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Add integration test for exponential histogram
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‎opentelemetry-sdk/tests/metrics/integration_test/test_exponential_bucket_histogram_aggregation.py‎

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# Copyright The OpenTelemetry Authors
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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from platform import system
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from unittest import TestCase
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from pytest import mark
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from opentelemetry.sdk.metrics import Histogram, MeterProvider
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from opentelemetry.sdk.metrics.export import (
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AggregationTemporality,
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InMemoryMetricReader,
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)
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from opentelemetry.sdk.metrics.view import (
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ExponentialBucketHistogramAggregation
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)
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class TestExponentialBucketHistogramAggregation(TestCase):
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test_values = [1, 6, 11, 26, 51, 76, 101, 251, 501, 751]
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@mark.skipif(
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system() == "Windows",
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reason=(
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"Tests fail because Windows time_ns resolution is too low so "
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"two different time measurements may end up having the exact same"
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"value."
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),
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)
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def test_synchronous_delta_temporality(self):
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aggregation = ExponentialBucketHistogramAggregation()
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reader = InMemoryMetricReader(
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preferred_aggregation={Histogram: aggregation},
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preferred_temporality={Histogram: AggregationTemporality.DELTA},
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)
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provider = MeterProvider(metric_readers=[reader])
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meter = provider.get_meter("name", "version")
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histogram = meter.create_histogram("histogram")
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results = []
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for _ in range(10):
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results.append(reader.get_metrics_data())
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for metrics_data in results:
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self.assertIsNone(metrics_data)
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results = []
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for test_value in self.test_values:
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histogram.record(test_value)
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results.append(reader.get_metrics_data())
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metric_data = (
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results[0]
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.resource_metrics[0]
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.scope_metrics[0]
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.metrics[0]
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.data.data_points[0]
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)
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previous_time_unix_nano = metric_data.time_unix_nano
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"""
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self.assertEqual(
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metric_data.bucket_counts,
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(0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0),
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)
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"""
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self.assertLess(
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metric_data.start_time_unix_nano,
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previous_time_unix_nano,
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)
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self.assertEqual(metric_data.min, self.test_values[0])
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self.assertEqual(metric_data.max, self.test_values[0])
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self.assertEqual(metric_data.sum, self.test_values[0])
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for index, metrics_data in enumerate(results[1:]):
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metric_data = (
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metrics_data.resource_metrics[0]
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.scope_metrics[0]
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.metrics[0]
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.data.data_points[0]
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)
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self.assertEqual(
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previous_time_unix_nano, metric_data.start_time_unix_nano
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)
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previous_time_unix_nano = metric_data.time_unix_nano
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"""
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self.assertEqual(
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metric_data.bucket_counts,
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tuple(
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[
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1 if internal_index == index + 2 else 0
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for internal_index in range(16)
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]
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),
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)
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"""
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self.assertLess(
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metric_data.start_time_unix_nano, metric_data.time_unix_nano
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)
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self.assertEqual(metric_data.min, self.test_values[index + 1])
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self.assertEqual(metric_data.max, self.test_values[index + 1])
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self.assertEqual(metric_data.sum, self.test_values[index + 1])
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results = []
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for _ in range(10):
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results.append(reader.get_metrics_data())
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provider.shutdown()
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for metrics_data in results:
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self.assertIsNone(metrics_data)
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@mark.skipif(
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system() == "Windows",
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reason=(
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"Tests fail because Windows time_ns resolution is too low so "
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"two different time measurements may end up having the exact same"
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"value."
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),
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)
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def test_synchronous_cumulative_temporality(self):
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aggregation = ExponentialBucketHistogramAggregation()
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reader = InMemoryMetricReader(
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preferred_aggregation={Histogram: aggregation},
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preferred_temporality={
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Histogram: AggregationTemporality.CUMULATIVE
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},
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)
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provider = MeterProvider(metric_readers=[reader])
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meter = provider.get_meter("name", "version")
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histogram = meter.create_histogram("histogram")
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results = []
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for _ in range(10):
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results.append(reader.get_metrics_data())
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for metrics_data in results:
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self.assertIsNone(metrics_data)
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results = []
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for test_value in self.test_values:
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histogram.record(test_value)
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results.append(reader.get_metrics_data())
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start_time_unix_nano = (
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results[0]
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.resource_metrics[0]
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.scope_metrics[0]
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.metrics[0]
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.data.data_points[0]
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.start_time_unix_nano
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)
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for index, metrics_data in enumerate(results):
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metric_data = (
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metrics_data.resource_metrics[0]
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.scope_metrics[0]
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.metrics[0]
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.data.data_points[0]
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)
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self.assertEqual(
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start_time_unix_nano, metric_data.start_time_unix_nano
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)
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"""
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self.assertEqual(
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metric_data.bucket_counts,
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tuple(
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[
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(
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0
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if internal_index < 1 or internal_index > index + 1
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else 1
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)
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for internal_index in range(16)
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]
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),
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)
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"""
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self.assertEqual(metric_data.min, self.test_values[0])
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self.assertEqual(metric_data.max, self.test_values[index])
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self.assertEqual(
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metric_data.sum, sum(self.test_values[: index + 1])
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)
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results = []
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for i in range(10):
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results.append(reader.get_metrics_data())
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provider.shutdown()
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start_time_unix_nano = (
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results[0]
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.resource_metrics[0]
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.scope_metrics[0]
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.metrics[0]
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.data.data_points[0]
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.start_time_unix_nano
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)
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for metrics_data in results:
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metric_data = (
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metrics_data.resource_metrics[0]
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.scope_metrics[0]
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.metrics[0]
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.data.data_points[0]
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)
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self.assertEqual(
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start_time_unix_nano, metric_data.start_time_unix_nano
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)
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"""
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self.assertEqual(
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metric_data.bucket_counts,
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(0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0),
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)
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"""
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self.assertEqual(metric_data.min, self.test_values[0])
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self.assertEqual(metric_data.max, self.test_values[-1])
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self.assertEqual(metric_data.sum, sum(self.test_values))

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