History of Dictionary Searches using Damerau-Levenshtein distance in T-SQL
Fuzzy-string Searches
(up to 100 most recent)
for
"unharness"
Num | Started At (CA time) | Searched Word | Change Limit | Words Checked | Words Matched | Seconds | Words Per Sec |
474 | 2025-08-20 15:05:00 | unharness | 1 | 81242 | 1 | 1.360 | 59736.8 |
473 | 2025-08-19 00:20:22 | unharness | 1 | 81242 | 1 | 3.220 | 25230.4 |
472 | 2025-08-12 01:31:38 | unharness | 2 | 121436 | 7 | 15.970 | 7604.0 |
471 | 2025-08-12 00:22:01 | unharness | 3 | 148641 | 42 | 22.893 | 6492.9 |
470 | 2025-08-09 10:07:47 | unharness | 1 | 81242 | 1 | 2.920 | 27822.6 |
469 | 2025-08-08 20:05:49 | unharness | 1 | 81242 | 1 | 1.343 | 60492.9 |
468 | 2025-08-04 11:02:18 | unharness | 1 | 81242 | 1 | 3.656 | 22221.6 |
467 | 2025-08-02 09:13:16 | unharness | 4 | 165329 | 433 | 30.436 | 5432.0 |
466 | 2025-07-29 10:34:06 | unharness | 4 | 165329 | 433 | 47.846 | 3455.4 |
465 | 2025-07-28 23:06:17 | unharness | 4 | 165329 | 433 | 46.956 | 3520.9 |
464 | 2025-07-28 09:34:25 | unharness | 3 | 148641 | 42 | 18.593 | 7994.5 |
463 | 2025-07-28 09:23:28 | unharness | 3 | 148641 | 42 | 16.170 | 9192.4 |
462 | 2025-07-25 12:19:26 | unharness | 4 | 165329 | 433 | 58.850 | 2809.3 |
461 | 2025-07-25 08:01:32 | unharness | 3 | 148641 | 42 | 19.423 | 7652.8 |
460 | 2025-07-25 00:53:33 | unharness | 2 | 121436 | 7 | 11.860 | 10239.1 |
459 | 2025-07-22 18:17:14 | unharness | 1 | 81242 | 1 | 9.456 | 8591.6 |
458 | 2025-07-19 18:44:08 | unharness | 1 | 81242 | 1 | 1.436 | 56575.2 |
457 | 2025-07-10 14:24:11 | unharness | 1 | 81242 | 1 | 4.876 | 16661.6 |
456 | 2025-07-05 23:30:27 | unharness | 1 | 81242 | 1 | 6.393 | 12708.0 |
455 | 2025-07-05 00:51:03 | unharness | 1 | 81242 | 1 | 3.736 | 21745.7 |
454 | 2025-07-01 12:57:11 | unharness | 1 | 81242 | 1 | 1.393 | 58321.6 |
453 | 2025-06-30 10:11:03 | unharness | 1 | 81242 | 1 | 3.466 | 23439.7 |
452 | 2025-06-26 12:08:45 | unharness | 3 | 148641 | 42 | 28.563 | 5204.0 |
451 | 2025-06-26 00:16:13 | unharness | 1 | 81242 | 1 | 3.533 | 22995.2 |
450 | 2025-06-24 08:53:50 | unharness | 1 | 81242 | 1 | 4.966 | 16359.6 |
449 | 2025-06-24 08:29:54 | unharness | 3 | 148641 | 42 | 29.050 | 5116.7 |
448 | 2025-06-23 22:33:34 | unharness | 2 | 121436 | 7 | 20.563 | 5905.6 |
447 | 2025-06-21 04:05:16 | unharness | 3 | 148641 | 42 | 18.050 | 8235.0 |
446 | 2025-06-18 06:34:52 | unharness | 2 | 121436 | 7 | 25.063 | 4845.2 |
445 | 2025-06-17 16:35:29 | unharness | 1 | 81242 | 1 | 1.233 | 65889.7 |
444 | 2025-06-16 16:10:33 | unharness | 3 | 148641 | 42 | 32.406 | 4586.8 |
443 | 2025-06-14 20:30:42 | unharness | 3 | 148641 | 42 | 35.423 | 4196.2 |
442 | 2025-06-10 07:56:58 | unharness | 1 | 81242 | 1 | 5.030 | 16151.5 |
441 | 2025-06-10 07:43:01 | unharness | 1 | 81242 | 1 | 7.016 | 11579.5 |
440 | 2025-06-07 23:05:28 | unharness | 4 | 165329 | 433 | 67.850 | 2436.7 |
439 | 2025-06-02 04:00:38 | unharness | 4 | 165329 | 433 | 86.770 | 1905.4 |
438 | 2025-05-30 12:22:12 | unharness | 4 | 165329 | 433 | 52.363 | 3157.4 |
437 | 2025-05-30 05:08:52 | unharness | 4 | 165329 | 433 | 45.593 | 3626.2 |
436 | 2025-05-30 04:59:15 | unharness | 1 | 81242 | 1 | 3.230 | 25152.3 |
435 | 2025-05-29 08:28:54 | unharness | 4 | 165329 | 433 | 60.800 | 2719.2 |
434 | 2025-05-27 00:17:01 | unharness | 4 | 165329 | 433 | 55.050 | 3003.3 |
433 | 2025-05-26 10:43:06 | unharness | 1 | 81242 | 1 | 4.140 | 19623.7 |
432 | 2025-05-21 18:33:03 | unharness | 1 | 81242 | 1 | 1.356 | 59913.0 |
431 | 2025-05-16 16:42:52 | unharness | 1 | 81242 | 1 | 6.766 | 12007.4 |
430 | 2025-05-16 08:43:23 | unharness | 1 | 81242 | 1 | 4.936 | 16459.1 |
429 | 2025-05-01 22:50:58 | unharness | 4 | 165329 | 433 | 66.846 | 2473.3 |
428 | 2025-04-30 12:13:15 | unharness | 4 | 165329 | 433 | 43.846 | 3770.7 |
427 | 2025-04-30 03:35:26 | unharness | 4 | 165329 | 433 | 40.860 | 4046.2 |
426 | 2025-04-29 21:10:40 | unharness | 4 | 165329 | 433 | 57.080 | 2896.4 |
425 | 2025-04-28 08:32:19 | unharness | 4 | 165329 | 433 | 68.456 | 2415.1 |
424 | 2025-04-27 02:28:10 | unharness | 4 | 165329 | 433 | 15.640 | 10570.9 |
423 | 2025-04-17 15:55:27 | unharness | 1 | 81242 | 1 | 1.220 | 66591.8 |
422 | 2025-04-11 00:09:31 | unharness | 1 | 81242 | 1 | 9.736 | 8344.5 |
421 | 2025-04-09 07:34:45 | unharness | 1 | 81242 | 1 | 9.593 | 8468.9 |
420 | 2025-04-04 07:33:05 | unharness | 1 | 81242 | 1 | 8.796 | 9236.2 |
419 | 2025-03-23 11:34:12 | unharness | 1 | 81242 | 1 | 3.530 | 23014.7 |
418 | 2025-03-20 08:54:19 | unharness | 1 | 81242 | 1 | 9.453 | 8594.3 |
417 | 2025-03-04 15:43:45 | unharness | 1 | 81242 | 1 | 4.766 | 17046.2 |
416 | 2025-02-24 08:42:15 | unharness | 3 | 148641 | 42 | 27.936 | 5320.8 |
415 | 2025-02-23 16:38:03 | unharness | 3 | 148641 | 42 | 35.783 | 4154.0 |
414 | 2025-02-23 16:37:55 | unharness | 2 | 121436 | 7 | 13.940 | 8711.3 |
413 | 2025-02-22 03:57:34 | unharness | 3 | 148641 | 42 | 49.113 | 3026.5 |
412 | 2025-02-22 03:57:40 | unharness | 3 | 148641 | 42 | 28.656 | 5187.1 |
411 | 2025-02-22 03:57:39 | unharness | 2 | 121436 | 7 | 20.013 | 6067.9 |
410 | 2025-02-22 03:53:59 | unharness | 1 | 81242 | 1 | 6.390 | 12713.9 |
409 | 2025-02-20 23:38:31 | unharness | 2 | 121436 | 7 | 11.393 | 10658.8 |
408 | 2025-02-18 17:22:56 | unharness | 1 | 81242 | 1 | 6.906 | 11764.0 |
407 | 2025-02-01 09:17:20 | unharness | 3 | 148641 | 42 | 43.753 | 3397.3 |
406 | 2025-01-26 08:33:28 | unharness | 3 | 148641 | 42 | 44.723 | 3323.6 |
405 | 2025-01-26 08:17:37 | unharness | 3 | 148641 | 42 | 41.613 | 3572.0 |
404 | 2025-01-25 16:27:09 | unharness | 1 | 81242 | 1 | 6.236 | 13027.9 |
403 | 2025-01-22 22:21:40 | unharness | 1 | 81242 | 1 | 3.156 | 25742.1 |
402 | 2025-01-22 19:51:36 | unharness | 3 | 148641 | 42 | 37.596 | 3953.6 |
401 | 2025-01-21 16:13:09 | unharness | 3 | 148641 | 42 | 43.296 | 3433.1 |
400 | 2025-01-21 16:12:59 | unharness | 2 | 121436 | 7 | 16.516 | 7352.6 |
399 | 2025-01-19 05:51:34 | unharness | 3 | 148641 | 42 | 33.126 | 4487.1 |
398 | 2025-01-19 05:51:33 | unharness | 2 | 121436 | 7 | 26.160 | 4642.0 |
397 | 2025-01-18 23:43:04 | unharness | 3 | 148641 | 42 | 13.936 | 10666.0 |
396 | 2025-01-18 23:43:05 | unharness | 2 | 121436 | 7 | 4.016 | 30238.0 |
395 | 2025-01-18 23:42:51 | unharness | 1 | 81242 | 1 | 2.016 | 40298.6 |
394 | 2025-01-08 10:00:14 | unharness | 4 | 165329 | 433 | 60.753 | 2721.3 |
393 | 2025-01-05 08:52:21 | unharness | 1 | 81242 | 1 | 2.593 | 31331.3 |
392 | 2025-01-01 02:30:09 | unharness | 4 | 165329 | 433 | 58.676 | 2817.7 |
391 | 2024-12-26 07:38:21 | unharness | 1 | 81242 | 1 | 2.936 | 27671.0 |
390 | 2024-12-24 11:50:40 | unharness | 4 | 165329 | 433 | 71.410 | 2315.2 |
389 | 2024-12-23 13:13:56 | unharness | 4 | 165329 | 433 | 63.926 | 2586.3 |
388 | 2024-12-21 09:33:12 | unharness | 1 | 81242 | 1 | 2.310 | 35169.7 |
387 | 2024-12-16 17:24:29 | unharness | 1 | 81242 | 1 | 5.873 | 13833.1 |
386 | 2024-12-01 06:27:59 | unharness | 4 | 165329 | 433 | 30.610 | 5401.1 |
385 | 2024-11-27 12:53:45 | unharness | 4 | 165329 | 433 | 62.020 | 2665.7 |
384 | 2024-11-22 10:23:43 | unharness | 1 | 81242 | 1 | 6.373 | 12747.8 |
383 | 2024-11-18 18:42:17 | unharness | 4 | 165329 | 433 | 67.063 | 2465.3 |
382 | 2024-11-18 15:19:10 | unharness | 4 | 165329 | 433 | 70.610 | 2341.4 |
381 | 2024-11-13 22:53:12 | unharness | 1 | 81242 | 1 | 6.516 | 12468.1 |
380 | 2024-11-07 14:40:47 | unharness | 3 | 148641 | 42 | 20.500 | 7250.8 |
379 | 2024-11-07 12:53:41 | unharness | 1 | 81242 | 1 | 1.220 | 66591.8 |
378 | 2024-11-01 04:08:36 | unharness | 3 | 148641 | 42 | 31.190 | 4765.7 |
377 | 2024-11-01 04:07:43 | unharness | 1 | 81242 | 1 | 1.313 | 61875.1 |
376 | 2024-10-31 21:59:32 | unharness | 2 | 121436 | 7 | 25.686 | 4727.7 |
375 | 2024-10-31 03:40:38 | unharness | 2 | 121436 | 7 | 25.590 | 4745.4 |