问题描述
在HashMap中，为什么阈值（要调整大小的下一个大小值）为 capacity * load 因子。为什么不等于大小或地图容量。
In HashMap why threshold value (The next size value at which to resize) is capacity * load factor. Why not as equal to size or capacity of map.
例如，最初默认容量= 16，负载因子= 0.75，因此 threshold =（capacity * load factor）=（16 * 0.75） 12 。
For example initially default capacity = 16 , load factor = 0.75 and hence threshold = (capacity * load factor) = (16 * 0.75) = 12.
当我们添加第13个元素时，地图调整大小为什么会这样，为什么地图作者决定保留 capacity * load factor （12）？为什么不让容量（等于16）。
Map resize when we add 13th element why is it so, why author of map decided to keep it capacity * load factor (which is 12) ? Why not same as capacity (which is 16).
为什么不保持阈值等于容量，以便重新散列只发生在hashmap充满？
why not keep threshold value equal to capacity so that rehashing only takes place when hashmap gets full ?
推荐答案
Javadoc，Javadoc，Javadoc。这是你看的第一个地方。在 HashMap 它说：
Javadoc, Javadoc, Javadoc. That is the first place you look. On the HashMap it says:
对于散列图的理论 - 如果你的地图是满的，那么你在做一些非常，非常错误的事情。到那时，您可能在使用随机数据 - BAD 查找时 O（sqrt（N））。您从不希望您的哈希表已满。但是一个非常稀疏的地图将浪费太多的空间（如你所指出的），并且花费太长的时间来迭代。因此，应该是一个负载因子，在大多数情况下小于1.
As on the theory of hash maps - if your map is full, then you're doing something very, very wrong. By that time you're likely at O(sqrt(N)) on lookups with random data - BAD. You never want your hashmap to be full. But a very sparse map will waste too much space (as you've noted), and will take too long to iterate through. Hence there should be a load factor, that is less than 1 for most use cases.
注意：浪费空间地图的大小，并且与负载因子成反比。然而，查找时间具有更复杂的预期性能函数。这意味着相同的负载因子不适用于不同大小的哈希映射 - 因为这意味着不同的规模权衡。
Note: The "wasted space" is proportional to the size of the map, and inversely proportional to the load factor. However lookup times have a more complex expected performance function. This means that the same load factor will not work for different size hash maps - as it will mean different scale tradeoffs.
权衡的一般概述可以在KnuthThe Art of Computer Programmingvol 3中找到。
A general overview of the tradeoffs can be found in Knuth "The Art of Computer Programming" vol 3.
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