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Fix: filter exemplar for observable instrument and export of exemplar without trace and span ids #4251

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merged 15 commits into from
Nov 8, 2024
Merged

Fix: filter exemplar for observable instrument and export of exemplar without trace and span ids #4251

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80bd271
Deal with missing span and trace ids
fcollonval Oct 15, 2024
72519a1
Fix applying exemplar filter to observable instruments
fcollonval Nov 6, 2024
7c58545
Lint the code
fcollonval Nov 6, 2024
6ed6192
add tests
xrmx Nov 6, 2024
0e6d185
Add entry in changelog
fcollonval Nov 6, 2024
48d786e
Fix span and trace id typing
fcollonval Oct 15, 2024
45d7a71
Fix CI
fcollonval Nov 6, 2024
298cc1e
Test consume_measurement is called for async instrument
fcollonval Nov 6, 2024
02bdfa8
Merge branch 'main' into fix/exemplar-sampling-export
emdneto Nov 6, 2024
dd8b269
Add integration tests
xrmx Nov 7, 2024
aadd4be
fix integration tests
emdneto Nov 8, 2024
2ce2d28
Merge branch 'main' into fix/exemplar-sampling-export
emdneto Nov 8, 2024
575cd2d
Update opentelemetry-sdk/tests/metrics/integration_test/test_exemplar…
xrmx Nov 8, 2024
882fd2c
Merge branch 'main' into fix/exemplar-sampling-export
emdneto Nov 8, 2024
d5069e8
add test that default exemplar filter with no span does not create ex…
aabmass Nov 8, 2024
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3 changes: 3 additions & 0 deletions CHANGELOG.md
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Original file line number Diff line number Diff line change
Expand Up @@ -7,6 +7,9 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0

## Unreleased

- Fix metrics export with exemplar and no context and filtering observable instruments
([#4251](https://github.com/open-telemetry/opentelemetry-python/pull/4251))

## Version 1.28.0/0.49b0 (2024-11-05)

- Removed superfluous py.typed markers and added them where they were missing
Expand Down
33 changes: 23 additions & 10 deletions ...common/src/opentelemetry/exporter/otlp/proto/common/_internal/metrics_encoder/__init__.py
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Expand Up @@ -13,7 +13,7 @@
# limitations under the License.
import logging
from os import environ
from typing import Dict
from typing import Dict, List

from opentelemetry.exporter.otlp.proto.common._internal import (
_encode_attributes,
Expand All @@ -34,6 +34,7 @@
)
from opentelemetry.sdk.metrics import (
Counter,
Exemplar,
Histogram,
ObservableCounter,
ObservableGauge,
Expand Down Expand Up @@ -341,7 +342,7 @@ def _encode_metric(metric, pb2_metric):
)


def _encode_exemplars(sdk_exemplars: list) -> list:
def _encode_exemplars(sdk_exemplars: List[Exemplar]) -> List[pb2.Exemplar]:
"""
Converts a list of SDK Exemplars into a list of protobuf Exemplars.

Expand All @@ -353,14 +354,26 @@ def _encode_exemplars(sdk_exemplars: list) -> list:
"""
pb_exemplars = []
for sdk_exemplar in sdk_exemplars:
pb_exemplar = pb2.Exemplar(
time_unix_nano=sdk_exemplar.time_unix_nano,
span_id=_encode_span_id(sdk_exemplar.span_id),
trace_id=_encode_trace_id(sdk_exemplar.trace_id),
filtered_attributes=_encode_attributes(
sdk_exemplar.filtered_attributes
),
)
if (
sdk_exemplar.span_id is not None
and sdk_exemplar.trace_id is not None
):
pb_exemplar = pb2.Exemplar(
time_unix_nano=sdk_exemplar.time_unix_nano,
span_id=_encode_span_id(sdk_exemplar.span_id),
trace_id=_encode_trace_id(sdk_exemplar.trace_id),
filtered_attributes=_encode_attributes(
sdk_exemplar.filtered_attributes
),
)
else:
pb_exemplar = pb2.Exemplar(
time_unix_nano=sdk_exemplar.time_unix_nano,
filtered_attributes=_encode_attributes(
sdk_exemplar.filtered_attributes
),
)

# Assign the value based on its type in the SDK exemplar
if isinstance(sdk_exemplar.value, float):
pb_exemplar.as_double = sdk_exemplar.value
Expand Down
167 changes: 161 additions & 6 deletions exporter/opentelemetry-exporter-otlp-proto-common/tests/test_metrics_encoder.py
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Expand Up @@ -12,7 +12,7 @@
# See the License for the specific language governing permissions and
# limitations under the License.

# pylint: disable=protected-access
# pylint: disable=protected-access,too-many-lines
import unittest

from opentelemetry.exporter.otlp.proto.common._internal.metrics_encoder import (
Expand All @@ -33,6 +33,7 @@
from opentelemetry.proto.resource.v1.resource_pb2 import (
Resource as OTLPResource,
)
from opentelemetry.sdk.metrics import Exemplar
from opentelemetry.sdk.metrics.export import (
AggregationTemporality,
Buckets,
Expand All @@ -55,6 +56,9 @@


class TestOTLPMetricsEncoder(unittest.TestCase):
span_id = int("6e0c63257de34c92", 16)
trace_id = int("d4cda95b652f4a1592b449d5929fda1b", 16)

histogram = Metric(
name="histogram",
description="foo",
Expand All @@ -65,6 +69,22 @@ class TestOTLPMetricsEncoder(unittest.TestCase):
attributes={"a": 1, "b": True},
start_time_unix_nano=1641946016139533244,
time_unix_nano=1641946016139533244,
exemplars=[
Exemplar(
{"filtered": "banana"},
298.0,
1641946016139533400,
span_id,
trace_id,
),
Exemplar(
{"filtered": "banana"},
298.0,
1641946016139533400,
None,
None,
),
],
count=5,
sum=67,
bucket_counts=[1, 4],
Expand Down Expand Up @@ -460,7 +480,34 @@ def test_encode_histogram(self):
sum=67,
bucket_counts=[1, 4],
explicit_bounds=[10.0, 20.0],
exemplars=[],
exemplars=[
pb2.Exemplar(
time_unix_nano=1641946016139533400,
as_double=298,
span_id=b"n\x0cc%}\xe3L\x92",
trace_id=b"\xd4\xcd\xa9[e/J\x15\x92\xb4I\xd5\x92\x9f\xda\x1b",
filtered_attributes=[
KeyValue(
key="filtered",
value=AnyValue(
string_value="banana"
),
)
],
),
pb2.Exemplar(
time_unix_nano=1641946016139533400,
as_double=298,
filtered_attributes=[
KeyValue(
key="filtered",
value=AnyValue(
string_value="banana"
),
)
],
),
],
max=18.0,
min=8.0,
)
Expand Down Expand Up @@ -563,7 +610,34 @@ def test_encode_multiple_scope_histogram(self):
sum=67,
bucket_counts=[1, 4],
explicit_bounds=[10.0, 20.0],
exemplars=[],
exemplars=[
pb2.Exemplar(
time_unix_nano=1641946016139533400,
as_double=298,
span_id=b"n\x0cc%}\xe3L\x92",
trace_id=b"\xd4\xcd\xa9[e/J\x15\x92\xb4I\xd5\x92\x9f\xda\x1b",
filtered_attributes=[
KeyValue(
key="filtered",
value=AnyValue(
string_value="banana"
),
)
],
),
pb2.Exemplar(
time_unix_nano=1641946016139533400,
as_double=298,
filtered_attributes=[
KeyValue(
key="filtered",
value=AnyValue(
string_value="banana"
),
)
],
),
],
max=18.0,
min=8.0,
)
Expand Down Expand Up @@ -598,7 +672,34 @@ def test_encode_multiple_scope_histogram(self):
sum=67,
bucket_counts=[1, 4],
explicit_bounds=[10.0, 20.0],
exemplars=[],
exemplars=[
pb2.Exemplar(
time_unix_nano=1641946016139533400,
as_double=298,
span_id=b"n\x0cc%}\xe3L\x92",
trace_id=b"\xd4\xcd\xa9[e/J\x15\x92\xb4I\xd5\x92\x9f\xda\x1b",
filtered_attributes=[
KeyValue(
key="filtered",
value=AnyValue(
string_value="banana"
),
)
],
),
pb2.Exemplar(
time_unix_nano=1641946016139533400,
as_double=298,
filtered_attributes=[
KeyValue(
key="filtered",
value=AnyValue(
string_value="banana"
),
)
],
),
],
max=18.0,
min=8.0,
)
Expand Down Expand Up @@ -640,7 +741,34 @@ def test_encode_multiple_scope_histogram(self):
sum=67,
bucket_counts=[1, 4],
explicit_bounds=[10.0, 20.0],
exemplars=[],
exemplars=[
pb2.Exemplar(
time_unix_nano=1641946016139533400,
as_double=298,
span_id=b"n\x0cc%}\xe3L\x92",
trace_id=b"\xd4\xcd\xa9[e/J\x15\x92\xb4I\xd5\x92\x9f\xda\x1b",
filtered_attributes=[
KeyValue(
key="filtered",
value=AnyValue(
string_value="banana"
),
)
],
),
pb2.Exemplar(
time_unix_nano=1641946016139533400,
as_double=298,
filtered_attributes=[
KeyValue(
key="filtered",
value=AnyValue(
string_value="banana"
),
)
],
),
],
max=18.0,
min=8.0,
)
Expand Down Expand Up @@ -682,7 +810,34 @@ def test_encode_multiple_scope_histogram(self):
sum=67,
bucket_counts=[1, 4],
explicit_bounds=[10.0, 20.0],
exemplars=[],
exemplars=[
pb2.Exemplar(
time_unix_nano=1641946016139533400,
as_double=298,
span_id=b"n\x0cc%}\xe3L\x92",
trace_id=b"\xd4\xcd\xa9[e/J\x15\x92\xb4I\xd5\x92\x9f\xda\x1b",
filtered_attributes=[
KeyValue(
key="filtered",
value=AnyValue(
string_value="banana"
),
)
],
),
pb2.Exemplar(
time_unix_nano=1641946016139533400,
as_double=298,
filtered_attributes=[
KeyValue(
key="filtered",
value=AnyValue(
string_value="banana"
),
)
],
),
],
max=18.0,
min=8.0,
)
Expand Down
4 changes: 2 additions & 2 deletions opentelemetry-sdk/src/opentelemetry/sdk/metrics/_internal/exemplar/exemplar.py
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Expand Up @@ -46,5 +46,5 @@ class Exemplar:
filtered_attributes: Attributes
value: Union[int, float]
time_unix_nano: int
span_id: Optional[str] = None
trace_id: Optional[str] = None
span_id: Optional[int] = None
trace_id: Optional[int] = None
4 changes: 2 additions & 2 deletions opentelemetry-sdk/src/opentelemetry/sdk/metrics/_internal/exemplar/exemplar_reservoir.py
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Expand Up @@ -77,8 +77,8 @@ def __init__(self) -> None:
self.__value: Union[int, float] = 0
self.__attributes: Attributes = None
self.__time_unix_nano: int = 0
self.__span_id: Optional[str] = None
self.__trace_id: Optional[str] = None
self.__span_id: Optional[int] = None
self.__trace_id: Optional[int] = None
self.__offered: bool = False

def offer(
Expand Down
28 changes: 20 additions & 8 deletions opentelemetry-sdk/src/opentelemetry/sdk/metrics/_internal/measurement_consumer.py
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Expand Up @@ -78,15 +78,17 @@ def __init__(
] = []

def consume_measurement(self, measurement: Measurement) -> None:
should_sample_exemplar = (
self._sdk_config.exemplar_filter.should_sample(
measurement.value,
measurement.time_unix_nano,
measurement.attributes,
measurement.context,
)
)
for reader_storage in self._reader_storages.values():
reader_storage.consume_measurement(
measurement,
self._sdk_config.exemplar_filter.should_sample(
measurement.value,
measurement.time_unix_nano,
measurement.attributes,
measurement.context,
),
measurement, should_sample_exemplar
)

def register_asynchronous_instrument(
Expand Down Expand Up @@ -126,7 +128,17 @@ def collect(
)

for measurement in measurements:
metric_reader_storage.consume_measurement(measurement)
should_sample_exemplar = (
self._sdk_config.exemplar_filter.should_sample(
measurement.value,
measurement.time_unix_nano,
measurement.attributes,
measurement.context,
)
)
metric_reader_storage.consume_measurement(
measurement, should_sample_exemplar
)

result = self._reader_storages[metric_reader].collect()

Expand Down
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