向量载体存在哪些问题? [英] What are the Issues with a vector-of-vectors?
问题描述
我已经读到vector -of- vector s在给定的2 nd 维度下是不好的，但是我找不到关于 http://www.stackoverflow.com .
I've read that a vector-of-vectors is bad given a fixed 2nd dimension, but I cannot find a clear explanation of the problems on http://www.stackoverflow.com.
有人可以解释为什么在单个vector上使用2D索引比在固定的2 nd 维度上使用vector -of- vector更好吗?
Could someone give an explanation of why using 2D indexing on a single vector is preferable to using a vector-of-vectors for a fixed 2nd dimension?
此外，我假设vector -of- vector s是具有2 nd 变量的2D数组的首选数据结构?如果有相反的证据，我很乐意看到.
Also, I'm assuming that a vector-of-vectors is the preferable data structure for a 2D array with a variable 2nd dimension? If there is any proof to the contrary I'd love to see that.
推荐答案
我将用一个简单的类比来回答.
I shall answer with a simple analogy.
在这两件事中，更好"通常是什么?
What is "better" in general out of the two things?
- 电话簿，其中每个条目都是一个代码，它是指您必须查找并阅读以发现某人电话号码的另一本书的代码
- 一本列出人们电话号码的电话簿
在计算机缓存中将所有数据保存在一个大blob中更简单，更明智，更容易.在内部带有 N 个向量的向量要复杂得多(请记住，每个向量都需要动态分配和大小管理操作！)；一个向量就是一个向量您还没有将工作量乘以 N .
Keeping all your data in a single big blob is more simple, more sensible, and easier on your computer's cache. A vector with N vectors inside it is much more operationally complex (remember, each of those requires a dynamic allocation and size management operations!); one vector is, well, one vector. You haven't multiplied the workload by N.
唯一的缺点是要使用1D基础数据存储来模拟2D阵列访问，您需要编写一个Facade.幸运的是，这很容易.
The only downside really is that to simulate 2D array access with a 1D underlying data store, you need to write a facade. Fortunately, this is very easy.
现在是主观部分:总的来说，除非您真的很急并且您的代码质量并不特别重要，否则我认为这是值得的.
Now for the subjective part: on balance I'd say that it's worthwhile unless you're really in a rush and your code quality doesn't particularly matter.
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