多维数据结构
下列哪种数据结构是
R树,
R*-树,
X树,
SS 树,
SR 树,
VP 树,
度量树
在以相应形式存储的多维数据的插入、更新和搜索方面提供相当好的性能?
是否有更好的数据结构来处理多维数据?
Which of the following data structure
R-tree,
R*-tree,
X-tree,
SS-tree,
SR-tree,
VP-tree,
metric-trees
provide reasonably good performance in insert, update and searching of multidimensional data stored in its corresponding form?
Is there a better data structure out there for handling multidimensional data?
如果你对这篇内容有疑问,欢迎到本站社区发帖提问 参与讨论,获取更多帮助,或者扫码二维码加入 Web 技术交流群。
绑定邮箱获取回复消息
由于您还没有绑定你的真实邮箱,如果其他用户或者作者回复了您的评论,将不能在第一时间通知您!
发布评论
评论(1)
您所说的多维数据是什么样的?在 R-tree wiki 中,它指出它用于索引多维数据,但似乎很明显,它主要用于同一类型特征中的多维数据——即垂直位置和水平位置、经度和纬度等。
如果数据是多维的,仅仅是因为数据有很多属性并且需要沿着许多这些维度进行分析,那么关系表示可能是最好的。
真正的问题是如何针对需要回答的查询类型优化关系和索引?为此,您需要事先进行一些域分析,并在第一次迭代后进行一些性能分析,以确定是否有更好的方法来构建和索引表。
What kind of multi-dimensional data are you talkign about? In the R-tree wiki, it states that itis used for indexing multi-dimensional data, but it seems clear that it will be primarily useful for data which is multi-dimensional in the same kind of feature -- i.e. vertical location and horizontal location, longitude and latitude, etc.
If the data is multi-dimensional simply because there are a lot of attributes for the data and it needs to be analyzed along many of these dimensions, then a relational representation is probably best.
The real issue is how do you optimize the relations and indices for the type of queries you need to answer? For this, you need to do some domain analysis beforehand, and some performance analysis after the first iteration, to determine if there are better ways to structure and index your tables.