[profiling] add ffi for crossbeam::ArrayQueue

[taegyunkim]

What does this PR do?

Adds ffi for crossbeam::ArrayQueue<*mut c_void>

Motivation

Python profiler allocates a new Sample whenever a it collects an event (stack/memory/lock). Then, the Sample is freed right after. Code for new/delete Sample is here. This results in calling new/delete a lot and creates some memory pressure to the system and shows up on native profiler. Frequent calls to new/delete can be avoided if we use a pool of Samples. And this ArrayQueue will be used to implement the pool.

Another option we considered is using mutex guarded vector in C++ in dd-trace-py. However, it would be little tricky to handle fork() if we use a lock. So we decided to use lock-free list/queue/stack.

Additional Notes

Anything else we should know when reviewing?

How to test the change?

Describe here in detail how the change can be validated.

[pr-commenter]

Benchmarks

Comparison

Benchmark execution time: 2024-08-01 18:55:43

Comparing candidate commit 2b03b84 in PR branch taegyunkim/prof-10011-arrayqueue with baseline commit d7e8fee in branch main.

Found 0 performance improvements and 1 performance regressions! Performance is the same for 41 metrics, 2 unstable metrics.

scenario:tags/replace_trace_tags

• 🟥 execution_time [+72.452ns; +75.139ns] or [+3.120%; +3.235%]

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	2b03b84	1722537638	taegyunkim/prof-10011-arrayqueue

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	1.475µs	2.930µs ± 1.842µs	2.759µs ± 0.015µs	2.774µs	2.964µs	3.807µs	24.478µs	787.05%	10.291	108.669	62.71%	0.130µs	1	200

scenario	metric	95% CI mean	Shapiro-Wilk pvalue	Ljung-Box pvalue (lag=1)	Dip test pvalue
write only interface	execution_time	[2.674µs; 3.185µs] or [-8.712%; +8.712%]	None	None	None

Group 2

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	2b03b84	1722537638	taegyunkim/prof-10011-arrayqueue

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	17.071µs	37.263µs ± 32.234µs	37.583µs ± 3.277µs	40.404µs	50.725µs	59.551µs	462.813µs	1131.43%	11.611	150.566	86.29%	2.279µs	1	200

scenario	metric	95% CI mean	Shapiro-Wilk pvalue	Ljung-Box pvalue (lag=1)	Dip test pvalue
two way interface	execution_time	[32.796µs; 41.730µs] or [-11.989%; +11.989%]	None	None	None

Group 3

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	2b03b84	1722537638	taegyunkim/prof-10011-arrayqueue

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	36.816µs	36.897µs ± 0.040µs	36.890µs ± 0.019µs	36.915µs	36.943µs	37.001µs	37.256µs	0.99%	4.285	33.841	0.11%	0.003µs	1	200

scenario	metric	95% CI mean	Shapiro-Wilk pvalue	Ljung-Box pvalue (lag=1)	Dip test pvalue
redis/obfuscate_redis_string	execution_time	[36.892µs; 36.903µs] or [-0.015%; +0.015%]	None	None	None

Group 4

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	2b03b84	1722537638	taegyunkim/prof-10011-arrayqueue

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	70.157µs	70.331µs ± 0.113µs	70.318µs ± 0.035µs	70.356µs	70.405µs	70.540µs	71.419µs	1.57%	6.887	59.158	0.16%	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	[70.315µs; 70.346µs] or [-0.022%; +0.022%]	None	None	None

Group 5

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	2b03b84	1722537638	taegyunkim/prof-10011-arrayqueue

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	320.375ns	330.748ns ± 8.517ns	330.669ns ± 1.305ns	331.665ns	335.944ns	340.520ns	439.476ns	32.91%	10.479	131.291	2.57%	0.602ns	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	[329.568ns; 331.929ns] or [-0.357%; +0.357%]	None	None	None

Group 6

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	2b03b84	1722537638	taegyunkim/prof-10011-arrayqueue

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	1.653µs	1.655µs ± 0.001µs	1.655µs ± 0.000µs	1.656µs	1.656µs	1.658µs	1.661µs	0.34%	3.086	21.781	0.04%	0.000µs	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	[1.655µs; 1.655µs] or [-0.006%; +0.006%]	None	None	None

Group 7

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	2b03b84	1722537638	taegyunkim/prof-10011-arrayqueue

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	279.923ns	281.951ns ± 0.430ns	281.966ns ± 0.127ns	282.091ns	282.295ns	283.042ns	285.659ns	1.31%	2.982	30.970	0.15%	0.030ns	1	200
normalization/normalize_name/normalize_name/bad-name	execution_time	33.620ns	34.386ns ± 0.426ns	34.368ns ± 0.223ns	34.571ns	34.926ns	35.391ns	37.563ns	9.29%	2.345	15.060	1.24%	0.030ns	1	200
normalization/normalize_name/normalize_name/good	execution_time	21.354ns	21.844ns ± 0.163ns	21.798ns ± 0.080ns	21.917ns	22.125ns	22.338ns	22.524ns	3.33%	0.966	2.431	0.74%	0.011ns	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	[281.891ns; 282.010ns] or [-0.021%; +0.021%]	None	None	None
normalization/normalize_name/normalize_name/bad-name	execution_time	[34.327ns; 34.445ns] or [-0.172%; +0.172%]	None	None	None
normalization/normalize_name/normalize_name/good	execution_time	[21.821ns; 21.866ns] or [-0.103%; +0.103%]	None	None	None

Group 8

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	2b03b84	1722537638	taegyunkim/prof-10011-arrayqueue

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	578.465ns	591.567ns ± 5.839ns	591.594ns ± 3.787ns	595.369ns	600.404ns	605.684ns	613.664ns	3.73%	0.181	0.552	0.98%	0.413ns	1	200
normalization/normalize_service/normalize_service/Data🐨dog🐶 繋がっ⛰てて	execution_time	439.955ns	453.993ns ± 3.635ns	454.975ns ± 0.321ns	455.239ns	455.510ns	457.411ns	461.825ns	1.51%	-3.105	8.764	0.80%	0.257ns	1	200
normalization/normalize_service/normalize_service/Test Conversion 0f Weird !@#$%^&**() Characters	execution_time	192.866ns	201.725ns ± 3.513ns	201.435ns ± 2.696ns	204.140ns	206.024ns	212.711ns	214.982ns	6.73%	0.398	1.309	1.74%	0.248ns	1	200
normalization/normalize_service/normalize_service/[empty string]	execution_time	36.997ns	43.382ns ± 7.144ns	40.651ns ± 2.979ns	46.666ns	58.857ns	59.061ns	59.330ns	45.95%	1.327	0.427	16.43%	0.505ns	1	200
normalization/normalize_service/normalize_service/test_ASCII	execution_time	62.557ns	69.873ns ± 5.637ns	67.967ns ± 2.819ns	69.397ns	80.405ns	80.905ns	81.525ns	19.95%	0.941	-0.619	8.05%	0.399ns	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	[590.758ns; 592.376ns] or [-0.137%; +0.137%]	None	None	None
normalization/normalize_service/normalize_service/Data🐨dog🐶 繋がっ⛰てて	execution_time	[453.489ns; 454.497ns] or [-0.111%; +0.111%]	None	None	None
normalization/normalize_service/normalize_service/Test Conversion 0f Weird !@#$%^&**() Characters	execution_time	[201.238ns; 202.212ns] or [-0.241%; +0.241%]	None	None	None
normalization/normalize_service/normalize_service/[empty string]	execution_time	[42.391ns; 44.372ns] or [-2.282%; +2.282%]	None	None	None
normalization/normalize_service/normalize_service/test_ASCII	execution_time	[69.092ns; 70.654ns] or [-1.118%; +1.118%]	None	None	None

Group 9

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	2b03b84	1722537638	taegyunkim/prof-10011-arrayqueue

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	3.251ns	3.427ns ± 0.017ns	3.429ns ± 0.001ns	3.429ns	3.431ns	3.435ns	3.438ns	0.29%	-9.754	94.386	0.49%	0.001ns	1	200
credit_card/is_card_number/	throughput	290827043.958op/s	291811793.232op/s ± 1515358.960op/s	291671246.534op/s ± 72996.708op/s	291746187.332op/s	291880823.319op/s	292094997.884op/s	307628049.375op/s	5.47%	9.773	94.683	0.52%	107152.060op/s	1	200
credit_card/is_card_number/ 3782-8224-6310-005	execution_time	85.215ns	87.353ns ± 0.967ns	87.221ns ± 0.518ns	87.819ns	88.829ns	90.367ns	92.435ns	5.98%	1.266	4.129	1.10%	0.068ns	1	200
credit_card/is_card_number/ 3782-8224-6310-005	throughput	10818468.069op/s	11449229.714op/s ± 125141.338op/s	11465177.487op/s ± 68103.005op/s	11523884.706op/s	11631931.670op/s	11713759.422op/s	11734957.416op/s	2.35%	-1.122	3.496	1.09%	8848.829op/s	1	200
credit_card/is_card_number/ 378282246310005	execution_time	80.626ns	82.503ns ± 0.831ns	82.435ns ± 0.485ns	82.938ns	83.883ns	84.805ns	86.543ns	4.98%	0.935	2.764	1.00%	0.059ns	1	200
credit_card/is_card_number/ 378282246310005	throughput	11554915.519op/s	12121947.054op/s ± 121029.304op/s	12130810.956op/s ± 71740.822op/s	12199073.575op/s	12310133.068op/s	12399689.086op/s	12402939.568op/s	2.24%	-0.821	2.362	1.00%	8558.064op/s	1	200
credit_card/is_card_number/37828224631	execution_time	3.267ns	3.427ns ± 0.016ns	3.429ns ± 0.001ns	3.430ns	3.432ns	3.445ns	3.471ns	1.24%	-8.926	84.661	0.48%	0.001ns	1	200
credit_card/is_card_number/37828224631	throughput	288091970.936op/s	291766102.404op/s ± 1458745.111op/s	291662919.421op/s ± 108175.112op/s	291764949.221op/s	291896253.498op/s	292222210.027op/s	306048261.262op/s	4.93%	9.023	85.652	0.50%	103148.856op/s	1	200
credit_card/is_card_number/378282246310005	execution_time	77.862ns	80.258ns ± 0.857ns	80.192ns ± 0.452ns	80.691ns	81.763ns	82.715ns	83.216ns	3.77%	0.491	1.583	1.07%	0.061ns	1	200
credit_card/is_card_number/378282246310005	throughput	12016980.715op/s	12461270.786op/s ± 132442.361op/s	12470011.697op/s ± 70331.451op/s	12531773.895op/s	12660289.195op/s	12819842.258op/s	12843251.593op/s	2.99%	-0.384	1.500	1.06%	9365.089op/s	1	200
credit_card/is_card_number/37828224631000521389798	execution_time	67.320ns	68.201ns ± 0.338ns	68.202ns ± 0.180ns	68.374ns	68.667ns	69.110ns	70.056ns	2.72%	0.774	4.503	0.49%	0.024ns	1	200
credit_card/is_card_number/37828224631000521389798	throughput	14274246.489op/s	14662869.638op/s ± 72412.302op/s	14662337.933op/s ± 38820.248op/s	14702531.006op/s	14790746.078op/s	14840538.393op/s	14854374.113op/s	1.31%	-0.688	4.152	0.49%	5120.323op/s	1	200
credit_card/is_card_number/x371413321323331	execution_time	21.318ns	22.514ns ± 0.419ns	22.472ns ± 0.262ns	22.754ns	23.250ns	23.644ns	24.001ns	6.80%	0.470	0.742	1.86%	0.030ns	1	200
credit_card/is_card_number/x371413321323331	throughput	41664319.222op/s	44432145.895op/s ± 821180.187op/s	44499115.716op/s ± 521890.126op/s	44988519.443op/s	45656172.375op/s	46002981.535op/s	46909127.045op/s	5.42%	-0.332	0.571	1.84%	58066.208op/s	1	200
credit_card/is_card_number_no_luhn/	execution_time	3.263ns	3.429ns ± 0.016ns	3.431ns ± 0.000ns	3.431ns	3.432ns	3.433ns	3.439ns	0.24%	-9.779	94.261	0.48%	0.001ns	1	200
credit_card/is_card_number_no_luhn/	throughput	290769487.431op/s	291623998.492op/s ± 1460816.063op/s	291475239.194op/s ± 40830.266op/s	291518687.659op/s	291639518.138op/s	292020535.945op/s	306505068.610op/s	5.16%	9.788	94.391	0.50%	103295.294op/s	1	200
credit_card/is_card_number_no_luhn/ 3782-8224-6310-005	execution_time	66.802ns	67.900ns ± 0.544ns	67.870ns ± 0.291ns	68.133ns	68.856ns	69.441ns	71.076ns	4.72%	1.366	5.589	0.80%	0.038ns	1	200
credit_card/is_card_number_no_luhn/ 3782-8224-6310-005	throughput	14069541.129op/s	14728444.993op/s ± 116706.988op/s	14734005.403op/s ± 63344.568op/s	14804220.512op/s	14886060.921op/s	14959961.802op/s	14969608.371op/s	1.60%	-1.234	4.860	0.79%	8252.430op/s	1	200
credit_card/is_card_number_no_luhn/ 378282246310005	execution_time	62.166ns	62.986ns ± 0.377ns	62.953ns ± 0.206ns	63.164ns	63.753ns	63.952ns	64.202ns	1.98%	0.544	0.565	0.60%	0.027ns	1	200
credit_card/is_card_number_no_luhn/ 378282246310005	throughput	15575857.639op/s	15877155.621op/s ± 94813.755op/s	15884904.666op/s ± 51808.716op/s	15933851.849op/s	16015128.524op/s	16081149.903op/s	16085949.934op/s	1.27%	-0.503	0.521	0.60%	6704.345op/s	1	200
credit_card/is_card_number_no_luhn/37828224631	execution_time	3.263ns	3.429ns ± 0.016ns	3.431ns ± 0.000ns	3.431ns	3.433ns	3.437ns	3.441ns	0.28%	-9.729	93.610	0.48%	0.001ns	1	200
credit_card/is_card_number_no_luhn/37828224631	throughput	290650504.273op/s	291612130.595op/s ± 1459908.228op/s	291476546.778op/s ± 41525.818op/s	291516285.294op/s	291648595.732op/s	291975776.138op/s	306434844.348op/s	5.13%	9.743	93.792	0.50%	103231.101op/s	1	200
credit_card/is_card_number_no_luhn/378282246310005	execution_time	58.802ns	60.753ns ± 0.495ns	60.752ns ± 0.242ns	61.003ns	61.347ns	62.069ns	63.010ns	3.72%	0.147	4.587	0.81%	0.035ns	1	200
credit_card/is_card_number_no_luhn/378282246310005	throughput	15870478.126op/s	16461229.965op/s ± 134079.404op/s	16460247.225op/s ± 65721.325op/s	16522881.392op/s	16683193.284op/s	16778908.389op/s	17006266.994op/s	3.32%	0.012	4.496	0.81%	9480.846op/s	1	200
credit_card/is_card_number_no_luhn/37828224631000521389798	execution_time	66.402ns	67.341ns ± 0.450ns	67.355ns ± 0.215ns	67.565ns	67.697ns	68.119ns	71.726ns	6.49%	4.327	43.644	0.67%	0.032ns	1	200
credit_card/is_card_number_no_luhn/37828224631000521389798	throughput	13941899.944op/s	14850412.006op/s ± 96625.083op/s	14846702.120op/s ± 47490.560op/s	14894414.522op/s	14998561.586op/s	15058787.924op/s	15059725.223op/s	1.43%	-3.813	37.748	0.65%	6832.425op/s	1	200
credit_card/is_card_number_no_luhn/x371413321323331	execution_time	20.975ns	22.116ns ± 0.418ns	22.060ns ± 0.211ns	22.307ns	22.753ns	23.605ns	24.193ns	9.67%	1.418	5.074	1.89%	0.030ns	1	200
credit_card/is_card_number_no_luhn/x371413321323331	throughput	41333901.188op/s	45231671.410op/s ± 835104.219op/s	45330985.901op/s ± 436168.363op/s	45683523.086op/s	46279010.534op/s	46868779.181op/s	47676128.059op/s	5.17%	-1.144	4.051	1.84%	59050.786op/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	[3.425ns; 3.429ns] or [-0.069%; +0.069%]	None	None	None
credit_card/is_card_number/	throughput	[291601779.055op/s; 292021807.410op/s] or [-0.072%; +0.072%]	None	None	None
credit_card/is_card_number/ 3782-8224-6310-005	execution_time	[87.219ns; 87.487ns] or [-0.153%; +0.153%]	None	None	None
credit_card/is_card_number/ 3782-8224-6310-005	throughput	[11431886.328op/s; 11466573.100op/s] or [-0.151%; +0.151%]	None	None	None
credit_card/is_card_number/ 378282246310005	execution_time	[82.388ns; 82.618ns] or [-0.140%; +0.140%]	None	None	None
credit_card/is_card_number/ 378282246310005	throughput	[12105173.556op/s; 12138720.551op/s] or [-0.138%; +0.138%]	None	None	None
credit_card/is_card_number/37828224631	execution_time	[3.425ns; 3.430ns] or [-0.066%; +0.066%]	None	None	None
credit_card/is_card_number/37828224631	throughput	[291563934.361op/s; 291968270.447op/s] or [-0.069%; +0.069%]	None	None	None
credit_card/is_card_number/378282246310005	execution_time	[80.139ns; 80.376ns] or [-0.148%; +0.148%]	None	None	None
credit_card/is_card_number/378282246310005	throughput	[12442915.548op/s; 12479626.023op/s] or [-0.147%; +0.147%]	None	None	None
credit_card/is_card_number/37828224631000521389798	execution_time	[68.154ns; 68.248ns] or [-0.069%; +0.069%]	None	None	None
credit_card/is_card_number/37828224631000521389798	throughput	[14652833.990op/s; 14672905.287op/s] or [-0.068%; +0.068%]	None	None	None
credit_card/is_card_number/x371413321323331	execution_time	[22.456ns; 22.572ns] or [-0.258%; +0.258%]	None	None	None
credit_card/is_card_number/x371413321323331	throughput	[44318338.219op/s; 44545953.571op/s] or [-0.256%; +0.256%]	None	None	None
credit_card/is_card_number_no_luhn/	execution_time	[3.427ns; 3.431ns] or [-0.066%; +0.066%]	None	None	None
credit_card/is_card_number_no_luhn/	throughput	[291421543.435op/s; 291826453.549op/s] or [-0.069%; +0.069%]	None	None	None
credit_card/is_card_number_no_luhn/ 3782-8224-6310-005	execution_time	[67.825ns; 67.975ns] or [-0.111%; +0.111%]	None	None	None
credit_card/is_card_number_no_luhn/ 3782-8224-6310-005	throughput	[14712270.526op/s; 14744619.459op/s] or [-0.110%; +0.110%]	None	None	None
credit_card/is_card_number_no_luhn/ 378282246310005	execution_time	[62.934ns; 63.038ns] or [-0.083%; +0.083%]	None	None	None
credit_card/is_card_number_no_luhn/ 378282246310005	throughput	[15864015.346op/s; 15890295.895op/s] or [-0.083%; +0.083%]	None	None	None
credit_card/is_card_number_no_luhn/37828224631	execution_time	[3.427ns; 3.432ns] or [-0.066%; +0.066%]	None	None	None
credit_card/is_card_number_no_luhn/37828224631	throughput	[291409801.355op/s; 291814459.834op/s] or [-0.069%; +0.069%]	None	None	None
credit_card/is_card_number_no_luhn/378282246310005	execution_time	[60.684ns; 60.821ns] or [-0.113%; +0.113%]	None	None	None
credit_card/is_card_number_no_luhn/378282246310005	throughput	[16442647.849op/s; 16479812.080op/s] or [-0.113%; +0.113%]	None	None	None
credit_card/is_card_number_no_luhn/37828224631000521389798	execution_time	[67.279ns; 67.403ns] or [-0.093%; +0.093%]	None	None	None
credit_card/is_card_number_no_luhn/37828224631000521389798	throughput	[14837020.699op/s; 14863803.314op/s] or [-0.090%; +0.090%]	None	None	None
credit_card/is_card_number_no_luhn/x371413321323331	execution_time	[22.058ns; 22.174ns] or [-0.262%; +0.262%]	None	None	None
credit_card/is_card_number_no_luhn/x371413321323331	throughput	[45115933.997op/s; 45347408.823op/s] or [-0.256%; +0.256%]	None	None	None

Group 10

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	2b03b84	1722537638	taegyunkim/prof-10011-arrayqueue

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	2.386µs	2.396µs ± 0.006µs	2.396µs ± 0.004µs	2.399µs	2.407µs	2.412µs	2.413µs	0.72%	0.679	0.295	0.23%	0.000µs	1	200

scenario	metric	95% CI mean	Shapiro-Wilk pvalue	Ljung-Box pvalue (lag=1)	Dip test pvalue
tags/replace_trace_tags	execution_time	[2.395µs; 2.397µs] or [-0.032%; +0.032%]	None	None	None

Group 11

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	2b03b84	1722537638	taegyunkim/prof-10011-arrayqueue

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	137.973µs	138.302µs ± 0.196µs	138.284µs ± 0.078µs	138.347µs	138.574µs	138.895µs	139.722µs	1.04%	3.428	19.900	0.14%	0.014µs	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	[138.274µs; 138.329µs] or [-0.020%; +0.020%]	None	None	None

Baseline

Omitted due to size.

[datadog-datadog-prod-us1]

Library Vulnerabilities

✅ No library vulnerabilities found (scanned 5d0d2e3).

[codecov-commenter]

Codecov Report

❌ Patch coverage is 67.80303% with 85 lines in your changes missing coverage. Please review.
✅ Project coverage is 70.22%. Comparing base (d7e8fee) to head (2b03b84).
⚠️ Report is 1042 commits behind head on main.

Additional details and impacted files

@@            Coverage Diff             @@
##             main     #538      +/-   ##
==========================================
- Coverage   70.22%   70.22%   -0.01%     
==========================================
  Files         213      214       +1     
  Lines       28549    28813     +264     
==========================================
+ Hits        20048    20233     +185     
- Misses       8501     8580      +79     

Components	Coverage Δ
crashtracker	21.17% <ø> (ø)
datadog-alloc	98.73% <ø> (ø)
data-pipeline	50.00% <ø> (ø)
data-pipeline-ffi	0.00% <ø> (ø)
ddcommon	83.07% <67.80%> (-1.90%)	⬇️
ddcommon-ffi	70.20% <67.80%> (-0.08%)	⬇️
ddtelemetry	58.95% <ø> (ø)
ipc	84.18% <ø> (ø)
profiling	84.26% <ø> (ø)
profiling-ffi	77.42% <ø> (ø)
serverless	0.00% <ø> (ø)
sidecar	34.55% <ø> (ø)
sidecar-ffi	0.00% <ø> (ø)
spawn-worker	54.98% <ø> (ø)
trace-mini-agent	70.88% <ø> (ø)
trace-normalization	98.24% <ø> (ø)
trace-obfuscation	95.73% <ø> (ø)
trace-protobuf	77.16% <ø> (ø)
trace-utils	90.90% <ø> (ø)

🚀 New features to boost your workflow:

• ❄️ Test Analytics: Detect flaky tests, report on failures, and find test suite problems.
• 📦 JS Bundle Analysis: Save yourself from yourself by tracking and limiting bundle sizes in JS merges.

[ivoanjo]

This looks quite reasonable! I've been holding off on buffering things on the Ruby library (instead try to make everything immediate) in part because of the complexity of getting this kind of queue going in a C codebase, but I guess after this is in I should probably consider using it in a few places :)

My rust-foo isn't great so I recommend waiting for @danielsn's final pass/approval as well, but here sir, take my 👍

[paullegranddc]

As a general comment, all of the extern "C" functions in this PR take an *ArrayQueue and cast it to an &'a crossbeam::ArrayQueue, but the thing is, the lifetime is never bound, so you could very well get an &'static crossbeam::ArrayQueue and have it escape the fucntion.

I think it'd be better to take an &'a ArrayQueue in the ffi fucntions, which is translated to the same ArrayQueue* in the C header, which would allow to derive the &'a crossbeam::ArrayQueue lifetime safely and ensure it doesn't escape.

[gleocadie]

Can you add description and what motivates this PR please ? (as describe in the template)
It's difficult to understand why we are adding this and if it would benefit us (other libraries)
Thx

[danielsn]

Modulo a few ⛏️ LGTM