/*
 * Copyright 2017 Facebook, Inc.
 *
 * 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.
 */

/*
 * AtomicHashMap --
 *
 * A high-performance concurrent hash map with int32 or int64 keys. Supports
 * insert, find(key), findAt(index), erase(key), size, and more.  Memory cannot
 * be freed or reclaimed by erase.  Can grow to a maximum of about 18 times the
 * initial capacity, but performance degrades linearly with growth. Can also be
 * used as an object store with unique 32-bit references directly into the
 * internal storage (retrieved with iterator::getIndex()).
 *
 * Advantages:
 *    - High-performance (~2-4x tbb::concurrent_hash_map in heavily
 *      multi-threaded environments).
 *    - Efficient memory usage if initial capacity is not over estimated
 *      (especially for small keys and values).
 *    - Good fragmentation properties (only allocates in large slabs which can
 *      be reused with clear() and never move).
 *    - Can generate unique, long-lived 32-bit references for efficient lookup
 *      (see findAt()).
 *
 * Disadvantages:
 *    - Keys must be native int32 or int64, or explicitly converted.
 *    - Must be able to specify unique empty, locked, and erased keys
 *    - Performance degrades linearly as size grows beyond initialization
 *      capacity.
 *    - Max size limit of ~18x initial size (dependent on max load factor).
 *    - Memory is not freed or reclaimed by erase.
 *
 * Usage and Operation Details:
 *   Simple performance/memory tradeoff with maxLoadFactor.  Higher load factors
 *   give better memory utilization but probe lengths increase, reducing
 *   performance.
 *
 * Implementation and Performance Details:
 *   AHArray is a fixed size contiguous block of value_type cells.  When
 *   writing a cell, the key is locked while the rest of the record is
 *   written.  Once done, the cell is unlocked by setting the key.  find()
 *   is completely wait-free and doesn't require any non-relaxed atomic
 *   operations.  AHA cannot grow beyond initialization capacity, but is
 *   faster because of reduced data indirection.
 *
 *   AHMap is a wrapper around AHArray sub-maps that allows growth and provides
 *   an interface closer to the STL UnorderedAssociativeContainer concept. These
 *   sub-maps are allocated on the fly and are processed in series, so the more
 *   there are (from growing past initial capacity), the worse the performance.
 *
 *   Insert returns false if there is a key collision and throws if the max size
 *   of the map is exceeded.
 *
 *   Benchmark performance with 8 simultaneous threads processing 1 million
 *   unique <int64, int64> entries on a 4-core, 2.5 GHz machine:
 *
 *     Load Factor   Mem Efficiency   usec/Insert   usec/Find
 *         50%             50%           0.19         0.05
 *         85%             85%           0.20         0.06
 *         90%             90%           0.23         0.08
 *         95%             95%           0.27         0.10
 *
 *   See folly/tests/AtomicHashMapTest.cpp for more benchmarks.
 *
 * @author Spencer Ahrens <sahrens@fb.com>
 * @author Jordan DeLong <delong.j@fb.com>
 *
 */

#pragma once
#define FOLLY_ATOMICHASHMAP_H_

#include <boost/iterator/iterator_facade.hpp>
#include <boost/noncopyable.hpp>
#include <boost/type_traits/is_convertible.hpp>

#include <atomic>
#include <functional>
#include <stdexcept>

#include <folly/AtomicHashArray.h>
#include <folly/Likely.h>
#include <folly/ThreadCachedInt.h>
#include <folly/container/Foreach.h>
#include <folly/hash/Hash.h>

namespace folly {

/*
 * AtomicHashMap provides an interface somewhat similar to the
 * UnorderedAssociativeContainer concept in C++.  This does not
 * exactly match this concept (or even the basic Container concept),
 * because of some restrictions imposed by our datastructure.
 *
 * Specific differences (there are quite a few):
 *
 * - Efficiently thread safe for inserts (main point of this stuff),
 *   wait-free for lookups.
 *
 * - You can erase from this container, but the cell containing the key will
 *   not be free or reclaimed.
 *
 * - You can erase everything by calling clear() (and you must guarantee only
 *   one thread can be using the container to do that).
 *
 * - We aren't DefaultConstructible, CopyConstructible, Assignable, or
 *   EqualityComparable.  (Most of these are probably not something
 *   you actually want to do with this anyway.)
 *
 * - We don't support the various bucket functions, rehash(),
 *   reserve(), or equal_range().  Also no constructors taking
 *   iterators, although this could change.
 *
 * - Several insertion functions, notably operator[], are not
 *   implemented.  It is a little too easy to misuse these functions
 *   with this container, where part of the point is that when an
 *   insertion happens for a new key, it will atomically have the
 *   desired value.
 *
 * - The map has no templated insert() taking an iterator range, but
 *   we do provide an insert(key, value).  The latter seems more
 *   frequently useful for this container (to avoid sprinkling
 *   make_pair everywhere), and providing both can lead to some gross
 *   template error messages.
 *
 * - The Allocator must not be stateful (a new instance will be spun up for
 *   each allocation), and its allocate() method must take a raw number of
 *   bytes.
 *
 * - KeyT must be a 32 bit or 64 bit atomic integer type, and you must
 *   define special 'locked' and 'empty' key values in the ctor
 *
 * - We don't take the Hash function object as an instance in the
 *   constructor.
 *
 */

// Thrown when insertion fails due to running out of space for
// submaps.
struct AtomicHashMapFullError : std::runtime_error {
  explicit AtomicHashMapFullError()
    : std::runtime_error("AtomicHashMap is full")
  {}
};

template <
    class KeyT,
    class ValueT,
    class HashFcn,
    class EqualFcn,
    class Allocator,
    class ProbeFcn,
    class KeyConvertFcn>
class AtomicHashMap : boost::noncopyable {
typedef AtomicHashArray<KeyT, ValueT, HashFcn, EqualFcn,
                        Allocator, ProbeFcn, KeyConvertFcn>
    SubMap;

 public:
  typedef KeyT                key_type;
  typedef ValueT              mapped_type;
  typedef std::pair<const KeyT, ValueT> value_type;
  typedef HashFcn             hasher;
  typedef EqualFcn            key_equal;
  typedef KeyConvertFcn       key_convert;
  typedef value_type*         pointer;
  typedef value_type&         reference;
  typedef const value_type&   const_reference;
  typedef std::ptrdiff_t      difference_type;
  typedef std::size_t         size_type;
  typedef typename SubMap::Config Config;

  template <class ContT, class IterVal, class SubIt>
  struct ahm_iterator;

  typedef ahm_iterator<const AtomicHashMap,
                       const value_type,
                       typename SubMap::const_iterator>
    const_iterator;
  typedef ahm_iterator<AtomicHashMap,
                       value_type,
                       typename SubMap::iterator>
    iterator;

 public:
  const float kGrowthFrac_;  // How much to grow when we run out of capacity.

  // The constructor takes a finalSizeEst which is the optimal
  // number of elements to maximize space utilization and performance,
  // and a Config object to specify more advanced options.
  explicit AtomicHashMap(size_t finalSizeEst, const Config& c = Config());

  ~AtomicHashMap() {
    const unsigned int numMaps =
        numMapsAllocated_.load(std::memory_order_relaxed);
    FOR_EACH_RANGE (i, 0, numMaps) {
      SubMap* thisMap = subMaps_[i].load(std::memory_order_relaxed);
      DCHECK(thisMap);
      SubMap::destroy(thisMap);
    }
  }

  key_equal key_eq() const { return key_equal(); }
  hasher hash_function() const { return hasher(); }

  /*
   * insert --
   *
   *   Returns a pair with iterator to the element at r.first and
   *   success.  Retrieve the index with ret.first.getIndex().
   *
   *   Does not overwrite on key collision, but returns an iterator to
   *   the existing element (since this could due to a race with
   *   another thread, it is often important to check this return
   *   value).
   *
   *   Allocates new sub maps as the existing ones become full.  If
   *   all sub maps are full, no element is inserted, and
   *   AtomicHashMapFullError is thrown.
   */
  std::pair<iterator,bool> insert(const value_type& r) {
    return emplace(r.first, r.second);
  }
  std::pair<iterator,bool> insert(key_type k, const mapped_type& v) {
    return emplace(k, v);
  }
  std::pair<iterator,bool> insert(value_type&& r) {
    return emplace(r.first, std::move(r.second));
  }
  std::pair<iterator,bool> insert(key_type k, mapped_type&& v) {
    return emplace(k, std::move(v));
  }

  /*
   * emplace --
   *
   *   Same contract as insert(), but performs in-place construction
   *   of the value type using the specified arguments.
   *
   *   Also, like find(), this method optionally allows 'key_in' to have a type
   *   different from that stored in the table; see find(). If and only if no
   *   equal key is already present, this method converts 'key_in' to a key of
   *   type KeyT using the provided LookupKeyToKeyFcn.
   */
  template <
      typename LookupKeyT = key_type,
      typename LookupHashFcn = hasher,
      typename LookupEqualFcn = key_equal,
      typename LookupKeyToKeyFcn = key_convert,
      typename... ArgTs>
  std::pair<iterator,bool> emplace(LookupKeyT k, ArgTs&&... vCtorArg);

  /*
   * find --
   *
   *   Returns the iterator to the element if found, otherwise end().
   *
   *   As an optional feature, the type of the key to look up (LookupKeyT) is
   *   allowed to be different from the type of keys actually stored (KeyT).
   *
   *   This enables use cases where materializing the key is costly and usually
   *   redudant, e.g., canonicalizing/interning a set of strings and being able
   *   to look up by StringPiece. To use this feature, LookupHashFcn must take
   *   a LookupKeyT, and LookupEqualFcn must take KeyT and LookupKeyT as first
   *   and second parameter, respectively.
   *
   *   See folly/test/ArrayHashMapTest.cpp for sample usage.
   */
  template <
      typename LookupKeyT = key_type,
      typename LookupHashFcn = hasher,
      typename LookupEqualFcn = key_equal>
  iterator find(LookupKeyT k);

  template <
      typename LookupKeyT = key_type,
      typename LookupHashFcn = hasher,
      typename LookupEqualFcn = key_equal>
  const_iterator find(LookupKeyT k) const;

  /*
   * erase --
   *
   *   Erases key k from the map
   *
   *   Returns 1 iff the key is found and erased, and 0 otherwise.
   */
  size_type erase(key_type k);

  /*
   * clear --
   *
   *   Wipes all keys and values from primary map and destroys all secondary
   *   maps.  Primary map remains allocated and thus the memory can be reused
   *   in place.  Not thread safe.
   *
   */
  void clear();

  /*
   * size --
   *
   *  Returns the exact size of the map.  Note this is not as cheap as typical
   *  size() implementations because, for each AtomicHashArray in this AHM, we
   *  need to grab a lock and accumulate the values from all the thread local
   *  counters.  See folly/ThreadCachedInt.h for more details.
   */
  size_t size() const;

  bool empty() const { return size() == 0; }

  size_type count(key_type k) const {
    return find(k) == end() ? 0 : 1;
  }


  /*
   * findAt --
   *
   *   Returns an iterator into the map.
   *
   *   idx should only be an unmodified value returned by calling getIndex() on
   *   a valid iterator returned by find() or insert(). If idx is invalid you
   *   have a bug and the process aborts.
   */
  iterator findAt(uint32_t idx) {
    SimpleRetT ret = findAtInternal(idx);
    DCHECK_LT(ret.i, numSubMaps());
    return iterator(this, ret.i,
      subMaps_[ret.i].load(std::memory_order_relaxed)->makeIter(ret.j));
  }
  const_iterator findAt(uint32_t idx) const {
    return const_cast<AtomicHashMap*>(this)->findAt(idx);
  }

  // Total capacity - summation of capacities of all submaps.
  size_t capacity() const;

  // Number of new insertions until current submaps are all at max load factor.
  size_t spaceRemaining() const;

  void setEntryCountThreadCacheSize(int32_t newSize) {
    const int numMaps = numMapsAllocated_.load(std::memory_order_acquire);
    for (int i = 0; i < numMaps; ++i) {
      SubMap* map = subMaps_[i].load(std::memory_order_relaxed);
      map->setEntryCountThreadCacheSize(newSize);
    }
  }

  // Number of sub maps allocated so far to implement this map.  The more there
  // are, the worse the performance.
  int numSubMaps() const {
    return numMapsAllocated_.load(std::memory_order_acquire);
  }

  iterator begin() {
    iterator it(this, 0,
      subMaps_[0].load(std::memory_order_relaxed)->begin());
    it.checkAdvanceToNextSubmap();
    return it;
  }

  const_iterator begin() const {
    const_iterator it(this, 0,
      subMaps_[0].load(std::memory_order_relaxed)->begin());
    it.checkAdvanceToNextSubmap();
    return it;
  }

  iterator end() {
    return iterator();
  }

  const_iterator end() const {
    return const_iterator();
  }

  /* Advanced functions for direct access: */

  inline uint32_t recToIdx(const value_type& r, bool mayInsert = true) {
    SimpleRetT ret = mayInsert ?
      insertInternal(r.first, r.second) : findInternal(r.first);
    return encodeIndex(ret.i, ret.j);
  }

  inline uint32_t recToIdx(value_type&& r, bool mayInsert = true) {
    SimpleRetT ret = mayInsert ?
      insertInternal(r.first, std::move(r.second)) : findInternal(r.first);
    return encodeIndex(ret.i, ret.j);
  }

  inline uint32_t recToIdx(key_type k, const mapped_type& v,
    bool mayInsert = true) {
    SimpleRetT ret = mayInsert ? insertInternal(k, v) : findInternal(k);
    return encodeIndex(ret.i, ret.j);
  }

  inline uint32_t recToIdx(key_type k, mapped_type&& v, bool mayInsert = true) {
    SimpleRetT ret = mayInsert ?
      insertInternal(k, std::move(v)) : findInternal(k);
    return encodeIndex(ret.i, ret.j);
  }

  inline uint32_t keyToIdx(const KeyT k, bool mayInsert = false) {
    return recToIdx(value_type(k), mayInsert);
  }

  inline const value_type& idxToRec(uint32_t idx) const {
    SimpleRetT ret = findAtInternal(idx);
    return subMaps_[ret.i].load(std::memory_order_relaxed)->idxToRec(ret.j);
  }

  /* Private data and helper functions... */

 private:
  // This limits primary submap size to 2^31 ~= 2 billion, secondary submap
  // size to 2^(32 - kNumSubMapBits_ - 1) = 2^27 ~= 130 million, and num subMaps
  // to 2^kNumSubMapBits_ = 16.
  static const uint32_t  kNumSubMapBits_     = 4;
  static const uint32_t  kSecondaryMapBit_   = 1u << 31; // Highest bit
  static const uint32_t  kSubMapIndexShift_  = 32 - kNumSubMapBits_ - 1;
  static const uint32_t  kSubMapIndexMask_   = (1 << kSubMapIndexShift_) - 1;
  static const uint32_t  kNumSubMaps_        = 1 << kNumSubMapBits_;
  static const uintptr_t kLockedPtr_         = 0x88ULL << 48; // invalid pointer

  struct SimpleRetT { uint32_t i; size_t j; bool success;
    SimpleRetT(uint32_t ii, size_t jj, bool s) : i(ii), j(jj), success(s) {}
    SimpleRetT() = default;
  };

  template <
      typename LookupKeyT = key_type,
      typename LookupHashFcn = hasher,
      typename LookupEqualFcn = key_equal,
      typename LookupKeyToKeyFcn = key_convert,
      typename... ArgTs>
  SimpleRetT insertInternal(LookupKeyT key, ArgTs&&... value);

  template <
      typename LookupKeyT = key_type,
      typename LookupHashFcn = hasher,
      typename LookupEqualFcn = key_equal>
  SimpleRetT findInternal(const LookupKeyT k) const;

  SimpleRetT findAtInternal(uint32_t idx) const;

  std::atomic<SubMap*> subMaps_[kNumSubMaps_];
  std::atomic<uint32_t> numMapsAllocated_;

  inline bool tryLockMap(unsigned int idx) {
    SubMap* val = nullptr;
    return subMaps_[idx].compare_exchange_strong(val, (SubMap*)kLockedPtr_,
      std::memory_order_acquire);
  }

  static inline uint32_t encodeIndex(uint32_t subMap, uint32_t subMapIdx);

}; // AtomicHashMap

template <
    class KeyT,
    class ValueT,
    class HashFcn = std::hash<KeyT>,
    class EqualFcn = std::equal_to<KeyT>,
    class Allocator = std::allocator<char>>
using QuadraticProbingAtomicHashMap =
    AtomicHashMap<KeyT,
                  ValueT,
                  HashFcn,
                  EqualFcn,
                  Allocator,
                  AtomicHashArrayQuadraticProbeFcn>;
} // namespace folly

#include <folly/AtomicHashMap-inl.h>
