Add max_scale option (#3323)

CHANGELOG.md

@@ -6,7 +6,10 @@ The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/),
 and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).
 
 ## Unreleased
+
+- Add max_scale option to Exponential Bucket Histogram Aggregation [#3323](https://github.com/open-telemetry/opentelemetry-python/pull/3323))
 - Use BoundedAttributes instead of raw dict to extract attributes from LogRecord and Support dropped_attributes_count in LogRecord ([#3310](https://github.com/open-telemetry/opentelemetry-python/pull/3310))
+
 ## Version 1.18.0/0.39b0 (2023-05-04)
 
 - Select histogram aggregation with an environment variable

opentelemetry-sdk/src/opentelemetry/sdk/metrics/_internal/aggregation.py

@@ -386,6 +386,7 @@ def __init__(
         # See the derivation here:
         # https://github.com/open-telemetry/opentelemetry-specification/blob/main/specification/metrics/sdk.md#exponential-bucket-histogram-aggregation)
         max_size: int = 160,
+        max_scale: int = 20,
     ):
         super().__init__(attributes)
         # max_size is the maximum capacity of the positive and negative
@@ -403,6 +404,7 @@ def __init__(
             )
 
         self._max_size = max_size
+        self._max_scale = max_scale
 
         # _sum is the sum of all the values aggregated by this aggregator.
         self._sum = 0
@@ -428,7 +430,14 @@ def __init__(
 
         # _mapping corresponds to the current scale, is shared by both the
         # positive and negative buckets.
-        self._mapping = LogarithmMapping(LogarithmMapping._max_scale)
+
+        if self._max_scale > 20:
+            _logger.warning(
+                "max_scale is set to %s which is "
+                "larger than the recommended value of 20",
+                self._max_scale,
+            )
+        self._mapping = LogarithmMapping(self._max_scale)
 
         self._instrument_temporality = AggregationTemporality.DELTA
         self._start_time_unix_nano = start_time_unix_nano
@@ -941,9 +950,10 @@ class ExponentialBucketHistogramAggregation(Aggregation):
     def __init__(
         self,
         max_size: int = 160,
+        max_scale: int = 20,
     ):
-
         self._max_size = max_size
+        self._max_scale = max_scale
 
     def _create_aggregation(
         self,
@@ -955,6 +965,7 @@ def _create_aggregation(
             attributes,
             start_time_unix_nano,
             max_size=self._max_size,
+            max_scale=self._max_scale,
         )
 
 

opentelemetry-sdk/tests/metrics/exponential_histogram/test_exponential_bucket_histogram_aggregation.py

@@ -13,6 +13,7 @@
 # limitations under the License.
 
 from itertools import permutations
+from logging import WARNING
 from math import ldexp
 from sys import float_info
 from types import MethodType
@@ -37,6 +38,9 @@
     LogarithmMapping,
 )
 from opentelemetry.sdk.metrics._internal.measurement import Measurement
+from opentelemetry.sdk.metrics.view import (
+    ExponentialBucketHistogramAggregation,
+)
 
 
 def get_counts(buckets: Buckets) -> int:
@@ -77,6 +81,39 @@ def swap(
 
 
 class TestExponentialBucketHistogramAggregation(TestCase):
+    @patch("opentelemetry.sdk.metrics._internal.aggregation.LogarithmMapping")
+    def test_create_aggregation(self, mock_logarithm_mapping):
+        exponential_bucket_histogram_aggregation = (
+            ExponentialBucketHistogramAggregation()
+        )._create_aggregation(Mock(), Mock(), Mock())
+
+        self.assertEqual(
+            exponential_bucket_histogram_aggregation._max_scale, 20
+        )
+
+        mock_logarithm_mapping.assert_called_with(20)
+
+        exponential_bucket_histogram_aggregation = (
+            ExponentialBucketHistogramAggregation(max_scale=10)
+        )._create_aggregation(Mock(), Mock(), Mock())
+
+        self.assertEqual(
+            exponential_bucket_histogram_aggregation._max_scale, 10
+        )
+
+        mock_logarithm_mapping.assert_called_with(10)
+
+        with self.assertLogs(level=WARNING):
+            exponential_bucket_histogram_aggregation = (
+                ExponentialBucketHistogramAggregation(max_scale=100)
+            )._create_aggregation(Mock(), Mock(), Mock())
+
+        self.assertEqual(
+            exponential_bucket_histogram_aggregation._max_scale, 100
+        )
+
+        mock_logarithm_mapping.assert_called_with(100)
+
     def assertInEpsilon(self, first, second, epsilon):
         self.assertLessEqual(first, (second * (1 + epsilon)))
         self.assertGreaterEqual(first, (second * (1 - epsilon)))