.
mytop还提供了一个有关关键字缓冲区和查询缓存效率的实时数据和历史数据，以及有关正在运行的查询的统计信息。
mytop also provides real-time and historical data about key-buffer and query-cache efficiency, and statistics about the queries being run.
例2：一家包括“最后登录”字段的用户表，用户每登录网站都会要更新，而每次对表的更新都会导致这个表的查询缓存要刷新。
Example 2: you have a "last_login" field in your table. It updates every time a user logs in to the website. But every update on a table causes the query cache for that table to be flushed.
虽然可以使用memcached存储加载自数据库的数据行，但这实际上是查询缓存，并且大多数数据库都提供各自的查询缓存的机制。
Although you can use memcached to store the rows of data as loaded from a database, this is really query caching, and most databases provide their own query-caching mechanism.
为了提速，您可以高速缓存从搜索查询得到的结果，然后在用户每次提交查询时使用这些缓存的结果。
To speed this up, you can cache the results from a search query and use these cached results whenever a user submits a query.
文件系统缓存仅对查询Q1(检索全部文档，无谓词运算)有较大影响。
File system caching has a significant impact only on query Q1 which retrieves all documents without any predicate evaluation.
它允许使用64位数据源驱动程序，且可以利用64位满足查询处理、元数据缓存和数据缓存的空间。
It permits the use of 64 bit data source drivers and can leverage the 64 bit address space for query processing, metadata caching and data caching.
在优化查询和缓存页面这两个选项当中，如果您能“消受”复杂性，缓存页面将会带来更大的回报。
Given a choice between optimizing a query and caching a page, caching the page will give you a far greater return, if you can stomach the complexity.
在运行时，这个平台将管理所有数据库事务，发出SQL查询，缓存结果并将结果绑定到表单和API对象。
At runtime, the platform will manage all database transactions, issuing SQL queries, caching and binding results to forms and API objects.
开发人员必须编写代码来实现数据访问层，包括优化SQL查询、缓存结果以优化性能，而不会损害应用程序的规模。
Developers must write code to implement the data access layer, including optimizing SQL queries, caching results to optimize performance, without compromising an application's footprint.
若能分析日志和确保常用的查询被缓存，将会非常有帮助。
Analyzing your logs and making sure frequent queries are cached can be significantly helpful.
它可以基于灵活的授权规则执行人员解析查询，并可以缓存查询结果，以获得更好的授权性能。
It performs staff resolution queries based on flexible authorization rules, and caches the query results for better authorization performance.
它还可以从SQL缓存捕获查询并生成解释计划。
It can also capture queries from SQL cache and produce the explain plan.
现在我们来谈谈关于二级缓存的查询优化问题。
Now let us discuss the issue with the query optimization for the objects which are configured for second level cache.
一旦创建了MQT，就需要用数据填充它，以反映MQT将缓存的查询结果。
Once the MQT is created, it needs to be populated with data to reflect the results of the query that the MQT is supposed to cache.
第一个查询项的位置就是缓存。
第一个查询项的位置就是缓存。
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