使用数据消息传递模型和数据访问模式。
Data messaging model and data access patterns are being used.
这两个示例均基于SOA，使用的是模板化非关系数据访问模式。
Both are SOA-based, using the templated non-relational data access pattern.
命中率与缓存大小、底层数据的数量和数据访问模式有关。
The hit ratio is a function of the cache size, the amount of underlying data, and the data access pattern.
然后，消费者应用通过面向服务的数据访问模式对这一集成的数据平台进行抽象。
And we abstract that integrated data platform from the consuming applications via service-oriented data access patterns.
RDBMS设计者的精力主要集中于优化I/O和设法用驱动器的块结构来安排数据访问模式。
RDBMS designers concentrated on optimizing I/O and tried to align the data access patterns with the block structure imposed by the drives.
我们讨论了所支持的各种数据访问模式和基本使用场景，并给出了非常简单的示例和较为复杂的示例。
We have discussed the various data access patterns that are supported and the basic usage scenarios, and we have demonstrated examples ranging from very simple to somewhat complex.
如果使用服务的数量增加，则数据量和并发数据访问模式可能会与最初投入使用时的情况大为不同。
If the number of consuming services increases then both data volumes and concurrent data access patterns may be significantly different from the initial situation.
常见的实现方式是在并行文件系统上层再加入一个可以获取并行程序数据访问模式的层次—并行I/O库。
The common implementation is just adding an I/O library between the applications and the file system to acquire the access pattern of parallel applications.
联机事务处理(OLTP)与联机分析处理(OLAP)并不相同，两种技术所使用的数据访问模式也有很大的区别。
Online transaction processing (OLTP) is not the same thing as online analytical processing (OLAP), and data access patterns for each technique are quite different.
仿真实验结果表明，对于多用户小数据访问模式，优化布局的性能明显优于简单RAID5布局，且具有更高的伸缩性。
The results of simulations show that, optimized data layouts have higher performance than simple RAID5layouts for multiuser small access pattern, and have higher scalability.
NET组件结构入手，通过分析数据访问模式及存储过程等实际问题，研究提高数据访问性能的方法，并提出若干优化性能的方法。
This paper mainly analyzes the structure, data access model and stored procedure, and studies the performance optimization on ADO. NET. Other ways to benefit performance also studied in this paper.
模板化的非关系数据访问：模板化非关系数据访问模式用于将CMPBean 保存到非关系数据存储，而这是 CMP/A的主要设计用途。
Templated Non-relational Data Access: The templated non-relational data access pattern is used to persist CMP beans to a non-relational datastore, which is the primary intended use of CMP/A.
此模式鼓励您分层（表示层、域层、数据访问层）处理应用程序。
This pattern encourages you to treat an application in layers -- presentation, domain, data access.
如果应用程序访问模式主要是更新数据，那么乐观锁定方法能有利地避免乐观并发性更新的失败。
If the application access pattern is predominately update access, then pessimistic approach might be advantageous in that it avoids optimistic concurrency update failures.
数据压缩能力、内存使用情况和访问模式等因素决定了一些不常见的AME优势。
Factors like data compressibility, memory usage and access patterns decide the benefit of AME which are not commonly known.
正如本文所展示的，实现DAO模式需要做比编写低级别的数据访问代码更多的工作。
As this article has shown, implementing the DAO pattern entails more than just writing low-level data access code.
我们将以对DAO设计模式和数据访问对象的概述开始。
We'll start with a review of the DAO design pattern and data access objects.
我们将从回顾数据访问对象模式入手。
We'll begin with a review of the Data Access Object pattern.
消息交换模式：数据服务可以通过四种主要的消息交换模式被访问：请求-应答（严格SLA）、请求-应答（宽松SLA ），即发即弃和发布-订阅。
Message exchange pattern: data services could be accessed via the four primary message exchange patterns - request/reply (tight SLA), request/reply (relaxed SLA), fire/forget, and publish/subscribe.
访问和修改数据的应用程序越多，对模式所提供的结构和指导的需求越迫切。
The more applications that access and modify the data, the greater the need for the structure and guidance that a schema provides.
通过对数据量的预计以及访问模式的理解，就可以估算出成本。
By understanding the volume projections and the access patterns, a cost can be estimated.
而且，对于大多数BI工具而言，分解到关系模式中的MIML数据更易于访问。
Also, MIML data shredded into a relational schema is more easily accessible for most BI tools.
开发人员用这种模式将底层数据访问操作与高层业务逻辑分离开。
Developers use this pattern to separate low-level data access operations from high-level business logic. A typical DAO implementation has the following components.
通过增量解组(incrementalunmarshalling)并提供xget方法来访问内置的模式数据类型，XMLBeans取得了较好的性能。
XMLBeans scores well on performance by doing incremental unmarshalling and providing xget methods to access built-in schema data types.
另外一方面，如果您要处理大量数据集(数据挖掘或数据库操作)，访问更大的数据缓存，那么对于64位模式来说这非常容易。
On the other hand, if you're working with a huge data set (data mining, or database operations), having access to a much larger data cache may quite easily make up for this.
在大多数情况下，由于写访问非常复杂，因此数据联合模式主要用于进行读访问。
In most cases, the data federation pattern is used for read access because of the complexity of write access.
更好的解决方案可能是通过使用模式控制数据库对象访问。
A better solution might be to control database object access through the use of schemas.
访问者模式是一种处理任意数据结构的简单技术。
The visitor pattern is a simple technique to process arbitrary data structures.
数据联合模式允许以实时集成的方式访问源，具有最高的数据并发级别。
The data federation pattern allows for real-time, integrated access to sources with the highest level of data currency.
而模式4和模式5 则涉及访问非聚合格式的数据的其他选项。
Patterns 4 and 5, though, cover other options for accessing data in nonsyndication format.
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