History of Dictionary Searches using Damerau-Levenshtein distance in T-SQL
Fuzzy-string Searches
(up to 100 most recent)
for
"forecasters"
| Num | Started At (CA time) | Searched Word | Change Limit | Words Checked | Words Matched | Seconds | Words Per Sec |
| 435 | 2025-10-20 01:43:29 | forecasters | 1 | 49908 | 2 | 3.313 | 15064.3 |
| 434 | 2025-10-06 05:19:13 | forecasters | 1 | 49908 | 2 | 0.766 | 65154.0 |
| 433 | 2025-09-24 00:19:47 | forecasters | 3 | 121633 | 29 | 4.610 | 26384.6 |
| 432 | 2025-09-18 05:36:58 | forecasters | 3 | 121633 | 29 | 5.606 | 21696.9 |
| 431 | 2025-09-02 14:29:41 | forecasters | 3 | 121633 | 29 | 4.610 | 26384.6 |
| 430 | 2025-08-25 20:23:29 | forecasters | 1 | 49908 | 2 | 0.906 | 55086.1 |
| 429 | 2025-08-23 18:14:17 | forecasters | 4 | 148819 | 163 | 9.546 | 15589.7 |
| 428 | 2025-08-22 06:33:25 | forecasters | 2 | 86808 | 7 | 2.483 | 34960.9 |
| 427 | 2025-08-20 09:16:04 | forecasters | 1 | 49908 | 2 | 0.830 | 60130.1 |
| 426 | 2025-08-18 06:07:06 | forecasters | 1 | 49908 | 2 | 0.763 | 65410.2 |
| 425 | 2025-08-17 07:12:32 | forecasters | 1 | 49908 | 2 | 4.686 | 10650.4 |
| 424 | 2025-08-11 15:50:11 | forecasters | 4 | 148819 | 163 | 44.486 | 3345.3 |
| 423 | 2025-08-11 12:12:26 | forecasters | 3 | 121633 | 29 | 13.376 | 9093.4 |
| 422 | 2025-08-11 06:12:39 | forecasters | 2 | 86808 | 7 | 2.220 | 39102.7 |
| 421 | 2025-08-09 17:03:57 | forecasters | 1 | 49908 | 2 | 3.920 | 12731.6 |
| 420 | 2025-08-09 13:32:53 | forecasters | 1 | 49908 | 2 | 5.186 | 9623.6 |
| 419 | 2025-08-08 16:28:02 | forecasters | 4 | 148819 | 163 | 9.376 | 15872.3 |
| 418 | 2025-07-28 09:31:15 | forecasters | 3 | 121633 | 29 | 13.110 | 9277.9 |
| 417 | 2025-07-27 04:51:59 | forecasters | 3 | 121633 | 29 | 26.296 | 4625.5 |
| 416 | 2025-07-25 10:50:38 | forecasters | 2 | 86808 | 7 | 7.303 | 11886.6 |
| 415 | 2025-07-24 23:18:43 | forecasters | 4 | 148819 | 163 | 26.770 | 5559.2 |
| 414 | 2025-07-24 15:58:58 | forecasters | 1 | 49908 | 2 | 5.563 | 8971.4 |
| 413 | 2025-07-23 12:31:25 | forecasters | 1 | 49908 | 2 | 5.296 | 9423.7 |
| 412 | 2025-07-23 02:13:32 | forecasters | 3 | 121633 | 29 | 19.550 | 6221.6 |
| 411 | 2025-07-23 00:10:24 | forecasters | 1 | 49908 | 2 | 3.970 | 12571.3 |
| 410 | 2025-07-22 10:44:50 | forecasters | 2 | 86808 | 7 | 9.076 | 9564.6 |
| 409 | 2025-07-22 09:07:53 | forecasters | 4 | 148819 | 163 | 22.686 | 6559.9 |
| 408 | 2025-07-21 18:52:52 | forecasters | 4 | 148819 | 163 | 9.030 | 16480.5 |
| 407 | 2025-07-19 04:24:09 | forecasters | 1 | 49908 | 2 | 0.876 | 56972.6 |
| 406 | 2025-07-19 04:24:08 | forecasters | 1 | 49908 | 2 | 0.860 | 58032.6 |
| 405 | 2025-07-15 20:39:59 | forecasters | 4 | 148819 | 163 | 9.686 | 15364.3 |
| 404 | 2025-07-10 21:18:23 | forecasters | 3 | 121633 | 29 | 23.550 | 5164.9 |
| 403 | 2025-07-10 18:58:58 | forecasters | 3 | 121633 | 29 | 24.376 | 4989.9 |
| 402 | 2025-07-09 12:38:42 | forecasters | 1 | 49908 | 2 | 0.923 | 54071.5 |
| 401 | 2025-07-07 16:08:01 | forecasters | 1 | 49908 | 2 | 5.203 | 9592.2 |
| 400 | 2025-07-07 07:54:33 | forecasters | 3 | 121633 | 29 | 32.406 | 3753.4 |
| 399 | 2025-07-05 03:55:54 | forecasters | 3 | 121633 | 29 | 29.563 | 4114.4 |
| 398 | 2025-06-29 21:54:46 | forecasters | 3 | 121633 | 29 | 25.403 | 4788.1 |
| 397 | 2025-06-23 20:37:31 | forecasters | 1 | 49908 | 2 | 4.356 | 11457.3 |
| 396 | 2025-06-14 10:25:57 | forecasters | 1 | 49908 | 2 | 2.140 | 23321.5 |
| 395 | 2025-06-02 07:32:05 | forecasters | 3 | 121633 | 29 | 42.063 | 2891.7 |
| 394 | 2025-06-01 23:29:45 | forecasters | 4 | 148819 | 163 | 58.130 | 2560.1 |
| 393 | 2025-05-30 21:39:33 | forecasters | 1 | 49908 | 2 | 3.203 | 15581.6 |
| 392 | 2025-05-30 06:24:06 | forecasters | 4 | 148819 | 163 | 50.953 | 2920.7 |
| 391 | 2025-05-29 16:17:52 | forecasters | 2 | 86808 | 7 | 18.160 | 4780.2 |
| 390 | 2025-05-29 05:34:41 | forecasters | 3 | 121633 | 29 | 19.330 | 6292.4 |
| 389 | 2025-05-25 16:31:55 | forecasters | 1 | 49908 | 2 | 0.843 | 59202.8 |
| 388 | 2025-05-25 07:52:36 | forecasters | 2 | 86808 | 7 | 7.220 | 12023.3 |
| 387 | 2025-05-25 02:45:51 | forecasters | 3 | 121633 | 29 | 17.893 | 6797.8 |
| 386 | 2025-05-24 13:18:28 | forecasters | 2 | 86808 | 7 | 12.593 | 6893.4 |
| 385 | 2025-05-23 20:59:18 | forecasters | 1 | 49908 | 2 | 4.266 | 11699.0 |
| 384 | 2025-05-23 04:51:32 | forecasters | 1 | 49908 | 2 | 0.826 | 60421.3 |
| 383 | 2025-05-23 01:00:44 | forecasters | 1 | 49908 | 2 | 4.563 | 10937.5 |
| 382 | 2025-05-22 10:08:38 | forecasters | 2 | 86808 | 7 | 16.796 | 5168.4 |
| 381 | 2025-05-21 12:10:49 | forecasters | 1 | 49908 | 2 | 2.623 | 19027.1 |
| 380 | 2025-05-20 10:52:02 | forecasters | 1 | 49908 | 2 | 3.860 | 12929.5 |
| 379 | 2025-05-20 01:12:25 | forecasters | 4 | 148819 | 163 | 45.346 | 3281.9 |
| 378 | 2025-05-18 17:31:01 | forecasters | 4 | 148819 | 163 | 53.846 | 2763.8 |
| 377 | 2025-05-18 10:50:29 | forecasters | 4 | 148819 | 163 | 43.130 | 3450.5 |
| 376 | 2025-05-16 01:23:05 | forecasters | 4 | 148819 | 163 | 52.363 | 2842.1 |
| 375 | 2025-05-13 15:23:45 | forecasters | 4 | 148819 | 163 | 46.546 | 3197.2 |
| 374 | 2025-05-06 14:03:53 | forecasters | 1 | 49908 | 2 | 3.966 | 12584.0 |
| 373 | 2025-04-22 20:31:31 | forecasters | 1 | 49908 | 2 | 2.716 | 18375.6 |
| 372 | 2025-04-20 21:24:16 | forecasters | 1 | 49908 | 2 | 5.656 | 8823.9 |
| 371 | 2025-04-20 06:47:11 | forecasters | 1 | 49908 | 2 | 5.950 | 8387.9 |
| 370 | 2025-04-19 06:50:49 | forecasters | 2 | 86808 | 7 | 2.233 | 38875.1 |
| 369 | 2025-04-19 02:01:12 | forecasters | 3 | 121633 | 29 | 5.423 | 22429.1 |
| 368 | 2025-04-18 11:55:56 | forecasters | 1 | 49908 | 2 | 4.296 | 11617.3 |
| 367 | 2025-04-16 09:16:52 | forecasters | 4 | 148819 | 163 | 44.786 | 3322.9 |
| 366 | 2025-04-11 10:29:03 | forecasters | 1 | 49908 | 2 | 3.906 | 12777.3 |
| 365 | 2025-04-11 09:13:59 | forecasters | 1 | 49908 | 2 | 3.593 | 13890.3 |
| 364 | 2025-03-25 18:29:11 | forecasters | 4 | 148819 | 163 | 32.313 | 4605.5 |
| 363 | 2025-03-24 13:19:33 | forecasters | 3 | 121633 | 29 | 24.440 | 4976.8 |
| 362 | 2025-03-24 05:28:16 | forecasters | 2 | 86808 | 7 | 6.186 | 14033.0 |
| 361 | 2025-03-24 00:21:29 | forecasters | 4 | 148819 | 163 | 9.393 | 15843.6 |
| 360 | 2025-03-23 17:03:39 | forecasters | 4 | 148819 | 163 | 63.486 | 2344.1 |
| 359 | 2025-03-23 05:06:00 | forecasters | 3 | 121633 | 29 | 23.750 | 5121.4 |
| 358 | 2025-03-22 17:42:50 | forecasters | 1 | 49908 | 2 | 2.266 | 22024.7 |
| 357 | 2025-03-21 21:42:07 | forecasters | 1 | 49908 | 2 | 0.860 | 58032.6 |
| 356 | 2025-03-10 12:48:44 | forecasters | 1 | 49908 | 2 | 2.173 | 22967.3 |
| 355 | 2025-03-03 16:05:16 | forecasters | 1 | 49908 | 2 | 2.330 | 21419.7 |
| 354 | 2025-02-22 22:09:53 | forecasters | 3 | 121633 | 29 | 41.750 | 2913.4 |
| 353 | 2025-02-18 20:40:00 | forecasters | 1 | 49908 | 2 | 2.953 | 16900.8 |
| 352 | 2025-02-16 17:31:29 | forecasters | 3 | 121633 | 29 | 25.800 | 4714.5 |
| 351 | 2025-02-11 03:57:02 | forecasters | 3 | 121633 | 29 | 25.203 | 4826.1 |
| 350 | 2025-01-21 03:46:30 | forecasters | 3 | 121633 | 29 | 36.220 | 3358.2 |
| 349 | 2025-01-21 03:46:32 | forecasters | 2 | 86808 | 7 | 10.703 | 8110.6 |
| 348 | 2025-01-21 03:42:51 | forecasters | 1 | 49908 | 2 | 4.486 | 11125.3 |
| 347 | 2025-01-21 02:11:35 | forecasters | 1 | 49908 | 2 | 4.080 | 12232.4 |
| 346 | 2025-01-16 10:19:15 | forecasters | 2 | 86808 | 7 | 13.080 | 6636.7 |
| 345 | 2025-01-16 10:16:26 | forecasters | 1 | 49908 | 2 | 3.660 | 13636.1 |
| 344 | 2025-01-16 10:11:32 | forecasters | 3 | 121633 | 29 | 27.813 | 4373.2 |
| 343 | 2025-01-16 07:45:57 | forecasters | 4 | 148819 | 163 | 49.126 | 3029.3 |
| 342 | 2025-01-16 07:45:42 | forecasters | 3 | 121633 | 29 | 14.906 | 8160.0 |
| 341 | 2025-01-16 02:55:58 | forecasters | 4 | 148819 | 163 | 49.893 | 2982.8 |
| 340 | 2025-01-16 02:56:01 | forecasters | 3 | 121633 | 29 | 20.033 | 6071.6 |
| 339 | 2025-01-16 02:56:08 | forecasters | 2 | 86808 | 7 | 12.000 | 7234.0 |
| 338 | 2025-01-16 02:52:37 | forecasters | 1 | 49908 | 2 | 1.610 | 30998.8 |
| 337 | 2025-01-15 22:40:45 | forecasters | 4 | 148819 | 163 | 29.550 | 5036.2 |
| 336 | 2025-01-02 04:27:28 | forecasters | 4 | 148819 | 163 | 53.076 | 2803.9 |