稀疏哈希表背后的主要实现思想是什么？ [英] What is the main implementation idea behind sparse hash table?

问题描述

为什么Google sparsehash开源库有两个实现：一个密集的哈希表和一个稀疏的

Why does Google sparsehash open-source library has two implementations: a dense hashtable and a sparse one?

推荐答案

密集哈希表是您普通的教科书散列表实现。

The dense hashtable is your ordinary textbook hashtable implementation.

稀疏哈希表仅存储实际设置的元素，并分割数组。引用稀疏执行中的评论表：

The sparse hashtable stores only the elements that have actually been set, divided over a number of arrays. To quote from the comments in the implementation of sparse tables:

// The idea is that a table with (logically) t buckets is divided
// into t/M *groups* of M buckets each.  (M is a constant set in
// GROUP_SIZE for efficiency.)  Each group is stored sparsely.
// Thus, inserting into the table causes some array to grow, which is
// slow but still constant time.  Lookup involves doing a
// logical-position-to-sparse-position lookup, which is also slow but
// constant time.  The larger M is, the slower these operations are
// but the less overhead (slightly).

要知道数组的哪些元素被设置，一个稀疏表包含一个位图：

To know which elements of the arrays are set, a sparse table includes a bitmap:

// To store the sparse array, we store a bitmap B, where B[i] = 1 iff
// bucket i is non-empty.  Then to look up bucket i we really look up
// array[# of 1s before i in B].  This is constant time for fixed M.

的固定时间，以便每个元素只产生一个开销（在限制）。

so that each element incurs an overhead of only 1 bit (in the limit).

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