History of Dictionary Searches using Damerau-Levenshtein distance in T-SQL
Fuzzy-string Searches
(up to 100 most recent)
for
"coarsens"
Num | Started At (CA time) | Searched Word | Change Limit | Words Checked | Words Matched | Seconds | Words Per Sec |
477 | 2024-12-25 10:13:00 | coarsens | 1 | 82945 | 3 | 5.626 | 14743.2 |
476 | 2024-12-25 01:55:18 | coarsens | 3 | 146162 | 218 | 40.726 | 3588.9 |
475 | 2024-12-24 13:39:53 | coarsens | 3 | 146162 | 218 | 26.160 | 5587.2 |
474 | 2024-12-15 17:21:24 | coarsens | 1 | 82945 | 3 | 10.860 | 7637.7 |
473 | 2024-11-30 08:35:35 | coarsens | 3 | 146162 | 218 | 42.406 | 3446.7 |
472 | 2024-11-30 01:02:03 | coarsens | 3 | 146162 | 218 | 29.690 | 4922.9 |
471 | 2024-11-29 20:58:45 | coarsens | 3 | 146162 | 218 | 39.313 | 3717.9 |
470 | 2024-11-29 20:58:47 | coarsens | 2 | 121059 | 18 | 18.266 | 6627.6 |
469 | 2024-11-29 20:58:27 | coarsens | 1 | 82945 | 3 | 3.796 | 21850.6 |
468 | 2024-11-19 03:13:45 | coarsens | 1 | 82945 | 3 | 11.736 | 7067.6 |
467 | 2024-11-11 19:26:44 | coarsens | 2 | 121059 | 18 | 18.440 | 6565.0 |
466 | 2024-11-11 09:39:41 | coarsens | 1 | 82945 | 3 | 1.343 | 61761.0 |
465 | 2024-11-09 06:11:51 | coarsens | 1 | 82945 | 3 | 1.516 | 54713.1 |
464 | 2024-10-28 20:17:48 | coarsens | 2 | 121059 | 18 | 15.656 | 7732.4 |
463 | 2024-10-22 09:01:07 | coarsens | 1 | 82945 | 3 | 6.936 | 11958.6 |
462 | 2024-10-13 07:45:02 | coarsens | 2 | 121059 | 18 | 12.250 | 9882.4 |
461 | 2024-10-13 07:42:51 | coarsens | 1 | 82945 | 3 | 1.873 | 44284.6 |
460 | 2024-10-13 04:38:07 | coarsens | 3 | 146162 | 218 | 39.720 | 3679.8 |
459 | 2024-10-12 13:03:06 | coarsens | 3 | 146162 | 218 | 40.660 | 3594.7 |
458 | 2024-10-11 18:12:32 | coarsens | 3 | 146162 | 218 | 41.670 | 3507.6 |
457 | 2024-10-11 12:57:06 | coarsens | 1 | 82945 | 3 | 7.513 | 11040.2 |
456 | 2024-10-11 11:01:28 | coarsens | 3 | 146162 | 218 | 41.676 | 3507.1 |
455 | 2024-10-11 11:01:29 | coarsens | 2 | 121059 | 18 | 12.250 | 9882.4 |
454 | 2024-10-10 07:08:18 | coarsens | 1 | 82945 | 3 | 6.750 | 12288.1 |
453 | 2024-09-16 12:45:50 | coarsens | 1 | 82945 | 3 | 11.360 | 7301.5 |
452 | 2024-09-02 22:33:54 | coarsens | 1 | 82945 | 3 | 8.843 | 9379.7 |
451 | 2024-08-15 06:45:45 | coarsens | 1 | 82945 | 3 | 10.500 | 7899.5 |
450 | 2024-08-08 00:22:01 | coarsens | 2 | 121059 | 18 | 8.296 | 14592.5 |
449 | 2024-08-08 00:21:44 | coarsens | 1 | 82945 | 3 | 6.080 | 13642.3 |
448 | 2024-08-02 20:01:35 | coarsens | 1 | 82945 | 3 | 5.466 | 15174.7 |
447 | 2024-08-01 07:53:52 | coarsens | 1 | 82945 | 3 | 4.923 | 16848.5 |
446 | 2024-07-30 22:35:59 | coarsens | 3 | 146162 | 218 | 41.006 | 3564.4 |
445 | 2024-07-30 11:45:58 | coarsens | 3 | 146162 | 218 | 39.173 | 3731.2 |
444 | 2024-07-29 09:57:50 | coarsens | 3 | 146162 | 218 | 17.876 | 8176.4 |
443 | 2024-07-29 00:43:54 | coarsens | 3 | 146162 | 218 | 37.016 | 3948.6 |
442 | 2024-07-28 13:42:47 | coarsens | 3 | 146162 | 218 | 39.520 | 3698.4 |
441 | 2024-07-28 13:42:50 | coarsens | 2 | 121059 | 18 | 14.266 | 8485.8 |
440 | 2024-07-25 07:58:29 | coarsens | 1 | 82945 | 3 | 5.373 | 15437.4 |
439 | 2024-07-20 06:16:28 | coarsens | 1 | 82945 | 3 | 7.033 | 11793.7 |
438 | 2024-07-07 01:40:20 | coarsens | 1 | 82945 | 3 | 7.033 | 11793.7 |
437 | 2024-07-04 05:08:19 | coarsens | 1 | 82945 | 3 | 9.733 | 8522.0 |
436 | 2024-07-01 02:29:56 | coarsens | 1 | 82945 | 3 | 5.140 | 16137.2 |
435 | 2024-06-14 17:55:18 | coarsens | 1 | 82945 | 3 | 2.063 | 40206.0 |
434 | 2024-06-13 06:20:28 | coarsens | 1 | 82945 | 3 | 6.843 | 12121.1 |
433 | 2024-06-03 01:08:49 | coarsens | 1 | 82945 | 3 | 1.516 | 54713.1 |
432 | 2024-06-02 19:43:38 | coarsens | 1 | 82945 | 3 | 6.673 | 12429.9 |
431 | 2024-06-01 08:28:08 | coarsens | 1 | 82945 | 3 | 7.483 | 11084.5 |
430 | 2024-05-16 07:20:50 | coarsens | 2 | 121059 | 18 | 4.300 | 28153.3 |
429 | 2024-05-16 02:22:37 | coarsens | 3 | 146162 | 218 | 25.316 | 5773.5 |
428 | 2024-05-16 02:22:36 | coarsens | 2 | 121059 | 18 | 8.920 | 13571.6 |
427 | 2024-05-16 01:34:59 | coarsens | 1 | 82945 | 3 | 1.550 | 53512.9 |
426 | 2024-05-07 02:21:28 | coarsens | 1 | 82945 | 3 | 1.716 | 48336.2 |
425 | 2024-04-15 00:48:27 | coarsens | 3 | 146162 | 218 | 10.016 | 14592.9 |
424 | 2024-04-15 00:48:22 | coarsens | 3 | 146162 | 218 | 10.500 | 13920.2 |
423 | 2024-04-11 04:58:34 | coarsens | 3 | 146162 | 218 | 10.673 | 13694.6 |
422 | 2024-04-11 04:58:35 | coarsens | 2 | 121059 | 18 | 7.796 | 15528.3 |
421 | 2024-04-10 09:09:49 | coarsens | 2 | 121059 | 18 | 6.936 | 17453.7 |
420 | 2024-04-10 09:09:48 | coarsens | 3 | 146162 | 218 | 8.030 | 18202.0 |
419 | 2024-04-10 09:08:35 | coarsens | 1 | 82945 | 3 | 2.266 | 36604.1 |
418 | 2024-04-09 11:31:00 | coarsens | 2 | 121059 | 18 | 15.003 | 8069.0 |
417 | 2024-04-09 11:30:54 | coarsens | 3 | 146162 | 218 | 17.736 | 8241.0 |
416 | 2024-04-09 10:14:48 | coarsens | 1 | 82945 | 3 | 1.343 | 61761.0 |
415 | 2024-04-04 20:38:49 | coarsens | 3 | 146162 | 218 | 20.410 | 7161.3 |
414 | 2024-04-03 18:41:07 | coarsens | 3 | 146162 | 218 | 9.483 | 15413.1 |
413 | 2024-03-29 09:59:49 | coarsens | 1 | 82945 | 3 | 4.360 | 19024.1 |
412 | 2024-03-29 09:59:21 | coarsens | 2 | 121059 | 18 | 4.156 | 29128.7 |
411 | 2024-03-29 04:21:43 | coarsens | 3 | 146162 | 218 | 14.266 | 10245.5 |
410 | 2024-03-29 03:41:13 | coarsens | 3 | 146162 | 218 | 20.733 | 7049.7 |
409 | 2024-03-29 03:41:14 | coarsens | 2 | 121059 | 18 | 8.030 | 15075.8 |
408 | 2024-03-29 03:41:02 | coarsens | 1 | 82945 | 3 | 5.030 | 16490.1 |
407 | 2024-03-27 14:23:58 | coarsens | 1 | 82945 | 3 | 3.156 | 26281.7 |
406 | 2024-03-12 00:10:52 | coarsens | 2 | 121059 | 18 | 8.093 | 14958.5 |
405 | 2024-03-12 00:10:27 | coarsens | 3 | 146162 | 218 | 8.890 | 16441.2 |
404 | 2024-03-11 01:30:34 | coarsens | 3 | 146162 | 218 | 29.376 | 4975.6 |
403 | 2024-03-10 23:27:01 | coarsens | 2 | 121059 | 18 | 3.563 | 33976.7 |
402 | 2024-03-10 23:26:58 | coarsens | 1 | 82945 | 3 | 1.563 | 53067.8 |
401 | 2024-03-04 23:41:21 | coarsens | 1 | 82945 | 3 | 1.376 | 60279.8 |
400 | 2024-02-26 10:14:55 | coarsens | 1 | 82945 | 3 | 1.296 | 64000.8 |
399 | 2024-02-02 18:38:26 | coarsens | 1 | 82945 | 3 | 3.080 | 26930.2 |
398 | 2024-01-30 14:25:47 | coarsens | 3 | 146162 | 218 | 8.250 | 17716.6 |
397 | 2024-01-30 14:25:39 | coarsens | 2 | 121059 | 18 | 3.843 | 31501.2 |
396 | 2024-01-30 06:20:58 | coarsens | 1 | 82945 | 3 | 1.516 | 54713.1 |
395 | 2024-01-29 13:36:59 | coarsens | 2 | 121059 | 18 | 3.766 | 32145.2 |
394 | 2024-01-17 21:22:11 | coarsens | 2 | 121059 | 18 | 4.673 | 25906.1 |
393 | 2024-01-08 19:21:03 | coarsens | 3 | 146162 | 218 | 8.580 | 17035.2 |
392 | 2023-12-25 16:15:55 | coarsens | 1 | 82945 | 3 | 1.500 | 55296.7 |
391 | 2023-12-12 22:13:02 | coarsens | 3 | 146162 | 218 | 7.643 | 19123.6 |
390 | 2023-12-06 00:03:43 | coarsens | 2 | 121059 | 18 | 3.283 | 36874.5 |
389 | 2023-12-05 11:22:18 | coarsens | 3 | 146162 | 218 | 7.936 | 18417.6 |
388 | 2023-11-27 18:26:29 | coarsens | 1 | 82945 | 3 | 1.346 | 61623.3 |
387 | 2023-11-20 05:35:40 | coarsens | 1 | 82945 | 3 | 1.453 | 57085.3 |
386 | 2023-11-16 08:50:29 | coarsens | 3 | 146162 | 218 | 7.233 | 20207.7 |
385 | 2023-11-16 08:50:19 | coarsens | 2 | 121059 | 18 | 3.453 | 35059.1 |
384 | 2023-11-10 09:29:26 | coarsens | 1 | 82945 | 3 | 1.296 | 64000.8 |
383 | 2023-10-26 22:17:17 | coarsens | 1 | 82945 | 3 | 1.533 | 54106.3 |
382 | 2023-10-20 14:51:39 | coarsens | 1 | 82945 | 3 | 1.560 | 53169.9 |
381 | 2023-10-17 12:01:13 | coarsens | 1 | 82945 | 3 | 1.346 | 61623.3 |
380 | 2023-10-11 18:02:44 | coarsens | 1 | 82945 | 3 | 1.310 | 63316.8 |
379 | 2023-10-04 03:47:27 | coarsens | 1 | 82945 | 3 | 1.343 | 61761.0 |
378 | 2023-09-22 23:20:16 | coarsens | 1 | 82945 | 3 | 1.330 | 62364.7 |