Export of internal Abseil changes

--
c42a234e2c186bf697ce8d77e85628601fa514a6 by Abseil Team <absl-team@google.com>:

Enable the assertion in the iterator's operator++

PiperOrigin-RevId: 290134813

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f8c53ba8e9c5bb16bbcc1e412a5c2519c912c83e by Abseil Team <absl-team@google.com>:

Define operator== and operator!= for absl::{weak,strong}_equality and
absl::{partial,weak,strong}_ordering types themselves.

PiperOrigin-RevId: 290111564

--
36bc574090cefad74a451719ce2761982647a51d by Tom Manshreck <shreck@google.com>:

Specify Time library flag formats

PiperOrigin-RevId: 289928010

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26dd40281add260baab2b60fec05dfb9c5304aaa by Mark Barolak <mbar@google.com>:

Delete an extraneous forward declaration of absl::Cord.

PiperOrigin-RevId: 289708481

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e60aea7f33554ff66d7699bb70e7af1d26323f1d by Abseil Team <absl-team@google.com>:

Release b-tree benchmarks.

PiperOrigin-RevId: 289654429

--
660aa83fa000d4bae072b2d1c790f81d0939bc7e by Greg Falcon <gfalcon@google.com>:

Use https links.

Import of https://github.com/abseil/abseil-cpp/pull/586

PiperOrigin-RevId: 289479559

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0611ea4482dcf23d6b0a0389fe041eeb9052449a by Derek Mauro <dmauro@google.com>:

Removes the static initializer for LookupTables<absl::uint128>::kVmaxOverBase

Uses template specialization to hard code the resulting array.

Static initializers are problematic for a number of reasons. Not only
are they responsible for the static initialization order fiasco, but
they are in the critical path during program startup. For these
reasons, the Google C++ style guide strongly discourages them (and
forbids them when they are not trivially destructible), and Chromium
even has a test forbidding them.

https://google.github.io/styleguide/cppguide.html#Static_and_Global_Variables
https://chromium.googlesource.com/chromium/src.git/+/master/docs/static_initializers.md
http://neugierig.org/software/chromium/notes/2011/08/static-initializers.html

PiperOrigin-RevId: 289458677

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c869362f6bb7a872314f74750d38d81bdaa73f95 by Greg Falcon <gfalcon@google.com>:

Step 2 of 2 to fix our CCTZ fork to respect inline namespaces.

Re-import of CCTZ from GitHub, applying new changes to honor Abseil's optional inline namespace in MSVC.

PiperOrigin-RevId: 289454407

--
fdb3474d76c2ee0371ccdf7593a78137c03a3f58 by Greg Falcon <gfalcon@google.com>:

Step 1 of 2 to fix our CCTZ fork to respect inline namespaces.

CCTZ uses a linker flag to simulate weak symbol support in MSVC.  This takes the form of a #pragma that includes the mangled names of two types: the symbol to treat as weak, and the symbol to use as its default value if no override is provided.

When Abseil is configured to use inline namespaces, the mangled names of these symbols change, and the pragma should change to reflect that.  Fortunately for us, MSVC name mangling is simple enough that we can generate the needed string literals in the preprocessor.

This CL introduces the new macros; the uses will be introduced in a follow-up CL.

PiperOrigin-RevId: 289435599

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5f152cc36f008acb9ab78f30b5efa40ebaf2754b by Matt Kulukundis <kfm@google.com>:

Improve documentation for lazy_emplace

PiperOrigin-RevId: 289333112
GitOrigin-RevId: c42a234e2c186bf697ce8d77e85628601fa514a6
Change-Id: I139ce6c7044a70d083af53e428bcb987f0fd88c6

1 files changed, 707 insertions, 0 deletions

diff --git a/absl/container/btree_benchmark.cc b/absl/container/btree_benchmark.cc
new file mode 100644
index 0000000..4af92f9
--- /dev/null
+++ b/absl/container/btree_benchmark.cc
@@ -0,0 +1,707 @@
+// Copyright 2018 The Abseil Authors.
+//
+// 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
+//
+//      https://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.
+
+#include <stdint.h>
+
+#include <algorithm>
+#include <functional>
+#include <map>
+#include <numeric>
+#include <random>
+#include <set>
+#include <string>
+#include <type_traits>
+#include <unordered_map>
+#include <unordered_set>
+#include <vector>
+
+#include "absl/base/internal/raw_logging.h"
+#include "absl/container/btree_map.h"
+#include "absl/container/btree_set.h"
+#include "absl/container/btree_test.h"
+#include "absl/container/flat_hash_map.h"
+#include "absl/container/flat_hash_set.h"
+#include "absl/container/internal/hashtable_debug.h"
+#include "absl/flags/flag.h"
+#include "absl/hash/hash.h"
+#include "absl/memory/memory.h"
+#include "absl/strings/str_format.h"
+#include "absl/time/time.h"
+#include "benchmark/benchmark.h"
+
+namespace absl {
+ABSL_NAMESPACE_BEGIN
+namespace container_internal {
+namespace {
+
+constexpr size_t kBenchmarkValues = 1 << 20;
+
+// How many times we add and remove sub-batches in one batch of *AddRem
+// benchmarks.
+constexpr size_t kAddRemBatchSize = 1 << 2;
+
+// Generates n values in the range [0, 4 * n].
+template <typename V>
+std::vector<V> GenerateValues(int n) {
+  constexpr int kSeed = 23;
+  return GenerateValuesWithSeed<V>(n, 4 * n, kSeed);
+}
+
+// Benchmark insertion of values into a container.
+template <typename T>
+void BM_InsertImpl(benchmark::State& state, bool sorted) {
+  using V = typename remove_pair_const<typename T::value_type>::type;
+  typename KeyOfValue<typename T::key_type, V>::type key_of_value;
+
+  std::vector<V> values = GenerateValues<V>(kBenchmarkValues);
+  if (sorted) {
+    std::sort(values.begin(), values.end());
+  }
+  T container(values.begin(), values.end());
+
+  // Remove and re-insert 10% of the keys per batch.
+  const int batch_size = (kBenchmarkValues + 9) / 10;
+  while (state.KeepRunningBatch(batch_size)) {
+    state.PauseTiming();
+    const auto i = static_cast<int>(state.iterations());
+
+    for (int j = i; j < i + batch_size; j++) {
+      int x = j % kBenchmarkValues;
+      container.erase(key_of_value(values[x]));
+    }
+
+    state.ResumeTiming();
+
+    for (int j = i; j < i + batch_size; j++) {
+      int x = j % kBenchmarkValues;
+      container.insert(values[x]);
+    }
+  }
+}
+
+template <typename T>
+void BM_Insert(benchmark::State& state) {
+  BM_InsertImpl<T>(state, false);
+}
+
+template <typename T>
+void BM_InsertSorted(benchmark::State& state) {
+  BM_InsertImpl<T>(state, true);
+}
+
+// container::insert sometimes returns a pair<iterator, bool> and sometimes
+// returns an iterator (for multi- containers).
+template <typename Iter>
+Iter GetIterFromInsert(const std::pair<Iter, bool>& pair) {
+  return pair.first;
+}
+template <typename Iter>
+Iter GetIterFromInsert(const Iter iter) {
+  return iter;
+}
+
+// Benchmark insertion of values into a container at the end.
+template <typename T>
+void BM_InsertEnd(benchmark::State& state) {
+  using V = typename remove_pair_const<typename T::value_type>::type;
+  typename KeyOfValue<typename T::key_type, V>::type key_of_value;
+
+  T container;
+  const int kSize = 10000;
+  for (int i = 0; i < kSize; ++i) {
+    container.insert(Generator<V>(kSize)(i));
+  }
+  V v = Generator<V>(kSize)(kSize - 1);
+  typename T::key_type k = key_of_value(v);
+
+  auto it = container.find(k);
+  while (state.KeepRunning()) {
+    // Repeatedly removing then adding v.
+    container.erase(it);
+    it = GetIterFromInsert(container.insert(v));
+  }
+}
+
+template <typename T>
+void BM_LookupImpl(benchmark::State& state, bool sorted) {
+  using V = typename remove_pair_const<typename T::value_type>::type;
+  typename KeyOfValue<typename T::key_type, V>::type key_of_value;
+
+  std::vector<V> values = GenerateValues<V>(kBenchmarkValues);
+  if (sorted) {
+    std::sort(values.begin(), values.end());
+  }
+  T container(values.begin(), values.end());
+
+  while (state.KeepRunning()) {
+    int idx = state.iterations() % kBenchmarkValues;
+    benchmark::DoNotOptimize(container.find(key_of_value(values[idx])));
+  }
+}
+
+// Benchmark lookup of values in a container.
+template <typename T>
+void BM_Lookup(benchmark::State& state) {
+  BM_LookupImpl<T>(state, false);
+}
+
+// Benchmark lookup of values in a full container, meaning that values
+// are inserted in-order to take advantage of biased insertion, which
+// yields a full tree.
+template <typename T>
+void BM_FullLookup(benchmark::State& state) {
+  BM_LookupImpl<T>(state, true);
+}
+
+// Benchmark deletion of values from a container.
+template <typename T>
+void BM_Delete(benchmark::State& state) {
+  using V = typename remove_pair_const<typename T::value_type>::type;
+  typename KeyOfValue<typename T::key_type, V>::type key_of_value;
+  std::vector<V> values = GenerateValues<V>(kBenchmarkValues);
+  T container(values.begin(), values.end());
+
+  // Remove and re-insert 10% of the keys per batch.
+  const int batch_size = (kBenchmarkValues + 9) / 10;
+  while (state.KeepRunningBatch(batch_size)) {
+    const int i = state.iterations();
+
+    for (int j = i; j < i + batch_size; j++) {
+      int x = j % kBenchmarkValues;
+      container.erase(key_of_value(values[x]));
+    }
+
+    state.PauseTiming();
+    for (int j = i; j < i + batch_size; j++) {
+      int x = j % kBenchmarkValues;
+      container.insert(values[x]);
+    }
+    state.ResumeTiming();
+  }
+}
+
+// Benchmark deletion of multiple values from a container.
+template <typename T>
+void BM_DeleteRange(benchmark::State& state) {
+  using V = typename remove_pair_const<typename T::value_type>::type;
+  typename KeyOfValue<typename T::key_type, V>::type key_of_value;
+  std::vector<V> values = GenerateValues<V>(kBenchmarkValues);
+  T container(values.begin(), values.end());
+
+  // Remove and re-insert 10% of the keys per batch.
+  const int batch_size = (kBenchmarkValues + 9) / 10;
+  while (state.KeepRunningBatch(batch_size)) {
+    const int i = state.iterations();
+
+    const int start_index = i % kBenchmarkValues;
+
+    state.PauseTiming();
+    {
+      std::vector<V> removed;
+      removed.reserve(batch_size);
+      auto itr = container.find(key_of_value(values[start_index]));
+      auto start = itr;
+      for (int j = 0; j < batch_size; j++) {
+        if (itr == container.end()) {
+          state.ResumeTiming();
+          container.erase(start, itr);
+          state.PauseTiming();
+          itr = container.begin();
+          start = itr;
+        }
+        removed.push_back(*itr++);
+      }
+
+      state.ResumeTiming();
+      container.erase(start, itr);
+      state.PauseTiming();
+
+      container.insert(removed.begin(), removed.end());
+    }
+    state.ResumeTiming();
+  }
+}
+
+// Benchmark steady-state insert (into first half of range) and remove (from
+// second half of range), treating the container approximately like a queue with
+// log-time access for all elements. This benchmark does not test the case where
+// insertion and removal happen in the same region of the tree.  This benchmark
+// counts two value constructors.
+template <typename T>
+void BM_QueueAddRem(benchmark::State& state) {
+  using V = typename remove_pair_const<typename T::value_type>::type;
+  typename KeyOfValue<typename T::key_type, V>::type key_of_value;
+
+  ABSL_RAW_CHECK(kBenchmarkValues % 2 == 0, "for performance");
+
+  T container;
+
+  const size_t half = kBenchmarkValues / 2;
+  std::vector<int> remove_keys(half);
+  std::vector<int> add_keys(half);
+
+  // We want to do the exact same work repeatedly, and the benchmark can end
+  // after a different number of iterations depending on the speed of the
+  // individual run so we use a large batch size here and ensure that we do
+  // deterministic work every batch.
+  while (state.KeepRunningBatch(half * kAddRemBatchSize)) {
+    state.PauseTiming();
+
+    container.clear();
+
+    for (size_t i = 0; i < half; ++i) {
+      remove_keys[i] = i;
+      add_keys[i] = i;
+    }
+    constexpr int kSeed = 5;
+    std::mt19937_64 rand(kSeed);
+    std::shuffle(remove_keys.begin(), remove_keys.end(), rand);
+    std::shuffle(add_keys.begin(), add_keys.end(), rand);
+
+    // Note needs lazy generation of values.
+    Generator<V> g(kBenchmarkValues * kAddRemBatchSize);
+
+    for (size_t i = 0; i < half; ++i) {
+      container.insert(g(add_keys[i]));
+      container.insert(g(half + remove_keys[i]));
+    }
+
+    // There are three parts each of size "half":
+    // 1 is being deleted from  [offset - half, offset)
+    // 2 is standing            [offset, offset + half)
+    // 3 is being inserted into [offset + half, offset + 2 * half)
+    size_t offset = 0;
+
+    for (size_t i = 0; i < kAddRemBatchSize; ++i) {
+      std::shuffle(remove_keys.begin(), remove_keys.end(), rand);
+      std::shuffle(add_keys.begin(), add_keys.end(), rand);
+      offset += half;
+
+      state.ResumeTiming();
+      for (size_t idx = 0; idx < half; ++idx) {
+        container.erase(key_of_value(g(offset - half + remove_keys[idx])));
+        container.insert(g(offset + half + add_keys[idx]));
+      }
+      state.PauseTiming();
+    }
+    state.ResumeTiming();
+  }
+}
+
+// Mixed insertion and deletion in the same range using pre-constructed values.
+template <typename T>
+void BM_MixedAddRem(benchmark::State& state) {
+  using V = typename remove_pair_const<typename T::value_type>::type;
+  typename KeyOfValue<typename T::key_type, V>::type key_of_value;
+
+  ABSL_RAW_CHECK(kBenchmarkValues % 2 == 0, "for performance");
+
+  T container;
+
+  // Create two random shuffles
+  std::vector<int> remove_keys(kBenchmarkValues);
+  std::vector<int> add_keys(kBenchmarkValues);
+
+  // We want to do the exact same work repeatedly, and the benchmark can end
+  // after a different number of iterations depending on the speed of the
+  // individual run so we use a large batch size here and ensure that we do
+  // deterministic work every batch.
+  while (state.KeepRunningBatch(kBenchmarkValues * kAddRemBatchSize)) {
+    state.PauseTiming();
+
+    container.clear();
+
+    constexpr int kSeed = 7;
+    std::mt19937_64 rand(kSeed);
+
+    std::vector<V> values = GenerateValues<V>(kBenchmarkValues * 2);
+
+    // Insert the first half of the values (already in random order)
+    container.insert(values.begin(), values.begin() + kBenchmarkValues);
+
+    // Insert the first half of the values (already in random order)
+    for (size_t i = 0; i < kBenchmarkValues; ++i) {
+      // remove_keys and add_keys will be swapped before each round,
+      // therefore fill add_keys here w/ the keys being inserted, so
+      // they'll be the first to be removed.
+      remove_keys[i] = i + kBenchmarkValues;
+      add_keys[i] = i;
+    }
+
+    for (size_t i = 0; i < kAddRemBatchSize; ++i) {
+      remove_keys.swap(add_keys);
+      std::shuffle(remove_keys.begin(), remove_keys.end(), rand);
+      std::shuffle(add_keys.begin(), add_keys.end(), rand);
+
+      state.ResumeTiming();
+      for (size_t idx = 0; idx < kBenchmarkValues; ++idx) {
+        container.erase(key_of_value(values[remove_keys[idx]]));
+        container.insert(values[add_keys[idx]]);
+      }
+      state.PauseTiming();
+    }
+    state.ResumeTiming();
+  }
+}
+
+// Insertion at end, removal from the beginning.  This benchmark
+// counts two value constructors.
+// TODO(ezb): we could add a GenerateNext version of generator that could reduce
+// noise for string-like types.
+template <typename T>
+void BM_Fifo(benchmark::State& state) {
+  using V = typename remove_pair_const<typename T::value_type>::type;
+
+  T container;
+  // Need lazy generation of values as state.max_iterations is large.
+  Generator<V> g(kBenchmarkValues + state.max_iterations);
+
+  for (int i = 0; i < kBenchmarkValues; i++) {
+    container.insert(g(i));
+  }
+
+  while (state.KeepRunning()) {
+    container.erase(container.begin());
+    container.insert(container.end(), g(state.iterations() + kBenchmarkValues));
+  }
+}
+
+// Iteration (forward) through the tree
+template <typename T>
+void BM_FwdIter(benchmark::State& state) {
+  using V = typename remove_pair_const<typename T::value_type>::type;
+  using R = typename T::value_type const*;
+
+  std::vector<V> values = GenerateValues<V>(kBenchmarkValues);
+  T container(values.begin(), values.end());
+
+  auto iter = container.end();
+
+  R r = nullptr;
+
+  while (state.KeepRunning()) {
+    if (iter == container.end()) iter = container.begin();
+    r = &(*iter);
+    ++iter;
+  }
+
+  benchmark::DoNotOptimize(r);
+}
+
+// Benchmark random range-construction of a container.
+template <typename T>
+void BM_RangeConstructionImpl(benchmark::State& state, bool sorted) {
+  using V = typename remove_pair_const<typename T::value_type>::type;
+
+  std::vector<V> values = GenerateValues<V>(kBenchmarkValues);
+  if (sorted) {
+    std::sort(values.begin(), values.end());
+  }
+  {
+    T container(values.begin(), values.end());
+  }
+
+  while (state.KeepRunning()) {
+    T container(values.begin(), values.end());
+    benchmark::DoNotOptimize(container);
+  }
+}
+
+template <typename T>
+void BM_InsertRangeRandom(benchmark::State& state) {
+  BM_RangeConstructionImpl<T>(state, false);
+}
+
+template <typename T>
+void BM_InsertRangeSorted(benchmark::State& state) {
+  BM_RangeConstructionImpl<T>(state, true);
+}
+
+#define STL_ORDERED_TYPES(value)                     \
+  using stl_set_##value = std::set<value>;           \
+  using stl_map_##value = std::map<value, intptr_t>; \
+  using stl_multiset_##value = std::multiset<value>; \
+  using stl_multimap_##value = std::multimap<value, intptr_t>
+
+using StdString = std::string;
+STL_ORDERED_TYPES(int32_t);
+STL_ORDERED_TYPES(int64_t);
+STL_ORDERED_TYPES(StdString);
+STL_ORDERED_TYPES(Time);
+
+#define STL_UNORDERED_TYPES(value)                                       \
+  using stl_unordered_set_##value = std::unordered_set<value>;           \
+  using stl_unordered_map_##value = std::unordered_map<value, intptr_t>; \
+  using flat_hash_set_##value = flat_hash_set<value>;                    \
+  using flat_hash_map_##value = flat_hash_map<value, intptr_t>;          \
+  using stl_unordered_multiset_##value = std::unordered_multiset<value>; \
+  using stl_unordered_multimap_##value =                                 \
+      std::unordered_multimap<value, intptr_t>
+
+#define STL_UNORDERED_TYPES_CUSTOM_HASH(value, hash)                           \
+  using stl_unordered_set_##value = std::unordered_set<value, hash>;           \
+  using stl_unordered_map_##value = std::unordered_map<value, intptr_t, hash>; \
+  using flat_hash_set_##value = flat_hash_set<value, hash>;                    \
+  using flat_hash_map_##value = flat_hash_map<value, intptr_t, hash>;          \
+  using stl_unordered_multiset_##value = std::unordered_multiset<value, hash>; \
+  using stl_unordered_multimap_##value =                                       \
+      std::unordered_multimap<value, intptr_t, hash>
+
+STL_UNORDERED_TYPES(int32_t);
+STL_UNORDERED_TYPES(int64_t);
+STL_UNORDERED_TYPES(StdString);
+STL_UNORDERED_TYPES_CUSTOM_HASH(Time, absl::Hash<absl::Time>);
+
+#define BTREE_TYPES(value)                                            \
+  using btree_256_set_##value =                                       \
+      btree_set<value, std::less<value>, std::allocator<value>>;      \
+  using btree_256_map_##value =                                       \
+      btree_map<value, intptr_t, std::less<value>,                    \
+                std::allocator<std::pair<const value, intptr_t>>>;    \
+  using btree_256_multiset_##value =                                  \
+      btree_multiset<value, std::less<value>, std::allocator<value>>; \
+  using btree_256_multimap_##value =                                  \
+      btree_multimap<value, intptr_t, std::less<value>,               \
+                     std::allocator<std::pair<const value, intptr_t>>>
+
+BTREE_TYPES(int32_t);
+BTREE_TYPES(int64_t);
+BTREE_TYPES(StdString);
+BTREE_TYPES(Time);
+
+#define MY_BENCHMARK4(type, func)                                              \
+  void BM_##type##_##func(benchmark::State& state) { BM_##func<type>(state); } \
+  BENCHMARK(BM_##type##_##func)
+
+#define MY_BENCHMARK3(type)               \
+  MY_BENCHMARK4(type, Insert);            \
+  MY_BENCHMARK4(type, InsertSorted);      \
+  MY_BENCHMARK4(type, InsertEnd);         \
+  MY_BENCHMARK4(type, Lookup);            \
+  MY_BENCHMARK4(type, FullLookup);        \
+  MY_BENCHMARK4(type, Delete);            \
+  MY_BENCHMARK4(type, DeleteRange);       \
+  MY_BENCHMARK4(type, QueueAddRem);       \
+  MY_BENCHMARK4(type, MixedAddRem);       \
+  MY_BENCHMARK4(type, Fifo);              \
+  MY_BENCHMARK4(type, FwdIter);           \
+  MY_BENCHMARK4(type, InsertRangeRandom); \
+  MY_BENCHMARK4(type, InsertRangeSorted)
+
+#define MY_BENCHMARK2_SUPPORTS_MULTI_ONLY(type) \
+  MY_BENCHMARK3(stl_##type);                    \
+  MY_BENCHMARK3(stl_unordered_##type);          \
+  MY_BENCHMARK3(btree_256_##type)
+
+#define MY_BENCHMARK2(type)                \
+  MY_BENCHMARK2_SUPPORTS_MULTI_ONLY(type); \
+  MY_BENCHMARK3(flat_hash_##type)
+
+// Define MULTI_TESTING to see benchmarks for multi-containers also.
+//
+// You can use --copt=-DMULTI_TESTING.
+#ifdef MULTI_TESTING
+#define MY_BENCHMARK(type)                            \
+  MY_BENCHMARK2(set_##type);                          \
+  MY_BENCHMARK2(map_##type);                          \
+  MY_BENCHMARK2_SUPPORTS_MULTI_ONLY(multiset_##type); \
+  MY_BENCHMARK2_SUPPORTS_MULTI_ONLY(multimap_##type)
+#else
+#define MY_BENCHMARK(type)   \
+  MY_BENCHMARK2(set_##type); \
+  MY_BENCHMARK2(map_##type)
+#endif
+
+MY_BENCHMARK(int32_t);
+MY_BENCHMARK(int64_t);
+MY_BENCHMARK(StdString);
+MY_BENCHMARK(Time);
+
+// Define a type whose size and cost of moving are independently customizable.
+// When sizeof(value_type) increases, we expect btree to no longer have as much
+// cache-locality advantage over STL. When cost of moving increases, we expect
+// btree to actually do more work than STL because it has to move values around
+// and STL doesn't have to.
+template <int Size, int Copies>
+struct BigType {
+  BigType() : BigType(0) {}
+  explicit BigType(int x) { std::iota(values.begin(), values.end(), x); }
+
+  void Copy(const BigType& x) {
+    for (int i = 0; i < Size && i < Copies; ++i) values[i] = x.values[i];
+    // If Copies > Size, do extra copies.
+    for (int i = Size, idx = 0; i < Copies; ++i) {
+      int64_t tmp = x.values[idx];
+      benchmark::DoNotOptimize(tmp);
+      idx = idx + 1 == Size ? 0 : idx + 1;
+    }
+  }
+
+  BigType(const BigType& x) { Copy(x); }
+  BigType& operator=(const BigType& x) {
+    Copy(x);
+    return *this;
+  }
+
+  // Compare only the first Copies elements if Copies is less than Size.
+  bool operator<(const BigType& other) const {
+    return std::lexicographical_compare(
+        values.begin(), values.begin() + std::min(Size, Copies),
+        other.values.begin(), other.values.begin() + std::min(Size, Copies));
+  }
+  bool operator==(const BigType& other) const {
+    return std::equal(values.begin(), values.begin() + std::min(Size, Copies),
+                      other.values.begin());
+  }
+
+  // Support absl::Hash.
+  template <typename State>
+  friend State AbslHashValue(State h, const BigType& b) {
+    for (int i = 0; i < Size && i < Copies; ++i)
+      h = State::combine(std::move(h), b.values[i]);
+    return h;
+  }
+
+  std::array<int64_t, Size> values;
+};
+
+#define BIG_TYPE_BENCHMARKS(SIZE, COPIES)                                     \
+  using stl_set_size##SIZE##copies##COPIES = std::set<BigType<SIZE, COPIES>>; \
+  using stl_map_size##SIZE##copies##COPIES =                                  \
+      std::map<BigType<SIZE, COPIES>, intptr_t>;                              \
+  using stl_multiset_size##SIZE##copies##COPIES =                             \
+      std::multiset<BigType<SIZE, COPIES>>;                                   \
+  using stl_multimap_size##SIZE##copies##COPIES =                             \
+      std::multimap<BigType<SIZE, COPIES>, intptr_t>;                         \
+  using stl_unordered_set_size##SIZE##copies##COPIES =                        \
+      std::unordered_set<BigType<SIZE, COPIES>,                               \
+                         absl::Hash<BigType<SIZE, COPIES>>>;                  \
+  using stl_unordered_map_size##SIZE##copies##COPIES =                        \
+      std::unordered_map<BigType<SIZE, COPIES>, intptr_t,                     \
+                         absl::Hash<BigType<SIZE, COPIES>>>;                  \
+  using flat_hash_set_size##SIZE##copies##COPIES =                            \
+      flat_hash_set<BigType<SIZE, COPIES>>;                                   \
+  using flat_hash_map_size##SIZE##copies##COPIES =                            \
+      flat_hash_map<BigType<SIZE, COPIES>, intptr_t>;                         \
+  using stl_unordered_multiset_size##SIZE##copies##COPIES =                   \
+      std::unordered_multiset<BigType<SIZE, COPIES>,                          \
+                              absl::Hash<BigType<SIZE, COPIES>>>;             \
+  using stl_unordered_multimap_size##SIZE##copies##COPIES =                   \
+      std::unordered_multimap<BigType<SIZE, COPIES>, intptr_t,                \
+                              absl::Hash<BigType<SIZE, COPIES>>>;             \
+  using btree_256_set_size##SIZE##copies##COPIES =                            \
+      btree_set<BigType<SIZE, COPIES>>;                                       \
+  using btree_256_map_size##SIZE##copies##COPIES =                            \
+      btree_map<BigType<SIZE, COPIES>, intptr_t>;                             \
+  using btree_256_multiset_size##SIZE##copies##COPIES =                       \
+      btree_multiset<BigType<SIZE, COPIES>>;                                  \
+  using btree_256_multimap_size##SIZE##copies##COPIES =                       \
+      btree_multimap<BigType<SIZE, COPIES>, intptr_t>;                        \
+  MY_BENCHMARK(size##SIZE##copies##COPIES)
+
+// Define BIG_TYPE_TESTING to see benchmarks for more big types.
+//
+// You can use --copt=-DBIG_TYPE_TESTING.
+#ifndef NODESIZE_TESTING
+#ifdef BIG_TYPE_TESTING
+BIG_TYPE_BENCHMARKS(1, 4);
+BIG_TYPE_BENCHMARKS(4, 1);
+BIG_TYPE_BENCHMARKS(4, 4);
+BIG_TYPE_BENCHMARKS(1, 8);
+BIG_TYPE_BENCHMARKS(8, 1);
+BIG_TYPE_BENCHMARKS(8, 8);
+BIG_TYPE_BENCHMARKS(1, 16);
+BIG_TYPE_BENCHMARKS(16, 1);
+BIG_TYPE_BENCHMARKS(16, 16);
+BIG_TYPE_BENCHMARKS(1, 32);
+BIG_TYPE_BENCHMARKS(32, 1);
+BIG_TYPE_BENCHMARKS(32, 32);
+#else
+BIG_TYPE_BENCHMARKS(32, 32);
+#endif
+#endif
+
+// Benchmark using unique_ptrs to large value types. In order to be able to use
+// the same benchmark code as the other types, use a type that holds a
+// unique_ptr and has a copy constructor.
+template <int Size>
+struct BigTypePtr {
+  BigTypePtr() : BigTypePtr(0) {}
+  explicit BigTypePtr(int x) {
+    ptr = absl::make_unique<BigType<Size, Size>>(x);
+  }
+  BigTypePtr(const BigTypePtr& x) {
+    ptr = absl::make_unique<BigType<Size, Size>>(*x.ptr);
+  }
+  BigTypePtr(BigTypePtr&& x) noexcept = default;
+  BigTypePtr& operator=(const BigTypePtr& x) {
+    ptr = absl::make_unique<BigType<Size, Size>>(*x.ptr);
+  }
+  BigTypePtr& operator=(BigTypePtr&& x) noexcept = default;
+
+  bool operator<(const BigTypePtr& other) const { return *ptr < *other.ptr; }
+  bool operator==(const BigTypePtr& other) const { return *ptr == *other.ptr; }
+
+  std::unique_ptr<BigType<Size, Size>> ptr;
+};
+
+template <int Size>
+double ContainerInfo(const btree_set<BigTypePtr<Size>>& b) {
+  const double bytes_used =
+      b.bytes_used() + b.size() * sizeof(BigType<Size, Size>);
+  const double bytes_per_value = bytes_used / b.size();
+  BtreeContainerInfoLog(b, bytes_used, bytes_per_value);
+  return bytes_per_value;
+}
+template <int Size>
+double ContainerInfo(const btree_map<int, BigTypePtr<Size>>& b) {
+  const double bytes_used =
+      b.bytes_used() + b.size() * sizeof(BigType<Size, Size>);
+  const double bytes_per_value = bytes_used / b.size();
+  BtreeContainerInfoLog(b, bytes_used, bytes_per_value);
+  return bytes_per_value;
+}
+
+#define BIG_TYPE_PTR_BENCHMARKS(SIZE)                                          \
+  using stl_set_size##SIZE##copies##SIZE##ptr = std::set<BigType<SIZE, SIZE>>; \
+  using stl_map_size##SIZE##copies##SIZE##ptr =                                \
+      std::map<int, BigType<SIZE, SIZE>>;                                      \
+  using stl_unordered_set_size##SIZE##copies##SIZE##ptr =                      \
+      std::unordered_set<BigType<SIZE, SIZE>,                                  \
+                         absl::Hash<BigType<SIZE, SIZE>>>;                     \
+  using stl_unordered_map_size##SIZE##copies##SIZE##ptr =                      \
+      std::unordered_map<int, BigType<SIZE, SIZE>>;                            \
+  using flat_hash_set_size##SIZE##copies##SIZE##ptr =                          \
+      flat_hash_set<BigType<SIZE, SIZE>>;                                      \
+  using flat_hash_map_size##SIZE##copies##SIZE##ptr =                          \
+      flat_hash_map<int, BigTypePtr<SIZE>>;                                    \
+  using btree_256_set_size##SIZE##copies##SIZE##ptr =                          \
+      btree_set<BigTypePtr<SIZE>>;                                             \
+  using btree_256_map_size##SIZE##copies##SIZE##ptr =                          \
+      btree_map<int, BigTypePtr<SIZE>>;                                        \
+  MY_BENCHMARK3(stl_set_size##SIZE##copies##SIZE##ptr);                        \
+  MY_BENCHMARK3(stl_unordered_set_size##SIZE##copies##SIZE##ptr);              \
+  MY_BENCHMARK3(flat_hash_set_size##SIZE##copies##SIZE##ptr);                  \
+  MY_BENCHMARK3(btree_256_set_size##SIZE##copies##SIZE##ptr);                  \
+  MY_BENCHMARK3(stl_map_size##SIZE##copies##SIZE##ptr);                        \
+  MY_BENCHMARK3(stl_unordered_map_size##SIZE##copies##SIZE##ptr);              \
+  MY_BENCHMARK3(flat_hash_map_size##SIZE##copies##SIZE##ptr);                  \
+  MY_BENCHMARK3(btree_256_map_size##SIZE##copies##SIZE##ptr)
+
+BIG_TYPE_PTR_BENCHMARKS(32);
+
+}  // namespace
+}  // namespace container_internal
+ABSL_NAMESPACE_END
+}  // namespace absl