The database session stores these query logs in memory and periodically commits the local history to disk.
数据库会话在内存中保存这些查询日志，并定期将本地历史写入磁盘。
Figure 1 is for a simple query where the results from individual slices need not to be processed further in memory.
图1是一个简单的查询，其中来自各个片的结果无需在内存中做进一步的处理。
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。
The typical consumer of agent private memory is the sort heap memory that is used by the agent to sort rows during query execution.
代理私有内存的常见消费者是排序堆内存，代理在查询执行期间使用这部分内存来对记录行进行排序。
Large buffer pools also have an effect on query optimization, since more of the work can be done in memory.
大型缓冲池还会对查询优化产生影响，因为更多的工作可在内存中完成。
If the goal of a change is to reduce the memory footprint of the database, eliminating various buffers will certainly help, at the expense of query speed and application performance.
如果一项修改的目标是减少数据库的内存占用量，那么取消各种缓冲区肯定会有帮助，但是这会牺牲查询速度和应用程序性能。
DB2 automatically increases the database Shared memory (graph on the left) to satisfy the demands of the workload, resulting in a corresponding increase in query throughput (graph on the right).
DB 2自动增加数据库共享内存(左侧的图)以满足工作负载的需求，最终导致查询吞吐量增加(右侧的图)。
The FPGA then filters out any data not relevant to the query, streaming the remaining data back to memory for concurrent processing by the CPU core.
FPGA然后过滤掉与查询无关的数据，将剩余的数据放回内存，供 CPU 内核进行并发处理。
A query heap is used to store each query in the agent's private memory.
查询堆用于在代理的私有内存中存储每个查询。
In this process, the label, the query we plugged into the search box, remains embedded in working memory.
在这个过程里面，我们放在搜索框里的搜索词，已经印刻在我们的即时记忆之中。
The client and server can query the location of the shared memory resource
客户机和服务器可以查询共享内存区域的位置。
To improve both document loading and query times, you can give eXist more memory.
为了缩短文档装载和查询时间，您可以给eXist更多的内存。
By default, slice executes a query across all active slices and consolidates the result if necessary in memory.
默认情况下，Slice会跨所有的活动片执行查询并在需要的时候在内存中合并结果。
Running this query with IWA took nine minutes, and we were able to reduce the size of the Informix memory buffers.
在结合IWA技术的情况下运行此项查询只需花费9分钟时间，我们可以减少Informix内存缓冲。
Running the same query a second time on Informix alone did not speed things up much because all the data would not fit in memory and the buffers were continually thrashing.
单独在Informix 上再次运行相同查询速度并没有快多少，因为无法将所有数据放入内存中，并且缓冲器一直在超负荷运转。
While you can load the results of a query directly into a DataSet object, a large query result will consume a large amount of memory.
尽管您可以将查询的结果直接加载到DataSet对象中，但大型查询结果将消耗大量内存。
MySQL has a feature called the query cache that stores the result of a query in memory, should it be needed again.
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。
Every five seconds, query the available physical memory and write the result to the log file.
每五秒钟查询一个可用物理内存并将结果写入日志文件。
This parameter specifies the maximum amount of memory that can be allocated for the query heap.
这个参数指定可以分配给查询堆的最大内存量。
Up to 32 levels of nesting is possible, although the limit varies based on available memory and the complexity of other expressions in the query.
尽管根据可用内存和查询中其他表达式的复杂程度的不同，嵌套限制也有所不同，但嵌套到32层是可能的。
Terracotta also released back in February, an extension to Ehcache product called Ehcache search that can be used to query, search and analyze in-memory data.
早在二月份，Terracotta就发布了Ehcache产品的一个扩展EhcacheSearch，这个扩展可用来查询、检索、分析内存中的数据。
The Data Bound Generator USES the query to fill a dictionary, holds this in memory for the duration of the generation and randomly select values from the dictionary.
DataBoundGenerator则使用查询来填充一个字典对象，在生成期间保存到内存里，并从字典对象中随机选择值。
Because the resulting List is lazy, you can query quite a lot of objects without affecting application performance or memory consumption.
由于作为结果的List是惰性的，因而可以不影响应用程序性能或内存消耗即可查询大量对象。
Query Parsing and optimization needs memory. This is usually small to be ignored but certain queries can have very large memory requrement for this step, especially specially crafted ones.
解析查询和优化都需要内存。这些内存通常比较小，可以忽略，不过如果是某些查询在这个步骤中则需要大量内存，尤其是那些设计的比较特别的查询。
The optimizer avoids generating access plans using the hash distinct algorithm if it detects that a low memory situation may occur during query execution.
如果优化程序检测到在查询执行过程中可能会出现内存不足的情况，它将避免使用非重复散列算法生成访问计划。
Accumulate vocabulary. In ordinary life, meets the new words, best form immediately went to the habit of query and memory.
积累词汇。在平时生活中，遇到新单词，最好养成立刻去查询和记忆的习惯。
A context memory model and an approach for context query and association discovery are proposed.
提出了上下文记忆模型以及进行上下文查询和关联关系发现的方法。
D3D Error - Failed to query memory. Please re-start the game.
D3D错误-无法查询内存。请重新启动游戏。
Similar to relational systems, RTQP provides an algorithm for saving main memory space under the MMDB, and a query optimization integrated the rules in RTDBs and the GAs.
类似于关系系统RTQP提供了在MMDB环境下节省内存的查询处理的实现算法，以及遗传算法和实时数据库规则相结合的查询优化方案。
If you use a query operator that materializes its source before yielding the first item, you will not retain a small memory footprint.
如果您使用的查询运算符在生成第一项之前具体化其源，则您不会保持很少的内存需求量。
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