opentelemetry-dotnet/test/Benchmarks/Metrics/ExemplarBenchmarks.cs

148 lines
6.0 KiB
C#

// <copyright file="ExemplarBenchmarks.cs" company="OpenTelemetry Authors">
// 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.
// </copyright>
using System.Diagnostics;
using System.Diagnostics.Metrics;
using BenchmarkDotNet.Attributes;
using OpenTelemetry;
using OpenTelemetry.Metrics;
using OpenTelemetry.Tests;
/*
BenchmarkDotNet=v0.13.5, OS=Windows 11 (10.0.23424.1000)
Intel Core i7-9700 CPU 3.00GHz, 1 CPU, 8 logical and 8 physical cores
.NET SDK=7.0.203
[Host] : .NET 7.0.5 (7.0.523.17405), X64 RyuJIT AVX2
DefaultJob : .NET 7.0.5 (7.0.523.17405), X64 RyuJIT AVX2
| Method | ExemplarFilter | Mean | Error | StdDev | Allocated |
|-------------------------- |--------------- |---------:|--------:|--------:|----------:|
| HistogramNoTagReduction | AlwaysOff | 315.5 ns | 5.93 ns | 5.55 ns | - |
| HistogramWithTagReduction | AlwaysOff | 296.4 ns | 0.95 ns | 0.89 ns | - |
| HistogramNoTagReduction | AlwaysOn | 366.5 ns | 6.96 ns | 7.74 ns | - |
| HistogramWithTagReduction | AlwaysOn | 397.1 ns | 4.09 ns | 3.82 ns | - |
| HistogramNoTagReduction | HighValueOnly | 364.8 ns | 2.73 ns | 2.28 ns | - |
| HistogramWithTagReduction | HighValueOnly | 391.9 ns | 4.38 ns | 4.10 ns | - |
*/
namespace Benchmarks.Metrics
{
public class ExemplarBenchmarks
{
private static readonly ThreadLocal<Random> ThreadLocalRandom = new(() => new Random());
private readonly string[] dimensionValues = new string[] { "DimVal1", "DimVal2", "DimVal3", "DimVal4", "DimVal5", "DimVal6", "DimVal7", "DimVal8", "DimVal9", "DimVal10" };
private Histogram<long> histogramWithoutTagReduction;
private Histogram<long> histogramWithTagReduction;
private MeterProvider provider;
private Meter meter;
[System.Diagnostics.CodeAnalysis.SuppressMessage("StyleCop.CSharp.DocumentationRules", "SA1602:Enumeration items should be documented", Justification = "Test only.")]
public enum ExemplarFilterTouse
{
AlwaysOff,
AlwaysOn,
HighValueOnly,
}
[Params(ExemplarFilterTouse.AlwaysOn, ExemplarFilterTouse.AlwaysOff, ExemplarFilterTouse.HighValueOnly)]
public ExemplarFilterTouse ExemplarFilter { get; set; }
[GlobalSetup]
public void Setup()
{
this.meter = new Meter(Utils.GetCurrentMethodName());
this.histogramWithoutTagReduction = this.meter.CreateHistogram<long>("HistogramWithoutTagReduction");
this.histogramWithTagReduction = this.meter.CreateHistogram<long>("HistogramWithTagReduction");
var exportedItems = new List<Metric>();
ExemplarFilter exemplarFilter = new AlwaysOffExemplarFilter();
if (this.ExemplarFilter == ExemplarFilterTouse.AlwaysOn)
{
exemplarFilter = new AlwaysOnExemplarFilter();
}
else if (this.ExemplarFilter == ExemplarFilterTouse.HighValueOnly)
{
exemplarFilter = new HighValueExemplarFilter();
}
this.provider = Sdk.CreateMeterProviderBuilder()
.AddMeter(this.meter.Name)
.SetExemplarFilter(exemplarFilter)
.AddView("HistogramWithTagReduction", new MetricStreamConfiguration() { TagKeys = new string[] { "DimName1", "DimName2", "DimName3" } })
.AddInMemoryExporter(exportedItems, metricReaderOptions =>
{
metricReaderOptions.PeriodicExportingMetricReaderOptions.ExportIntervalMilliseconds = 1000;
})
.Build();
}
[GlobalCleanup]
public void Cleanup()
{
this.meter?.Dispose();
this.provider?.Dispose();
}
[Benchmark]
public void HistogramNoTagReduction()
{
var random = ThreadLocalRandom.Value;
var tags = new TagList
{
{ "DimName1", this.dimensionValues[random.Next(0, 2)] },
{ "DimName2", this.dimensionValues[random.Next(0, 2)] },
{ "DimName3", this.dimensionValues[random.Next(0, 5)] },
{ "DimName4", this.dimensionValues[random.Next(0, 5)] },
{ "DimName5", this.dimensionValues[random.Next(0, 10)] },
};
this.histogramWithoutTagReduction.Record(random.Next(1000), tags);
}
[Benchmark]
public void HistogramWithTagReduction()
{
var random = ThreadLocalRandom.Value;
var tags = new TagList
{
{ "DimName1", this.dimensionValues[random.Next(0, 2)] },
{ "DimName2", this.dimensionValues[random.Next(0, 2)] },
{ "DimName3", this.dimensionValues[random.Next(0, 5)] },
{ "DimName4", this.dimensionValues[random.Next(0, 5)] },
{ "DimName5", this.dimensionValues[random.Next(0, 10)] },
};
this.histogramWithTagReduction.Record(random.Next(1000), tags);
}
public class HighValueExemplarFilter : ExemplarFilter
{
public override bool ShouldSample(long value, ReadOnlySpan<KeyValuePair<string, object>> tags)
{
return value > 800;
}
public override bool ShouldSample(double value, ReadOnlySpan<KeyValuePair<string, object>> tags)
{
return value > 800;
}
}
}
}