众所周知，内部unordered_map是使用哈希表实现的，因此存储桶是内部哈希表中的一个插槽，根据其键的哈希值将元素分配给该插槽。存储桶的编号从0到(bucket_count-1)。因此，此函数返回存储桶编号。其中具有键的元素位于unordered_map中。
时间复杂度：O(1)。
句法：
unordered_map.bucket(k);
k is the key corresponds to which we want to know bucket number.
Returns: The order number of the bucket corresponding to key k.
关于存储桶，还有另外两个功能：
1. std :: bucket_count：此函数用于计算总数。 unordered_map中的存储桶数。不需要任何参数即可传递给此函数。
时间复杂度：O(1)。
句法：
unordered_map.bucket_count();
Returns: The number of the bucket present in hash table of unordered_map.
2. std :: bucket_size：此函数计算unordered_map的每个存储桶中存在的元素数。
时间复杂度：时段大小呈线性关系。
句法：
unordered_map.bucket_size(i);
where 'i' is the bucket number in which we want
to find no. of elements. (i < bucket_count)
Returns: The number of elements present in bucket 'i'.
// C++ program to demonstrate the use of std::bucket
#include
using namespace std;
int main()
{
// Declaring umap to be of type
// key will be of string type and mapped value will
// be of double type
unordered_map umap;
// inserting values by using [] operator
umap["PI"] = 3.14;
umap["root2"] = 1.414;
umap["log10"] = 2.302;
umap["loge"] = 1.0;
umap["e"] = 2.718;
// Display bucket no. where key, value pair is located
// using bucket(key)
for (auto& x : umap) {
cout << "(" << x.first << ", " << x.second << ")";
cout << " is in bucket= "
<< umap.bucket(x.first) << endl;
}
cout << endl;
// Count the no.of buckets in the unordered_map
// using bucket_count()
int n = umap.bucket_count();
cout << "umap has " << n << " buckets.\n\n";
// Count no. of elements in each bucket using
// bucket_size(position)
for (int i = 0; i < n; i++) {
cout << "Bucket " << i << " has "
<< umap.bucket_size(i) << " elements.\n";
}
return 0;
}
输出：
(PI, 3.14) is in bucket= 5
(e, 2.718) is in bucket= 1
(root2, 1.414) is in bucket= 1
(log10, 2.302) is in bucket= 10
(loge, 1) is in bucket= 7
umap has 11 buckets.
Bucket 0 has 0 elements.
Bucket 1 has 2 elements.
Bucket 2 has 0 elements.
Bucket 3 has 0 elements.
Bucket 4 has 0 elements.
Bucket 5 has 1 elements.
Bucket 6 has 0 elements.
Bucket 7 has 1 elements.
Bucket 8 has 0 elements.
Bucket 9 has 0 elements.
Bucket 10 has 1 elements.
我们还可以打印unordered_map每个存储桶中存在的所有元素。
// C++ program to print all elements present in each bucket
#include
using namespace std;
int main()
{
// Declaring umap to be of type
// key will be of string type and mapped value
// will be of double type
unordered_map umap;
// inserting values by using [] operator
umap["PI"] = 3.14;
umap["root2"] = 1.414;
umap["log10"] = 2.302;
umap["loge"] = 1.0;
umap["e"] = 2.718;
unsigned n = umap.bucket_count();
// Prints elements present in each bucket
for (unsigned i = 0; i < n; i++) {
cout << "Bucket " << i << " contains: ";
for (auto it = umap.begin(i); it != umap.end(i); it++)
cout << "(" << it->first << ", "
<< it->second << ") ";
cout << "\n";
}
return 0;
}
输出：
Bucket 0 contains:
Bucket 1 contains: (e, 2.718) (root2, 1.414)
Bucket 2 contains:
Bucket 3 contains:
Bucket 4 contains:
Bucket 5 contains: (PI, 3.14)
Bucket 6 contains:
Bucket 7 contains: (loge, 1)
Bucket 8 contains:
Bucket 9 contains:
Bucket 10 contains: (log10, 2.302)
std :: unordered_map中存储桶的使用：有许多算法要求将对象散列到一定数量的存储桶中，然后处理每个存储桶。假设您要在集合中查找重复项。您对集合中的所有项目进行哈希处理，然后在每个存储桶中成对比较项目。一个简单的例子是用于查找频繁项集的Apriori算法。
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