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77 changes: 77 additions & 0 deletions
77
opentelemetry-sdk/tests/performance/benchmarks/metrics/test_benchmark_metrics.py
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# Copyright The OpenTelemetry 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 | ||
# | ||
# 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. | ||
import pytest | ||
|
||
from opentelemetry.sdk.metrics import Counter, MeterProvider | ||
from opentelemetry.sdk.metrics.export import ( | ||
AggregationTemporality, | ||
InMemoryMetricReader, | ||
) | ||
|
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reader_cumulative = InMemoryMetricReader() | ||
reader_delta = InMemoryMetricReader( | ||
preferred_temporality={ | ||
Counter: AggregationTemporality.DELTA, | ||
}, | ||
) | ||
provider_reader_cumulative = MeterProvider( | ||
metric_readers=[reader_cumulative], | ||
) | ||
provider_reader_delta = MeterProvider(metric_readers=[reader_delta]) | ||
meter_cumulative = provider_reader_cumulative.get_meter("sdk_meter_provider") | ||
meter_delta = provider_reader_delta.get_meter("sdk_meter_provider_delta") | ||
counter_cumulative = meter_cumulative.create_counter("test_counter") | ||
counter_delta = meter_delta.create_counter("test_counter2") | ||
udcounter = meter_cumulative.create_up_down_counter("test_udcounter") | ||
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@pytest.mark.parametrize( | ||
("num_labels", "temporality"), | ||
[ | ||
(0, "delta"), | ||
(1, "delta"), | ||
(3, "delta"), | ||
(5, "delta"), | ||
(10, "delta"), | ||
(0, "cumulative"), | ||
(1, "cumulative"), | ||
(3, "cumulative"), | ||
(5, "cumulative"), | ||
(10, "cumulative"), | ||
], | ||
) | ||
def test_counter_add(benchmark, num_labels, temporality): | ||
labels = {} | ||
for i in range(num_labels): | ||
labels = {f"Key{i}": f"Value{i}" for i in range(num_labels)} | ||
|
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def benchmark_counter_add(): | ||
if temporality == "cumulative": | ||
counter_cumulative.add(1, labels) | ||
else: | ||
counter_delta.add(1, labels) | ||
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benchmark(benchmark_counter_add) | ||
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@pytest.mark.parametrize("num_labels", [0, 1, 3, 5, 10]) | ||
def test_up_down_counter_add(benchmark, num_labels): | ||
labels = {} | ||
for i in range(num_labels): | ||
labels = {f"Key{i}": f"Value{i}" for i in range(num_labels)} | ||
|
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def benchmark_up_down_counter_add(): | ||
udcounter.add(1, labels) | ||
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benchmark(benchmark_up_down_counter_add) |
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126
opentelemetry-sdk/tests/performance/benchmarks/metrics/test_benchmark_metrics_histogram,.py
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# Copyright The OpenTelemetry 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 | ||
# | ||
# 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. | ||
import random | ||
|
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import pytest | ||
|
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from opentelemetry.sdk.metrics import MeterProvider | ||
from opentelemetry.sdk.metrics.export import InMemoryMetricReader | ||
from opentelemetry.sdk.metrics.view import ( | ||
ExplicitBucketHistogramAggregation, | ||
View, | ||
) | ||
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MAX_BOUND_VALUE = 10000 | ||
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def _generate_bounds(bound_count): | ||
bounds = [] | ||
for i in range(bound_count): | ||
bounds.append(i * MAX_BOUND_VALUE / bound_count) | ||
return bounds | ||
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hist_view_10 = View( | ||
instrument_name="test_histogram_10_bound", | ||
aggregation=ExplicitBucketHistogramAggregation(_generate_bounds(10)), | ||
) | ||
hist_view_49 = View( | ||
instrument_name="test_histogram_49_bound", | ||
aggregation=ExplicitBucketHistogramAggregation(_generate_bounds(49)), | ||
) | ||
hist_view_50 = View( | ||
instrument_name="test_histogram_50_bound", | ||
aggregation=ExplicitBucketHistogramAggregation(_generate_bounds(50)), | ||
) | ||
hist_view_1000 = View( | ||
instrument_name="test_histogram_1000_bound", | ||
aggregation=ExplicitBucketHistogramAggregation(_generate_bounds(1000)), | ||
) | ||
reader = InMemoryMetricReader() | ||
provider = MeterProvider( | ||
metric_readers=[reader], | ||
views=[ | ||
hist_view_10, | ||
hist_view_49, | ||
hist_view_50, | ||
hist_view_1000, | ||
], | ||
) | ||
meter = provider.get_meter("sdk_meter_provider") | ||
hist = meter.create_histogram("test_histogram_default") | ||
hist10 = meter.create_histogram("test_histogram_10_bound") | ||
hist49 = meter.create_histogram("test_histogram_49_bound") | ||
hist50 = meter.create_histogram("test_histogram_50_bound") | ||
hist1000 = meter.create_histogram("test_histogram_1000_bound") | ||
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@pytest.mark.parametrize("num_labels", [0, 1, 3, 5, 7]) | ||
def test_histogram_record(benchmark, num_labels): | ||
labels = {} | ||
for i in range(num_labels): | ||
labels["Key{}".format(i)] = "Value{}".format(i) | ||
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def benchmark_histogram_record(): | ||
hist.record(random.random() * MAX_BOUND_VALUE) | ||
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benchmark(benchmark_histogram_record) | ||
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@pytest.mark.parametrize("num_labels", [0, 1, 3, 5, 7]) | ||
def test_histogram_record_10(benchmark, num_labels): | ||
labels = {} | ||
for i in range(num_labels): | ||
labels["Key{}".format(i)] = "Value{}".format(i) | ||
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def benchmark_histogram_record_10(): | ||
hist10.record(random.random() * MAX_BOUND_VALUE) | ||
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benchmark(benchmark_histogram_record_10) | ||
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@pytest.mark.parametrize("num_labels", [0, 1, 3, 5, 7]) | ||
def test_histogram_record_49(benchmark, num_labels): | ||
labels = {} | ||
for i in range(num_labels): | ||
labels["Key{}".format(i)] = "Value{}".format(i) | ||
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def benchmark_histogram_record_49(): | ||
hist49.record(random.random() * MAX_BOUND_VALUE) | ||
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benchmark(benchmark_histogram_record_49) | ||
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@pytest.mark.parametrize("num_labels", [0, 1, 3, 5, 7]) | ||
def test_histogram_record_50(benchmark, num_labels): | ||
labels = {} | ||
for i in range(num_labels): | ||
labels["Key{}".format(i)] = "Value{}".format(i) | ||
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def benchmark_histogram_record_50(): | ||
hist50.record(random.random() * MAX_BOUND_VALUE) | ||
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benchmark(benchmark_histogram_record_50) | ||
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@pytest.mark.parametrize("num_labels", [0, 1, 3, 5, 7]) | ||
def test_histogram_record_1000(benchmark, num_labels): | ||
labels = {} | ||
for i in range(num_labels): | ||
labels["Key{}".format(i)] = "Value{}".format(i) | ||
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def benchmark_histogram_record_1000(): | ||
hist1000.record(random.random() * MAX_BOUND_VALUE) | ||
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benchmark(benchmark_histogram_record_1000) |