hist

opentelemetry-sdk/src/opentelemetry/sdk/_metrics/aggregation.py

@@ -267,18 +267,25 @@ def collect(self) -> HistogramPoint:
             value = self._bucket_counts
             start_time_unix_nano = self._start_time_unix_nano
             histogram_sum = self._sum
+            if self._record_min_max:
+                histogram_max = self._max
+                histogram_min = self._min
 
             self._bucket_counts = self._get_empty_bucket_counts()
             self._start_time_unix_nano = now + 1
             self._sum = 0
+            self._min = inf
+            self._max = -inf
 
         return HistogramPoint(
-            start_time_unix_nano=start_time_unix_nano,
-            time_unix_nano=now,
+            aggregation_temporality=AggregationTemporality.DELTA,
             bucket_counts=tuple(value),
             explicit_bounds=self._boundaries,
-            aggregation_temporality=AggregationTemporality.DELTA,
+            max=histogram_max,
+            min=histogram_min,
+            start_time_unix_nano=start_time_unix_nano,
             sum=histogram_sum,
+            time_unix_nano=now,
         )
 
 

opentelemetry-sdk/src/opentelemetry/sdk/_metrics/point.py

@@ -15,7 +15,7 @@
 import json
 from dataclasses import asdict, dataclass
 from enum import IntEnum
-from typing import Sequence, Union
+from typing import Optional, Sequence, Union
 
 from opentelemetry.sdk.resources import Resource
 from opentelemetry.sdk.util.instrumentation import InstrumentationInfo
@@ -30,11 +30,11 @@ class AggregationTemporality(IntEnum):
 
 @dataclass(frozen=True)
 class Sum:
+    aggregation_temporality: AggregationTemporality
+    is_monotonic: bool
     start_time_unix_nano: int
     time_unix_nano: int
     value: Union[int, float]
-    aggregation_temporality: AggregationTemporality
-    is_monotonic: bool
 
 
 @dataclass(frozen=True)
@@ -45,12 +45,14 @@ class Gauge:
 
 @dataclass(frozen=True)
 class Histogram:
-    start_time_unix_nano: int
-    time_unix_nano: int
+    aggregation_temporality: AggregationTemporality
     bucket_counts: Sequence[int]
     explicit_bounds: Sequence[float]
+    max: Optional[int]
+    min: Optional[int]
+    start_time_unix_nano: int
     sum: Union[int, float]
-    aggregation_temporality: AggregationTemporality
+    time_unix_nano: int
 
 
 PointT = Union[Sum, Gauge, Histogram]

opentelemetry-sdk/tests/metrics/test_point.py

@@ -37,15 +37,16 @@ class TestDatapointToJSON(TestCase):
     def test_sum(self):
         point = _create_metric(
             Sum(
+                aggregation_temporality=2,
+                is_monotonic=True,
                 start_time_unix_nano=10,
                 time_unix_nano=20,
                 value=9,
-                aggregation_temporality=2,
-                is_monotonic=True,
             )
         )
+        print(point.to_json())
         self.assertEqual(
-            '{"attributes": {"attr-key": "test-val"}, "description": "test-description", "instrumentation_info": "InstrumentationInfo(name, version, None)", "name": "test-name", "resource": "BoundedAttributes({\'resource-key\': \'resource-val\'}, maxlen=None)", "unit": "test-unit", "point": {"start_time_unix_nano": 10, "time_unix_nano": 20, "value": 9, "aggregation_temporality": 2, "is_monotonic": true}}',
+            '{"attributes": {"attr-key": "test-val"}, "description": "test-description", "instrumentation_info": "InstrumentationInfo(name, version, None)", "name": "test-name", "resource": "BoundedAttributes({\'resource-key\': \'resource-val\'}, maxlen=None)", "unit": "test-unit", "point": {"aggregation_temporality": 2, "is_monotonic": true, "start_time_unix_nano": 10, "time_unix_nano": 20, "value": 9}}',
             point.to_json(),
         )
 
@@ -59,16 +60,19 @@ def test_gauge(self):
     def test_histogram(self):
         point = _create_metric(
             Histogram(
-                start_time_unix_nano=50,
-                time_unix_nano=60,
+                aggregation_temporality=1,
                 bucket_counts=[0, 0, 1, 0],
                 explicit_bounds=[0.1, 0.5, 0.9, 1],
-                aggregation_temporality=1,
+                max=0.8,
+                min=0.8,
+                start_time_unix_nano=50,
                 sum=0.8,
+                time_unix_nano=60,
             )
         )
         self.maxDiff = None
+        print(point.to_json())
         self.assertEqual(
-            '{"attributes": {"attr-key": "test-val"}, "description": "test-description", "instrumentation_info": "InstrumentationInfo(name, version, None)", "name": "test-name", "resource": "BoundedAttributes({\'resource-key\': \'resource-val\'}, maxlen=None)", "unit": "test-unit", "point": {"start_time_unix_nano": 50, "time_unix_nano": 60, "bucket_counts": [0, 0, 1, 0], "explicit_bounds": [0.1, 0.5, 0.9, 1], "sum": 0.8, "aggregation_temporality": 1}}',
+            '{"attributes": {"attr-key": "test-val"}, "description": "test-description", "instrumentation_info": "InstrumentationInfo(name, version, None)", "name": "test-name", "resource": "BoundedAttributes({\'resource-key\': \'resource-val\'}, maxlen=None)", "unit": "test-unit", "point": {"aggregation_temporality": 1, "bucket_counts": [0, 0, 1, 0], "explicit_bounds": [0.1, 0.5, 0.9, 1], "max": 0.8, "min": 0.8, "start_time_unix_nano": 50, "sum": 0.8, "time_unix_nano": 60}}',
             point.to_json(),
         )