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524 lines
18 KiB
C++
524 lines
18 KiB
C++
/*
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* Copyright 2016 Facebook, Inc.
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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#pragma once
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#include <atomic>
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#include <functional>
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#include <stdexcept>
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#include <system_error>
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#include <type_traits>
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#include <stdint.h>
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#include <folly/Bits.h>
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#include <folly/Conv.h>
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#include <folly/Likely.h>
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#include <folly/Random.h>
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#include <folly/detail/AtomicUnorderedMapUtils.h>
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#include <folly/portability/SysMman.h>
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#include <folly/portability/Unistd.h>
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#include <boost/type_traits/has_trivial_destructor.hpp>
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#include <limits>
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namespace folly {
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/// You're probably reading this because you are looking for an
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/// AtomicUnorderedMap<K,V> that is fully general, highly concurrent (for
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/// reads, writes, and iteration), and makes no performance compromises.
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/// We haven't figured that one out yet. What you will find here is a
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/// hash table implementation that sacrifices generality so that it can
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/// give you all of the other things.
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///
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/// LIMITATIONS:
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///
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/// * Insert only (*) - the only write operation supported directly by
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/// AtomicUnorderedInsertMap is findOrConstruct. There is a (*) because
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/// values aren't moved, so you can roll your own concurrency control for
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/// in-place updates of values (see MutableData and MutableAtom below),
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/// but the hash table itself doesn't help you.
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///
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/// * No resizing - you must specify the capacity up front, and once
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/// the hash map gets full you won't be able to insert. Insert
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/// performance will degrade once the load factor is high. Insert is
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/// O(1/(1-actual_load_factor)). Note that this is a pretty strong
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/// limitation, because you can't remove existing keys.
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///
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/// * 2^30 maximum default capacity - by default AtomicUnorderedInsertMap
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/// uses uint32_t internal indexes (and steals 2 bits), limiting you
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/// to about a billion entries. If you need more you can fill in all
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/// of the template params so you change IndexType to uint64_t, or you
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/// can use AtomicUnorderedInsertMap64. 64-bit indexes will increase
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/// the space over of the map, of course.
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///
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/// WHAT YOU GET IN EXCHANGE:
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///
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/// * Arbitrary key and value types - any K and V that can be used in a
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/// std::unordered_map can be used here. In fact, the key and value
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/// types don't even have to be copyable or moveable!
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///
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/// * Keys and values in the map won't be moved - it is safe to keep
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/// pointers or references to the keys and values in the map, because
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/// they are never moved or destroyed (until the map itself is destroyed).
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///
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/// * Iterators are never invalidated - writes don't invalidate iterators,
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/// so you can scan and insert in parallel.
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///
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/// * Fast wait-free reads - reads are usually only a single cache miss,
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/// even when the hash table is very large. Wait-freedom means that
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/// you won't see latency outliers even in the face of concurrent writes.
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///
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/// * Lock-free insert - writes proceed in parallel. If a thread in the
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/// middle of a write is unlucky and gets suspended, it doesn't block
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/// anybody else.
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///
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/// COMMENTS ON INSERT-ONLY
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///
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/// This map provides wait-free linearizable reads and lock-free
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/// linearizable inserts. Inserted values won't be moved, but no
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/// concurrency control is provided for safely updating them. To remind
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/// you of that fact they are only provided in const form. This is the
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/// only simple safe thing to do while preserving something like the normal
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/// std::map iteration form, which requires that iteration be exposed
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/// via std::pair (and prevents encapsulation of access to the value).
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///
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/// There are a couple of reasonable policies for doing in-place
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/// concurrency control on the values. I am hoping that the policy can
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/// be injected via the value type or an extra template param, to keep
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/// the core AtomicUnorderedInsertMap insert-only:
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///
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/// CONST: this is the currently implemented strategy, which is simple,
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/// performant, and not that expressive. You can always put in a value
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/// with a mutable field (see MutableAtom below), but that doesn't look
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/// as pretty as it should.
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///
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/// ATOMIC: for integers and integer-size trivially copyable structs
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/// (via an adapter like tao/queues/AtomicStruct) the value can be a
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/// std::atomic and read and written atomically.
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///
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/// SEQ-LOCK: attach a counter incremented before and after write.
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/// Writers serialize by using CAS to make an even->odd transition,
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/// then odd->even after the write. Readers grab the value with memcpy,
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/// checking sequence value before and after. Readers retry until they
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/// see an even sequence number that doesn't change. This works for
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/// larger structs, but still requires memcpy to be equivalent to copy
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/// assignment, and it is no longer lock-free. It scales very well,
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/// because the readers are still invisible (no cache line writes).
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///
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/// LOCK: folly's SharedMutex would be a good choice here.
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///
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/// MEMORY ALLOCATION
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///
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/// Underlying memory is allocated as a big anonymous mmap chunk, which
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/// might be cheaper than calloc() and is certainly not more expensive
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/// for large maps. If the SkipKeyValueDeletion template param is true
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/// then deletion of the map consists of unmapping the backing memory,
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/// which is much faster than destructing all of the keys and values.
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/// Feel free to override if std::is_trivial_destructor isn't recognizing
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/// the triviality of your destructors.
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template <typename Key,
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typename Value,
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typename Hash = std::hash<Key>,
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typename KeyEqual = std::equal_to<Key>,
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bool SkipKeyValueDeletion =
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(boost::has_trivial_destructor<Key>::value &&
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boost::has_trivial_destructor<Value>::value),
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template<typename> class Atom = std::atomic,
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typename IndexType = uint32_t,
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typename Allocator = folly::detail::MMapAlloc>
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struct AtomicUnorderedInsertMap {
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typedef Key key_type;
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typedef Value mapped_type;
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typedef std::pair<Key,Value> value_type;
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typedef std::size_t size_type;
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typedef std::ptrdiff_t difference_type;
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typedef Hash hasher;
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typedef KeyEqual key_equal;
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typedef const value_type& const_reference;
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typedef struct ConstIterator {
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ConstIterator(const AtomicUnorderedInsertMap& owner, IndexType slot)
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: owner_(owner)
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, slot_(slot)
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{}
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ConstIterator(const ConstIterator&) = default;
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ConstIterator& operator= (const ConstIterator&) = default;
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const value_type& operator* () const {
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return owner_.slots_[slot_].keyValue();
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}
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const value_type* operator-> () const {
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return &owner_.slots_[slot_].keyValue();
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}
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// pre-increment
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const ConstIterator& operator++ () {
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while (slot_ > 0) {
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--slot_;
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if (owner_.slots_[slot_].state() == LINKED) {
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break;
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}
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}
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return *this;
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}
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// post-increment
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ConstIterator operator++(int /* dummy */) {
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auto prev = *this;
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++*this;
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return prev;
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}
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bool operator== (const ConstIterator& rhs) const {
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return slot_ == rhs.slot_;
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}
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bool operator!= (const ConstIterator& rhs) const {
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return !(*this == rhs);
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}
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private:
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const AtomicUnorderedInsertMap& owner_;
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IndexType slot_;
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} const_iterator;
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friend ConstIterator;
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/// Constructs a map that will support the insertion of maxSize key-value
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/// pairs without exceeding the max load factor. Load factors of greater
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/// than 1 are not supported, and once the actual load factor of the
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/// map approaches 1 the insert performance will suffer. The capacity
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/// is limited to 2^30 (about a billion) for the default IndexType,
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/// beyond which we will throw invalid_argument.
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explicit AtomicUnorderedInsertMap(
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size_t maxSize,
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float maxLoadFactor = 0.8f,
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const Allocator& alloc = Allocator())
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: allocator_(alloc)
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{
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size_t capacity = maxSize / std::min(1.0f, maxLoadFactor) + 128;
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size_t avail = size_t{1} << (8 * sizeof(IndexType) - 2);
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if (capacity > avail && maxSize < avail) {
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// we'll do our best
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capacity = avail;
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}
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if (capacity < maxSize || capacity > avail) {
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throw std::invalid_argument(
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"AtomicUnorderedInsertMap capacity must fit in IndexType with 2 bits "
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"left over");
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}
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numSlots_ = capacity;
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slotMask_ = folly::nextPowTwo(capacity * 4) - 1;
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mmapRequested_ = sizeof(Slot) * capacity;
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slots_ = reinterpret_cast<Slot*>(allocator_.allocate(mmapRequested_));
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zeroFillSlots();
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// mark the zero-th slot as in-use but not valid, since that happens
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// to be our nil value
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slots_[0].stateUpdate(EMPTY, CONSTRUCTING);
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}
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~AtomicUnorderedInsertMap() {
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if (!SkipKeyValueDeletion) {
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for (size_t i = 1; i < numSlots_; ++i) {
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slots_[i].~Slot();
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}
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}
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allocator_.deallocate(reinterpret_cast<char*>(slots_), mmapRequested_);
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}
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/// Searches for the key, returning (iter,false) if it is found.
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/// If it is not found calls the functor Func with a void* argument
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/// that is raw storage suitable for placement construction of a Value
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/// (see raw_value_type), then returns (iter,true). May call Func and
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/// then return (iter,false) if there are other concurrent writes, in
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/// which case the newly constructed value will be immediately destroyed.
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///
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/// This function does not block other readers or writers. If there
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/// are other concurrent writes, many parallel calls to func may happen
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/// and only the first one to complete will win. The values constructed
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/// by the other calls to func will be destroyed.
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///
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/// Usage:
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///
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/// AtomicUnorderedInsertMap<std::string,std::string> memo;
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///
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/// auto value = memo.findOrConstruct(key, [=](void* raw) {
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/// new (raw) std::string(computation(key));
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/// })->first;
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template<typename Func>
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std::pair<const_iterator,bool> findOrConstruct(const Key& key, Func&& func) {
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auto const slot = keyToSlotIdx(key);
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auto prev = slots_[slot].headAndState_.load(std::memory_order_acquire);
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auto existing = find(key, slot);
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if (existing != 0) {
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return std::make_pair(ConstIterator(*this, existing), false);
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}
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auto idx = allocateNear(slot);
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new (&slots_[idx].keyValue().first) Key(key);
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func(static_cast<void*>(&slots_[idx].keyValue().second));
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while (true) {
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slots_[idx].next_ = prev >> 2;
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// we can merge the head update and the CONSTRUCTING -> LINKED update
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// into a single CAS if slot == idx (which should happen often)
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auto after = idx << 2;
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if (slot == idx) {
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after += LINKED;
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} else {
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after += (prev & 3);
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}
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if (slots_[slot].headAndState_.compare_exchange_strong(prev, after)) {
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// success
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if (idx != slot) {
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slots_[idx].stateUpdate(CONSTRUCTING, LINKED);
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}
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return std::make_pair(ConstIterator(*this, idx), true);
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}
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// compare_exchange_strong updates its first arg on failure, so
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// there is no need to reread prev
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existing = find(key, slot);
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if (existing != 0) {
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// our allocated key and value are no longer needed
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slots_[idx].keyValue().first.~Key();
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slots_[idx].keyValue().second.~Value();
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slots_[idx].stateUpdate(CONSTRUCTING, EMPTY);
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return std::make_pair(ConstIterator(*this, existing), false);
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}
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}
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}
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/// This isn't really emplace, but it is what we need to test.
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/// Eventually we can duplicate all of the std::pair constructor
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/// forms, including a recursive tuple forwarding template
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/// http://functionalcpp.wordpress.com/2013/08/28/tuple-forwarding/).
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template<class K, class V>
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std::pair<const_iterator,bool> emplace(const K& key, V&& value) {
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return findOrConstruct(key, [&](void* raw) {
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new (raw) Value(std::forward<V>(value));
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});
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}
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const_iterator find(const Key& key) const {
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return ConstIterator(*this, find(key, keyToSlotIdx(key)));
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}
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const_iterator cbegin() const {
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IndexType slot = numSlots_ - 1;
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while (slot > 0 && slots_[slot].state() != LINKED) {
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--slot;
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}
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return ConstIterator(*this, slot);
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}
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const_iterator cend() const {
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return ConstIterator(*this, 0);
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}
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private:
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enum {
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kMaxAllocationTries = 1000, // after this we throw
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};
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enum BucketState : IndexType {
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EMPTY = 0,
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CONSTRUCTING = 1,
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LINKED = 2,
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};
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/// Lock-free insertion is easiest by prepending to collision chains.
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/// A large chaining hash table takes two cache misses instead of
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/// one, however. Our solution is to colocate the bucket storage and
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/// the head storage, so that even though we are traversing chains we
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/// are likely to stay within the same cache line. Just make sure to
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/// traverse head before looking at any keys. This strategy gives us
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/// 32 bit pointers and fast iteration.
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struct Slot {
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/// The bottom two bits are the BucketState, the rest is the index
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/// of the first bucket for the chain whose keys map to this slot.
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/// When things are going well the head usually links to this slot,
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/// but that doesn't always have to happen.
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Atom<IndexType> headAndState_;
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/// The next bucket in the chain
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IndexType next_;
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/// Key and Value
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typename std::aligned_storage<sizeof(value_type),
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alignof(value_type)>::type raw_;
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~Slot() {
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auto s = state();
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assert(s == EMPTY || s == LINKED);
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if (s == LINKED) {
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keyValue().first.~Key();
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keyValue().second.~Value();
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}
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}
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BucketState state() const {
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return BucketState(headAndState_.load(std::memory_order_acquire) & 3);
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}
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void stateUpdate(BucketState before, BucketState after) {
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assert(state() == before);
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headAndState_ += (after - before);
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}
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value_type& keyValue() {
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assert(state() != EMPTY);
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return *static_cast<value_type*>(static_cast<void*>(&raw_));
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}
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const value_type& keyValue() const {
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assert(state() != EMPTY);
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return *static_cast<const value_type*>(static_cast<const void*>(&raw_));
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}
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};
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// We manually manage the slot memory so we can bypass initialization
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// (by getting a zero-filled mmap chunk) and optionally destruction of
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// the slots
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size_t mmapRequested_;
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size_t numSlots_;
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/// tricky, see keyToSlodIdx
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size_t slotMask_;
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Allocator allocator_;
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Slot* slots_;
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IndexType keyToSlotIdx(const Key& key) const {
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size_t h = hasher()(key);
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h &= slotMask_;
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while (h >= numSlots_) {
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h -= numSlots_;
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}
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return h;
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}
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IndexType find(const Key& key, IndexType slot) const {
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KeyEqual ke = {};
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auto hs = slots_[slot].headAndState_.load(std::memory_order_acquire);
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for (slot = hs >> 2; slot != 0; slot = slots_[slot].next_) {
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if (ke(key, slots_[slot].keyValue().first)) {
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return slot;
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}
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}
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return 0;
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}
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/// Allocates a slot and returns its index. Tries to put it near
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/// slots_[start].
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IndexType allocateNear(IndexType start) {
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for (auto tries = 0; tries < kMaxAllocationTries; ++tries) {
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auto slot = allocationAttempt(start, tries);
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auto prev = slots_[slot].headAndState_.load(std::memory_order_acquire);
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if ((prev & 3) == EMPTY &&
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slots_[slot].headAndState_.compare_exchange_strong(
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prev, prev + CONSTRUCTING - EMPTY)) {
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return slot;
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}
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}
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throw std::bad_alloc();
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}
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/// Returns the slot we should attempt to allocate after tries failed
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/// tries, starting from the specified slot. This is pulled out so we
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/// can specialize it differently during deterministic testing
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IndexType allocationAttempt(IndexType start, IndexType tries) const {
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if (LIKELY(tries < 8 && start + tries < numSlots_)) {
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return start + tries;
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} else {
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IndexType rv;
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if (sizeof(IndexType) <= 4) {
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rv = folly::Random::rand32(numSlots_);
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} else {
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rv = folly::Random::rand64(numSlots_);
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}
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assert(rv < numSlots_);
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return rv;
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}
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}
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void zeroFillSlots() {
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using folly::detail::GivesZeroFilledMemory;
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if (!GivesZeroFilledMemory<Allocator>::value) {
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memset(slots_, 0, mmapRequested_);
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}
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}
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};
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/// AtomicUnorderedInsertMap64 is just a type alias that makes it easier
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/// to select a 64 bit slot index type. Use this if you need a capacity
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/// bigger than 2^30 (about a billion). This increases memory overheads,
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/// obviously.
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template <typename Key,
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typename Value,
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typename Hash = std::hash<Key>,
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typename KeyEqual = std::equal_to<Key>,
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bool SkipKeyValueDeletion =
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(boost::has_trivial_destructor<Key>::value &&
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boost::has_trivial_destructor<Value>::value),
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template <typename> class Atom = std::atomic,
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typename Allocator = folly::detail::MMapAlloc>
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using AtomicUnorderedInsertMap64 =
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AtomicUnorderedInsertMap<Key,
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Value,
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Hash,
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KeyEqual,
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SkipKeyValueDeletion,
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Atom,
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uint64_t,
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Allocator>;
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/// MutableAtom is a tiny wrapper than gives you the option of atomically
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/// updating values inserted into an AtomicUnorderedInsertMap<K,
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/// MutableAtom<V>>. This relies on AtomicUnorderedInsertMap's guarantee
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/// that it doesn't move values.
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template <typename T,
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template<typename> class Atom = std::atomic>
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struct MutableAtom {
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mutable Atom<T> data;
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explicit MutableAtom(const T& init) : data(init) {}
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};
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/// MutableData is a tiny wrapper than gives you the option of using an
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/// external concurrency control mechanism to updating values inserted
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/// into an AtomicUnorderedInsertMap.
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template <typename T>
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struct MutableData {
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mutable T data;
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explicit MutableData(const T& init) : data(init) {}
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};
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}
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