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