Add micro benchmark tests for metric instrument operations

CHANGELOG.md

@@ -19,6 +19,8 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
   ([#3223](https://github.com/open-telemetry/opentelemetry-python/pull/3223))
 - Add speced out environment variables and arguments for BatchLogRecordProcessor
   ([#3237](https://github.com/open-telemetry/opentelemetry-python/pull/3237))
+- Add benchmark tests for metrics
+  ([#3267](https://github.com/open-telemetry/opentelemetry-python/pull/3267))
 
 ## Version 1.17.0/0.38b0 (2023-03-22)
 

opentelemetry-sdk/tests/performance/benchmarks/metrics/test_benchmark_metrics.py

@@ -0,0 +1,77 @@
+# 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,
+)
+
+reader = InMemoryMetricReader()
+reader_delta = InMemoryMetricReader(
+    preferred_temporality={
+        Counter: AggregationTemporality.DELTA,
+    },
+)
+provider = MeterProvider(
+    metric_readers=[reader],
+)
+provider2 = MeterProvider(metric_readers=[reader_delta])
+meter = provider.get_meter("sdk_meter_provider")
+meter2 = provider2.get_meter("sdk_meter_provider_delta")
+counter = meter.create_counter("test_counter")
+counter2 = meter2.create_counter("test_counter2")
+udcounter = meter.create_up_down_counter("test_udcounter")
+
+
+@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["Key{}".format(i)] = "Value{}".format(i)
+
+    def benchmark_counter_add():
+        if temporality == "cumulative":
+            counter.add(1, labels)
+        else:
+            counter2.add(1, labels)
+
+    benchmark(benchmark_counter_add)
+
+
+@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["Key{}".format(i)] = "Value{}".format(i)
+
+    def benchmark_up_down_counter_add():
+        udcounter.add(1, labels)
+
+    benchmark(benchmark_up_down_counter_add)

opentelemetry-sdk/tests/performance/benchmarks/metrics/test_benchmark_metrics_histogram,.py

@@ -0,0 +1,126 @@
+# 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
+
+import pytest
+
+from opentelemetry.sdk.metrics import MeterProvider
+from opentelemetry.sdk.metrics.export import InMemoryMetricReader
+from opentelemetry.sdk.metrics.view import (
+    ExplicitBucketHistogramAggregation,
+    View,
+)
+
+MAX_BOUND_VALUE = 10000
+
+
+def _generate_bounds(bound_count):
+    bounds = []
+    for i in range(bound_count):
+        bounds.append(i * MAX_BOUND_VALUE / bound_count)
+    return bounds
+
+
+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")
+
+
+@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)
+
+    def benchmark_histogram_record():
+        hist.record(random.random() * MAX_BOUND_VALUE)
+
+    benchmark(benchmark_histogram_record)
+
+
+@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)
+
+    def benchmark_histogram_record_10():
+        hist10.record(random.random() * MAX_BOUND_VALUE)
+
+    benchmark(benchmark_histogram_record_10)
+
+
+@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)
+
+    def benchmark_histogram_record_49():
+        hist49.record(random.random() * MAX_BOUND_VALUE)
+
+    benchmark(benchmark_histogram_record_49)
+
+
+@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)
+
+    def benchmark_histogram_record_50():
+        hist50.record(random.random() * MAX_BOUND_VALUE)
+
+    benchmark(benchmark_histogram_record_50)
+
+
+@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)
+
+    def benchmark_histogram_record_1000():
+        hist1000.record(random.random() * MAX_BOUND_VALUE)
+
+    benchmark(benchmark_histogram_record_1000)