You may consider an alternative of using a simple single-column identity clustering key, and creating an indexed view clustered around the 3 columns.
你可能会考虑使用一个简单的另一个单列身份集群键，并创建一个索引视图聚集在3列。
Multi DIMENSIONAL CLUSTERING (MDC) - organizing data in table (or range of a table) by multiple key values.
MULTIDIMENSIONALCLUSTERING (MDC)——根据多个键值组织表(或一个表中的范围)中的数据。
There are two key options when it comes to clustering messaging engines.
集群消息传递引擎时存在两个主要选项。
Clustering Algorithm is a kind of key technique used to reduce energy consumption, which can increase network scalability and lifetime.
成簇算法是传感器网络中减少能量消耗的一种关键技术，它能够增强网络的扩展性和延长网络的生存时间。
We have already discussed this option in the section Key Topologies for WebSphere Process Server Clustering.
我们已经在“WebSphereProcessServer集群的关键拓朴”部分讨论了此选项。
At first, we summarize the key techniques used in the content-based video retrieval, such as shots division, video character analysis, shots clustering, etc.
本文首先分析了基于内容的视频检索的关键技术。总结了镜头分割、视频流特征分析和镜头聚类方面的相关研究和算法。
At the same time, it also puts forward the key technique, including Clustering Analysis and Regression Analysis.
同时，也提出了本文所使用的关键技术，包括聚类分析和回归分析。
This paper briefly discusses the existing approaches. To overcome the shortcomings of the existing approaches, it presents a new approach for key frame extraction based on clustering.
该文简单介绍了目前的关键帧提取技术，提出了一种基于聚类利用颜色直方图提取关键帧的方法来克服其它方法的不足。
An algorithm for selecting episode representation frames by using an approach of key frame extraction based on multiple characters and C-Mean fuzzy clustering is detailed in the paper.
该文在子镜头的关键帧提取方法基础上，利用模糊c -均值聚类算法，实现了一种基于子镜头聚类的情节代表帧选取方法。
This article has also put forward the key procedure and method how to set up high-precision and high-efficiency classification model, regression model and clustering model with the system.
本文还重点提出了利用该系统建立精度好、效率高的分类、回归及聚类模型关键流程及方法。
Clustering of the wireless sensor network and the energy consumption model are the key factors to survival periods of the whole network.
无线传感器网络的分簇以及能量消耗模型是决定整个网络的生存周期等指标的关键因素。
As a result of clustering analysis and railway transport conditions, the transport network of express goods is designed, that contains 10 key nodes, 13 main nodes and 15 general nodes.
根据聚类结果和铁路运输条件，规划出由10个关键节点、13个重要节点和15个一般节点构成的快捷货物运输运力网络。
Discussing the application of fuzzy clustering analysis to product family design, which is the key to mass customization design.
产品族设计是大批量定制设计的关键和核心。分析了模糊聚类分析方法在产品族设计中的应用。
The cluster distance computing method is the key issue affecting the performance of hierarchical clustering algorithm.
在聚类的过程中簇间距离计算的准确性是影响算法性能的重要因素。
How to measure the distance among Web pages is a key problem of Web page clustering.
如何衡量网页间的距离是网页组簇的关键问题。
And the process of clustering enterprises implementing such key factors was also the process of organizational change to adapting the clustered operation model.
这些职能要素在供应链企业集群中实施的过程，也就是各个成员企业进行组织变革以适应集群化生产模式的过程。
The scale of original data is very large. It is difficult to realize the clustering algorithm. Clustering analysis often takes the key attributes as classification parameters.
由于原始海量数据规模较大，聚类算法难以实现，而且聚类分析有时候只考虑关键属性作为分类参数。
The new scheme exploits the clustering algorithm of WSN deployment and the merit of random key pre-distribution.
该模式充分利用了目前无线传感器网络部署中提出的分簇算法，并结合随机密钥预分布模型的优点。
Key attributes are used as inputs for learning by SOM neural network so as to obtain better clustering quality.
将关键属性作为SOM神经模型的输入，提高客户细分质量。
The premise and key of the research of layered routing protocol is an excellent clustering algorithm.
一个良好的分簇算法是进行分层路由协议研究的关键和前提。
Common alternatives include clustering index columns or other unique key columns.
常见的替代项包括索引列或其他唯一键列的群集。
Clustering is one of the key technologies in improving network performance in AD Hoc networks. Enhancing the stability of a clustering algorithm can reduce the maintenance overhead.
分簇技术是提高无线自组网性能的关键技术之一，增强分簇算法的稳定性即减少簇结构的变化可以有效降低其维护开销。
We focus on finding abnormity in datasets with clustering and classified structure and studying the implement and optimization of key technology for outlier detection in this paper.
主要工作和成果如下：①对谱聚类基本原理和典型算法做了较为全面的分析和研究，利用谱聚类的特性实现了在复杂数据集上的聚类。
We focus on finding abnormity in datasets with clustering and classified structure and studying the implement and optimization of key technology for outlier detection in this paper.
主要工作和成果如下：①对谱聚类基本原理和典型算法做了较为全面的分析和研究，利用谱聚类的特性实现了在复杂数据集上的聚类。
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