Simplifies JDBC access patterns.
简化jdbc访问模式。
By understanding the volume projections and the access patterns, a cost can be estimated.
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。
Other application areas include intrusion detection, web log analysis, database access patterns, and so on.
其他的应用领域还包括侵入检测、Web日志分析、数据库访问模式等等。
Sequential scans are typical in decision support system (DSS) applications but rare with OLTP access patterns.
顺序扫描一般在决策支持系统(DSS)应用程序中很常见，但很少出现在OLTP访问模式中。
It's also optimized for full table scans (one of the most common-and most time-consuming-business intelligence query access patterns).
它还针对完全表扫描(一个最常见—也最耗时—的商业智能查询访问模式)进行了优化。
Access patterns: The access patterns of an OLTP system consist mainly of short, atomic transactions.
访问模式：OLTP系统的访问主要由短的、原子事务组成。
By theoretic analysis and experimental tests, the algorithm can be used to discover all types of users frequent access patterns.
通过理论分析和实验验证，该算法可以有效地发现用户频繁访问模式。
By analyzing access patterns, a model of evaluating cost was constructed, and its efficiency under various workloads was validated.
通过分析负载的访问模式，构造了一个代价评估模型，并在不同工作负载下验证模型的有效性。
RDBMS designers concentrated on optimizing I/O and tried to align the data access patterns with the block structure imposed by the drives.
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。
In Table 1 you can see a breakdown of the differences between OLTP and OLAP databases, with particular regard to access patterns and resource usage for each type.
在表1中，您可以看到OLTP和OLAP数据库间差异的细目，这些差异主要与每种技术使用的访问模式和资源使用情况相关。
If the number of consuming services increases then both data volumes and concurrent data access patterns may be significantly different from the initial situation.
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。
Online transaction processing (OLTP) is not the same thing as online analytical processing (OLAP), and data access patterns for each technique are quite different.
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。
We derived our deployment requirements from a thorough understanding of our users' access patterns, and the realization that we could not spend time managing physical hardware.
我们通过充分了解用户的访问模式确定了部署需求，同时意识到不能花时间去管理物理硬件。
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.
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。
As explained in Access patterns for service Creation scenario, the main difference between indirect and direct exposure is the inclusion of a service component layer.
正如服务创建场景的访问模式中所述，间接公开和直接公开的区别在于其中包含了服务组件层。
As explained in Access patterns for service Creation scenario, the main difference between indirect and direct exposure is the inclusion of a service component layer.
正如服务创建场景的访问模式中所述，间接公开和直接公开的区别在于其中包含了服务组件层。
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