Compiling liblevenshtein v0.1.0 (/home/dylon/Workspace/f1r3fly.io/liblevenshtein-rust) warning: variable does not need to be mutable --> benches/dawg_benchmarks.rs:71:21 | 71 | let mut dawg = DynamicDawg::default(); | ----^^^^ | | | help: remove this `mut` | = note: `#[warn(unused_mut)]` on by default warning: variable does not need to be mutable --> benches/dawg_benchmarks.rs:160:21 | 160 | let mut dawg_clone = dawg.clone(); | ----^^^^^^^^^^ | | | help: remove this `mut` warning: variable does not need to be mutable --> benches/dawg_benchmarks.rs:152:13 | 152 | let mut dawg = DynamicDawg::default(); | ----^^^^ | | | help: remove this `mut` warning: `liblevenshtein` (bench "dawg_benchmarks") generated 3 warnings (run `cargo fix --bench "dawg_benchmarks"` to apply 3 suggestions) Finished `bench` profile [optimized + debuginfo] target(s) in 43.70s Running benches/dawg_benchmarks.rs (target/release/deps/dawg_benchmarks-6005c94a1d9b6dc5) Benchmarking dawg_edge_lookup/100 Benchmarking dawg_edge_lookup/100: Warming up for 3.0000 s Benchmarking dawg_edge_lookup/100: Collecting 100 samples in estimated 5.0217 s (323k iterations) Benchmarking dawg_edge_lookup/100: Analyzing dawg_edge_lookup/100 time: [15.027 µs 15.150 µs 15.284 µs] thrpt: [6.5428 Melem/s 6.6005 Melem/s 6.6547 Melem/s] change: time: [-0.2402% +0.7682% +1.8015%] (p = 0.13 > 0.05) thrpt: [-1.7696% -0.7623% +0.2408%] No change in performance detected. Found 2 outliers among 100 measurements (2.00%) 1 (1.00%) high mild 1 (1.00%) high severe Benchmarking dawg_edge_lookup/500 Benchmarking dawg_edge_lookup/500: Warming up for 3.0000 s Benchmarking dawg_edge_lookup/500: Collecting 100 samples in estimated 5.0310 s (364k iterations) Benchmarking dawg_edge_lookup/500: Analyzing dawg_edge_lookup/500 time: [13.605 µs 13.676 µs 13.751 µs] thrpt: [7.2722 Melem/s 7.3119 Melem/s 7.3503 Melem/s] change: time: [-3.1885% -2.4403% -1.6337%] (p = 0.00 < 0.05) thrpt: [+1.6609% +2.5014% +3.2935%] Performance has improved. Found 3 outliers among 100 measurements (3.00%) 2 (2.00%) high mild 1 (1.00%) high severe Benchmarking dawg_edge_lookup/1000 Benchmarking dawg_edge_lookup/1000: Warming up for 3.0000 s Benchmarking dawg_edge_lookup/1000: Collecting 100 samples in estimated 5.0670 s (328k iterations) Benchmarking dawg_edge_lookup/1000: Analyzing dawg_edge_lookup/1000 time: [16.183 µs 16.267 µs 16.349 µs] thrpt: [6.1164 Melem/s 6.1474 Melem/s 6.1792 Melem/s] change: time: [+0.6659% +1.6011% +2.5108%] (p = 0.00 < 0.05) thrpt: [-2.4493% -1.5759% -0.6615%] Change within noise threshold. Found 4 outliers among 100 measurements (4.00%) 1 (1.00%) low mild 2 (2.00%) high mild 1 (1.00%) high severe Benchmarking dawg_edge_lookup/5000 Benchmarking dawg_edge_lookup/5000: Warming up for 3.0000 s Benchmarking dawg_edge_lookup/5000: Collecting 100 samples in estimated 5.0030 s (293k iterations) Benchmarking dawg_edge_lookup/5000: Analyzing dawg_edge_lookup/5000 time: [16.325 µs 16.451 µs 16.586 µs] thrpt: [6.0291 Melem/s 6.0787 Melem/s 6.1255 Melem/s] change: time: [+3.8996% +5.0999% +6.5057%] (p = 0.00 < 0.05) thrpt: [-6.1083% -4.8524% -3.7532%] Performance has regressed. Found 1 outliers among 100 measurements (1.00%) 1 (1.00%) high severe Benchmarking dynamic_dawg_insertion/100 Benchmarking dynamic_dawg_insertion/100: Warming up for 3.0000 s Benchmarking dynamic_dawg_insertion/100: Collecting 100 samples in estimated 5.1538 s (111k iterations) Benchmarking dynamic_dawg_insertion/100: Analyzing dynamic_dawg_insertion/100 time: [47.497 µs 48.239 µs 48.980 µs] thrpt: [2.0416 Melem/s 2.0730 Melem/s 2.1054 Melem/s] change: time: [-2.0172% -0.6087% +0.7597%] (p = 0.43 > 0.05) thrpt: [-0.7540% +0.6124% +2.0587%] No change in performance detected. Benchmarking dynamic_dawg_insertion/500 Benchmarking dynamic_dawg_insertion/500: Warming up for 3.0000 s Benchmarking dynamic_dawg_insertion/500: Collecting 100 samples in estimated 5.1850 s (30k iterations) Benchmarking dynamic_dawg_insertion/500: Analyzing dynamic_dawg_insertion/500 time: [170.83 µs 171.73 µs 172.72 µs] thrpt: [2.8948 Melem/s 2.9115 Melem/s 2.9268 Melem/s] change: time: [+0.1108% +0.9590% +1.7731%] (p = 0.02 < 0.05) thrpt: [-1.7422% -0.9499% -0.1107%] Change within noise threshold. Found 9 outliers among 100 measurements (9.00%) 4 (4.00%) low mild 5 (5.00%) high mild Benchmarking dynamic_dawg_insertion/1000 Benchmarking dynamic_dawg_insertion/1000: Warming up for 3.0000 s Benchmarking dynamic_dawg_insertion/1000: Collecting 100 samples in estimated 5.6527 s (15k iterations) Benchmarking dynamic_dawg_insertion/1000: Analyzing dynamic_dawg_insertion/1000 time: [369.20 µs 370.54 µs 371.88 µs] thrpt: [2.6890 Melem/s 2.6988 Melem/s 2.7085 Melem/s] change: time: [+0.2238% +1.1608% +2.0955%] (p = 0.01 < 0.05) thrpt: [-2.0524% -1.1475% -0.2233%] Change within noise threshold. Found 8 outliers among 100 measurements (8.00%) 2 (2.00%) low mild 4 (4.00%) high mild 2 (2.00%) high severe Benchmarking dawg_edge_iteration/100 Benchmarking dawg_edge_iteration/100: Warming up for 3.0000 s Benchmarking dawg_edge_iteration/100: Collecting 100 samples in estimated 5.0037 s (2.3M iterations) Benchmarking dawg_edge_iteration/100: Analyzing dawg_edge_iteration/100 time: [2.1308 µs 2.1419 µs 2.1538 µs] thrpt: [46.430 Melem/s 46.688 Melem/s 46.931 Melem/s] change: time: [+5.1356% +6.0384% +6.9565%] (p = 0.00 < 0.05) thrpt: [-6.5040% -5.6945% -4.8847%] Performance has regressed. Found 5 outliers among 100 measurements (5.00%) 2 (2.00%) low mild 2 (2.00%) high mild 1 (1.00%) high severe Benchmarking dawg_edge_iteration/500 Benchmarking dawg_edge_iteration/500: Warming up for 3.0000 s Benchmarking dawg_edge_iteration/500: Collecting 100 samples in estimated 5.0027 s (2.6M iterations) Benchmarking dawg_edge_iteration/500: Analyzing dawg_edge_iteration/500 time: [1.9278 µs 1.9364 µs 1.9456 µs] thrpt: [256.99 Melem/s 258.21 Melem/s 259.37 Melem/s] change: time: [-4.1793% -3.1592% -2.1616%] (p = 0.00 < 0.05) thrpt: [+2.2093% +3.2623% +4.3615%] Performance has improved. Found 7 outliers among 100 measurements (7.00%) 5 (5.00%) high mild 2 (2.00%) high severe Benchmarking dawg_edge_iteration/1000 Benchmarking dawg_edge_iteration/1000: Warming up for 3.0000 s Benchmarking dawg_edge_iteration/1000: Collecting 100 samples in estimated 5.0009 s (2.5M iterations) Benchmarking dawg_edge_iteration/1000: Analyzing dawg_edge_iteration/1000 time: [1.9684 µs 1.9780 µs 1.9877 µs] thrpt: [503.08 Melem/s 505.57 Melem/s 508.04 Melem/s] change: time: [-1.5540% -0.4984% +0.6044%] (p = 0.37 > 0.05) thrpt: [-0.6008% +0.5009% +1.5785%] No change in performance detected. Found 5 outliers among 100 measurements (5.00%) 1 (1.00%) low mild 2 (2.00%) high mild 2 (2.00%) high severe Benchmarking dawg_edge_iteration/5000 Benchmarking dawg_edge_iteration/5000: Warming up for 3.0000 s Benchmarking dawg_edge_iteration/5000: Collecting 100 samples in estimated 5.0044 s (2.5M iterations) Benchmarking dawg_edge_iteration/5000: Analyzing dawg_edge_iteration/5000 time: [1.9687 µs 1.9788 µs 1.9894 µs] thrpt: [2.5133 Gelem/s 2.5268 Gelem/s 2.5397 Gelem/s] change: time: [-1.4394% -0.4107% +0.6829%] (p = 0.45 > 0.05) thrpt: [-0.6783% +0.4124% +1.4604%] No change in performance detected. Found 6 outliers among 100 measurements (6.00%) 1 (1.00%) low mild 1 (1.00%) high mild 4 (4.00%) high severe Benchmarking dawg_contains/100 Benchmarking dawg_contains/100: Warming up for 3.0000 s Benchmarking dawg_contains/100: Collecting 100 samples in estimated 5.0177 s (540k iterations) Benchmarking dawg_contains/100: Analyzing dawg_contains/100 time: [9.2470 µs 9.2983 µs 9.3502 µs] thrpt: [10.695 Melem/s 10.755 Melem/s 10.814 Melem/s] change: time: [-2.0474% -1.2608% -0.4706%] (p = 0.00 < 0.05) thrpt: [+0.4728% +1.2769% +2.0902%] Change within noise threshold. Found 3 outliers among 100 measurements (3.00%) 3 (3.00%) high mild Benchmarking dawg_contains/500 Benchmarking dawg_contains/500: Warming up for 3.0000 s Benchmarking dawg_contains/500: Collecting 100 samples in estimated 5.0317 s (525k iterations) Benchmarking dawg_contains/500: Analyzing dawg_contains/500 time: [9.3551 µs 9.4045 µs 9.4575 µs] thrpt: [10.574 Melem/s 10.633 Melem/s 10.689 Melem/s] change: time: [-4.1692% -2.8791% -1.6478%] (p = 0.00 < 0.05) thrpt: [+1.6754% +2.9645% +4.3505%] Performance has improved. Found 5 outliers among 100 measurements (5.00%) 3 (3.00%) high mild 2 (2.00%) high severe Benchmarking dawg_contains/1000 Benchmarking dawg_contains/1000: Warming up for 3.0000 s Benchmarking dawg_contains/1000: Collecting 100 samples in estimated 5.0043 s (525k iterations) Benchmarking dawg_contains/1000: Analyzing dawg_contains/1000 time: [9.5635 µs 9.6097 µs 9.6568 µs] thrpt: [10.355 Melem/s 10.406 Melem/s 10.456 Melem/s] change: time: [-2.0146% -1.1646% -0.3439%] (p = 0.01 < 0.05) thrpt: [+0.3451% +1.1783% +2.0560%] Change within noise threshold. Found 7 outliers among 100 measurements (7.00%) 3 (3.00%) low mild 4 (4.00%) high mild Benchmarking dawg_contains/5000 Benchmarking dawg_contains/5000: Warming up for 3.0000 s Benchmarking dawg_contains/5000: Collecting 100 samples in estimated 5.0237 s (525k iterations) Benchmarking dawg_contains/5000: Analyzing dawg_contains/5000 time: [9.6643 µs 9.7103 µs 9.7597 µs] thrpt: [10.246 Melem/s 10.298 Melem/s 10.347 Melem/s] change: time: [-2.1183% -1.0936% +0.0035%] (p = 0.04 < 0.05) thrpt: [-0.0035% +1.1057% +2.1641%] Change within noise threshold. Found 8 outliers among 100 measurements (8.00%) 1 (1.00%) low mild 3 (3.00%) high mild 4 (4.00%) high severe Benchmarking dynamic_dawg_minimize/100 Benchmarking dynamic_dawg_minimize/100: Warming up for 3.0000 s Benchmarking dynamic_dawg_minimize/100: Collecting 100 samples in estimated 6.3215 s (15k iterations) Benchmarking dynamic_dawg_minimize/100: Analyzing dynamic_dawg_minimize/100 time: [423.50 µs 427.97 µs 432.57 µs] thrpt: [231.17 Kelem/s 233.66 Kelem/s 236.13 Kelem/s] change: time: [-5.2600% -4.2395% -3.1989%] (p = 0.00 < 0.05) thrpt: [+3.3046% +4.4271% +5.5520%] Performance has improved. Found 7 outliers among 100 measurements (7.00%) 5 (5.00%) high mild 2 (2.00%) high severe Benchmarking dynamic_dawg_minimize/500 Benchmarking dynamic_dawg_minimize/500: Warming up for 3.0000 s Benchmarking dynamic_dawg_minimize/500: Collecting 100 samples in estimated 8.9187 s (10k iterations) Benchmarking dynamic_dawg_minimize/500: Analyzing dynamic_dawg_minimize/500 time: [828.92 µs 833.35 µs 837.52 µs] thrpt: [597.00 Kelem/s 599.99 Kelem/s 603.19 Kelem/s] change: time: [+3.3288% +4.6467% +6.0307%] (p = 0.00 < 0.05) thrpt: [-5.6877% -4.4404% -3.2215%] Performance has regressed. Found 6 outliers among 100 measurements (6.00%) 6 (6.00%) high mild Benchmarking dynamic_dawg_minimize/1000 Benchmarking dynamic_dawg_minimize/1000: Warming up for 3.0000 s Benchmarking dynamic_dawg_minimize/1000: Collecting 100 samples in estimated 5.0763 s (2500 iterations) Benchmarking dynamic_dawg_minimize/1000: Analyzing dynamic_dawg_minimize/1000 time: [1.9938 ms 2.0092 ms 2.0255 ms] thrpt: [493.70 Kelem/s 497.72 Kelem/s 501.54 Kelem/s] change: time: [+2.2517% +3.3352% +4.3859%] (p = 0.00 < 0.05) thrpt: [-4.2016% -3.2276% -2.2021%] Performance has regressed. Found 6 outliers among 100 measurements (6.00%) 6 (6.00%) high mild Benchmarking dawg_construction/100 Benchmarking dawg_construction/100: Warming up for 3.0000 s Benchmarking dawg_construction/100: Collecting 100 samples in estimated 5.4773 s (56k iterations) Benchmarking dawg_construction/100: Analyzing dawg_construction/100 time: [97.865 µs 99.052 µs 100.31 µs] thrpt: [996.94 Kelem/s 1.0096 Melem/s 1.0218 Melem/s] change: time: [+1.6646% +2.6164% +3.6102%] (p = 0.00 < 0.05) thrpt: [-3.4845% -2.5497% -1.6373%] Performance has regressed. Found 4 outliers among 100 measurements (4.00%) 3 (3.00%) high mild 1 (1.00%) high severe Benchmarking dawg_construction/500 Benchmarking dawg_construction/500: Warming up for 3.0000 s Benchmarking dawg_construction/500: Collecting 100 samples in estimated 5.8207 s (30k iterations) Benchmarking dawg_construction/500: Analyzing dawg_construction/500 time: [192.30 µs 193.41 µs 194.49 µs] thrpt: [2.5708 Melem/s 2.5852 Melem/s 2.6002 Melem/s] change: time: [+0.6592% +1.4317% +2.1933%] (p = 0.00 < 0.05) thrpt: [-2.1462% -1.4115% -0.6549%] Change within noise threshold. Found 5 outliers among 100 measurements (5.00%) 2 (2.00%) low mild 3 (3.00%) high mild Benchmarking dawg_construction/1000 Benchmarking dawg_construction/1000: Warming up for 3.0000 s Benchmarking dawg_construction/1000: Collecting 100 samples in estimated 6.7896 s (15k iterations) Benchmarking dawg_construction/1000: Analyzing dawg_construction/1000 time: [450.47 µs 452.56 µs 454.65 µs] thrpt: [2.1995 Melem/s 2.2097 Melem/s 2.2199 Melem/s] change: time: [+0.5983% +1.2440% +1.9582%] (p = 0.00 < 0.05) thrpt: [-1.9206% -1.2287% -0.5947%] Change within noise threshold. Found 9 outliers among 100 measurements (9.00%) 1 (1.00%) low severe 1 (1.00%) low mild 7 (7.00%) high mild Benchmarking dawg_construction/5000 Benchmarking dawg_construction/5000: Warming up for 3.0000 s Benchmarking dawg_construction/5000: Collecting 100 samples in estimated 6.8288 s (15k iterations) Benchmarking dawg_construction/5000: Analyzing dawg_construction/5000 time: [449.59 µs 451.69 µs 453.92 µs] thrpt: [11.015 Melem/s 11.070 Melem/s 11.121 Melem/s] change: time: [-1.5264% -0.5843% +0.4991%] (p = 0.27 > 0.05) thrpt: [-0.4967% +0.5877% +1.5500%] No change in performance detected. Found 5 outliers among 100 measurements (5.00%) 1 (1.00%) low mild 3 (3.00%) high mild 1 (1.00%) high severe