Telegram: update for TDLIB

1 files changed, 647 insertions, 0 deletions

diff --git a/protocols/Telegram/tdlib/td/tdutils/test/hashset_benchmark.cpp b/protocols/Telegram/tdlib/td/tdutils/test/hashset_benchmark.cpp
new file mode 100644
index 0000000000..f07f58c8f0
--- /dev/null
+++ b/protocols/Telegram/tdlib/td/tdutils/test/hashset_benchmark.cpp
@@ -0,0 +1,647 @@
+//
+// Copyright Aliaksei Levin (levlam@telegram.org), Arseny Smirnov (arseny30@gmail.com) 2014-2022
+//
+// Distributed under the Boost Software License, Version 1.0. (See accompanying
+// file LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+//
+#include "td/utils/algorithm.h"
+#include "td/utils/common.h"
+#include "td/utils/FlatHashMap.h"
+#include "td/utils/FlatHashMapChunks.h"
+#include "td/utils/FlatHashTable.h"
+#include "td/utils/format.h"
+#include "td/utils/HashTableUtils.h"
+#include "td/utils/logging.h"
+#include "td/utils/MapNode.h"
+#include "td/utils/Random.h"
+#include "td/utils/Slice.h"
+#include "td/utils/Span.h"
+#include "td/utils/StringBuilder.h"
+#include "td/utils/Time.h"
+#include "td/utils/VectorQueue.h"
+
+#ifdef SCOPE_EXIT
+#undef SCOPE_EXIT
+#endif
+
+#include <absl/container/flat_hash_map.h>
+#include <absl/hash/hash.h>
+#include <algorithm>
+#include <benchmark/benchmark.h>
+#include <folly/container/F14Map.h>
+#include <functional>
+#include <map>
+#include <random>
+#include <unordered_map>
+#include <utility>
+
+template <class TableT>
+static void reserve(TableT &table, std::size_t size) {
+  table.reserve(size);
+}
+
+template <class A, class B>
+static void reserve(std::map<A, B> &table, std::size_t size) {
+}
+
+template <class KeyT, class ValueT>
+class NoOpTable {
+ public:
+  using key_type = KeyT;
+  using value_type = std::pair<const KeyT, ValueT>;
+  template <class It>
+  NoOpTable(It begin, It end) {
+  }
+
+  ValueT &operator[](const KeyT &) const {
+    static ValueT dummy;
+    return dummy;
+  }
+
+  KeyT find(const KeyT &key) const {
+    return key;
+  }
+};
+
+template <class KeyT, class ValueT>
+class VectorTable {
+ public:
+  using key_type = KeyT;
+  using value_type = std::pair<const KeyT, ValueT>;
+  template <class It>
+  VectorTable(It begin, It end) : table_(begin, end) {
+  }
+
+  ValueT &operator[](const KeyT &needle) {
+    auto it = find(needle);
+    if (it == table_.end()) {
+      table_.emplace_back(needle, ValueT{});
+      return table_.back().second;
+    }
+    return it->second;
+  }
+  auto find(const KeyT &needle) {
+    return std::find_if(table_.begin(), table_.end(), [&](auto &key) { return key.first == needle; });
+  }
+
+ private:
+  using KeyValue = value_type;
+  td::vector<KeyValue> table_;
+};
+
+template <class KeyT, class ValueT>
+class SortedVectorTable {
+ public:
+  using key_type = KeyT;
+  using value_type = std::pair<KeyT, ValueT>;
+  template <class It>
+  SortedVectorTable(It begin, It end) : table_(begin, end) {
+    std::sort(table_.begin(), table_.end());
+  }
+
+  ValueT &operator[](const KeyT &needle) {
+    auto it = std::lower_bound(table_.begin(), table_.end(), needle,
+                               [](const auto &l, const auto &r) { return l.first < r; });
+    if (it == table_.end() || it->first != needle) {
+      it = table_.insert(it, {needle, ValueT{}});
+    }
+    return it->second;
+  }
+
+  auto find(const KeyT &needle) {
+    auto it = std::lower_bound(table_.begin(), table_.end(), needle,
+                               [](const auto &l, const auto &r) { return l.first < r; });
+    if (it != table_.end() && it->first == needle) {
+      return it;
+    }
+    return table_.end();
+  }
+
+ private:
+  using KeyValue = value_type;
+  td::vector<KeyValue> table_;
+};
+
+template <class KeyT, class ValueT, class HashT = td::Hash<KeyT>>
+class SimpleHashTable {
+ public:
+  using key_type = KeyT;
+  using value_type = std::pair<KeyT, ValueT>;
+  template <class It>
+  SimpleHashTable(It begin, It end) {
+    nodes_.resize((end - begin) * 2);
+    for (; begin != end; ++begin) {
+      insert(begin->first, begin->second);
+    }
+  }
+
+  ValueT &operator[](const KeyT &needle) {
+    UNREACHABLE();
+  }
+
+  ValueT *find(const KeyT &needle) {
+    auto hash = HashT()(needle);
+    std::size_t i = hash % nodes_.size();
+    while (true) {
+      if (nodes_[i].key == needle) {
+        return &nodes_[i].value;
+      }
+      if (nodes_[i].hash == 0) {
+        return nullptr;
+      }
+      i++;
+      if (i == nodes_.size()) {
+        i = 0;
+      }
+    }
+  }
+
+ private:
+  using KeyValue = value_type;
+  struct Node {
+    std::size_t hash{0};
+    KeyT key;
+    ValueT value;
+  };
+  td::vector<Node> nodes_;
+
+  void insert(KeyT key, ValueT value) {
+    auto hash = HashT()(key);
+    std::size_t i = hash % nodes_.size();
+    while (true) {
+      if (nodes_[i].hash == 0 || (nodes_[i].hash == hash && nodes_[i].key == key)) {
+        nodes_[i].value = value;
+        nodes_[i].key = key;
+        nodes_[i].hash = hash;
+        return;
+      }
+      i++;
+      if (i == nodes_.size()) {
+        i = 0;
+      }
+    }
+  }
+};
+
+template <typename TableT>
+static void BM_Get(benchmark::State &state) {
+  std::size_t n = state.range(0);
+  constexpr std::size_t BATCH_SIZE = 1024;
+  td::Random::Xorshift128plus rnd(123);
+  using Key = typename TableT::key_type;
+  using Value = typename TableT::value_type::second_type;
+  using KeyValue = std::pair<Key, Value>;
+  td::vector<KeyValue> data;
+  td::vector<Key> keys;
+
+  TableT table;
+  for (std::size_t i = 0; i < n; i++) {
+    auto key = rnd();
+    auto value = rnd();
+    data.emplace_back(key, value);
+    table.emplace(key, value);
+    keys.push_back(key);
+  }
+
+  std::size_t key_i = 0;
+  td::random_shuffle(td::as_mutable_span(keys), rnd);
+  auto next_key = [&] {
+    key_i++;
+    if (key_i == data.size()) {
+      key_i = 0;
+    }
+    return keys[key_i];
+  };
+
+  while (state.KeepRunningBatch(BATCH_SIZE)) {
+    for (std::size_t i = 0; i < BATCH_SIZE; i++) {
+      benchmark::DoNotOptimize(table.find(next_key()));
+    }
+  }
+}
+
+template <typename TableT>
+static void BM_find_same(benchmark::State &state) {
+  td::Random::Xorshift128plus rnd(123);
+  TableT table;
+  constexpr std::size_t N = 100000;
+  constexpr std::size_t BATCH_SIZE = 1024;
+  reserve(table, N);
+
+  for (std::size_t i = 0; i < N; i++) {
+    table.emplace(rnd(), i);
+  }
+
+  auto key = td::Random::secure_uint64();
+  table[key] = 123;
+
+  while (state.KeepRunningBatch(BATCH_SIZE)) {
+    for (std::size_t i = 0; i < BATCH_SIZE; i++) {
+      benchmark::DoNotOptimize(table.find(key));
+    }
+  }
+}
+
+template <typename TableT>
+static void BM_emplace_same(benchmark::State &state) {
+  td::Random::Xorshift128plus rnd(123);
+  TableT table;
+  constexpr std::size_t N = 100000;
+  constexpr std::size_t BATCH_SIZE = 1024;
+  reserve(table, N);
+
+  for (std::size_t i = 0; i < N; i++) {
+    table.emplace(rnd(), i);
+  }
+
+  auto key = 123743;
+  table[key] = 123;
+
+  while (state.KeepRunningBatch(BATCH_SIZE)) {
+    for (std::size_t i = 0; i < BATCH_SIZE; i++) {
+      benchmark::DoNotOptimize(table.emplace(key + (i & 15) * 100, 43784932));
+    }
+  }
+}
+
+template <typename TableT>
+static void BM_emplace_string(benchmark::State &state) {
+  td::Random::Xorshift128plus rnd(123);
+  TableT table;
+  constexpr std::size_t N = 100000;
+  constexpr std::size_t BATCH_SIZE = 1024;
+  reserve(table, N);
+
+  for (std::size_t i = 0; i < N; i++) {
+    table.emplace(td::to_string(rnd()), i);
+  }
+
+  table["0"] = 123;
+  td::vector<td::string> strings;
+  for (std::size_t i = 0; i < 16; i++) {
+    strings.emplace_back(1, static_cast<char>('0' + i));
+  }
+
+  while (state.KeepRunningBatch(BATCH_SIZE)) {
+    for (std::size_t i = 0; i < BATCH_SIZE; i++) {
+      benchmark::DoNotOptimize(table.emplace(strings[i & 15], 43784932));
+    }
+  }
+}
+
+namespace td {
+template <class K, class V, class FunctT>
+static void table_remove_if(absl::flat_hash_map<K, V> &table, FunctT &&func) {
+  for (auto it = table.begin(); it != table.end();) {
+    if (func(*it)) {
+      auto copy = it;
+      ++it;
+      table.erase(copy);
+    } else {
+      ++it;
+    }
+  }
+}
+}  // namespace td
+
+template <typename TableT>
+static void BM_remove_if(benchmark::State &state) {
+  constexpr std::size_t N = 100000;
+  constexpr std::size_t BATCH_SIZE = N;
+
+  TableT table;
+  reserve(table, N);
+  while (state.KeepRunningBatch(BATCH_SIZE)) {
+    state.PauseTiming();
+    td::Random::Xorshift128plus rnd(123);
+    for (std::size_t i = 0; i < N; i++) {
+      table.emplace(rnd(), i);
+    }
+    state.ResumeTiming();
+
+    td::table_remove_if(table, [](auto &it) { return it.second % 2 == 0; });
+  }
+}
+
+template <typename TableT>
+static void BM_erase_all_with_begin(benchmark::State &state) {
+  constexpr std::size_t N = 100000;
+  constexpr std::size_t BATCH_SIZE = N;
+
+  TableT table;
+  td::Random::Xorshift128plus rnd(123);
+  while (state.KeepRunningBatch(BATCH_SIZE)) {
+    for (std::size_t i = 0; i < BATCH_SIZE; i++) {
+      table.emplace(rnd() + 1, i);
+    }
+    while (!table.empty()) {
+      table.erase(table.begin());
+    }
+  }
+}
+
+template <typename TableT>
+static void BM_cache(benchmark::State &state) {
+  constexpr std::size_t N = 1000;
+  constexpr std::size_t BATCH_SIZE = 1000000;
+
+  TableT table;
+  td::Random::Xorshift128plus rnd(123);
+  td::VectorQueue<td::uint64> keys;
+  while (state.KeepRunningBatch(BATCH_SIZE)) {
+    for (std::size_t i = 0; i < BATCH_SIZE; i++) {
+      auto key = rnd() + 1;
+      keys.push(key);
+      table.emplace(key, i);
+      if (table.size() > N) {
+        table.erase(keys.pop());
+      }
+    }
+  }
+}
+
+template <typename TableT>
+static void BM_cache2(benchmark::State &state) {
+  constexpr std::size_t N = 1000;
+  constexpr std::size_t BATCH_SIZE = 1000000;
+
+  TableT table;
+  td::Random::Xorshift128plus rnd(123);
+  td::VectorQueue<td::uint64> keys;
+  while (state.KeepRunningBatch(BATCH_SIZE)) {
+    for (std::size_t i = 0; i < BATCH_SIZE; i++) {
+      auto key = rnd() + 1;
+      keys.push(key);
+      table.emplace(key, i);
+      if (table.size() > N) {
+        table.erase(keys.pop_rand(rnd));
+      }
+    }
+  }
+}
+
+template <typename TableT>
+static void BM_cache3(benchmark::State &state) {
+  std::size_t N = state.range(0);
+  constexpr std::size_t BATCH_SIZE = 1000000;
+
+  TableT table;
+  td::Random::Xorshift128plus rnd(123);
+  td::VectorQueue<td::uint64> keys;
+  std::size_t step = 20;
+  while (state.KeepRunningBatch(BATCH_SIZE)) {
+    for (std::size_t i = 0; i < BATCH_SIZE; i += step) {
+      auto key = rnd() + 1;
+      keys.push(key);
+      table.emplace(key, i);
+
+      for (std::size_t j = 1; j < step; j++) {
+        auto key_to_find = keys.data()[rnd() % keys.size()];
+        benchmark::DoNotOptimize(table.find(key_to_find));
+      }
+
+      if (table.size() > N) {
+        table.erase(keys.pop_rand(rnd));
+      }
+    }
+  }
+}
+
+template <typename TableT>
+static void BM_remove_if_slow(benchmark::State &state) {
+  constexpr std::size_t N = 5000;
+  constexpr std::size_t BATCH_SIZE = 500000;
+
+  TableT table;
+  td::Random::Xorshift128plus rnd(123);
+  for (std::size_t i = 0; i < N; i++) {
+    table.emplace(rnd() + 1, i);
+  }
+  auto first_key = table.begin()->first;
+  {
+    std::size_t cnt = 0;
+    td::table_remove_if(table, [&cnt, n = N](auto &) {
+      cnt += 2;
+      return cnt <= n;
+    });
+  }
+  while (state.KeepRunningBatch(BATCH_SIZE)) {
+    for (std::size_t i = 0; i < BATCH_SIZE; i++) {
+      table.emplace(first_key, i);
+      table.erase(first_key);
+    }
+  }
+}
+
+template <typename TableT>
+static void BM_remove_if_slow_old(benchmark::State &state) {
+  constexpr std::size_t N = 100000;
+  constexpr std::size_t BATCH_SIZE = 5000000;
+
+  TableT table;
+  while (state.KeepRunningBatch(BATCH_SIZE)) {
+    td::Random::Xorshift128plus rnd(123);
+    for (std::size_t i = 0; i < BATCH_SIZE; i++) {
+      table.emplace(rnd() + 1, i);
+      if (table.size() > N) {
+        std::size_t cnt = 0;
+        td::table_remove_if(table, [&cnt, n = N](auto &) {
+          cnt += 2;
+          return cnt <= n;
+        });
+      }
+    }
+  }
+}
+
+template <typename TableT>
+static void benchmark_create(td::Slice name) {
+  td::Random::Xorshift128plus rnd(123);
+  {
+    constexpr std::size_t N = 10000000;
+    TableT table;
+    reserve(table, N);
+    auto start = td::Timestamp::now();
+    for (std::size_t i = 0; i < N; i++) {
+      table.emplace(rnd(), i);
+    }
+    auto end = td::Timestamp::now();
+    LOG(INFO) << name << ": create " << N << " elements: " << td::format::as_time(end.at() - start.at());
+
+    double res = 0;
+    td::vector<std::pair<std::size_t, td::format::Time>> pauses;
+    for (std::size_t i = 0; i < N; i++) {
+      auto emplace_start = td::Timestamp::now();
+      table.emplace(rnd(), i);
+      auto emplace_end = td::Timestamp::now();
+      auto pause = emplace_end.at() - emplace_start.at();
+      res = td::max(pause, res);
+      if (pause > 0.001) {
+        pauses.emplace_back(i, td::format::as_time(pause));
+      }
+    }
+
+    LOG(INFO) << name << ": create another " << N << " elements, max pause = " << td::format::as_time(res) << " "
+              << pauses;
+  }
+}
+
+struct CacheMissNode {
+  td::uint32 data{};
+  char padding[64 - sizeof(data)];
+};
+
+class IterateFast {
+ public:
+  static td::uint32 iterate(CacheMissNode *ptr, std::size_t max_shift) {
+    td::uint32 res = 1;
+    for (std::size_t i = 0; i < max_shift; i++) {
+      if (ptr[i].data % max_shift != 0) {
+        res *= ptr[i].data;
+      } else {
+        res /= ptr[i].data;
+      }
+    }
+    return res;
+  }
+};
+
+class IterateSlow {
+ public:
+  static td::uint32 iterate(CacheMissNode *ptr, std::size_t max_shift) {
+    td::uint32 res = 1;
+    for (std::size_t i = 0;; i++) {
+      if (ptr[i].data % max_shift != 0) {
+        res *= ptr[i].data;
+      } else {
+        break;
+      }
+    }
+    return res;
+  }
+};
+
+template <class F>
+static void BM_cache_miss(benchmark::State &state) {
+  td::uint32 max_shift = state.range(0);
+  bool flag = state.range(1);
+  std::random_device rd;
+  std::mt19937 rnd(rd());
+  int N = 50000000;
+  td::vector<CacheMissNode> nodes(N);
+  td::uint32 i = 0;
+  for (auto &node : nodes) {
+    if (flag) {
+      node.data = i++ % max_shift;
+    } else {
+      node.data = rnd();
+    }
+  }
+
+  td::vector<int> positions(N);
+  std::uniform_int_distribution<td::uint32> rnd_pos(0, N - 1000);
+  for (auto &pos : positions) {
+    pos = rnd_pos(rnd);
+    if (flag) {
+      pos = pos / max_shift * max_shift + 1;
+    }
+  }
+
+  while (state.KeepRunningBatch(positions.size())) {
+    for (const auto pos : positions) {
+      auto *ptr = &nodes[pos];
+      auto res = F::iterate(ptr, max_shift);
+      benchmark::DoNotOptimize(res);
+    }
+  }
+}
+
+static td::uint64 equal_mask_slow(td::uint8 *bytes, td::uint8 needle) {
+  td::uint64 mask = 0;
+  for (int i = 0; i < 16; i++) {
+    mask |= (bytes[i] == needle) << i;
+  }
+  return mask;
+}
+
+template <class MaskT>
+static void BM_mask(benchmark::State &state) {
+  std::size_t BATCH_SIZE = 1024;
+  td::vector<td::uint8> bytes(BATCH_SIZE + 16);
+  for (auto &b : bytes) {
+    b = static_cast<td::uint8>(td::Random::fast(0, 17));
+  }
+
+  while (state.KeepRunningBatch(BATCH_SIZE)) {
+    for (std::size_t i = 0; i < BATCH_SIZE; i++) {
+      benchmark::DoNotOptimize(MaskT::equal_mask(bytes.data() + i, 17));
+    }
+  }
+}
+
+BENCHMARK_TEMPLATE(BM_mask, td::MaskPortable);
+#ifdef __aarch64__
+BENCHMARK_TEMPLATE(BM_mask, td::MaskNeonFolly);
+BENCHMARK_TEMPLATE(BM_mask, td::MaskNeon);
+#endif
+#if TD_SSE2
+BENCHMARK_TEMPLATE(BM_mask, td::MaskSse2);
+#endif
+
+template <class KeyT, class ValueT, class HashT = td::Hash<KeyT>, class EqT = std::equal_to<KeyT>>
+using FlatHashMapImpl = td::FlatHashTable<td::MapNode<KeyT, ValueT>, HashT, EqT>;
+
+#define FOR_EACH_TABLE(F)  \
+  F(FlatHashMapImpl)       \
+  F(td::FlatHashMapChunks) \
+  F(folly::F14FastMap)     \
+  F(absl::flat_hash_map)   \
+  F(std::unordered_map)    \
+  F(std::map)
+
+//BENCHMARK(BM_cache_miss<IterateSlow>)->Ranges({{1, 16}, {0, 1}});
+//BENCHMARK(BM_cache_miss<IterateFast>)->Ranges({{1, 16}, {0, 1}});
+//BENCHMARK_TEMPLATE(BM_Get, VectorTable<td::uint64, td::uint64>)->Range(1, 1 << 26);
+//BENCHMARK_TEMPLATE(BM_Get, SortedVectorTable<td::uint64, td::uint64>)->Range(1, 1 << 26);
+//BENCHMARK_TEMPLATE(BM_Get, NoOpTable<td::uint64, td::uint64>)->Range(1, 1 << 26);
+
+#define REGISTER_GET_BENCHMARK(HT) BENCHMARK_TEMPLATE(BM_Get, HT<td::uint64, td::uint64>)->Range(1, 1 << 23);
+
+#define REGISTER_FIND_BENCHMARK(HT)                                                                                 \
+  BENCHMARK_TEMPLATE(BM_find_same, HT<td::uint64, td::uint64>)                                                      \
+      ->ComputeStatistics("max", [](const td::vector<double> &v) { return *std::max_element(v.begin(), v.end()); }) \
+      ->ComputeStatistics("min", [](const td::vector<double> &v) { return *std::min_element(v.begin(), v.end()); }) \
+      ->Repetitions(20)                                                                                             \
+      ->DisplayAggregatesOnly(true);
+
+#define REGISTER_REMOVE_IF_BENCHMARK(HT) BENCHMARK_TEMPLATE(BM_remove_if, HT<td::uint64, td::uint64>);
+#define REGISTER_EMPLACE_BENCHMARK(HT) BENCHMARK_TEMPLATE(BM_emplace_same, HT<td::uint64, td::uint64>);
+#define REGISTER_EMPLACE_STRING_BENCHMARK(HT) BENCHMARK_TEMPLATE(BM_emplace_string, HT<td::string, td::uint64>);
+#define REGISTER_CACHE_BENCHMARK(HT) BENCHMARK_TEMPLATE(BM_cache, HT<td::uint64, td::uint64>);
+#define REGISTER_CACHE2_BENCHMARK(HT) BENCHMARK_TEMPLATE(BM_cache2, HT<td::uint64, td::uint64>);
+#define REGISTER_CACHE3_BENCHMARK(HT) BENCHMARK_TEMPLATE(BM_cache3, HT<td::uint64, td::uint64>)->Range(1, 1 << 23);
+#define REGISTER_ERASE_ALL_BENCHMARK(HT) BENCHMARK_TEMPLATE(BM_erase_all_with_begin, HT<td::uint64, td::uint64>);
+#define REGISTER_REMOVE_IF_SLOW_BENCHMARK(HT) BENCHMARK_TEMPLATE(BM_remove_if_slow, HT<td::uint64, td::uint64>);
+#define REGISTER_REMOVE_IF_SLOW_OLD_BENCHMARK(HT) BENCHMARK_TEMPLATE(BM_remove_if_slow_old, HT<td::uint64, td::uint64>);
+
+FOR_EACH_TABLE(REGISTER_GET_BENCHMARK)
+FOR_EACH_TABLE(REGISTER_CACHE3_BENCHMARK)
+FOR_EACH_TABLE(REGISTER_CACHE2_BENCHMARK)
+FOR_EACH_TABLE(REGISTER_CACHE_BENCHMARK)
+FOR_EACH_TABLE(REGISTER_REMOVE_IF_BENCHMARK)
+FOR_EACH_TABLE(REGISTER_EMPLACE_BENCHMARK)
+FOR_EACH_TABLE(REGISTER_EMPLACE_STRING_BENCHMARK)
+FOR_EACH_TABLE(REGISTER_ERASE_ALL_BENCHMARK)
+FOR_EACH_TABLE(REGISTER_FIND_BENCHMARK)
+FOR_EACH_TABLE(REGISTER_REMOVE_IF_SLOW_OLD_BENCHMARK)
+FOR_EACH_TABLE(REGISTER_REMOVE_IF_SLOW_BENCHMARK)
+
+#define RUN_CREATE_BENCHMARK(HT) benchmark_create<HT<td::uint64, td::uint64>>(#HT);
+
+int main(int argc, char **argv) {
+  //  FOR_EACH_TABLE(RUN_CREATE_BENCHMARK);
+
+  benchmark::Initialize(&argc, argv);
+  benchmark::RunSpecifiedBenchmarks();
+  benchmark::Shutdown();
+}