Implement LabelSet for metrics

examples/opentelemetry-example-app/src/opentelemetry_example_app/metrics_example.py

@@ -30,17 +30,17 @@
     ("environment",),
 )
 
-label_values = ("staging",)
+label_set = meter.get_label_set({"environment": "staging"})
 
 # Direct metric usage
-counter.add(label_values, 25)
+counter.add(label_set, 25)
 
 # Handle usage
-counter_handle = counter.get_handle(label_values)
+counter_handle = counter.get_handle(label_set)
 counter_handle.add(100)
 
 # Record batch usage
-meter.record_batch(label_values, [(counter, 50)])
+meter.record_batch(label_set, [(counter, 50)])
 print(counter_handle.data)
 
 # TODO: exporters

opentelemetry-api/src/opentelemetry/metrics/__init__.py

@@ -26,7 +26,8 @@
 
 
 """
-from typing import Callable, Optional, Sequence, Tuple, Type, TypeVar
+import abc
+from typing import Callable, Dict, Optional, Sequence, Tuple, Type, TypeVar
 
 from opentelemetry.util import loader
 
@@ -67,14 +68,33 @@ def record(self, value: ValueT) -> None:
         """
 
 
+class LabelSet(abc.ABC):
+    """A canonicalized set of labels useful for preaggregation
+
+    Re-usable LabelSet objects provide a potential optimization for scenarios
+    where handles might not be effective. For example, if the LabelSet will be
+    re-used but only used once per metrics, handles do not offer any
+    optimization. It may best to pre-compute a canonicalized LabelSet once and
+    re-use it with the direct calling convention. LabelSets are immutable and
+    should be opaque in implementation.
+    """
+
+
+class DefaultLabelSet(LabelSet):
+    """The default LabelSet.
+
+    Used when no LabelSet implementation is available.
+    """
+
+
 class Metric:
     """Base class for various types of metrics.
 
     Metric class that inherit from this class are specialized with the type of
     handle that the metric holds.
     """
 
-    def get_handle(self, label_values: Sequence[str]) -> "object":
+    def get_handle(self, label_set: LabelSet) -> "object":
         """Gets a handle, used for repeated-use of metrics instruments.
 
         Handles are useful to reduce the cost of repeatedly recording a metric
@@ -85,34 +105,34 @@ def get_handle(self, label_values: Sequence[str]) -> "object":
         a value was not provided are permitted.
 
         Args:
-            label_values: Values to associate with the returned handle.
+            label_set: `LabelSet` to associate with the returned handle.
         """
 
 
 class DefaultMetric(Metric):
     """The default Metric used when no Metric implementation is available."""
 
-    def get_handle(self, label_values: Sequence[str]) -> "DefaultMetricHandle":
+    def get_handle(self, label_set: LabelSet) -> "DefaultMetricHandle":
         """Gets a `DefaultMetricHandle`.
 
         Args:
-            label_values: The label values associated with the handle.
+            label_set: `LabelSet` to associate with the returned handle.
         """
         return DefaultMetricHandle()
 
 
 class Counter(Metric):
     """A counter type metric that expresses the computation of a sum."""
 
-    def get_handle(self, label_values: Sequence[str]) -> "CounterHandle":
+    def get_handle(self, label_set: LabelSet) -> "CounterHandle":
         """Gets a `CounterHandle`."""
         return CounterHandle()
 
-    def add(self, label_values: Sequence[str], value: ValueT) -> None:
+    def add(self, label_set: LabelSet, value: ValueT) -> None:
         """Increases the value of the counter by ``value``.
 
         Args:
-            label_values: The label values associated with the metric.
+            label_set: `LabelSet` to associate with the returned handle.
             value: The value to add to the counter metric.
         """
 
@@ -126,15 +146,15 @@ class Gauge(Metric):
     the measurement interval is arbitrary.
     """
 
-    def get_handle(self, label_values: Sequence[str]) -> "GaugeHandle":
+    def get_handle(self, label_set: LabelSet) -> "GaugeHandle":
         """Gets a `GaugeHandle`."""
         return GaugeHandle()
 
-    def set(self, label_values: Sequence[str], value: ValueT) -> None:
+    def set(self, label_set: LabelSet, value: ValueT) -> None:
         """Sets the value of the gauge to ``value``.
 
         Args:
-            label_values: The label values associated with the metric.
+            label_set: `LabelSet` to associate with the returned handle.
             value: The value to set the gauge metric to.
         """
 
@@ -147,15 +167,15 @@ class Measure(Metric):
     Negative inputs will be discarded when monotonic is True.
     """
 
-    def get_handle(self, label_values: Sequence[str]) -> "MeasureHandle":
+    def get_handle(self, label_set: LabelSet) -> "MeasureHandle":
         """Gets a `MeasureHandle` with a float value."""
         return MeasureHandle()
 
-    def record(self, label_values: Sequence[str], value: ValueT) -> None:
+    def record(self, label_set: LabelSet, value: ValueT) -> None:
         """Records the ``value`` to the measure.
 
         Args:
-            label_values: The label values associated with the metric.
+            label_set: `LabelSet` to associate with the returned handle.
             value: The value to record to this measure metric.
         """
 
@@ -174,7 +194,7 @@ class Meter:
 
     def record_batch(
         self,
-        label_values: Sequence[str],
+        label_set: LabelSet,
         record_tuples: Sequence[Tuple["Metric", ValueT]],
     ) -> None:
         """Atomically records a batch of `Metric` and value pairs.
@@ -184,7 +204,7 @@ def record_batch(
         match the key-value pairs in the label tuples.
 
         Args:
-            label_values: The label values associated with all measurements in
+            label_set: The `LabelSet` associated with all measurements in
                 the batch. A measurement is a tuple, representing the `Metric`
                 being recorded and the corresponding value to record.
             record_tuples: A sequence of pairs of `Metric` s and the
@@ -211,8 +231,6 @@ def create_metric(
             value_type: The type of values being recorded by the metric.
             metric_type: The type of metric being created.
             label_keys: The keys for the labels with dynamic values.
-                Order of the sequence is important as the same order must be
-                used on recording when suppling values for these labels.
             enabled: Whether to report the metric by default.
             monotonic: Whether to only allow non-negative values.
 
@@ -221,6 +239,17 @@ def create_metric(
         # pylint: disable=no-self-use
         return DefaultMetric()
 
+    def get_label_set(self, labels: Dict[str, str]) -> "LabelSet":
+        """Gets a `LabelSet` with the given labels.
+
+        Args:
+            labels: A dictionary representing label key to label value pairs.
+
+        Returns: A `LabelSet` object canonicalized using the given input.
+        """
+        # pylint: disable=no-self-use
+        return DefaultLabelSet()
+
 
 # Once https://github.com/python/mypy/issues/7092 is resolved,
 # the following type definition should be replaced with

opentelemetry-api/tests/metrics/test_metrics.py

@@ -24,45 +24,57 @@ def setUp(self):
 
     def test_record_batch(self):
         counter = metrics.Counter()
-        self.meter.record_batch(("values"), ((counter, 1),))
+        label_set = metrics.LabelSet()
+        self.meter.record_batch(label_set, ((counter, 1),))
 
     def test_create_metric(self):
         metric = self.meter.create_metric("", "", "", float, metrics.Counter)
         self.assertIsInstance(metric, metrics.DefaultMetric)
 
+    def test_get_label_set(self):
+        metric = self.meter.get_label_set({})
+        self.assertIsInstance(metric, metrics.DefaultLabelSet)
+
 
 class TestMetrics(unittest.TestCase):
     def test_default(self):
         default = metrics.DefaultMetric()
-        handle = default.get_handle(("test", "test1"))
+        default_ls = metrics.DefaultLabelSet()
+        handle = default.get_handle(default_ls)
         self.assertIsInstance(handle, metrics.DefaultMetricHandle)
 
     def test_counter(self):
         counter = metrics.Counter()
-        handle = counter.get_handle(("test", "test1"))
+        label_set = metrics.LabelSet()
+        handle = counter.get_handle(label_set)
         self.assertIsInstance(handle, metrics.CounterHandle)
 
     def test_counter_add(self):
         counter = metrics.Counter()
-        counter.add(("value",), 1)
+        label_set = metrics.LabelSet()
+        counter.add(label_set, 1)
 
     def test_gauge(self):
         gauge = metrics.Gauge()
-        handle = gauge.get_handle(("test", "test1"))
+        label_set = metrics.LabelSet()
+        handle = gauge.get_handle(label_set)
         self.assertIsInstance(handle, metrics.GaugeHandle)
 
     def test_gauge_set(self):
         gauge = metrics.Gauge()
-        gauge.set(("value",), 1)
+        label_set = metrics.LabelSet()
+        gauge.set(label_set, 1)
 
     def test_measure(self):
         measure = metrics.Measure()
-        handle = measure.get_handle(("test", "test1"))
+        label_set = metrics.LabelSet()
+        handle = measure.get_handle(label_set)
         self.assertIsInstance(handle, metrics.MeasureHandle)
 
     def test_measure_record(self):
         measure = metrics.Measure()
-        measure.record(("value",), 1)
+        label_set = metrics.LabelSet()
+        measure.record(label_set, 1)
 
     def test_default_handle(self):
         metrics.DefaultMetricHandle()