From 66ae24e70acc92aac8412cd81c61f836eac442b4 Mon Sep 17 00:00:00 2001
From: Riccardo Magliocchetti <riccardo.magliocchetti@gmail.com>
Date: Fri, 8 Nov 2024 17:08:47 +0100
Subject: [PATCH] opentelemetry-sdk: speed up exemplars a bit

Use a sparse dict to allocate ExemplarsBucket on demand instead of
preallocating all of them in FixedSizeExemplarReservoirABC.

Make the following return around 2X more loops for both trace_based and
always_off exemplars filter:

.tox/benchmark-opentelemetry-sdk/bin/pytest opentelemetry-sdk/benchmarks/metrics/ -k 'test_histogram_record_1000[7]'
---
 .../_internal/exemplar/exemplar_reservoir.py  | 35 ++++++++++++-------
 1 file changed, 23 insertions(+), 12 deletions(-)

diff --git a/opentelemetry-sdk/src/opentelemetry/sdk/metrics/_internal/exemplar/exemplar_reservoir.py b/opentelemetry-sdk/src/opentelemetry/sdk/metrics/_internal/exemplar/exemplar_reservoir.py
index c8fa7f1453..22d1ee9f75 100644
--- a/opentelemetry-sdk/src/opentelemetry/sdk/metrics/_internal/exemplar/exemplar_reservoir.py
+++ b/opentelemetry-sdk/src/opentelemetry/sdk/metrics/_internal/exemplar/exemplar_reservoir.py
@@ -13,8 +13,18 @@
 # limitations under the License.
 
 from abc import ABC, abstractmethod
+from collections import defaultdict
 from random import randrange
-from typing import Any, Callable, Dict, List, Optional, Sequence, Union
+from typing import (
+    Any,
+    Callable,
+    Dict,
+    List,
+    Mapping,
+    Optional,
+    Sequence,
+    Union,
+)
 
 from opentelemetry import trace
 from opentelemetry.context import Context
@@ -155,9 +165,9 @@ class FixedSizeExemplarReservoirABC(ExemplarReservoir):
     def __init__(self, size: int, **kwargs) -> None:
         super().__init__(**kwargs)
         self._size: int = size
-        self._reservoir_storage: List[ExemplarBucket] = [
-            ExemplarBucket() for _ in range(self._size)
-        ]
+        self._reservoir_storage: Mapping[int, ExemplarBucket] = defaultdict(
+            ExemplarBucket
+        )
 
     def collect(self, point_attributes: Attributes) -> List[Exemplar]:
         """Returns accumulated Exemplars and also resets the reservoir for the next
@@ -171,15 +181,16 @@ def collect(self, point_attributes: Attributes) -> List[Exemplar]:
             exemplars contain the attributes that were filtered out by the aggregator,
             but recorded alongside the original measurement.
         """
-        exemplars = filter(
-            lambda e: e is not None,
-            map(
-                lambda bucket: bucket.collect(point_attributes),
-                self._reservoir_storage,
-            ),
-        )
+        exemplars = [
+            e
+            for e in (
+                bucket.collect(point_attributes)
+                for _, bucket in sorted(self._reservoir_storage.items())
+            )
+            if e is not None
+        ]
         self._reset()
-        return [*exemplars]
+        return exemplars
 
     def offer(
         self,