fix(crashtracking): use libunwind to unwind frames by gyuheon0h · Pull Request #1663 · DataDog/libdatadog

gyuheon0h · 2026-03-05T16:41:15Z

What does this PR do?

Use packaged libunwind to unwind crash stacktrace.

The diff is bigger than the actual change, because I moved some of the emitter functions around so that the file structure is

helper structs
main emit func (`emit_crashreport`)
... all the helper emitters ...

I also added unsafe comments to unsafe calls

Motivation

Crashtracker collects callstacks. When it comes to alpine/musl-libc (mainly on x86_64), we fail at retrieving the callstack passed the signal frame. The problem is that the musl-libc binary does not have the CFIs (unwinding information) and the unwinder does not know how to move forward and stop.

Libunwind provides a way to unwind starting from the ucontext: context (registers and state) of the crashing thread. Going that way, we can collect the callstack as much as possible (until hitting musl-libc). We previously packaged libunwind as a libdatadog crate here: feat(profiling): Wrap libunwind in a crate

Lets use this to unwind from crash ucontext

Additional Notes

Anything else we should know when reviewing?

How to test the change?

Describe here in detail how the change can be validated.

gyuheon0h · 2026-03-05T16:41:31Z

fix(crashtracking): use libunwind to unwind frames #1663 👈 (View in Graphite)
main

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github-actions · 2026-03-05T17:25:40Z

Clippy Allow Annotation Report

Comparing clippy allow annotations between branches:

Base Branch: origin/main
PR Branch: origin/gyuheon0h/PROF-13672-libunwind

Summary by Rule

Rule	Base Branch	PR Branch	Change
unwrap_used	12	0	✅ -12 (-100.0%)
Total	12	0	✅ -12 (-100.0%)

Annotation Counts by File

File	Base Branch	PR Branch	Change
`libdd-crashtracker/src/collector/emitters.rs`	12	0	✅ -12 (-100.0%)

Annotation Stats by Crate

Crate	Base Branch	PR Branch	Change
`clippy-annotation-reporter`	5	5	No change (0%)
`datadog-ffe-ffi`	1	1	No change (0%)
`datadog-ipc`	28	27	✅ -1 (-3.6%)
`datadog-live-debugger`	6	6	No change (0%)
`datadog-live-debugger-ffi`	10	10	No change (0%)
`datadog-profiling-replayer`	4	4	No change (0%)
`datadog-remote-config`	3	3	No change (0%)
`datadog-sidecar`	59	59	No change (0%)
`libdd-common`	10	10	No change (0%)
`libdd-common-ffi`	12	12	No change (0%)
`libdd-crashtracker`	12	0	✅ -12 (-100.0%)
`libdd-data-pipeline`	5	5	No change (0%)
`libdd-ddsketch`	2	2	No change (0%)
`libdd-dogstatsd-client`	1	1	No change (0%)
`libdd-profiling`	13	13	No change (0%)
`libdd-telemetry`	19	19	No change (0%)
`libdd-tinybytes`	4	4	No change (0%)
`libdd-trace-normalization`	2	2	No change (0%)
`libdd-trace-obfuscation`	9	9	No change (0%)
`libdd-trace-utils`	15	15	No change (0%)
Total	220	207	✅ -13 (-5.9%)

About This Report

This report tracks Clippy allow annotations for specific rules, showing how they've changed in this PR. Decreasing the number of these annotations generally improves code quality.

codecov-commenter · 2026-03-05T17:47:51Z

Codecov Report

❌ Patch coverage is 31.25000% with 77 lines in your changes missing coverage. Please review.
✅ Project coverage is 71.08%. Comparing base (0f3d46b) to head (30a1416).
⚠️ Report is 4 commits behind head on main.

Additional details and impacted files

@@            Coverage Diff             @@
##             main    #1663      +/-   ##
==========================================
- Coverage   71.19%   71.08%   -0.12%     
==========================================
  Files         427      427              
  Lines       62852    62920      +68     
==========================================
- Hits        44746    44725      -21     
- Misses      18106    18195      +89

Components	Coverage Δ
libdd-crashtracker	`62.37% <31.25%> (-0.57%)`	⬇️
libdd-crashtracker-ffi	`17.49% <ø> (+0.92%)`	⬆️
libdd-alloc	`98.77% <ø> (ø)`
libdd-data-pipeline	`88.02% <ø> (ø)`
libdd-data-pipeline-ffi	`75.72% <ø> (ø)`
libdd-common	`79.73% <ø> (ø)`
libdd-common-ffi	`73.40% <ø> (ø)`
libdd-telemetry	`62.48% <ø> (ø)`
libdd-telemetry-ffi	`16.75% <ø> (ø)`
libdd-dogstatsd-client	`82.64% <ø> (ø)`
datadog-ipc	`80.35% <ø> (-0.51%)`	⬇️
libdd-profiling	`81.60% <ø> (ø)`
libdd-profiling-ffi	`63.65% <ø> (ø)`
datadog-sidecar	`32.47% <ø> (+0.47%)`	⬆️
datdog-sidecar-ffi	`7.73% <ø> (+1.30%)`	⬆️
spawn-worker	`54.69% <ø> (ø)`
libdd-tinybytes	`93.16% <ø> (ø)`
libdd-trace-normalization	`81.71% <ø> (ø)`
libdd-trace-obfuscation	`94.69% <ø> (ø)`
libdd-trace-protobuf	`68.25% <ø> (+0.25%)`	⬆️
libdd-trace-utils	`89.08% <ø> (+<0.01%)`	⬆️
datadog-tracer-flare	`88.95% <ø> (ø)`
libdd-log	`74.69% <ø> (ø)`

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dd-octo-sts · 2026-03-05T17:59:17Z

Artifact Size Benchmark Report

aarch64-alpine-linux-musl

Artifact	Baseline	Commit	Change
/aarch64-alpine-linux-musl/lib/libdatadog_profiling.so	8.70 MB	8.63 MB	--.71% (-64.02 KB) 💪
/aarch64-alpine-linux-musl/lib/libdatadog_profiling.a	98.65 MB	100.06 MB	+1.42% (+1.40 MB) ⚠️

aarch64-unknown-linux-gnu

Artifact	Baseline	Commit	Change
/aarch64-unknown-linux-gnu/lib/libdatadog_profiling.a	114.29 MB	116.71 MB	+2.11% (+2.41 MB) ⚠️
/aarch64-unknown-linux-gnu/lib/libdatadog_profiling.so	11.29 MB	11.20 MB	--.75% (-87.43 KB) 💪

libdatadog-x64-windows

Artifact	Baseline	Commit	Change
/libdatadog-x64-windows/debug/dynamic/datadog_profiling_ffi.dll	27.16 MB	27.16 MB	0% (0 B) 👌
/libdatadog-x64-windows/debug/dynamic/datadog_profiling_ffi.lib	76.26 KB	76.26 KB	0% (0 B) 👌
/libdatadog-x64-windows/debug/dynamic/datadog_profiling_ffi.pdb	186.04 MB	186.01 MB	--.01% (-24.00 KB) 💪
/libdatadog-x64-windows/debug/static/datadog_profiling_ffi.lib	917.19 MB	917.17 MB	-0% (-22.09 KB) 👌
/libdatadog-x64-windows/release/dynamic/datadog_profiling_ffi.dll	9.93 MB	9.93 MB	0% (0 B) 👌
/libdatadog-x64-windows/release/dynamic/datadog_profiling_ffi.lib	76.26 KB	76.26 KB	0% (0 B) 👌
/libdatadog-x64-windows/release/dynamic/datadog_profiling_ffi.pdb	24.76 MB	24.76 MB	0% (0 B) 👌
/libdatadog-x64-windows/release/static/datadog_profiling_ffi.lib	51.43 MB	51.43 MB	+0% (+148 B) 👌

libdatadog-x86-windows

Artifact	Baseline	Commit	Change
/libdatadog-x86-windows/debug/dynamic/datadog_profiling_ffi.dll	22.97 MB	22.97 MB	0% (0 B) 👌
/libdatadog-x86-windows/debug/dynamic/datadog_profiling_ffi.lib	77.44 KB	77.44 KB	0% (0 B) 👌
/libdatadog-x86-windows/debug/dynamic/datadog_profiling_ffi.pdb	190.23 MB	190.24 MB	+0% (+8.00 KB) 👌
/libdatadog-x86-windows/debug/static/datadog_profiling_ffi.lib	900.84 MB	900.82 MB	-0% (-20.73 KB) 👌
/libdatadog-x86-windows/release/dynamic/datadog_profiling_ffi.dll	7.53 MB	7.53 MB	0% (0 B) 👌
/libdatadog-x86-windows/release/dynamic/datadog_profiling_ffi.lib	77.44 KB	77.44 KB	0% (0 B) 👌
/libdatadog-x86-windows/release/dynamic/datadog_profiling_ffi.pdb	26.52 MB	26.52 MB	0% (0 B) 👌
/libdatadog-x86-windows/release/static/datadog_profiling_ffi.lib	47.06 MB	47.06 MB	+0% (+150 B) 👌

x86_64-alpine-linux-musl

Artifact	Baseline	Commit	Change
/x86_64-alpine-linux-musl/lib/libdatadog_profiling.a	86.54 MB	87.28 MB	+.85% (+758.55 KB) 🔍
/x86_64-alpine-linux-musl/lib/libdatadog_profiling.so	10.23 MB	10.19 MB	--.38% (-40.02 KB) 💪

x86_64-unknown-linux-gnu

Artifact	Baseline	Commit	Change
/x86_64-unknown-linux-gnu/lib/libdatadog_profiling.a	107.16 MB	109.60 MB	+2.27% (+2.44 MB) ⚠️
/x86_64-unknown-linux-gnu/lib/libdatadog_profiling.so	11.98 MB	11.92 MB	--.50% (-62.46 KB) 💪

datadog-datadog-prod-us1 · 2026-03-05T19:39:01Z

✅ Tests

🎉 All green!

❄️ No new flaky tests detected
🧪 All tests passed

_{This comment will be updated automatically if new data arrives.

🔗 Commit SHA: 30a1416 | Docs | Datadog PR Page | Was this helpful? React with 👍/👎 or give us feedback!}

pr-commenter · 2026-03-05T22:46:04Z

Benchmarks

Comparison

Benchmark execution time: 2026-03-09 13:36:57

Comparing candidate commit 30a1416 in PR branch gyuheon0h/PROF-13672-libunwind with baseline commit 04394ec in branch main.

Found 1 performance improvements and 1 performance regressions! Performance is the same for 56 metrics, 2 unstable metrics.

Explanation

This is an A/B test comparing a candidate commit's performance against that of a baseline commit. Performance changes are noted in the tables below as:

🟩 = significantly better candidate vs. baseline
🟥 = significantly worse candidate vs. baseline

We compute a confidence interval (CI) over the relative difference of means between metrics from the candidate and baseline commits, considering the baseline as the reference.

If the CI is entirely outside the configured SIGNIFICANT_IMPACT_THRESHOLD (or the deprecated UNCONFIDENCE_THRESHOLD), the change is considered significant.

Feel free to reach out to #apm-benchmarking-platform on Slack if you have any questions.

More details about the CI and significant changes

You can imagine this CI as a range of values that is likely to contain the true difference of means between the candidate and baseline commits.

CIs of the difference of means are often centered around 0%, because often changes are not that big:

---------------------------------(------|---^--------)-------------------------------->
                              -0.6%    0%  0.3%     +1.2%
                                 |          |        |
         lower bound of the CI --'          |        |
sample mean (center of the CI) -------------'        |
         upper bound of the CI ----------------------'

As described above, a change is considered significant if the CI is entirely outside the configured SIGNIFICANT_IMPACT_THRESHOLD (or the deprecated UNCONFIDENCE_THRESHOLD).

For instance, for an execution time metric, this confidence interval indicates a significantly worse performance:

----------------------------------------|---------|---(---------^---------)---------->
                                       0%        1%  1.3%      2.2%      3.1%
                                                  |   |         |         |
       significant impact threshold --------------'   |         |         |
                      lower bound of CI --------------'         |         |
       sample mean (center of the CI) --------------------------'         |
                      upper bound of CI ----------------------------------'

scenario:benching deserializing traces from msgpack to their internal representation

🟩 execution_time [-3.333ms; -2.986ms] or [-6.473%; -5.799%]

scenario:receiver_entry_point/report/2598

🟥 execution_time [+256.082µs; +261.921µs] or [+8.157%; +8.343%]

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	`30a1416`	1773062374	gyuheon0h/PROF-13672-libunwind

scenario	metric	min	mean ± sd	median ± mad	p75	p95	p99	max	peak_to_median_ratio	skewness	kurtosis	cv	sem	runs	sample_size
profile_add_sample_frames_x1000	execution_time	4.192ms	4.195ms ± 0.007ms	4.195ms ± 0.001ms	4.196ms	4.198ms	4.200ms	4.293ms	2.33%	12.475	165.726	0.17%	0.001ms	1	200

scenario	metric	95% CI mean	Shapiro-Wilk pvalue	Ljung-Box pvalue (lag=1)	Dip test pvalue
profile_add_sample_frames_x1000	execution_time	[4.194ms; 4.196ms] or [-0.024%; +0.024%]	None	None	None

Group 2

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	`30a1416`	1773062374	gyuheon0h/PROF-13672-libunwind

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	533.821µs	534.887µs ± 1.051µs	534.758µs ± 0.262µs	535.022µs	535.439µs	541.255µs	543.621µs	1.66%	5.969	40.174	0.20%	0.074µs	1	200
normalization/normalize_service/normalize_service/A0000000000000000000000000000000000000000000000000...	throughput	1839515.476op/s	1869560.406op/s ± 3631.771op/s	1870005.573op/s ± 917.114op/s	1870916.656op/s	1872051.883op/s	1872546.390op/s	1873288.764op/s	0.18%	-5.931	39.751	0.19%	256.805op/s	1	200
normalization/normalize_service/normalize_service/Data🐨dog🐶 繋がっ⛰てて	execution_time	380.743µs	381.588µs ± 0.360µs	381.539µs ± 0.264µs	381.853µs	382.181µs	382.470µs	382.600µs	0.28%	0.341	-0.345	0.09%	0.025µs	1	200
normalization/normalize_service/normalize_service/Data🐨dog🐶 繋がっ⛰てて	throughput	2613696.657op/s	2620632.147op/s ± 2468.310op/s	2620964.939op/s ± 1817.035op/s	2622501.312op/s	2624000.615op/s	2625650.520op/s	2626440.260op/s	0.21%	-0.337	-0.349	0.09%	174.536op/s	1	200
normalization/normalize_service/normalize_service/Test Conversion 0f Weird !@#$%^&**() Characters	execution_time	189.715µs	190.169µs ± 0.234µs	190.152µs ± 0.174µs	190.329µs	190.593µs	190.670µs	190.821µs	0.35%	0.239	-0.546	0.12%	0.017µs	1	200
normalization/normalize_service/normalize_service/Test Conversion 0f Weird !@#$%^&**() Characters	throughput	5240518.290op/s	5258496.355op/s ± 6459.964op/s	5258961.017op/s ± 4813.878op/s	5263196.250op/s	5268807.998op/s	5270394.737op/s	5271070.903op/s	0.23%	-0.233	-0.551	0.12%	456.788op/s	1	200
normalization/normalize_service/normalize_service/[empty string]	execution_time	37.288µs	37.482µs ± 0.060µs	37.483µs ± 0.034µs	37.522µs	37.574µs	37.599µs	37.659µs	0.47%	-0.316	0.553	0.16%	0.004µs	1	200
normalization/normalize_service/normalize_service/[empty string]	throughput	26553833.947op/s	26679676.153op/s ± 42528.882op/s	26678559.800op/s ± 24026.084op/s	26700294.204op/s	26755843.894op/s	26785449.171op/s	26818031.039op/s	0.52%	0.328	0.558	0.16%	3007.246op/s	1	200
normalization/normalize_service/normalize_service/test_ASCII	execution_time	45.777µs	45.878µs ± 0.046µs	45.869µs ± 0.029µs	45.907µs	45.975µs	45.993µs	46.045µs	0.38%	0.789	0.535	0.10%	0.003µs	1	200
normalization/normalize_service/normalize_service/test_ASCII	throughput	21717722.216op/s	21796733.712op/s ± 21745.400op/s	21801330.051op/s ± 13739.484op/s	21813072.273op/s	21824588.989op/s	21833017.965op/s	21844840.467op/s	0.20%	-0.784	0.522	0.10%	1537.632op/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	[534.741µs; 535.033µs] or [-0.027%; +0.027%]	None	None	None
normalization/normalize_service/normalize_service/A0000000000000000000000000000000000000000000000000...	throughput	[1869057.078op/s; 1870063.735op/s] or [-0.027%; +0.027%]	None	None	None
normalization/normalize_service/normalize_service/Data🐨dog🐶 繋がっ⛰てて	execution_time	[381.538µs; 381.637µs] or [-0.013%; +0.013%]	None	None	None
normalization/normalize_service/normalize_service/Data🐨dog🐶 繋がっ⛰てて	throughput	[2620290.063op/s; 2620974.231op/s] or [-0.013%; +0.013%]	None	None	None
normalization/normalize_service/normalize_service/Test Conversion 0f Weird !@#$%^&**() Characters	execution_time	[190.136µs; 190.201µs] or [-0.017%; +0.017%]	None	None	None
normalization/normalize_service/normalize_service/Test Conversion 0f Weird !@#$%^&**() Characters	throughput	[5257601.066op/s; 5259391.644op/s] or [-0.017%; +0.017%]	None	None	None
normalization/normalize_service/normalize_service/[empty string]	execution_time	[37.474µs; 37.490µs] or [-0.022%; +0.022%]	None	None	None
normalization/normalize_service/normalize_service/[empty string]	throughput	[26673782.059op/s; 26685570.247op/s] or [-0.022%; +0.022%]	None	None	None
normalization/normalize_service/normalize_service/test_ASCII	execution_time	[45.872µs; 45.885µs] or [-0.014%; +0.014%]	None	None	None
normalization/normalize_service/normalize_service/test_ASCII	throughput	[21793720.009op/s; 21799747.415op/s] or [-0.014%; +0.014%]	None	None	None

Group 3

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	`30a1416`	1773062374	gyuheon0h/PROF-13672-libunwind

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	240.994ns	250.052ns ± 11.843ns	245.053ns ± 3.342ns	251.779ns	280.699ns	284.921ns	285.939ns	16.68%	1.707	1.857	4.72%	0.837ns	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	[248.410ns; 251.693ns] or [-0.656%; +0.656%]	None	None	None

Group 4

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	`30a1416`	1773062374	gyuheon0h/PROF-13672-libunwind

scenario	metric	min	mean ± sd	median ± mad	p75	p95	p99	max	peak_to_median_ratio	skewness	kurtosis	cv	sem	runs	sample_size
sdk_test_data/rules-based	execution_time	145.311µs	147.336µs ± 1.629µs	147.052µs ± 0.582µs	147.774µs	148.663µs	153.848µs	163.537µs	11.21%	5.854	50.319	1.10%	0.115µs	1	200

scenario	metric	95% CI mean	Shapiro-Wilk pvalue	Ljung-Box pvalue (lag=1)	Dip test pvalue
sdk_test_data/rules-based	execution_time	[147.110µs; 147.562µs] or [-0.153%; +0.153%]	None	None	None

Group 5

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	`30a1416`	1773062374	gyuheon0h/PROF-13672-libunwind

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	33.545µs	33.901µs ± 0.537µs	33.673µs ± 0.066µs	33.852µs	34.869µs	34.911µs	37.948µs	12.70%	3.035	15.046	1.58%	0.038µs	1	200

scenario	metric	95% CI mean	Shapiro-Wilk pvalue	Ljung-Box pvalue (lag=1)	Dip test pvalue
redis/obfuscate_redis_string	execution_time	[33.826µs; 33.975µs] or [-0.220%; +0.220%]	None	None	None

Group 6

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	`30a1416`	1773062374	gyuheon0h/PROF-13672-libunwind

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	47.914ms	48.331ms ± 0.998ms	48.177ms ± 0.094ms	48.269ms	48.546ms	52.070ms	58.276ms	20.96%	7.677	64.696	2.06%	0.071ms	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	[48.193ms; 48.470ms] or [-0.286%; +0.286%]	None	None	None

Group 7

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	`30a1416`	1773062374	gyuheon0h/PROF-13672-libunwind

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	1.261µs	3.239µs ± 1.407µs	3.039µs ± 0.035µs	3.065µs	3.676µs	13.793µs	14.857µs	388.86%	7.321	54.945	43.32%	0.099µs	1	200

scenario	metric	95% CI mean	Shapiro-Wilk pvalue	Ljung-Box pvalue (lag=1)	Dip test pvalue
write only interface	execution_time	[3.044µs; 3.434µs] or [-6.018%; +6.018%]	None	None	None

Group 8

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	`30a1416`	1773062374	gyuheon0h/PROF-13672-libunwind

scenario	metric	min	mean ± sd	median ± mad	p75	p95	p99	max	peak_to_median_ratio	skewness	kurtosis	cv	sem	runs	sample_size
receiver_entry_point/report/2598	execution_time	3.372ms	3.398ms ± 0.013ms	3.396ms ± 0.007ms	3.404ms	3.426ms	3.442ms	3.463ms	1.98%	1.639	3.995	0.39%	0.001ms	1	200

scenario	metric	95% CI mean	Shapiro-Wilk pvalue	Ljung-Box pvalue (lag=1)	Dip test pvalue
receiver_entry_point/report/2598	execution_time	[3.397ms; 3.400ms] or [-0.054%; +0.054%]	None	None	None

Group 9

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	`30a1416`	1773062374	gyuheon0h/PROF-13672-libunwind

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	159.535µs	160.588µs ± 0.432µs	160.490µs ± 0.131µs	160.663µs	161.239µs	162.010µs	163.791µs	2.06%	3.686	20.845	0.27%	0.031µs	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	[160.528µs; 160.648µs] or [-0.037%; +0.037%]	None	None	None

Group 10

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	`30a1416`	1773062374	gyuheon0h/PROF-13672-libunwind

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	2.411µs	2.442µs ± 0.025µs	2.435µs ± 0.009µs	2.447µs	2.509µs	2.524µs	2.528µs	3.83%	2.145	4.330	1.00%	0.002µs	1	200

scenario	metric	95% CI mean	Shapiro-Wilk pvalue	Ljung-Box pvalue (lag=1)	Dip test pvalue
tags/replace_trace_tags	execution_time	[2.439µs; 2.446µs] or [-0.139%; +0.139%]	None	None	None

Group 11

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	`30a1416`	1773062374	gyuheon0h/PROF-13672-libunwind

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	3.896µs	3.913µs ± 0.003µs	3.912µs ± 0.002µs	3.914µs	3.918µs	3.921µs	3.928µs	0.39%	0.148	5.979	0.08%	0.000µs	1	200
credit_card/is_card_number/	throughput	254597370.097op/s	255581910.766op/s ± 203891.342op/s	255602159.838op/s ± 122107.723op/s	255705369.791op/s	255854673.982op/s	255918010.118op/s	256685626.187op/s	0.42%	-0.129	6.006	0.08%	14417.295op/s	1	200
credit_card/is_card_number/ 3782-8224-6310-005	execution_time	78.942µs	79.702µs ± 0.389µs	79.660µs ± 0.295µs	79.977µs	80.416µs	80.581µs	80.852µs	1.50%	0.509	-0.306	0.49%	0.028µs	1	200
credit_card/is_card_number/ 3782-8224-6310-005	throughput	12368303.337op/s	12547068.600op/s ± 61164.073op/s	12553388.754op/s ± 46526.213op/s	12598075.961op/s	12632178.308op/s	12645411.525op/s	12667503.861op/s	0.91%	-0.488	-0.339	0.49%	4324.953op/s	1	200
credit_card/is_card_number/ 378282246310005	execution_time	72.345µs	72.892µs ± 0.341µs	72.830µs ± 0.239µs	73.115µs	73.517µs	73.904µs	73.978µs	1.58%	0.765	0.307	0.47%	0.024µs	1	200
credit_card/is_card_number/ 378282246310005	throughput	13517549.452op/s	13719165.677op/s ± 64008.030op/s	13730561.840op/s ± 45113.761op/s	13769406.794op/s	13804032.531op/s	13816962.921op/s	13822737.020op/s	0.67%	-0.741	0.247	0.47%	4526.051op/s	1	200
credit_card/is_card_number/37828224631	execution_time	3.893µs	3.912µs ± 0.003µs	3.911µs ± 0.002µs	3.914µs	3.917µs	3.922µs	3.930µs	0.47%	0.392	10.732	0.08%	0.000µs	1	200
credit_card/is_card_number/37828224631	throughput	254478513.192op/s	255621544.518op/s ± 206722.086op/s	255661946.925op/s ± 100154.435op/s	255734170.936op/s	255851003.907op/s	255906651.960op/s	256871410.735op/s	0.47%	-0.361	10.776	0.08%	14617.459op/s	1	200
credit_card/is_card_number/378282246310005	execution_time	69.221µs	69.654µs ± 0.304µs	69.586µs ± 0.214µs	69.870µs	70.237µs	70.416µs	70.592µs	1.45%	0.717	-0.234	0.44%	0.021µs	1	200
credit_card/is_card_number/378282246310005	throughput	14165937.629op/s	14356980.767op/s ± 62444.688op/s	14370730.426op/s ± 44349.547op/s	14405536.051op/s	14437443.223op/s	14441170.448op/s	14446449.670op/s	0.53%	-0.701	-0.269	0.43%	4415.506op/s	1	200
credit_card/is_card_number/37828224631000521389798	execution_time	52.148µs	52.203µs ± 0.030µs	52.199µs ± 0.018µs	52.222µs	52.258µs	52.289µs	52.311µs	0.21%	0.739	0.450	0.06%	0.002µs	1	200
credit_card/is_card_number/37828224631000521389798	throughput	19116539.102op/s	19155836.885op/s ± 11038.391op/s	19157514.381op/s ± 6665.850op/s	19163609.742op/s	19170595.566op/s	19174918.957op/s	19176091.249op/s	0.10%	-0.736	0.443	0.06%	780.532op/s	1	200
credit_card/is_card_number/x371413321323331	execution_time	6.028µs	6.041µs ± 0.016µs	6.036µs ± 0.004µs	6.041µs	6.074µs	6.094µs	6.148µs	1.85%	3.249	13.859	0.26%	0.001µs	1	200
credit_card/is_card_number/x371413321323331	throughput	162651520.149op/s	165537853.907op/s ± 431715.167op/s	165661914.329op/s ± 110296.058op/s	165763657.394op/s	165835923.269op/s	165879370.842op/s	165894810.276op/s	0.14%	-3.207	13.454	0.26%	30526.872op/s	1	200
credit_card/is_card_number_no_luhn/	execution_time	3.893µs	3.913µs ± 0.003µs	3.913µs ± 0.002µs	3.915µs	3.917µs	3.918µs	3.920µs	0.17%	-1.239	7.489	0.08%	0.000µs	1	200
credit_card/is_card_number_no_luhn/	throughput	255128359.398op/s	255586425.698op/s ± 192473.609op/s	255556351.959op/s ± 134047.087op/s	255735655.948op/s	255833351.856op/s	255910532.993op/s	256843621.911op/s	0.50%	1.257	7.621	0.08%	13609.939op/s	1	200
credit_card/is_card_number_no_luhn/ 3782-8224-6310-005	execution_time	64.200µs	64.504µs ± 0.145µs	64.485µs ± 0.087µs	64.582µs	64.781µs	64.869µs	64.973µs	0.76%	0.697	0.323	0.22%	0.010µs	1	200
credit_card/is_card_number_no_luhn/ 3782-8224-6310-005	throughput	15391116.386op/s	15502956.557op/s ± 34704.793op/s	15507463.862op/s ± 20998.988op/s	15526692.275op/s	15553758.522op/s	15563973.900op/s	15576387.754op/s	0.44%	-0.684	0.303	0.22%	2453.999op/s	1	200
credit_card/is_card_number_no_luhn/ 378282246310005	execution_time	58.206µs	58.444µs ± 0.150µs	58.411µs ± 0.084µs	58.526µs	58.747µs	58.846µs	59.062µs	1.12%	1.147	1.406	0.26%	0.011µs	1	200
credit_card/is_card_number_no_luhn/ 378282246310005	throughput	16931301.931op/s	17110485.146op/s ± 43925.678op/s	17120113.272op/s ± 24549.757op/s	17142308.418op/s	17163260.246op/s	17177973.166op/s	17180235.857op/s	0.35%	-1.131	1.348	0.26%	3106.015op/s	1	200
credit_card/is_card_number_no_luhn/37828224631	execution_time	3.891µs	3.912µs ± 0.003µs	3.911µs ± 0.001µs	3.913µs	3.917µs	3.919µs	3.932µs	0.53%	0.918	15.834	0.08%	0.000µs	1	200
credit_card/is_card_number_no_luhn/37828224631	throughput	254335616.585op/s	255653595.496op/s ± 216508.620op/s	255688046.585op/s ± 96835.628op/s	255776803.380op/s	255851944.073op/s	255888029.452op/s	257000861.259op/s	0.51%	-0.875	15.841	0.08%	15309.471op/s	1	200
credit_card/is_card_number_no_luhn/378282246310005	execution_time	54.565µs	55.061µs ± 0.321µs	55.000µs ± 0.207µs	55.255µs	55.635µs	55.954µs	56.236µs	2.25%	0.874	0.559	0.58%	0.023µs	1	200
credit_card/is_card_number_no_luhn/378282246310005	throughput	17782134.455op/s	18162231.949op/s ± 105282.245op/s	18181868.763op/s ± 68349.034op/s	18235116.860op/s	18298179.791op/s	18314984.683op/s	18326714.852op/s	0.80%	-0.843	0.474	0.58%	7444.579op/s	1	200
credit_card/is_card_number_no_luhn/37828224631000521389798	execution_time	52.147µs	52.224µs ± 0.039µs	52.220µs ± 0.025µs	52.250µs	52.286µs	52.307µs	52.457µs	0.45%	1.229	5.393	0.07%	0.003µs	1	200
credit_card/is_card_number_no_luhn/37828224631000521389798	throughput	19063174.068op/s	19148411.289op/s ± 14217.597op/s	19149808.353op/s ± 9143.876op/s	19158301.478op/s	19167887.272op/s	19174413.356op/s	19176495.370op/s	0.14%	-1.216	5.306	0.07%	1005.336op/s	1	200
credit_card/is_card_number_no_luhn/x371413321323331	execution_time	6.028µs	6.039µs ± 0.015µs	6.034µs ± 0.003µs	6.038µs	6.072µs	6.107µs	6.112µs	1.30%	2.792	8.074	0.25%	0.001µs	1	200
credit_card/is_card_number_no_luhn/x371413321323331	throughput	163607056.727op/s	165579156.856op/s ± 407336.175op/s	165726590.832op/s ± 79001.728op/s	165781494.039op/s	165837033.629op/s	165859358.847op/s	165885924.945op/s	0.10%	-2.775	7.951	0.25%	28803.017op/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	[3.912µs; 3.913µs] or [-0.011%; +0.011%]	None	None	None
credit_card/is_card_number/	throughput	[255553653.387op/s; 255610168.146op/s] or [-0.011%; +0.011%]	None	None	None
credit_card/is_card_number/ 3782-8224-6310-005	execution_time	[79.648µs; 79.756µs] or [-0.068%; +0.068%]	None	None	None
credit_card/is_card_number/ 3782-8224-6310-005	throughput	[12538591.848op/s; 12555545.352op/s] or [-0.068%; +0.068%]	None	None	None
credit_card/is_card_number/ 378282246310005	execution_time	[72.845µs; 72.940µs] or [-0.065%; +0.065%]	None	None	None
credit_card/is_card_number/ 378282246310005	throughput	[13710294.780op/s; 13728036.575op/s] or [-0.065%; +0.065%]	None	None	None
credit_card/is_card_number/37828224631	execution_time	[3.912µs; 3.912µs] or [-0.011%; +0.011%]	None	None	None
credit_card/is_card_number/37828224631	throughput	[255592894.825op/s; 255650194.211op/s] or [-0.011%; +0.011%]	None	None	None
credit_card/is_card_number/378282246310005	execution_time	[69.612µs; 69.696µs] or [-0.060%; +0.060%]	None	None	None
credit_card/is_card_number/378282246310005	throughput	[14348326.534op/s; 14365635.001op/s] or [-0.060%; +0.060%]	None	None	None
credit_card/is_card_number/37828224631000521389798	execution_time	[52.199µs; 52.208µs] or [-0.008%; +0.008%]	None	None	None
credit_card/is_card_number/37828224631000521389798	throughput	[19154307.070op/s; 19157366.699op/s] or [-0.008%; +0.008%]	None	None	None
credit_card/is_card_number/x371413321323331	execution_time	[6.039µs; 6.043µs] or [-0.036%; +0.036%]	None	None	None
credit_card/is_card_number/x371413321323331	throughput	[165478022.337op/s; 165597685.477op/s] or [-0.036%; +0.036%]	None	None	None
credit_card/is_card_number_no_luhn/	execution_time	[3.912µs; 3.913µs] or [-0.010%; +0.010%]	None	None	None
credit_card/is_card_number_no_luhn/	throughput	[255559750.707op/s; 255613100.689op/s] or [-0.010%; +0.010%]	None	None	None
credit_card/is_card_number_no_luhn/ 3782-8224-6310-005	execution_time	[64.484µs; 64.524µs] or [-0.031%; +0.031%]	None	None	None
credit_card/is_card_number_no_luhn/ 3782-8224-6310-005	throughput	[15498146.806op/s; 15507766.307op/s] or [-0.031%; +0.031%]	None	None	None
credit_card/is_card_number_no_luhn/ 378282246310005	execution_time	[58.423µs; 58.465µs] or [-0.036%; +0.036%]	None	None	None
credit_card/is_card_number_no_luhn/ 378282246310005	throughput	[17104397.469op/s; 17116572.823op/s] or [-0.036%; +0.036%]	None	None	None
credit_card/is_card_number_no_luhn/37828224631	execution_time	[3.911µs; 3.912µs] or [-0.012%; +0.012%]	None	None	None
credit_card/is_card_number_no_luhn/37828224631	throughput	[255623589.483op/s; 255683601.508op/s] or [-0.012%; +0.012%]	None	None	None
credit_card/is_card_number_no_luhn/378282246310005	execution_time	[55.017µs; 55.106µs] or [-0.081%; +0.081%]	None	None	None
credit_card/is_card_number_no_luhn/378282246310005	throughput	[18147640.842op/s; 18176823.055op/s] or [-0.080%; +0.080%]	None	None	None
credit_card/is_card_number_no_luhn/37828224631000521389798	execution_time	[52.218µs; 52.229µs] or [-0.010%; +0.010%]	None	None	None
credit_card/is_card_number_no_luhn/37828224631000521389798	throughput	[19146440.867op/s; 19150381.711op/s] or [-0.010%; +0.010%]	None	None	None
credit_card/is_card_number_no_luhn/x371413321323331	execution_time	[6.037µs; 6.042µs] or [-0.034%; +0.034%]	None	None	None
credit_card/is_card_number_no_luhn/x371413321323331	throughput	[165522703.979op/s; 165635609.732op/s] or [-0.034%; +0.034%]	None	None	None

Group 12

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	`30a1416`	1773062374	gyuheon0h/PROF-13672-libunwind

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	18.020µs	26.546µs ± 10.294µs	18.454µs ± 0.245µs	34.464µs	44.110µs	53.483µs	77.621µs	320.62%	1.300	2.706	38.68%	0.728µs	1	200

scenario	metric	95% CI mean	Shapiro-Wilk pvalue	Ljung-Box pvalue (lag=1)	Dip test pvalue
two way interface	execution_time	[25.120µs; 27.973µs] or [-5.374%; +5.374%]	None	None	None

Group 13

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	`30a1416`	1773062374	gyuheon0h/PROF-13672-libunwind

scenario	metric	min	mean ± sd	median ± mad	p75	p95	p99	max	peak_to_median_ratio	skewness	kurtosis	cv	sem	runs	sample_size
benching serializing traces from their internal representation to msgpack	execution_time	14.002ms	14.048ms ± 0.030ms	14.042ms ± 0.011ms	14.055ms	14.086ms	14.168ms	14.224ms	1.29%	2.825	11.054	0.21%	0.002ms	1	200

scenario	metric	95% CI mean	Shapiro-Wilk pvalue	Ljung-Box pvalue (lag=1)	Dip test pvalue
benching serializing traces from their internal representation to msgpack	execution_time	[14.043ms; 14.052ms] or [-0.029%; +0.029%]	None	None	None

Group 14

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	`30a1416`	1773062374	gyuheon0h/PROF-13672-libunwind

scenario	metric	min	mean ± sd	median ± mad	p75	p95	p99	max	peak_to_median_ratio	skewness	kurtosis	cv	sem	runs	sample_size
profile_add_sample2_frames_x1000	execution_time	730.510µs	731.793µs ± 0.623µs	731.688µs ± 0.303µs	732.096µs	732.640µs	732.904µs	737.462µs	0.79%	3.893	32.623	0.08%	0.044µs	1	200

scenario	metric	95% CI mean	Shapiro-Wilk pvalue	Ljung-Box pvalue (lag=1)	Dip test pvalue
profile_add_sample2_frames_x1000	execution_time	[731.707µs; 731.879µs] or [-0.012%; +0.012%]	None	None	None

Group 15

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	`30a1416`	1773062374	gyuheon0h/PROF-13672-libunwind

scenario	metric	min	mean ± sd	median ± mad	p75	p95	p99	max	peak_to_median_ratio	skewness	kurtosis	cv	sem	runs	sample_size
single_flag_killswitch/rules-based	execution_time	187.501ns	189.612ns ± 1.749ns	189.587ns ± 1.418ns	190.653ns	192.775ns	194.983ns	196.289ns	3.54%	0.969	0.879	0.92%	0.124ns	1	200

scenario	metric	95% CI mean	Shapiro-Wilk pvalue	Ljung-Box pvalue (lag=1)	Dip test pvalue
single_flag_killswitch/rules-based	execution_time	[189.369ns; 189.854ns] or [-0.128%; +0.128%]	None	None	None

Group 16

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	`30a1416`	1773062374	gyuheon0h/PROF-13672-libunwind

scenario	metric	min	mean ± sd	median ± mad	p75	p95	p99	max	peak_to_median_ratio	skewness	kurtosis	cv	sem	runs	sample_size
ip_address/quantize_peer_ip_address_benchmark	execution_time	4.930µs	4.997µs ± 0.036µs	4.992µs ± 0.013µs	5.005µs	5.064µs	5.068µs	5.070µs	1.57%	0.535	-0.522	0.72%	0.003µs	1	200

scenario	metric	95% CI mean	Shapiro-Wilk pvalue	Ljung-Box pvalue (lag=1)	Dip test pvalue
ip_address/quantize_peer_ip_address_benchmark	execution_time	[4.992µs; 5.002µs] or [-0.100%; +0.100%]	None	None	None

Group 17

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	`30a1416`	1773062374	gyuheon0h/PROF-13672-libunwind

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	10.622ms	10.654ms ± 0.017ms	10.652ms ± 0.010ms	10.662ms	10.678ms	10.701ms	10.766ms	1.07%	1.891	9.645	0.16%	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	[10.651ms; 10.656ms] or [-0.022%; +0.022%]	None	None	None

Group 18

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	`30a1416`	1773062374	gyuheon0h/PROF-13672-libunwind

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	185.354µs	185.769µs ± 0.235µs	185.751µs ± 0.202µs	185.954µs	186.166µs	186.237µs	186.369µs	0.33%	0.278	-0.936	0.13%	0.017µs	1	200
normalization/normalize_name/normalize_name/Too-Long-.Too-Long-.Too-Long-.Too-Long-.Too-Long-.Too-Lo...	throughput	5365687.715op/s	5383048.130op/s ± 6810.743op/s	5383556.535op/s ± 5834.407op/s	5389301.953op/s	5392414.678op/s	5394130.819op/s	5395073.111op/s	0.21%	-0.274	-0.940	0.13%	481.592op/s	1	200
normalization/normalize_name/normalize_name/bad-name	execution_time	17.903µs	18.004µs ± 0.051µs	17.998µs ± 0.037µs	18.039µs	18.095µs	18.116µs	18.166µs	0.94%	0.466	-0.351	0.28%	0.004µs	1	200
normalization/normalize_name/normalize_name/bad-name	throughput	55048044.453op/s	55545058.194op/s ± 158348.233op/s	55563220.804op/s ± 115219.828op/s	55670698.033op/s	55773944.927op/s	55807665.882op/s	55856219.520op/s	0.53%	-0.454	-0.369	0.28%	11196.911op/s	1	200
normalization/normalize_name/normalize_name/good	execution_time	10.315µs	10.409µs ± 0.047µs	10.405µs ± 0.036µs	10.443µs	10.485µs	10.512µs	10.526µs	1.16%	0.249	-0.705	0.45%	0.003µs	1	200
normalization/normalize_name/normalize_name/good	throughput	95002234.712op/s	96076164.021op/s ± 430924.532op/s	96107885.915op/s ± 328372.474op/s	96414372.061op/s	96700661.352op/s	96917397.531op/s	96946337.265op/s	0.87%	-0.233	-0.718	0.45%	30470.966op/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	[185.736µs; 185.801µs] or [-0.018%; +0.018%]	None	None	None
normalization/normalize_name/normalize_name/Too-Long-.Too-Long-.Too-Long-.Too-Long-.Too-Long-.Too-Lo...	throughput	[5382104.226op/s; 5383992.033op/s] or [-0.018%; +0.018%]	None	None	None
normalization/normalize_name/normalize_name/bad-name	execution_time	[17.996µs; 18.011µs] or [-0.040%; +0.040%]	None	None	None
normalization/normalize_name/normalize_name/bad-name	throughput	[55523112.651op/s; 55567003.736op/s] or [-0.040%; +0.040%]	None	None	None
normalization/normalize_name/normalize_name/good	execution_time	[10.402µs; 10.415µs] or [-0.062%; +0.062%]	None	None	None
normalization/normalize_name/normalize_name/good	throughput	[96016442.026op/s; 96135886.017op/s] or [-0.062%; +0.062%]	None	None	None

Group 19

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	`30a1416`	1773062374	gyuheon0h/PROF-13672-libunwind

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	86.152µs	86.405µs ± 0.117µs	86.388µs ± 0.046µs	86.440µs	86.545µs	86.658µs	87.560µs	1.36%	5.067	46.764	0.13%	0.008µs	1	200

scenario	metric	95% CI mean	Shapiro-Wilk pvalue	Ljung-Box pvalue (lag=1)	Dip test pvalue
sql/obfuscate_sql_string	execution_time	[86.389µs; 86.421µs] or [-0.019%; +0.019%]	None	None	None

Baseline

Omitted due to size.

gyuheon0h · 2026-03-06T05:21:07Z

libdd-crashtracker/src/collector/emitters.rs

        assert!(out.contains("\"file\":\"test_file2\""));
    }

-    #[test]


unwinding specific logic with libunwind is tested in the libdd-libunwind-sys crate. No need to replicate those tests here. I test edge cases with ucontext here, however.

gleocadie

Only misusage, and questions.
Otherwise LGTM

libdd-crashtracker/src/collector/emitters.rs

# What does this PR do? Bump to 29.0.0 [feat(profiling)!: add Tracepoint sample type](#1676) [feat(obfuscation/redis): Reach feature parity on redis obfuscation [APMSP-2668]](#1632) [fix(sidecar): Handle backpressure more gracefully](#1682) [feat(trace-protobuf)!: Add two fields to ClientGroupedStats [SVLS-8627]](#1630) [chore: exclude libdatadog from ADMS auto generated PRs for dependency updates](#1688) [chore(ci): run crashtracking ffi example tests in CI](#1687) [fix(crashtracking): use libunwind to unwind frames](#1663) [feat: publish tracer metadata as OTel process ctx](#1658) [ci: run thread count test in own process](#1693) [feat(obfuscation/json): Init json obfuscation [APMSP-2665]](#1635) [chore(ci): add final_status property on junit XML [APMSP-2610]](#1681) [refactor(data-pipeline-ffi): move macro definitions for better reuse](#1699) [fix(obfuscation/memcached): fuzzing fix](#1695) [ci: replace use of cargo cross for centos7 tests](#1675) #1702 (comment) [feat(stats_exporter)!: add process tags to CSS payloads](#1709) # Motivation I mainly am creating this to use the new unwinding from ucontext for crashtracking # Additional Notes Anything else we should know when reviewing? # How to test the change? Describe here in detail how the change can be validated. [APMSP-2668]: https://datadoghq.atlassian.net/browse/APMSP-2668?atlOrigin=eyJpIjoiNWRkNTljNzYxNjVmNDY3MDlhMDU5Y2ZhYzA5YTRkZjUiLCJwIjoiZ2l0aHViLWNvbS1KU1cifQ [SVLS-8627]: https://datadoghq.atlassian.net/browse/SVLS-8627?atlOrigin=eyJpIjoiNWRkNTljNzYxNjVmNDY3MDlhMDU5Y2ZhYzA5YTRkZjUiLCJwIjoiZ2l0aHViLWNvbS1KU1cifQ [APMSP-2665]: https://datadoghq.atlassian.net/browse/APMSP-2665?atlOrigin=eyJpIjoiNWRkNTljNzYxNjVmNDY3MDlhMDU5Y2ZhYzA5YTRkZjUiLCJwIjoiZ2l0aHViLWNvbS1KU1cifQ Co-authored-by: gyuheon.oh <gyuheon.oh@datadoghq.com>

gyuheon0h force-pushed the gyuheon0h/PROF-13672-libunwind branch from db27cac to 12d5692 Compare March 5, 2026 16:48

gyuheon0h changed the title ~~libunwind~~ [dont review; WIP] libunwind Mar 5, 2026

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gyuheon0h changed the title ~~[dont review; WIP] libunwind~~ feat(crashtracking): use libunwind to unwind frames Mar 5, 2026

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gyuheon0h changed the title ~~feat(crashtracking): use libunwind to unwind frames~~ fix(crashtracking): use libunwind to unwind frames Mar 5, 2026

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gyuheon0h mentioned this pull request Mar 11, 2026

chore(cargo): bump to 29.0.0 #1702

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scenario:benching deserializing traces from msgpack to their internal representation

scenario:receiver_entry_point/report/2598

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