Use inplace normalization and add benchmark

[VianneyRuhlmann]

What does this PR do?

Work from @paullegranddc in #458

• Use inplace normalization to improve performance
• Handle chars as uint instead of utf8 chars to improve performance
• Add benchmark for trace-normalization

Motivation

Improve trace normalization performance

Additional Notes

How to test the change?

[codecov-commenter]

Codecov Report

Attention: Patch coverage is 93.96226% with 16 lines in your changes missing coverage. Please review.

Project coverage is 70.46%. Comparing base (ce2afd9) to head (d570cdf).

Additional details and impacted files

@@            Coverage Diff             @@
##             main     #506      +/-   ##
==========================================
+ Coverage   70.41%   70.46%   +0.05%     
==========================================
  Files         204      205       +1     
  Lines       27890    27939      +49     
==========================================
+ Hits        19639    19688      +49     
  Misses       8251     8251              

Components	Coverage Δ
crashtracker	16.72% <ø> (ø)
datadog-alloc	98.76% <ø> (ø)
data-pipeline	51.15% <ø> (ø)
data-pipeline-ffi	0.00% <ø> (ø)
ddcommon	86.58% <ø> (ø)
ddcommon-ffi	75.31% <ø> (ø)
ddtelemetry	59.33% <ø> (ø)
ipc	84.66% <ø> (ø)
profiling	78.63% <ø> (ø)
profiling-ffi	58.19% <ø> (ø)
serverless	0.00% <ø> (ø)
sidecar	36.19% <ø> (ø)
sidecar-ffi	0.00% <ø> (ø)
spawn-worker	54.98% <ø> (ø)
trace-mini-agent	69.70% <ø> (ø)
trace-normalization	98.24% <96.29%> (+0.44%)	⬆️
trace-obfuscation	95.75% <ø> (ø)
trace-protobuf	77.16% <ø> (ø)
trace-utils	90.76% <68.18%> (-0.09%)	⬇️

[pr-commenter]

Benchmarks

Comparison

Parameters

	Baseline	Candidate
config	baseline	candidate
git_branch	main	vianney/inplace-trace-normalization
git_commit_date	1720105540	1720183895
git_commit_sha	3142b2d	899ff91
iterations	706.0	713.0

See matching parameters

	Baseline	Candidate
ci_job_date	1720184138	1720184138
ci_job_id	563452051	563452051
ci_pipeline_id	38437982	38437982
cpu_model	Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz

Summary

Found 0 performance improvements and 0 performance regressions! Performance is the same for 1 metrics, 0 unstable metrics.

Candidate

Candidate benchmark details

Group 1

iterations	config	cpu_model	ci_job_date	ci_job_id	ci_pipeline_id	git_commit_sha	git_commit_date	git_branch
713.0	candidate	Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	1720184138	563452051	38437982	899ff91	1720183895	vianney/inplace-trace-normalization

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	70.083µs	70.143µs ± 0.030µs	70.139µs ± 0.020µs	70.162µs	70.194µs	70.212µs	70.219µs	0.11%	0.249	-0.426	0.04%	0.003µs	1	100

scenario	metric	95% CI mean	Shapiro-Wilk pvalue	Ljung-Box pvalue (lag=1)	Dip test pvalue
sql/obfuscate_sql_string	execution_time	[70.137µs; 70.149µs] or [-0.008%; +0.008%]	None	None	None

Warnings

Scenario: sql/obfuscate_sql_string, Metric: execution_time

Measurements are autocorrelated.

Autocorrelation is present for lags 1..10.

The measurements are not independent, thus confidence intervals
may be less precise.
---------------------------------------------------------------------------

Scenario: sql/obfuscate_sql_string, Metric: execution_time

Sample size is 100, which is lower than 105.

The minimal sample size in case of normal distribution to achieve significance
level of 0.05 for difference of means with effect size Cohen's d = 0.5 must be at
least 105.

The conclusions from confidence intervals may be invalid.
---------------------------------------------------------------------------

Baseline

Baseline benchmark details

Group 1

iterations	config	cpu_model	ci_job_date	ci_job_id	ci_pipeline_id	git_commit_sha	git_commit_date	git_branch
706.0	baseline	Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	1720184138	563452051	38437982	3142b2d	1720105540	main

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	70.503µs	70.595µs ± 0.028µs	70.594µs ± 0.016µs	70.611µs	70.637µs	70.661µs	70.671µs	0.11%	-0.129	0.993	0.04%	0.003µs	1	100

scenario	metric	95% CI mean	Shapiro-Wilk pvalue	Ljung-Box pvalue (lag=1)	Dip test pvalue
sql/obfuscate_sql_string	execution_time	[70.590µs; 70.601µs] or [-0.008%; +0.008%]	None	None	None

Warnings

Scenario: sql/obfuscate_sql_string, Metric: execution_time

Measurements are autocorrelated.

Autocorrelation is present for lags 1..10.

The measurements are not independent, thus confidence intervals
may be less precise.
---------------------------------------------------------------------------

Scenario: sql/obfuscate_sql_string, Metric: execution_time

Sample size is 100, which is lower than 105.

The minimal sample size in case of normal distribution to achieve significance
level of 0.05 for difference of means with effect size Cohen's d = 0.5 must be at
least 105.

The conclusions from confidence intervals may be invalid.
---------------------------------------------------------------------------

[VianneyRuhlmann]

Benchmark summary for performance compared to main:

• normalization/normalize_service/normalize_service/[empty string]
  time: [15.976 ns 16.035 ns 16.115 ns]
  change: [+45.893% +53.746% +61.239%]
  Performance has regressed.
• normalization/normalize_service/normalize_service/test_ASCII
  time: [23.852 ns 23.901 ns 23.959 ns]
  change: [-55.481% -55.187% -54.886%]
  Performance has improved.
• normalization/normalize_service/normalize_service/Test Conversion 0f Weird !@#$%^&() Characters**
  time: [78.656 ns 78.763 ns 78.899 ns]
  change: [-37.716% -37.450% -37.171%]
  Performance has improved.
• normalization/normalize_service/normalize_service/Data🐨dog🐶 繋がっ⛰てて
  time: [232.03 ns 232.56 ns 233.08 ns]
  change: [+15.116% +15.588% +16.041%]
  Performance has regressed.
• normalization/normalize_service/normalize_service/A000000000000000000000000000000000000000000...
  time: [192.13 ns 192.68 ns 193.33 ns]
  change: [-41.727% -41.477% -41.240%]
  Performance has improved.
• normalization/normalize_name/normalize_name/good
  time: [12.262 ns 12.283 ns 12.305 ns]
  change: [-58.695% -58.573% -58.440%]
  Performance has improved.
• normalization/normalize_name/normalize_name/bad-name
  time: [15.269 ns 15.332 ns 15.412 ns]
  change: [-77.235% -76.850% -76.358%]
  Performance has improved.
• normalization/normalize_name/normalize_name/Too-Long-.Too-Long-.Too-Long-.Too-Long-.Too-Lo...
  time: [121.96 ns 122.10 ns 122.27 ns]
  change: [-77.022% -76.825% -76.491%]
  Performance has improved.
• normalization/normalize_trace/test_trace
  time: [119.46 ns 120.80 ns 123.10 ns]
  change: [-66.853% -66.205% -65.721%]
  Performance has improved.

The regression for the empty service name case is probably due to the fact that in main the default value is written by normalize_span instead of normalize_service.
There is also a regression for string using non-ASCII characters.

[bantonsson]

Looks good. Only some small questions.