| // Copyright 2019 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 "absl/strings/internal/cordz_functions.h" |
| |
| #include <thread> // NOLINT we need real clean new threads |
| |
| #include "gmock/gmock.h" |
| #include "gtest/gtest.h" |
| #include "absl/base/config.h" |
| |
| namespace absl { |
| ABSL_NAMESPACE_BEGIN |
| namespace cord_internal { |
| namespace { |
| |
| using ::testing::Eq; |
| using ::testing::Ge; |
| using ::testing::Le; |
| |
| TEST(CordzFunctionsTest, SampleRate) { |
| int32_t orig_sample_rate = get_cordz_mean_interval(); |
| int32_t expected_sample_rate = 123; |
| set_cordz_mean_interval(expected_sample_rate); |
| EXPECT_THAT(get_cordz_mean_interval(), Eq(expected_sample_rate)); |
| set_cordz_mean_interval(orig_sample_rate); |
| } |
| |
| // Cordz is disabled when we don't have thread_local. All calls to |
| // should_profile will return false when cordz is disabled, so we might want to |
| // avoid those tests. |
| #ifdef ABSL_INTERNAL_CORDZ_ENABLED |
| |
| TEST(CordzFunctionsTest, ShouldProfileDisable) { |
| int32_t orig_sample_rate = get_cordz_mean_interval(); |
| |
| set_cordz_mean_interval(0); |
| cordz_set_next_sample_for_testing(0); |
| EXPECT_EQ(cordz_should_profile(), 0); |
| // 1 << 16 is from kIntervalIfDisabled in cordz_functions.cc. |
| EXPECT_THAT(cordz_next_sample.next_sample, Eq(1 << 16)); |
| |
| set_cordz_mean_interval(orig_sample_rate); |
| } |
| |
| TEST(CordzFunctionsTest, ShouldProfileAlways) { |
| int32_t orig_sample_rate = get_cordz_mean_interval(); |
| |
| set_cordz_mean_interval(1); |
| cordz_set_next_sample_for_testing(1); |
| EXPECT_GT(cordz_should_profile(), 0); |
| EXPECT_THAT(cordz_next_sample.next_sample, Le(1)); |
| |
| set_cordz_mean_interval(orig_sample_rate); |
| } |
| |
| TEST(CordzFunctionsTest, DoesNotAlwaysSampleFirstCord) { |
| // Set large enough interval such that the chance of 'tons' of threads |
| // randomly sampling the first call is infinitely small. |
| set_cordz_mean_interval(10000); |
| int tries = 0; |
| bool sampled = false; |
| do { |
| ++tries; |
| ASSERT_THAT(tries, Le(1000)); |
| std::thread thread([&sampled] { sampled = cordz_should_profile() > 0; }); |
| thread.join(); |
| } while (sampled); |
| } |
| |
| TEST(CordzFunctionsTest, ShouldProfileRate) { |
| static constexpr int kDesiredMeanInterval = 1000; |
| static constexpr int kSamples = 10000; |
| int32_t orig_sample_rate = get_cordz_mean_interval(); |
| |
| set_cordz_mean_interval(kDesiredMeanInterval); |
| |
| int64_t sum_of_intervals = 0; |
| for (int i = 0; i < kSamples; i++) { |
| // Setting next_sample to 0 will force cordz_should_profile to generate a |
| // new value for next_sample each iteration. |
| cordz_set_next_sample_for_testing(0); |
| cordz_should_profile(); |
| sum_of_intervals += cordz_next_sample.next_sample; |
| } |
| |
| // The sum of independent exponential variables is an Erlang distribution, |
| // which is a gamma distribution where the shape parameter is equal to the |
| // number of summands. The distribution used for cordz_should_profile is |
| // actually floor(Exponential(1/mean)) which introduces bias. However, we can |
| // apply the squint-really-hard correction factor. That is, when mean is |
| // large, then if we squint really hard the shape of the distribution between |
| // N and N+1 looks like a uniform distribution. On average, each value for |
| // next_sample will be about 0.5 lower than we would expect from an |
| // exponential distribution. This squint-really-hard correction approach won't |
| // work when mean is smaller than about 10 but works fine when mean is 1000. |
| // |
| // We can use R to calculate a confidence interval. This |
| // shows how to generate a confidence interval with a false positive rate of |
| // one in a billion. |
| // |
| // $ R -q |
| // > mean = 1000 |
| // > kSamples = 10000 |
| // > errorRate = 1e-9 |
| // > correction = -kSamples / 2 |
| // > low = qgamma(errorRate/2, kSamples, 1/mean) + correction |
| // > high = qgamma(1 - errorRate/2, kSamples, 1/mean) + correction |
| // > low |
| // [1] 9396115 |
| // > high |
| // [1] 10618100 |
| EXPECT_THAT(sum_of_intervals, Ge(9396115)); |
| EXPECT_THAT(sum_of_intervals, Le(10618100)); |
| |
| set_cordz_mean_interval(orig_sample_rate); |
| } |
| |
| #else // ABSL_INTERNAL_CORDZ_ENABLED |
| |
| TEST(CordzFunctionsTest, ShouldProfileDisabled) { |
| int32_t orig_sample_rate = get_cordz_mean_interval(); |
| |
| set_cordz_mean_interval(1); |
| cordz_set_next_sample_for_testing(0); |
| EXPECT_FALSE(cordz_should_profile()); |
| |
| set_cordz_mean_interval(orig_sample_rate); |
| } |
| |
| #endif // ABSL_INTERNAL_CORDZ_ENABLED |
| |
| } // namespace |
| } // namespace cord_internal |
| ABSL_NAMESPACE_END |
| } // namespace absl |