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The number of elements in bucket `n`.
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image::buckets.png[]
image::buckets.png[]
In order to decide which bucket to place an element in, the container applies the hash function, `Hash`, to the element's key (for sets the key is the whole element, but is referred to as the key so that the same terminology can be used for sets and maps). This returns a value of type `std::size_t`. `std::size_t` has a much greater range of values then the number of buckets, so the container applies another transformation to that value to choose a bucket to place the element in.
容器通过哈希函数 `Hash` 作用于元素的键来确定其所属的桶（对于集合而言，键即元素本身，但为统一集合与映射表的术语仍称作键）。该函数返回 `std::size_t` 类型的值。由于 `std::size_t` 的取值范围远大于桶的数量，容器会对此值进行二次转换以确定元素应存入的桶。
Retrieving the elements for a given key is simple. The same process is applied to the key to find the correct bucket. Then the key is compared with the elements in the bucket to find any elements that match (using the equality predicate `Pred`). If the hash function has worked well the elements will be evenly distributed amongst the buckets so only a small number of elements will need to be examined.
根据指定键检索元素的过程非常简单：首先对键执行相同处理以定位对应桶，随后通过相等性谓词 `Pred` 将键与桶内元素进行比较以寻找匹配项。若哈希函数表现良好，元素将均匀分布于各桶中，此时仅需检查少量元素即可完成检索。
There is xref:hash_equality.adoc#hash_equality[more information on hash functions and equality predicates in the next section].
关于哈希函数与相等性谓词的详细说明请参阅 xref:hash_equality.adoc#hash_equality[后续章节] 。
You can see in the diagram that `A` & `D` have been placed in the same bucket. When looking for elements in this bucket up to 2 comparisons are made, making the search slower. This is known as a *collision*. To keep things fast we try to keep collisions to a minimum.
如图所示， `A` 与 `D` 被置于同一桶内。在此桶内查找元素时最多需要进行 2 次比对，这会降低检索效率，该现象称为**冲突**。为维持高效运作，我们需尽可能减少冲突的发生。
If instead of `boost::unordered_set` we had used `xref:reference/unordered_flat_set.adoc[boost::unordered_flat_set]`, the diagram would look as follows:
若使用 xref:reference/unordered_flat_set.adoc[boost::unordered_flat_set]替代 `boost::unordered_set` ，其结构示意图将呈现如下形式：
image::buckets-oa.png[]
image::buckets-oa.png[]
In open-addressing containers, buckets can hold at most one element; if a collision happens (like is the case of `D` in the example), the element uses some other available bucket in the vicinity of the original position. Given this simpler scenario, Boost.Unordered open-addressing containers offer a very limited API for accessing buckets.
在开放寻址式容器中，每个桶最多只能容纳一个元素；若发生冲突（如示例中的元素 `D` 的情况），该元素将使用原始位置附近的其他可用桶。基于此简化设计，Boost.Unordered开放寻址容器仅提供极其有限的桶访问API。
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2+^h| *All containers* h|*Method* h|*Description*
2+^h| *所有容器* h|*方法* h|*描述*
`size_type bucket_count() const`
`size_type bucket_count() const`
The number of buckets.
桶的数量。
2+^h| *Closed-addressing containers only* h|*Method* h|*Description*
2+^h| *仅限闭寻址容器* h|*方法* h|*描述*
`size_type max_bucket_count() const`
`size_type max_bucket_count() const`
An upper bound on the number of buckets.
桶数量的上限。
`size_type bucket_size(size_type n) const`
`size_type bucket_size(size_type n) const`
The number of elements in bucket `n`.
返回桶 `n` 中的元素数量。
`size_type bucket(key_type const& k) const`
`size_type bucket(key_type const& k) const`
Returns the index of the bucket which would contain `k`.
返回键 `k` 所对应的桶的索引。
`local_iterator begin(size_type n)`
`local_iterator begin(size_type n)`
1.6+|Return begin and end iterators for bucket `n`.
1.6+|返回编号为 `n` 的桶的起始与末尾迭代器。
`local_iterator end(size_type n)`
`local_iterator end(size_type n)`
`const_local_iterator begin(size_type n) const`
`const_local_iterator begin(size_type n) const`
`const_local_iterator end(size_type n) const`
`const_local_iterator end(size_type n) const`
`const_local_iterator cbegin(size_type n) const`
`const_local_iterator cbegin(size_type n) const`
`const_local_iterator cend(size_type n) const`
`const_local_iterator cend(size_type n) const`
Controlling the Number of Buckets
桶数量控制
As more elements are added to an unordered associative container, the number of collisions will increase causing performance to degrade. To combat this the containers increase the bucket count as elements are inserted. You can also tell the container to change the bucket count (if required) by calling `rehash`.
当无序关联容器中的元素不断增加时，冲突次数会随之上升，从而导致性能下降。为解决此问题，容器会在插入元素过程中自动增加桶的数量。用户也可以通过调用 `rehash` 方法来按需调整容器的桶数量。
The standard leaves a lot of freedom to the implementer to decide how the number of buckets is chosen, but it does make some requirements based on the container's _load factor_, the number of elements divided by the number of buckets. Containers also have a _maximum load factor_ which they should try to keep the load factor below.
标准规范虽未强制规定桶数量的具体选择方式，但基于容器的__负载因子__（即元素数量与桶数量的比值）提出了若干要求。同时，容器还设有一个__最大负载因子__，其运行过程中需始终将实际负载因子维持在该阈值以下。
You can't control the bucket count directly but there are two ways to influence it:
用户无法直接控制桶的数量，但可通过以下两种方式间接调控：
Specify the minimum number of buckets when constructing a container or when calling `rehash`.
用户可在构造容器或调用 `rehash` 方法时指定桶数量的最小值。
Suggest a maximum load factor by calling `max_load_factor`.
用户可通过调用 `max_load_factor` 方法来设定最大负载因子的建议值。
English Chinese (Simplified Han script) Actions
:idprefix: buckets_
:idprefix: buckets_
There is xref:hash_equality.adoc#hash_equality[more information on hash functions and equality predicates in the next section].
关于哈希函数与相等性谓词的详细说明请参阅 xref:hash_equality.adoc#hash_equality[后续章节] 。
Returns the index of the bucket which would contain `k`.
返回键 `k` 所对应的桶的索引。
In order to decide which bucket to place an element in, the container applies the hash function, `Hash`, to the element's key (for sets the key is the whole element, but is referred to as the key so that the same terminology can be used for sets and maps). This returns a value of type `std::size_t`. `std::size_t` has a much greater range of values then the number of buckets, so the container applies another transformation to that value to choose a bucket to place the element in.
容器通过哈希函数 `Hash` 作用于元素的键来确定其所属的桶（对于集合而言，键即元素本身，但为统一集合与映射表的术语仍称作键）。该函数返回 `std::size_t` 类型的值。由于 `std::size_t` 的取值范围远大于桶的数量，容器会对此值进行二次转换以确定元素应存入的桶。
Retrieving the elements for a given key is simple. The same process is applied to the key to find the correct bucket. Then the key is compared with the elements in the bucket to find any elements that match (using the equality predicate `Pred`). If the hash function has worked well the elements will be evenly distributed amongst the buckets so only a small number of elements will need to be examined.
根据指定键检索元素的过程非常简单：首先对键执行相同处理以定位对应桶，随后通过相等性谓词 `Pred` 将键与桶内元素进行比较以寻找匹配项。若哈希函数表现良好，元素将均匀分布于各桶中，此时仅需检查少量元素即可完成检索。
You can see in the diagram that `A` & `D` have been placed in the same bucket. When looking for elements in this bucket up to 2 comparisons are made, making the search slower. This is known as a *collision*. To keep things fast we try to keep collisions to a minimum.
如图所示， `A` 与 `D` 被置于同一桶内。在此桶内查找元素时最多需要进行 2 次比对，这会降低检索效率，该现象称为**冲突**。为维持高效运作，我们需尽可能减少冲突的发生。
If instead of `boost::unordered_set` we had used `xref:reference/unordered_flat_set.adoc[boost::unordered_flat_set]`, the diagram would look as follows:
若使用 xref:reference/unordered_flat_set.adoc[boost::unordered_flat_set]替代 `boost::unordered_set` ，其结构示意图将呈现如下形式：
image::buckets-oa.png[]
image::buckets-oa.png[]
In open-addressing containers, buckets can hold at most one element; if a collision happens (like is the case of `D` in the example), the element uses some other available bucket in the vicinity of the original position. Given this simpler scenario, Boost.Unordered open-addressing containers offer a very limited API for accessing buckets.
在开放寻址式容器中，每个桶最多只能容纳一个元素；若发生冲突（如示例中的元素 `D` 的情况），该元素将使用原始位置附近的其他可用桶。基于此简化设计，Boost.Unordered开放寻址容器仅提供极其有限的桶访问API。
`size_type bucket_count() const`
`size_type bucket_count() const`
2+^h| *Closed-addressing containers only* h|*Method* h|*Description*
2+^h| *仅限闭寻址容器* h|*方法* h|*描述*
`size_type max_bucket_count() const`
`size_type max_bucket_count() const`
An upper bound on the number of buckets.
桶数量的上限。
`size_type bucket_size(size_type n) const`
`size_type bucket_size(size_type n) const`
The number of elements in bucket `n`.
返回桶 `n` 中的元素数量。
`size_type bucket(key_type const& k) const`
`size_type bucket(key_type const& k) const`
`local_iterator begin(size_type n)`
`local_iterator begin(size_type n)`
1.6+|Return begin and end iterators for bucket `n`.
1.6+|返回编号为 `n` 的桶的起始与末尾迭代器。
`local_iterator end(size_type n)`
`local_iterator end(size_type n)`
`const_local_iterator begin(size_type n) const`
`const_local_iterator begin(size_type n) const`
`const_local_iterator end(size_type n) const`
`const_local_iterator end(size_type n) const`
`const_local_iterator cbegin(size_type n) const`
`const_local_iterator cbegin(size_type n) const`
`const_local_iterator cend(size_type n) const`
`const_local_iterator cend(size_type n) const`
Controlling the Number of Buckets
桶数量控制
As more elements are added to an unordered associative container, the number of collisions will increase causing performance to degrade. To combat this the containers increase the bucket count as elements are inserted. You can also tell the container to change the bucket count (if required) by calling `rehash`.
当无序关联容器中的元素不断增加时，冲突次数会随之上升，从而导致性能下降。为解决此问题，容器会在插入元素过程中自动增加桶的数量。用户也可以通过调用 `rehash` 方法来按需调整容器的桶数量。
Specify the minimum number of buckets when constructing a container or when calling `rehash`.
用户可在构造容器或调用 `rehash` 方法时指定桶数量的最小值。
Suggest a maximum load factor by calling `max_load_factor`.
用户可通过调用 `max_load_factor` 方法来设定最大负载因子的建议值。
`max_load_factor` doesn't let you set the maximum load factor yourself, it just lets you give a _hint_. And even then, the standard doesn't actually require the container to pay much attention to this value. The only time the load factor is _required_ to be less than the maximum is following a call to `rehash`. But most implementations will try to keep the number of elements below the max load factor, and set the maximum load factor to be the same as or close to the hint - unless your hint is unreasonably small or large.
`max_load_factor` 并不允许用户自行设定最大负载因子，该方法仅用于提供__提示__。即便如此，标准也并未强制要求容器必须严格遵守该数值。唯一强制要求负载因子必须小于最大值的场景是在调用 `rehash` 方法之后。但大多数实现会尝试将元素数量维持在最大负载因子以下，并将最大负载因子设定为与提示值相同或接近——除非用户提供的提示值过小或过大。
`X(size_type n)`
`X(size_type n)`
`size_type max_load() const`
`size_type max_load() const`

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The number of elements in bucket `n`.
The number of elements in bucket `n`.返回桶 `n` 中的元素数量。
06/05/2026
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The number of elements in bucket `n`.
The number of elements in bucket `n`.
06/05/2026
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safe-html, strict-same
Unit identifier
51284
Source string location
:57
String age
06/05/2026
Last updated
06/06/2026
Source string age
06/05/2026
Translation file AsciiDoc file
doc/modules/ROOT/pages/buckets_zh_Hans.adoc, string 19