// // 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/Random.h" #include "td/utils/Slice.h" #include "td/utils/tests.h" #include #include #include #include template static auto extract_kv(const T &reference) { auto expected = td::transform(reference, [](auto &it) { return std::make_pair(it.first, it.second); }); std::sort(expected.begin(), expected.end()); return expected; } TEST(FlatHashMap, basic) { { td::FlatHashMap map; map[1] = 2; ASSERT_EQ(2, map[1]); ASSERT_EQ(1, map.find(1)->first); ASSERT_EQ(2, map.find(1)->second); // ASSERT_EQ(1, map.find(1)->key()); // ASSERT_EQ(2, map.find(1)->value()); for (auto &kv : map) { ASSERT_EQ(1, kv.first); ASSERT_EQ(2, kv.second); } map.erase(map.find(1)); auto map_copy = map; } td::FlatHashMap, 10>> x; auto y = std::move(x); x[12]; x.erase(x.find(12)); { td::FlatHashMap map = {{1, "hello"}, {2, "world"}}; ASSERT_EQ("hello", map[1]); ASSERT_EQ("world", map[2]); ASSERT_EQ(2u, map.size()); ASSERT_EQ("", map[3]); ASSERT_EQ(3u, map.size()); } { td::FlatHashMap map = {{1, "hello"}, {1, "world"}}; ASSERT_EQ("world", map[1]); ASSERT_EQ(1u, map.size()); } using KV = td::FlatHashMapImpl; using Data = td::vector>; auto data = Data{{"a", "b"}, {"c", "d"}}; { ASSERT_EQ(Data{}, extract_kv(KV())); } { KV kv(data.begin(), data.end()); ASSERT_EQ(data, extract_kv(kv)); KV copied_kv(kv); ASSERT_EQ(data, extract_kv(copied_kv)); KV moved_kv(std::move(kv)); ASSERT_EQ(data, extract_kv(moved_kv)); ASSERT_EQ(Data{}, extract_kv(kv)); ASSERT_TRUE(kv.empty()); kv = std::move(moved_kv); ASSERT_EQ(data, extract_kv(kv)); KV assign_copied_kv; assign_copied_kv = kv; ASSERT_EQ(data, extract_kv(assign_copied_kv)); KV assign_moved_kv; assign_moved_kv = std::move(kv); ASSERT_EQ(data, extract_kv(assign_moved_kv)); ASSERT_EQ(Data{}, extract_kv(kv)); ASSERT_TRUE(kv.empty()); kv = std::move(assign_moved_kv); KV it_copy_kv(kv.begin(), kv.end()); ASSERT_EQ(data, extract_kv(it_copy_kv)); } { KV kv; ASSERT_TRUE(kv.empty()); ASSERT_EQ(0u, kv.size()); kv = KV(data.begin(), data.end()); ASSERT_TRUE(!kv.empty()); ASSERT_EQ(2u, kv.size()); ASSERT_EQ("a", kv.find("a")->first); ASSERT_EQ("b", kv.find("a")->second); ASSERT_EQ("a", kv.find("a")->key()); ASSERT_EQ("b", kv.find("a")->value()); kv.find("a")->second = "c"; ASSERT_EQ("c", kv.find("a")->second); ASSERT_EQ("c", kv["a"]); ASSERT_EQ(0u, kv.count("x")); ASSERT_EQ(1u, kv.count("a")); } { KV kv; kv["d"]; ASSERT_EQ((Data{{"d", ""}}), extract_kv(kv)); kv.erase(kv.find("d")); ASSERT_EQ(Data{}, extract_kv(kv)); } } TEST(FlatHashMap, remove_if_basic) { td::Random::Xorshift128plus rnd(123); constexpr int TESTS_N = 10000; constexpr int MAX_TABLE_SIZE = 1000; for (int test_i = 0; test_i < TESTS_N; test_i++) { std::unordered_map reference; td::FlatHashMap table; int N = rnd.fast(1, MAX_TABLE_SIZE); for (int i = 0; i < N; i++) { auto key = rnd(); auto value = i; reference[key] = value; table[key] = value; } ASSERT_EQ(extract_kv(reference), extract_kv(table)); td::vector> kv; td::table_remove_if(table, [&](auto &it) { kv.emplace_back(it.first, it.second); return it.second % 2 == 0; }); std::sort(kv.begin(), kv.end()); ASSERT_EQ(extract_kv(reference), kv); td::table_remove_if(reference, [](auto &it) { return it.second % 2 == 0; }); ASSERT_EQ(extract_kv(reference), extract_kv(table)); } } TEST(FlatHashMap, stress_test) { td::vector steps; auto add_step = [&steps](td::Slice, td::uint32 weight, auto f) { steps.emplace_back(td::RandomSteps::Step{std::move(f), weight}); }; td::Random::Xorshift128plus rnd(123); size_t max_table_size = 1000; // dynamic value std::unordered_map ref; td::FlatHashMapImpl tbl; auto validate = [&] { ASSERT_EQ(ref.empty(), tbl.empty()); ASSERT_EQ(ref.size(), tbl.size()); ASSERT_EQ(extract_kv(ref), extract_kv(tbl)); for (auto &kv : ref) { ASSERT_EQ(ref[kv.first], tbl[kv.first]); } }; auto gen_key = [&] { auto key = rnd() % 4000 + 1; return key; }; add_step("Reset hash table", 1, [&] { validate(); td::reset_to_empty(ref); td::reset_to_empty(tbl); max_table_size = rnd.fast(1, 1000); }); add_step("Clear hash table", 1, [&] { validate(); ref.clear(); tbl.clear(); max_table_size = rnd.fast(1, 1000); }); add_step("Insert random value", 1000, [&] { if (tbl.size() > max_table_size) { return; } auto key = gen_key(); auto value = rnd(); ref[key] = value; tbl[key] = value; ASSERT_EQ(ref[key], tbl[key]); }); add_step("Emplace random value", 1000, [&] { if (tbl.size() > max_table_size) { return; } auto key = gen_key(); auto value = rnd(); auto ref_it = ref.emplace(key, value); auto tbl_it = tbl.emplace(key, value); ASSERT_EQ(ref_it.second, tbl_it.second); ASSERT_EQ(key, tbl_it.first->first); }); add_step("empty operator[]", 1000, [&] { if (tbl.size() > max_table_size) { return; } auto key = gen_key(); ASSERT_EQ(ref[key], tbl[key]); }); add_step("reserve", 10, [&] { tbl.reserve(rnd() % max_table_size); }); add_step("find", 1000, [&] { auto key = gen_key(); auto ref_it = ref.find(key); auto tbl_it = tbl.find(key); ASSERT_EQ(ref_it == ref.end(), tbl_it == tbl.end()); if (ref_it != ref.end()) { ASSERT_EQ(ref_it->first, tbl_it->first); ASSERT_EQ(ref_it->second, tbl_it->second); } }); add_step("find_and_erase", 100, [&] { auto key = gen_key(); auto ref_it = ref.find(key); auto tbl_it = tbl.find(key); ASSERT_EQ(ref_it == ref.end(), tbl_it == tbl.end()); if (ref_it != ref.end()) { ref.erase(ref_it); tbl.erase(tbl_it); } }); add_step("remove_if", 5, [&] { auto mul = rnd(); auto bit = rnd() % 64; auto condition = [&](auto &it) { return (((it.second * mul) >> bit) & 1) == 0; }; td::table_remove_if(tbl, condition); td::table_remove_if(ref, condition); }); td::RandomSteps runner(std::move(steps)); for (size_t i = 0; i < 10000000; i++) { runner.step(rnd); } }