History of Dictionary Searches using Damerau-Levenshtein distance in T-SQL
Fuzzy-string Searches
(up to 100 most recent)
for
"sharpest"
| Num | Started At (CA time) | Searched Word | Change Limit | Words Checked | Words Matched | Seconds | Words Per Sec |
| 423 | 2025-10-31 12:23:02 | sharpest | 3 | 146162 | 215 | 7.733 | 18901.1 |
| 422 | 2025-10-29 01:57:19 | sharpest | 1 | 82945 | 1 | 1.313 | 63172.1 |
| 421 | 2025-10-28 23:17:38 | sharpest | 3 | 146162 | 215 | 7.843 | 18636.0 |
| 420 | 2025-10-28 23:13:53 | sharpest | 2 | 121059 | 26 | 3.906 | 30993.1 |
| 419 | 2025-10-28 22:01:03 | sharpest | 3 | 146162 | 215 | 7.750 | 18859.6 |
| 418 | 2025-10-28 14:52:16 | sharpest | 1 | 82945 | 1 | 1.563 | 53067.8 |
| 417 | 2025-10-27 11:33:19 | sharpest | 1 | 82945 | 1 | 1.483 | 55930.5 |
| 416 | 2025-10-26 07:05:03 | sharpest | 1 | 82945 | 1 | 1.530 | 54212.4 |
| 415 | 2025-10-15 17:38:49 | sharpest | 1 | 82945 | 1 | 1.486 | 55817.6 |
| 414 | 2025-10-06 10:22:06 | sharpest | 1 | 82945 | 1 | 1.390 | 59672.7 |
| 413 | 2025-10-06 05:32:54 | sharpest | 1 | 82945 | 1 | 1.376 | 60279.8 |
| 412 | 2025-10-06 05:27:11 | sharpest | 1 | 82945 | 1 | 1.596 | 51970.6 |
| 411 | 2025-09-30 13:36:16 | sharpest | 2 | 121059 | 26 | 3.720 | 32542.7 |
| 410 | 2025-09-28 12:24:06 | sharpest | 2 | 121059 | 26 | 3.266 | 37066.4 |
| 409 | 2025-09-20 20:45:24 | sharpest | 3 | 146162 | 215 | 15.830 | 9233.2 |
| 408 | 2025-09-20 10:17:35 | sharpest | 3 | 146162 | 215 | 7.530 | 19410.6 |
| 407 | 2025-09-18 21:54:52 | sharpest | 2 | 121059 | 26 | 3.813 | 31749.0 |
| 406 | 2025-09-16 23:28:00 | sharpest | 3 | 146162 | 215 | 7.796 | 18748.3 |
| 405 | 2025-09-11 06:48:12 | sharpest | 1 | 82945 | 1 | 1.390 | 59672.7 |
| 404 | 2025-09-11 02:04:22 | sharpest | 3 | 146162 | 215 | 6.626 | 22058.9 |
| 403 | 2025-09-09 09:41:48 | sharpest | 3 | 146162 | 215 | 6.936 | 21073.0 |
| 402 | 2025-09-08 06:00:47 | sharpest | 1 | 82945 | 1 | 1.546 | 53651.4 |
| 401 | 2025-09-06 07:53:54 | sharpest | 2 | 121059 | 26 | 3.843 | 31501.2 |
| 400 | 2025-09-06 00:17:22 | sharpest | 2 | 121059 | 26 | 3.330 | 36354.1 |
| 399 | 2025-09-02 08:01:59 | sharpest | 2 | 121059 | 26 | 3.330 | 36354.1 |
| 398 | 2025-09-02 07:05:49 | sharpest | 3 | 146162 | 215 | 6.593 | 22169.3 |
| 397 | 2025-09-01 18:31:02 | sharpest | 3 | 146162 | 215 | 11.080 | 13191.5 |
| 396 | 2025-09-01 16:01:32 | sharpest | 3 | 146162 | 215 | 6.516 | 22431.2 |
| 395 | 2025-09-01 14:24:31 | sharpest | 2 | 121059 | 26 | 3.250 | 37248.9 |
| 394 | 2025-09-01 03:31:09 | sharpest | 3 | 146162 | 215 | 9.906 | 14754.9 |
| 393 | 2025-08-30 06:56:03 | sharpest | 2 | 121059 | 26 | 3.266 | 37066.4 |
| 392 | 2025-08-29 07:40:54 | sharpest | 3 | 146162 | 215 | 7.016 | 20832.7 |
| 391 | 2025-08-28 23:18:11 | sharpest | 1 | 82945 | 1 | 1.343 | 61761.0 |
| 390 | 2025-08-25 00:39:29 | sharpest | 3 | 146162 | 215 | 39.250 | 3723.9 |
| 389 | 2025-08-24 11:22:27 | sharpest | 1 | 82945 | 1 | 1.346 | 61623.3 |
| 388 | 2025-08-23 06:55:51 | sharpest | 1 | 82945 | 1 | 8.126 | 10207.4 |
| 387 | 2025-08-17 16:31:40 | sharpest | 1 | 82945 | 1 | 3.703 | 22399.4 |
| 386 | 2025-08-12 21:22:18 | sharpest | 2 | 121059 | 26 | 12.736 | 9505.3 |
| 385 | 2025-08-06 15:07:24 | sharpest | 2 | 121059 | 26 | 9.003 | 13446.5 |
| 384 | 2025-08-06 13:14:48 | sharpest | 3 | 146162 | 215 | 19.686 | 7424.7 |
| 383 | 2025-08-02 11:02:53 | sharpest | 2 | 121059 | 26 | 9.483 | 12765.9 |
| 382 | 2025-08-02 10:37:22 | sharpest | 3 | 146162 | 215 | 16.530 | 8842.2 |
| 381 | 2025-08-02 02:14:50 | sharpest | 1 | 82945 | 1 | 3.470 | 23903.5 |
| 380 | 2025-08-01 14:29:48 | sharpest | 1 | 82945 | 1 | 6.076 | 13651.3 |
| 379 | 2025-07-31 16:15:22 | sharpest | 1 | 82945 | 1 | 1.450 | 57203.4 |
| 378 | 2025-07-31 00:11:39 | sharpest | 1 | 82945 | 1 | 1.513 | 54821.5 |
| 377 | 2025-07-29 15:05:58 | sharpest | 2 | 121059 | 26 | 9.030 | 13406.3 |
| 376 | 2025-07-29 14:25:31 | sharpest | 2 | 121059 | 26 | 8.873 | 13643.5 |
| 375 | 2025-07-29 13:08:24 | sharpest | 3 | 146162 | 215 | 21.533 | 6787.8 |
| 374 | 2025-07-29 00:53:21 | sharpest | 3 | 146162 | 215 | 41.643 | 3509.9 |
| 373 | 2025-07-27 02:50:32 | sharpest | 1 | 82945 | 1 | 3.236 | 25632.0 |
| 372 | 2025-07-26 13:25:07 | sharpest | 1 | 82945 | 1 | 1.533 | 54106.3 |
| 371 | 2025-07-25 09:58:22 | sharpest | 1 | 82945 | 1 | 3.420 | 24252.9 |
| 370 | 2025-07-25 06:53:28 | sharpest | 3 | 146162 | 215 | 25.393 | 5756.0 |
| 369 | 2025-07-25 00:37:03 | sharpest | 2 | 121059 | 26 | 13.670 | 8855.8 |
| 368 | 2025-07-23 09:31:34 | sharpest | 1 | 82945 | 1 | 4.000 | 20736.3 |
| 367 | 2025-07-21 16:20:09 | sharpest | 2 | 121059 | 26 | 8.896 | 13608.3 |
| 366 | 2025-07-21 08:44:12 | sharpest | 2 | 121059 | 26 | 3.703 | 32692.1 |
| 365 | 2025-07-18 18:39:23 | sharpest | 2 | 121059 | 26 | 8.423 | 14372.4 |
| 364 | 2025-07-16 02:05:20 | sharpest | 3 | 146162 | 215 | 40.986 | 3566.1 |
| 363 | 2025-07-15 11:12:06 | sharpest | 2 | 121059 | 26 | 18.520 | 6536.7 |
| 362 | 2025-07-15 08:51:44 | sharpest | 3 | 146162 | 215 | 23.970 | 6097.7 |
| 361 | 2025-07-13 17:23:01 | sharpest | 1 | 82945 | 1 | 1.326 | 62552.8 |
| 360 | 2025-07-12 06:10:07 | sharpest | 1 | 82945 | 1 | 1.530 | 54212.4 |
| 359 | 2025-07-11 09:37:55 | sharpest | 1 | 82945 | 1 | 10.423 | 7957.9 |
| 358 | 2025-06-24 12:55:44 | sharpest | 1 | 82945 | 1 | 7.813 | 10616.3 |
| 357 | 2025-06-21 06:41:00 | sharpest | 1 | 82945 | 1 | 4.860 | 17066.9 |
| 356 | 2025-06-16 10:04:58 | sharpest | 1 | 82945 | 1 | 5.483 | 15127.7 |
| 355 | 2025-06-15 07:05:11 | sharpest | 1 | 82945 | 1 | 1.470 | 56425.2 |
| 354 | 2025-06-10 17:12:19 | sharpest | 1 | 82945 | 1 | 10.656 | 7783.9 |
| 353 | 2025-05-31 12:22:58 | sharpest | 3 | 146162 | 215 | 42.906 | 3406.6 |
| 352 | 2025-05-29 18:50:18 | sharpest | 3 | 146162 | 215 | 6.970 | 20970.2 |
| 351 | 2025-05-29 18:48:45 | sharpest | 2 | 121059 | 26 | 6.033 | 20066.1 |
| 350 | 2025-05-28 12:31:45 | sharpest | 1 | 82945 | 1 | 1.343 | 61761.0 |
| 349 | 2025-05-27 14:05:35 | sharpest | 1 | 82945 | 1 | 3.440 | 24111.9 |
| 348 | 2025-05-22 12:57:17 | sharpest | 1 | 82945 | 1 | 7.733 | 10726.1 |
| 347 | 2025-05-10 18:33:36 | sharpest | 1 | 82945 | 1 | 8.766 | 9462.1 |
| 346 | 2025-05-03 09:46:26 | sharpest | 3 | 146162 | 215 | 19.486 | 7500.9 |
| 345 | 2025-05-01 13:53:14 | sharpest | 3 | 146162 | 215 | 28.706 | 5091.7 |
| 344 | 2025-05-01 12:22:27 | sharpest | 3 | 146162 | 215 | 41.113 | 3555.1 |
| 343 | 2025-04-29 06:37:30 | sharpest | 3 | 146162 | 215 | 22.596 | 6468.5 |
| 342 | 2025-04-29 01:07:51 | sharpest | 3 | 146162 | 215 | 34.440 | 4244.0 |
| 341 | 2025-04-27 16:17:37 | sharpest | 3 | 146162 | 215 | 17.626 | 8292.4 |
| 340 | 2025-04-24 03:54:42 | sharpest | 2 | 121059 | 26 | 16.453 | 7357.9 |
| 339 | 2025-04-23 13:50:10 | sharpest | 1 | 82945 | 1 | 1.453 | 57085.3 |
| 338 | 2025-04-22 13:01:42 | sharpest | 2 | 121059 | 26 | 5.530 | 21891.3 |
| 337 | 2025-04-21 22:17:12 | sharpest | 2 | 121059 | 26 | 3.733 | 32429.4 |
| 336 | 2025-04-21 17:07:43 | sharpest | 1 | 82945 | 1 | 7.716 | 10749.7 |
| 335 | 2025-04-20 06:06:12 | sharpest | 1 | 82945 | 1 | 7.903 | 10495.4 |
| 334 | 2025-04-04 16:17:26 | sharpest | 1 | 82945 | 1 | 3.906 | 21235.3 |
| 333 | 2025-04-02 10:07:11 | sharpest | 1 | 82945 | 1 | 5.000 | 16589.0 |
| 332 | 2025-03-29 12:21:24 | sharpest | 3 | 146162 | 215 | 44.376 | 3293.7 |
| 331 | 2025-03-28 14:57:07 | sharpest | 3 | 146162 | 215 | 32.456 | 4503.4 |
| 330 | 2025-03-25 10:53:26 | sharpest | 3 | 146162 | 215 | 20.376 | 7173.2 |
| 329 | 2025-03-09 20:03:06 | sharpest | 1 | 82945 | 1 | 5.703 | 14544.1 |
| 328 | 2025-03-02 02:22:12 | sharpest | 1 | 82945 | 1 | 13.250 | 6260.0 |
| 327 | 2025-02-25 18:07:08 | sharpest | 1 | 82945 | 1 | 6.533 | 12696.3 |
| 326 | 2025-02-24 13:21:07 | sharpest | 3 | 146162 | 215 | 20.843 | 7012.5 |
| 325 | 2025-02-22 07:38:13 | sharpest | 3 | 146162 | 215 | 32.566 | 4488.2 |
| 324 | 2025-02-15 01:07:44 | sharpest | 2 | 121059 | 26 | 18.906 | 6403.2 |