Exit Zen
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Parameterized by a function object `Hash` and an equivalence relation `Pred`
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`std::allocator_traits<Allocator>::pointer` and `std::allocator_traits<Allocator>::const_pointer` must be convertible to/from `value_type*` and `const value_type*`, respectively.
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image::benchmarks-set/gcc/scattered erasure.xlsx.practice.png[width=250,link=_images/benchmarks-set/gcc/scattered erasure.xlsx.practice.png,window=_blank]
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`BOOST_UNORDERED_ENABLE_SERIALIZATION_COMPATIBILITY_V0`
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`std::allocator_traits<Allocator>::pointer` and `std::allocator_traits<Allocator>::const_pointer` must be convertible to/from `value_type*` and `const value_type*`, respectively.
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`BOOST_UNORDERED_ENABLE_SERIALIZATION_COMPATIBILITY_V0`
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xref:reference/unordered_set.adoc[`unordered_set`]
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image::benchmarks-set/gcc/scattered erasure.xlsx.practice non-unique.png[width=250,link=_images/benchmarks-set/gcc/scattered erasure.xlsx.practice non-unique.png,window=_blank]
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image::foa-metadata.png[align=center]
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xref:reference/unordered_multiset.adoc[`unordered_multiset`]
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Added container `pmr` aliases when header `<memory_resource>` is available. The alias `boost::unordered::pmr::[container]` refers to `boost::unordered::[container]` with a `std::pmr::polymorphic_allocator` allocator type.
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You can load the pretty-printers externally from the non-embedded Python script. Add the script, link:https://github.com/boostorg/unordered/blob/develop/extra/boost_unordered_printers.py[/extra/boost_unordered_printers.py], using the `source` command as shown below.
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image::benchmarks-set/gcc/scattered erasure.xlsx.practice non-unique 5.png[width=250,link=_images/benchmarks-set/gcc/scattered erasure.xlsx.practice non-unique 5.png,window=_blank]
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`local_iterator begin(size_type n)`
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`BOOST_UNORDERED_ENABLE_SERIALIZATION_COMPATIBILITY_V0`
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`BOOST_UNORDERED_ENABLE_SERIALIZATION_COMPATIBILITY_V0`
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If `link:../../../../../container_hash/doc/html/hash.html#ref_hash_is_avalanchinghash[hash_is_avalanching]<Hash>::value` is `true`, the hash function is used as-is; otherwise, a bit-mixing post-processing stage is added to increase the quality of hashing at the expense of extra computational cost.
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Since release 1.79.0, https://en.wikipedia.org/wiki/Hash_function#Fibonacci_hashing[Fibonacci hashing] is used instead. With this implementation, the bucket number is determined by using `(h * m) >> (w - k)`, where `h` is the hash value, `m` is `2^w` divided by the golden ratio, `w` is the word size (32 or 64), and `2^k` is the number of buckets. This provides a good compromise between speed and distribution.
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If `link:../../../../../container_hash/doc/html/hash.html#ref_hash_is_avalanchinghash[hash_is_avalanching]<Hash>::value` is `true`, the hash function is used as-is; otherwise, a bit-mixing post-processing stage is added to increase the quality of hashing at the expense of extra computational cost.
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- 0 if the corresponding bucket is empty. - 1 to encode a special empty bucket called a _sentinel_, which is used internally to stop iteration when the container has been fully traversed. - If the bucket is occupied, a _reduced hash value_ obtained from the hash value of the element.
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