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[APMSP-1013] Add stats exporter

Open VianneyRuhlmann opened this issue 1 year ago • 3 comments
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What does this PR do?

A brief description of the change being made with this pull request.

Motivation

What inspired you to submit this pull request?

Additional Notes

Anything else we should know when reviewing?

How to test the change?

Describe here in detail how the change can be validated.

VianneyRuhlmann avatar Aug 09 '24 13:08 VianneyRuhlmann

Codecov Report

Attention: Patch coverage is 90.59561% with 60 lines in your changes missing coverage. Please review.

Project coverage is 73.58%. Comparing base (4c7552b) to head (3475380).

Additional details and impacted files
@@            Coverage Diff             @@
##             main     #584      +/-   ##
==========================================
+ Coverage   73.19%   73.58%   +0.39%     
==========================================
  Files         254      255       +1     
  Lines       36312    36941     +629     
==========================================
+ Hits        26578    27183     +605     
- Misses       9734     9758      +24     
Components Coverage Δ
crashtracker 20.53% <ø> (ø)
datadog-alloc 98.73% <ø> (ø)
data-pipeline 91.65% <90.30%> (+1.48%) :arrow_up:
data-pipeline-ffi 0.00% <0.00%> (ø)
ddcommon 83.08% <ø> (ø)
ddcommon-ffi 69.52% <ø> (ø)
ddtelemetry 59.10% <ø> (ø)
ipc 83.58% <ø> (ø)
profiling 84.26% <ø> (ø)
profiling-ffi 77.42% <ø> (ø)
serverless 0.00% <ø> (ø)
sidecar 40.10% <ø> (ø)
sidecar-ffi 0.00% <ø> (ø)
spawn-worker 50.36% <ø> (ø)
tinybytes 94.77% <ø> (ø)
trace-mini-agent 72.47% <ø> (ø)
trace-normalization 98.25% <ø> (ø)
trace-obfuscation 95.73% <ø> (ø)
trace-protobuf 77.67% <ø> (ø)
trace-utils 93.41% <100.00%> (-0.13%) :arrow_down:

codecov-commenter avatar Aug 09 '24 13:08 codecov-commenter

Benchmarks

Comparison

Benchmark execution time: 2024-09-20 08:13:26

Comparing candidate commit 3475380 in PR branch vianney/data-pipeline/APMSP-1013-stats-can-be-computed-from-the-spans-payload with baseline commit 4c7552b in branch main.

Found 1 performance improvements and 2 performance regressions! Performance is the same for 48 metrics, 2 unstable metrics.

scenario:benching deserializing traces from msgpack to their internal representation

  • 🟩 execution_time [-53.528ns; -44.490ns] or [-4.297%; -3.571%]

scenario:normalization/normalize_name/normalize_name/good

  • 🟥 execution_time [+394.903ns; +418.112ns] or [+2.447%; +2.591%]
  • 🟥 throughput [-1567057.934op/s; -1479256.143op/s] or [-2.529%; -2.387%]

Candidate

Candidate benchmark details

Group 1

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz 3475380 1726819201 vianney/data-pipeline/APMSP-1013-stats-can-be-computed-from-the-spans-payload
scenario metric min mean ± sd median ± mad p75 p95 p99 max peak_to_median_ratio skewness kurtosis cv sem runs sample_size
credit_card/is_card_number/ execution_time 2.415µs 2.416µs ± 0.001µs 2.416µs ± 0.001µs 2.417µs 2.418µs 2.419µs 2.420µs 0.15% 0.949 0.712 0.04% 0.000µs 1 200
credit_card/is_card_number/ throughput 413226110.858op/s 413825096.256op/s ± 160692.978op/s 413865794.021op/s ± 111920.874op/s 413956287.707op/s 414011205.480op/s 414036841.247op/s 414083231.830op/s 0.05% -0.947 0.705 0.04% 11362.709op/s 1 200
credit_card/is_card_number/ 3782-8224-6310-005 execution_time 111.526µs 115.434µs ± 1.302µs 115.610µs ± 0.887µs 116.421µs 117.281µs 117.476µs 118.980µs 2.91% -0.468 -0.012 1.13% 0.092µs 1 200
credit_card/is_card_number/ 3782-8224-6310-005 throughput 8404802.330op/s 8664062.053op/s ± 98278.412op/s 8649795.806op/s ± 66334.279op/s 8726519.700op/s 8821113.363op/s 8925734.573op/s 8966507.004op/s 3.66% 0.528 0.068 1.13% 6949.333op/s 1 200
credit_card/is_card_number/ 378282246310005 execution_time 104.479µs 107.225µs ± 1.357µs 107.177µs ± 0.937µs 108.113µs 109.517µs 110.258µs 110.365µs 2.97% 0.147 -0.557 1.26% 0.096µs 1 200
credit_card/is_card_number/ 378282246310005 throughput 9060860.337op/s 9327688.817op/s ± 117847.134op/s 9330334.375op/s ± 81418.314op/s 9413327.187op/s 9521538.230op/s 9558492.687op/s 9571316.186op/s 2.58% -0.093 -0.576 1.26% 8333.051op/s 1 200
credit_card/is_card_number/37828224631 execution_time 2.415µs 2.417µs ± 0.002µs 2.416µs ± 0.001µs 2.417µs 2.418µs 2.424µs 2.433µs 0.69% 6.251 55.907 0.07% 0.000µs 1 200
credit_card/is_card_number/37828224631 throughput 410996637.553op/s 413799955.140op/s ± 275791.244op/s 413825511.409op/s ± 120622.888op/s 413954724.815op/s 414016382.078op/s 414040319.921op/s 414044501.531op/s 0.05% -6.214 55.371 0.07% 19501.386op/s 1 200
credit_card/is_card_number/378282246310005 execution_time 100.775µs 105.851µs ± 1.603µs 106.205µs ± 0.917µs 107.054µs 107.720µs 108.045µs 108.239µs 1.92% -0.968 0.336 1.51% 0.113µs 1 200
credit_card/is_card_number/378282246310005 throughput 9238786.253op/s 9449451.459op/s ± 145298.242op/s 9415782.927op/s ± 80616.298op/s 9522983.721op/s 9772232.715op/s 9832194.366op/s 9923079.422op/s 5.39% 1.033 0.494 1.53% 10274.137op/s 1 200
credit_card/is_card_number/37828224631000521389798 execution_time 104.670µs 106.570µs ± 0.382µs 106.600µs ± 0.217µs 106.819µs 107.080µs 107.281µs 107.464µs 0.81% -1.013 2.764 0.36% 0.027µs 1 200
credit_card/is_card_number/37828224631000521389798 throughput 9305475.906op/s 9383617.797op/s ± 33766.564op/s 9380848.997op/s ± 19116.604op/s 9398502.203op/s 9448621.235op/s 9470090.588op/s 9553800.909op/s 1.84% 1.054 2.936 0.36% 2387.657op/s 1 200
credit_card/is_card_number/x371413321323331 execution_time 21.801µs 22.429µs ± 0.365µs 22.390µs ± 0.268µs 22.660µs 23.108µs 23.256µs 23.429µs 4.64% 0.424 -0.510 1.62% 0.026µs 1 200
credit_card/is_card_number/x371413321323331 throughput 42681386.657op/s 44596571.254op/s ± 721208.985op/s 44663634.261op/s ± 537975.472op/s 45201589.953op/s 45678497.770op/s 45816047.583op/s 45868722.254op/s 2.70% -0.361 -0.587 1.61% 50997.176op/s 1 200
credit_card/is_card_number_no_luhn/ execution_time 2.415µs 2.416µs ± 0.001µs 2.416µs ± 0.001µs 2.417µs 2.418µs 2.419µs 2.420µs 0.14% 0.995 0.679 0.04% 0.000µs 1 200
credit_card/is_card_number_no_luhn/ throughput 413295596.520op/s 413832669.158op/s ± 154553.581op/s 413864014.542op/s ± 102240.757op/s 413959899.998op/s 414005335.377op/s 414065642.821op/s 414075858.017op/s 0.05% -0.993 0.673 0.04% 10928.589op/s 1 200
credit_card/is_card_number_no_luhn/ 3782-8224-6310-005 execution_time 86.952µs 87.318µs ± 0.284µs 87.277µs ± 0.083µs 87.350µs 87.711µs 88.910µs 89.125µs 2.12% 3.917 19.280 0.32% 0.020µs 1 200
credit_card/is_card_number_no_luhn/ 3782-8224-6310-005 throughput 11220231.385op/s 11452538.082op/s ± 36795.634op/s 11457802.062op/s ± 10891.792op/s 11470051.696op/s 11485491.419op/s 11498619.661op/s 11500660.138op/s 0.37% -3.860 18.825 0.32% 2601.844op/s 1 200
credit_card/is_card_number_no_luhn/ 378282246310005 execution_time 79.655µs 80.269µs ± 0.600µs 80.092µs ± 0.271µs 80.444µs 81.417µs 82.447µs 83.105µs 3.76% 2.141 5.539 0.75% 0.042µs 1 200
credit_card/is_card_number_no_luhn/ 378282246310005 throughput 12032978.447op/s 12458819.826op/s ± 91687.980op/s 12485622.805op/s ± 42273.877op/s 12522188.074op/s 12544908.389op/s 12553816.668op/s 12554209.075op/s 0.55% -2.077 5.199 0.73% 6483.319op/s 1 200
credit_card/is_card_number_no_luhn/37828224631 execution_time 2.415µs 2.417µs ± 0.001µs 2.416µs ± 0.001µs 2.417µs 2.419µs 2.422µs 2.426µs 0.39% 2.876 11.688 0.06% 0.000µs 1 200
credit_card/is_card_number_no_luhn/37828224631 throughput 412251694.052op/s 413794652.150op/s ± 243004.992op/s 413855551.914op/s ± 106183.619op/s 413940203.944op/s 414021560.870op/s 414058519.822op/s 414104360.502op/s 0.06% -2.867 11.613 0.06% 17183.048op/s 1 200
credit_card/is_card_number_no_luhn/378282246310005 execution_time 76.684µs 77.050µs ± 0.411µs 76.942µs ± 0.120µs 77.098µs 77.667µs 78.979µs 79.089µs 2.79% 3.435 12.516 0.53% 0.029µs 1 200
credit_card/is_card_number_no_luhn/378282246310005 throughput 12644011.645op/s 12979008.915op/s ± 68078.212op/s 12996871.003op/s ± 20324.811op/s 13013387.848op/s 13026762.704op/s 13032291.438op/s 13040507.729op/s 0.34% -3.391 12.243 0.52% 4813.857op/s 1 200
credit_card/is_card_number_no_luhn/37828224631000521389798 execution_time 105.420µs 106.609µs ± 0.436µs 106.647µs ± 0.302µs 106.924µs 107.235µs 107.568µs 107.759µs 1.04% -0.232 0.005 0.41% 0.031µs 1 200
credit_card/is_card_number_no_luhn/37828224631000521389798 throughput 9279969.167op/s 9380197.287op/s ± 38419.604op/s 9376760.226op/s ± 26564.169op/s 9406400.883op/s 9437873.763op/s 9482877.336op/s 9485869.889op/s 1.16% 0.256 0.023 0.41% 2716.676op/s 1 200
credit_card/is_card_number_no_luhn/x371413321323331 execution_time 21.696µs 22.592µs ± 0.430µs 22.564µs ± 0.288µs 22.869µs 23.354µs 23.584µs 23.730µs 5.17% 0.225 -0.282 1.90% 0.030µs 1 200
credit_card/is_card_number_no_luhn/x371413321323331 throughput 42140958.309op/s 44279788.663op/s ± 839324.608op/s 44319311.361op/s ± 563889.398op/s 44833197.305op/s 45712186.766op/s 45873378.895op/s 46091757.988op/s 4.00% -0.131 -0.345 1.89% 59349.212op/s 1 200
scenario metric 95% CI mean Shapiro-Wilk pvalue Ljung-Box pvalue (lag=1) Dip test pvalue
credit_card/is_card_number/ execution_time [2.416µs; 2.417µs] or [-0.005%; +0.005%] None None None
credit_card/is_card_number/ throughput [413802825.755op/s; 413847366.758op/s] or [-0.005%; +0.005%] None None None
credit_card/is_card_number/ 3782-8224-6310-005 execution_time [115.254µs; 115.614µs] or [-0.156%; +0.156%] None None None
credit_card/is_card_number/ 3782-8224-6310-005 throughput [8650441.610op/s; 8677682.496op/s] or [-0.157%; +0.157%] None None None
credit_card/is_card_number/ 378282246310005 execution_time [107.037µs; 107.413µs] or [-0.175%; +0.175%] None None None
credit_card/is_card_number/ 378282246310005 throughput [9311356.337op/s; 9344021.296op/s] or [-0.175%; +0.175%] None None None
credit_card/is_card_number/37828224631 execution_time [2.416µs; 2.417µs] or [-0.009%; +0.009%] None None None
credit_card/is_card_number/37828224631 throughput [413761733.126op/s; 413838177.154op/s] or [-0.009%; +0.009%] None None None
credit_card/is_card_number/378282246310005 execution_time [105.629µs; 106.073µs] or [-0.210%; +0.210%] None None None
credit_card/is_card_number/378282246310005 throughput [9429314.520op/s; 9469588.398op/s] or [-0.213%; +0.213%] None None None
credit_card/is_card_number/37828224631000521389798 execution_time [106.517µs; 106.623µs] or [-0.050%; +0.050%] None None None
credit_card/is_card_number/37828224631000521389798 throughput [9378938.076op/s; 9388297.518op/s] or [-0.050%; +0.050%] None None None
credit_card/is_card_number/x371413321323331 execution_time [22.379µs; 22.480µs] or [-0.226%; +0.226%] None None None
credit_card/is_card_number/x371413321323331 throughput [44496618.625op/s; 44696523.883op/s] or [-0.224%; +0.224%] None None None
credit_card/is_card_number_no_luhn/ execution_time [2.416µs; 2.417µs] or [-0.005%; +0.005%] None None None
credit_card/is_card_number_no_luhn/ throughput [413811249.518op/s; 413854088.798op/s] or [-0.005%; +0.005%] None None None
credit_card/is_card_number_no_luhn/ 3782-8224-6310-005 execution_time [87.278µs; 87.357µs] or [-0.045%; +0.045%] None None None
credit_card/is_card_number_no_luhn/ 3782-8224-6310-005 throughput [11447438.561op/s; 11457637.603op/s] or [-0.045%; +0.045%] None None None
credit_card/is_card_number_no_luhn/ 378282246310005 execution_time [80.186µs; 80.352µs] or [-0.104%; +0.104%] None None None
credit_card/is_card_number_no_luhn/ 378282246310005 throughput [12446112.754op/s; 12471526.899op/s] or [-0.102%; +0.102%] None None None
credit_card/is_card_number_no_luhn/37828224631 execution_time [2.416µs; 2.417µs] or [-0.008%; +0.008%] None None None
credit_card/is_card_number_no_luhn/37828224631 throughput [413760973.995op/s; 413828330.305op/s] or [-0.008%; +0.008%] None None None
credit_card/is_card_number_no_luhn/378282246310005 execution_time [76.993µs; 77.107µs] or [-0.074%; +0.074%] None None None
credit_card/is_card_number_no_luhn/378282246310005 throughput [12969573.929op/s; 12988443.900op/s] or [-0.073%; +0.073%] None None None
credit_card/is_card_number_no_luhn/37828224631000521389798 execution_time [106.549µs; 106.670µs] or [-0.057%; +0.057%] None None None
credit_card/is_card_number_no_luhn/37828224631000521389798 throughput [9374872.699op/s; 9385521.875op/s] or [-0.057%; +0.057%] None None None
credit_card/is_card_number_no_luhn/x371413321323331 execution_time [22.532µs; 22.651µs] or [-0.264%; +0.264%] None None None
credit_card/is_card_number_no_luhn/x371413321323331 throughput [44163466.344op/s; 44396110.981op/s] or [-0.263%; +0.263%] None None None

Group 2

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz 3475380 1726819201 vianney/data-pipeline/APMSP-1013-stats-can-be-computed-from-the-spans-payload
scenario metric min mean ± sd median ± mad p75 p95 p99 max peak_to_median_ratio skewness kurtosis cv sem runs sample_size
tags/replace_trace_tags execution_time 2.685µs 2.736µs ± 0.017µs 2.739µs ± 0.008µs 2.747µs 2.756µs 2.762µs 2.765µs 0.93% -1.115 0.944 0.62% 0.001µs 1 200
scenario metric 95% CI mean Shapiro-Wilk pvalue Ljung-Box pvalue (lag=1) Dip test pvalue
tags/replace_trace_tags execution_time [2.733µs; 2.738µs] or [-0.087%; +0.087%] None None None

Group 3

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz 3475380 1726819201 vianney/data-pipeline/APMSP-1013-stats-can-be-computed-from-the-spans-payload
scenario metric min mean ± sd median ± mad p75 p95 p99 max peak_to_median_ratio skewness kurtosis cv sem runs sample_size
write only interface execution_time 1.355µs 3.162µs ± 1.528µs 3.007µs ± 0.024µs 3.030µs 3.084µs 13.712µs 17.404µs 478.73% 7.941 63.568 48.21% 0.108µs 1 200
scenario metric 95% CI mean Shapiro-Wilk pvalue Ljung-Box pvalue (lag=1) Dip test pvalue
write only interface execution_time [2.950µs; 3.373µs] or [-6.699%; +6.699%] None None None

Group 4

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz 3475380 1726819201 vianney/data-pipeline/APMSP-1013-stats-can-be-computed-from-the-spans-payload
scenario metric min mean ± sd median ± mad p75 p95 p99 max peak_to_median_ratio skewness kurtosis cv sem runs sample_size
benching deserializing traces from msgpack to their internal representation execution_time 1.134µs 1.197µs ± 0.023µs 1.203µs ± 0.013µs 1.215µs 1.218µs 1.219µs 1.220µs 1.37% -1.318 0.985 1.89% 0.002µs 1 200
scenario metric 95% CI mean Shapiro-Wilk pvalue Ljung-Box pvalue (lag=1) Dip test pvalue
benching deserializing traces from msgpack to their internal representation execution_time [1.194µs; 1.200µs] or [-0.263%; +0.263%] None None None

Group 5

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz 3475380 1726819201 vianney/data-pipeline/APMSP-1013-stats-can-be-computed-from-the-spans-payload
scenario metric min mean ± sd median ± mad p75 p95 p99 max peak_to_median_ratio skewness kurtosis cv sem runs sample_size
normalization/normalize_name/normalize_name/Too-Long-.Too-Long-.Too-Long-.Too-Long-.Too-Long-.Too-Lo... execution_time 275.753µs 276.316µs ± 0.177µs 276.285µs ± 0.111µs 276.420µs 276.611µs 276.760µs 276.994µs 0.26% 0.603 0.877 0.06% 0.013µs 1 200
normalization/normalize_name/normalize_name/Too-Long-.Too-Long-.Too-Long-.Too-Long-.Too-Long-.Too-Lo... throughput 3610180.660op/s 3619046.381op/s ± 2320.558op/s 3619452.962op/s ± 1455.864op/s 3620475.989op/s 3622096.528op/s 3622904.003op/s 3626437.429op/s 0.19% -0.598 0.871 0.06% 164.088op/s 1 200
normalization/normalize_name/normalize_name/bad-name execution_time 28.057µs 28.117µs ± 0.038µs 28.114µs ± 0.028µs 28.139µs 28.192µs 28.228µs 28.235µs 0.43% 0.950 0.385 0.14% 0.003µs 1 200
normalization/normalize_name/normalize_name/bad-name throughput 35417313.004op/s 35565659.788op/s ± 48621.714op/s 35569607.414op/s ± 34999.773op/s 35605250.747op/s 35622057.982op/s 35625867.987op/s 35641851.485op/s 0.20% -0.944 0.368 0.14% 3438.074op/s 1 200
normalization/normalize_name/normalize_name/good execution_time 16.501µs 16.546µs ± 0.038µs 16.532µs ± 0.018µs 16.563µs 16.622µs 16.691µs 16.712µs 1.09% 1.719 3.410 0.23% 0.003µs 1 200
normalization/normalize_name/normalize_name/good throughput 59837182.014op/s 60436485.328op/s ± 139719.160op/s 60490221.995op/s ± 64670.227op/s 60539123.991op/s 60562744.402op/s 60589590.021op/s 60600893.812op/s 0.18% -1.702 3.327 0.23% 9879.637op/s 1 200
scenario metric 95% CI mean Shapiro-Wilk pvalue Ljung-Box pvalue (lag=1) Dip test pvalue
normalization/normalize_name/normalize_name/Too-Long-.Too-Long-.Too-Long-.Too-Long-.Too-Long-.Too-Lo... execution_time [276.291µs; 276.341µs] or [-0.009%; +0.009%] None None None
normalization/normalize_name/normalize_name/Too-Long-.Too-Long-.Too-Long-.Too-Long-.Too-Long-.Too-Lo... throughput [3618724.774op/s; 3619367.988op/s] or [-0.009%; +0.009%] None None None
normalization/normalize_name/normalize_name/bad-name execution_time [28.112µs; 28.122µs] or [-0.019%; +0.019%] None None None
normalization/normalize_name/normalize_name/bad-name throughput [35558921.286op/s; 35572398.290op/s] or [-0.019%; +0.019%] None None None
normalization/normalize_name/normalize_name/good execution_time [16.541µs; 16.552µs] or [-0.032%; +0.032%] None None None
normalization/normalize_name/normalize_name/good throughput [60417121.596op/s; 60455849.060op/s] or [-0.032%; +0.032%] None None None

Group 6

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz 3475380 1726819201 vianney/data-pipeline/APMSP-1013-stats-can-be-computed-from-the-spans-payload
scenario metric min mean ± sd median ± mad p75 p95 p99 max peak_to_median_ratio skewness kurtosis cv sem runs sample_size
two way interface execution_time 17.623µs 21.389µs ± 8.256µs 17.852µs ± 0.118µs 18.021µs 36.040µs 36.837µs 89.037µs 398.74% 3.582 21.298 38.50% 0.584µs 1 200
scenario metric 95% CI mean Shapiro-Wilk pvalue Ljung-Box pvalue (lag=1) Dip test pvalue
two way interface execution_time [20.245µs; 22.533µs] or [-5.350%; +5.350%] None None None

Group 7

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz 3475380 1726819201 vianney/data-pipeline/APMSP-1013-stats-can-be-computed-from-the-spans-payload
scenario metric min mean ± sd median ± mad p75 p95 p99 max peak_to_median_ratio skewness kurtosis cv sem runs sample_size
normalization/normalize_trace/test_trace execution_time 297.770ns 307.419ns ± 12.288ns 301.949ns ± 2.725ns 307.318ns 336.712ns 344.938ns 345.924ns 14.56% 1.860 2.239 3.99% 0.869ns 1 200
scenario metric 95% CI mean Shapiro-Wilk pvalue Ljung-Box pvalue (lag=1) Dip test pvalue
normalization/normalize_trace/test_trace execution_time [305.716ns; 309.122ns] or [-0.554%; +0.554%] None None None

Group 8

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz 3475380 1726819201 vianney/data-pipeline/APMSP-1013-stats-can-be-computed-from-the-spans-payload
scenario metric min mean ± sd median ± mad p75 p95 p99 max peak_to_median_ratio skewness kurtosis cv sem runs sample_size
concentrator/add_spans_to_concentrator execution_time 8.986ms 9.024ms ± 0.016ms 9.024ms ± 0.009ms 9.033ms 9.049ms 9.065ms 9.091ms 0.74% 0.521 1.292 0.17% 0.001ms 1 200
scenario metric 95% CI mean Shapiro-Wilk pvalue Ljung-Box pvalue (lag=1) Dip test pvalue
concentrator/add_spans_to_concentrator execution_time [9.022ms; 9.026ms] or [-0.024%; +0.024%] None None None

Group 9

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz 3475380 1726819201 vianney/data-pipeline/APMSP-1013-stats-can-be-computed-from-the-spans-payload
scenario metric min mean ± sd median ± mad p75 p95 p99 max peak_to_median_ratio skewness kurtosis cv sem runs sample_size
redis/obfuscate_redis_string execution_time 38.977µs 39.540µs ± 1.009µs 39.085µs ± 0.043µs 39.136µs 41.715µs 41.781µs 42.320µs 8.28% 1.709 0.957 2.55% 0.071µs 1 200
scenario metric 95% CI mean Shapiro-Wilk pvalue Ljung-Box pvalue (lag=1) Dip test pvalue
redis/obfuscate_redis_string execution_time [39.400µs; 39.680µs] or [-0.354%; +0.354%] None None None

Group 10

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz 3475380 1726819201 vianney/data-pipeline/APMSP-1013-stats-can-be-computed-from-the-spans-payload
scenario metric min mean ± sd median ± mad p75 p95 p99 max peak_to_median_ratio skewness kurtosis cv sem runs sample_size
normalization/normalize_service/normalize_service/A0000000000000000000000000000000000000000000000000... execution_time 537.570µs 538.119µs ± 0.316µs 538.063µs ± 0.179µs 538.291µs 538.652µs 539.287µs 539.402µs 0.25% 1.074 2.231 0.06% 0.022µs 1 200
normalization/normalize_service/normalize_service/A0000000000000000000000000000000000000000000000000... throughput 1853903.667op/s 1858325.513op/s ± 1092.111op/s 1858518.427op/s ± 616.757op/s 1859040.191op/s 1859927.900op/s 1860124.765op/s 1860221.633op/s 0.09% -1.069 2.211 0.06% 77.224op/s 1 200
normalization/normalize_service/normalize_service/Data🐨dog🐶 繋がっ⛰てて execution_time 466.780µs 467.294µs ± 0.235µs 467.310µs ± 0.146µs 467.439µs 467.661µs 467.849µs 468.062µs 0.16% 0.087 -0.001 0.05% 0.017µs 1 200
normalization/normalize_service/normalize_service/Data🐨dog🐶 繋がっ⛰てて throughput 2136468.139op/s 2139982.403op/s ± 1076.974op/s 2139906.043op/s ± 667.600op/s 2140721.331op/s 2141876.960op/s 2142190.134op/s 2142337.586op/s 0.11% -0.084 -0.004 0.05% 76.154op/s 1 200
normalization/normalize_service/normalize_service/Test Conversion 0f Weird !@#$%^&**() Characters execution_time 184.535µs 185.075µs ± 0.234µs 185.066µs ± 0.141µs 185.205µs 185.481µs 185.659µs 186.033µs 0.52% 0.722 1.238 0.13% 0.017µs 1 200
normalization/normalize_service/normalize_service/Test Conversion 0f Weird !@#$%^&**() Characters throughput 5375385.331op/s 5403211.351op/s ± 6838.464op/s 5403488.994op/s ± 4126.861op/s 5407801.098op/s 5413654.352op/s 5415765.137op/s 5419024.733op/s 0.29% -0.711 1.209 0.13% 483.552op/s 1 200
normalization/normalize_service/normalize_service/[empty string] execution_time 44.666µs 44.731µs ± 0.033µs 44.728µs ± 0.023µs 44.753µs 44.793µs 44.809µs 44.835µs 0.24% 0.374 -0.040 0.07% 0.002µs 1 200
normalization/normalize_service/normalize_service/[empty string] throughput 22304038.357op/s 22355723.231op/s ± 16429.691op/s 22357522.583op/s ± 11402.343op/s 22366750.188op/s 22382435.768op/s 22386417.638op/s 22388635.716op/s 0.14% -0.370 -0.045 0.07% 1161.755op/s 1 200
normalization/normalize_service/normalize_service/test_ASCII execution_time 49.737µs 49.826µs ± 0.098µs 49.812µs ± 0.053µs 49.867µs 49.934µs 49.998µs 50.888µs 2.16% 6.427 66.122 0.20% 0.007µs 1 200
normalization/normalize_service/normalize_service/test_ASCII throughput 19650850.093op/s 20069820.412op/s ± 39120.204op/s 20075577.549op/s ± 21559.953op/s 20095366.535op/s 20102298.023op/s 20104506.075op/s 20105737.476op/s 0.15% -6.270 63.843 0.19% 2766.216op/s 1 200
scenario metric 95% CI mean Shapiro-Wilk pvalue Ljung-Box pvalue (lag=1) Dip test pvalue
normalization/normalize_service/normalize_service/A0000000000000000000000000000000000000000000000000... execution_time [538.075µs; 538.163µs] or [-0.008%; +0.008%] None None None
normalization/normalize_service/normalize_service/A0000000000000000000000000000000000000000000000000... throughput [1858174.157op/s; 1858476.869op/s] or [-0.008%; +0.008%] None None None
normalization/normalize_service/normalize_service/Data🐨dog🐶 繋がっ⛰てて execution_time [467.261µs; 467.326µs] or [-0.007%; +0.007%] None None None
normalization/normalize_service/normalize_service/Data🐨dog🐶 繋がっ⛰てて throughput [2139833.144op/s; 2140131.661op/s] or [-0.007%; +0.007%] None None None
normalization/normalize_service/normalize_service/Test Conversion 0f Weird !@#$%^&**() Characters execution_time [185.043µs; 185.108µs] or [-0.018%; +0.018%] None None None
normalization/normalize_service/normalize_service/Test Conversion 0f Weird !@#$%^&**() Characters throughput [5402263.606op/s; 5404159.096op/s] or [-0.018%; +0.018%] None None None
normalization/normalize_service/normalize_service/[empty string] execution_time [44.727µs; 44.736µs] or [-0.010%; +0.010%] None None None
normalization/normalize_service/normalize_service/[empty string] throughput [22353446.234op/s; 22358000.228op/s] or [-0.010%; +0.010%] None None None
normalization/normalize_service/normalize_service/test_ASCII execution_time [49.813µs; 49.840µs] or [-0.027%; +0.027%] None None None
normalization/normalize_service/normalize_service/test_ASCII throughput [20064398.728op/s; 20075242.096op/s] or [-0.027%; +0.027%] None None None

Group 11

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz 3475380 1726819201 vianney/data-pipeline/APMSP-1013-stats-can-be-computed-from-the-spans-payload
scenario metric min mean ± sd median ± mad p75 p95 p99 max peak_to_median_ratio skewness kurtosis cv sem runs sample_size
sql/obfuscate_sql_string execution_time 72.101µs 72.223µs ± 0.143µs 72.202µs ± 0.028µs 72.231µs 72.314µs 72.781µs 73.868µs 2.31% 8.334 87.120 0.20% 0.010µs 1 200
scenario metric 95% CI mean Shapiro-Wilk pvalue Ljung-Box pvalue (lag=1) Dip test pvalue
sql/obfuscate_sql_string execution_time [72.203µs; 72.243µs] or [-0.028%; +0.028%] None None None

Group 12

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz 3475380 1726819201 vianney/data-pipeline/APMSP-1013-stats-can-be-computed-from-the-spans-payload
scenario metric min mean ± sd median ± mad p75 p95 p99 max peak_to_median_ratio skewness kurtosis cv sem runs sample_size
benching string interning on wordpress profile execution_time 143.893µs 144.690µs ± 0.415µs 144.585µs ± 0.167µs 144.804µs 145.471µs 145.974µs 147.932µs 2.31% 3.068 18.268 0.29% 0.029µs 1 200
scenario metric 95% CI mean Shapiro-Wilk pvalue Ljung-Box pvalue (lag=1) Dip test pvalue
benching string interning on wordpress profile execution_time [144.633µs; 144.748µs] or [-0.040%; +0.040%] None None None

Baseline

Omitted due to size.

pr-commenter[bot] avatar Aug 09 '24 13:08 pr-commenter[bot]

You need to rebase on main if you want the benchmarks numbers to make sense.

And I see your PR is into your own branch, so I'll keep quiet...

bantonsson avatar Aug 09 '24 13:08 bantonsson