# 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.
from abc import ABC, abstractmethod
from typing import Union
from opentelemetry import trace
from opentelemetry.context import Context
from opentelemetry.trace.span import INVALID_SPAN
from opentelemetry.util.types import Attributes
[docs]
class ExemplarFilter(ABC):
"""``ExemplarFilter`` determines which measurements are eligible for becoming an
``Exemplar``.
Exemplar filters are used to filter measurements before attempting to store them
in a reservoir.
Reference:
https://github.com/open-telemetry/opentelemetry-specification/blob/main/specification/metrics/sdk.md#exemplarfilter
"""
[docs]
@abstractmethod
def should_sample(
self,
value: Union[int, float],
time_unix_nano: int,
attributes: Attributes,
context: Context,
) -> bool:
"""Returns whether or not a reservoir should attempt to filter a measurement.
Args:
value: The value of the measurement
timestamp: A timestamp that best represents when the measurement was taken
attributes: The complete set of measurement attributes
context: The Context of the measurement
"""
raise NotImplementedError(
"ExemplarFilter.should_sample is not implemented"
)
[docs]
class AlwaysOnExemplarFilter(ExemplarFilter):
"""An ExemplarFilter which makes all measurements eligible for being an Exemplar.
Reference:
https://github.com/open-telemetry/opentelemetry-specification/blob/main/specification/metrics/sdk.md#alwayson
"""
[docs]
def should_sample(
self,
value: Union[int, float],
time_unix_nano: int,
attributes: Attributes,
context: Context,
) -> bool:
"""Returns whether or not a reservoir should attempt to filter a measurement.
Args:
value: The value of the measurement
timestamp: A timestamp that best represents when the measurement was taken
attributes: The complete set of measurement attributes
context: The Context of the measurement
"""
return True
[docs]
class AlwaysOffExemplarFilter(ExemplarFilter):
"""An ExemplarFilter which makes no measurements eligible for being an Exemplar.
Using this ExemplarFilter is as good as disabling Exemplar feature.
Reference:
https://github.com/open-telemetry/opentelemetry-specification/blob/main/specification/metrics/sdk.md#alwaysoff
"""
[docs]
def should_sample(
self,
value: Union[int, float],
time_unix_nano: int,
attributes: Attributes,
context: Context,
) -> bool:
"""Returns whether or not a reservoir should attempt to filter a measurement.
Args:
value: The value of the measurement
timestamp: A timestamp that best represents when the measurement was taken
attributes: The complete set of measurement attributes
context: The Context of the measurement
"""
return False
[docs]
class TraceBasedExemplarFilter(ExemplarFilter):
"""An ExemplarFilter which makes those measurements eligible for being an Exemplar,
which are recorded in the context of a sampled parent span.
Reference:
https://github.com/open-telemetry/opentelemetry-specification/blob/main/specification/metrics/sdk.md#tracebased
"""
[docs]
def should_sample(
self,
value: Union[int, float],
time_unix_nano: int,
attributes: Attributes,
context: Context,
) -> bool:
"""Returns whether or not a reservoir should attempt to filter a measurement.
Args:
value: The value of the measurement
timestamp: A timestamp that best represents when the measurement was taken
attributes: The complete set of measurement attributes
context: The Context of the measurement
"""
span = trace.get_current_span(context)
if span == INVALID_SPAN:
return False
return span.get_span_context().trace_flags.sampled