History of Dictionary Searches using Damerau-Levenshtein distance in T-SQL
Fuzzy-string Searches
(up to 100 most recent)
for
"trained"
Num | Started At (CA time) | Searched Word | Change Limit | Words Checked | Words Matched | Seconds | Words Per Sec |
542 | 2025-08-12 15:45:05 | trained | 1 | 69583 | 11 | 2.326 | 29915.3 |
541 | 2025-08-08 05:16:58 | trained | 1 | 69583 | 11 | 4.360 | 15959.4 |
540 | 2025-08-06 07:00:24 | trained | 2 | 107671 | 69 | 7.970 | 13509.5 |
539 | 2025-08-05 01:41:57 | trained | 2 | 107671 | 69 | 9.376 | 11483.7 |
538 | 2025-08-05 01:16:02 | trained | 1 | 69583 | 11 | 3.206 | 21704.0 |
537 | 2025-08-04 02:12:10 | trained | 3 | 134027 | 755 | 8.533 | 15706.9 |
536 | 2025-08-03 10:02:59 | trained | 3 | 134027 | 755 | 50.003 | 2680.4 |
535 | 2025-08-03 10:00:11 | trained | 2 | 107671 | 69 | 12.656 | 8507.5 |
534 | 2025-08-01 01:26:25 | trained | 1 | 69583 | 11 | 3.096 | 22475.1 |
533 | 2025-07-31 22:00:26 | trained | 3 | 134027 | 755 | 24.406 | 5491.6 |
532 | 2025-07-31 07:07:39 | trained | 1 | 69583 | 11 | 1.250 | 55666.4 |
531 | 2025-07-28 14:54:11 | trained | 3 | 134027 | 755 | 18.973 | 7064.1 |
530 | 2025-07-27 16:59:11 | trained | 3 | 134027 | 755 | 18.563 | 7220.1 |
529 | 2025-07-25 03:06:05 | trained | 1 | 69583 | 11 | 5.456 | 12753.5 |
528 | 2025-07-25 01:25:17 | trained | 1 | 69583 | 11 | 3.373 | 20629.4 |
527 | 2025-07-24 09:32:12 | trained | 3 | 134027 | 755 | 22.500 | 5956.8 |
526 | 2025-07-24 08:54:06 | trained | 3 | 134027 | 755 | 19.186 | 6985.7 |
525 | 2025-07-24 01:45:56 | trained | 1 | 69583 | 11 | 5.593 | 12441.1 |
524 | 2025-07-24 00:45:31 | trained | 1 | 69583 | 11 | 6.123 | 11364.2 |
523 | 2025-07-23 12:15:27 | trained | 1 | 69583 | 11 | 4.296 | 16197.2 |
522 | 2025-07-22 02:22:59 | trained | 3 | 134027 | 755 | 12.220 | 10967.8 |
521 | 2025-07-20 19:52:10 | trained | 3 | 134027 | 755 | 6.360 | 21073.4 |
520 | 2025-07-17 20:45:57 | trained | 2 | 107671 | 69 | 23.050 | 4671.2 |
519 | 2025-07-16 22:42:02 | trained | 1 | 69583 | 11 | 3.046 | 22844.1 |
518 | 2025-07-14 07:07:39 | trained | 2 | 107671 | 69 | 21.953 | 4904.6 |
517 | 2025-07-13 14:32:44 | trained | 1 | 69583 | 11 | 1.266 | 54962.9 |
516 | 2025-07-13 08:53:40 | trained | 3 | 134027 | 755 | 7.593 | 17651.4 |
515 | 2025-07-11 03:30:53 | trained | 3 | 134027 | 755 | 41.093 | 3261.6 |
514 | 2025-07-10 02:53:47 | trained | 1 | 69583 | 11 | 8.203 | 8482.6 |
513 | 2025-07-08 16:04:15 | trained | 1 | 69583 | 11 | 5.843 | 11908.8 |
512 | 2025-07-06 19:41:05 | trained | 1 | 69583 | 11 | 1.283 | 54234.6 |
511 | 2025-07-05 10:10:36 | trained | 3 | 134027 | 755 | 38.973 | 3439.0 |
510 | 2025-07-05 04:59:32 | trained | 3 | 134027 | 755 | 39.906 | 3358.6 |
509 | 2025-07-04 01:24:49 | trained | 1 | 69583 | 11 | 5.826 | 11943.5 |
508 | 2025-07-03 21:41:46 | trained | 3 | 134027 | 755 | 6.750 | 19855.9 |
507 | 2025-07-02 03:10:55 | trained | 1 | 69583 | 11 | 4.280 | 16257.7 |
506 | 2025-07-01 20:25:18 | trained | 3 | 134027 | 755 | 35.063 | 3822.5 |
505 | 2025-06-29 23:41:41 | trained | 3 | 134027 | 755 | 49.126 | 2728.2 |
504 | 2025-06-29 11:38:37 | trained | 3 | 134027 | 755 | 7.716 | 17370.0 |
503 | 2025-06-28 20:42:36 | trained | 1 | 69583 | 11 | 1.203 | 57841.2 |
502 | 2025-06-23 13:55:58 | trained | 3 | 134027 | 755 | 19.253 | 6961.4 |
501 | 2025-06-22 00:43:33 | trained | 1 | 69583 | 11 | 9.016 | 7717.7 |
500 | 2025-06-13 02:24:42 | trained | 3 | 134027 | 755 | 10.750 | 12467.6 |
499 | 2025-06-12 16:35:26 | trained | 2 | 107671 | 69 | 16.816 | 6402.9 |
498 | 2025-06-12 13:35:17 | trained | 1 | 69583 | 11 | 5.843 | 11908.8 |
497 | 2025-06-12 00:03:05 | trained | 2 | 107671 | 69 | 17.003 | 6332.5 |
496 | 2025-06-11 04:06:14 | trained | 3 | 134027 | 755 | 41.923 | 3197.0 |
495 | 2025-06-11 00:51:41 | trained | 3 | 134027 | 755 | 7.703 | 17399.3 |
494 | 2025-06-10 23:31:18 | trained | 1 | 69583 | 11 | 4.546 | 15306.4 |
493 | 2025-06-10 21:14:06 | trained | 3 | 134027 | 755 | 7.266 | 18445.8 |
492 | 2025-06-10 14:00:12 | trained | 1 | 69583 | 11 | 5.470 | 12720.8 |
491 | 2025-06-09 18:06:32 | trained | 3 | 134027 | 755 | 5.983 | 22401.3 |
490 | 2025-06-04 00:07:38 | trained | 1 | 69583 | 11 | 4.500 | 15462.9 |
489 | 2025-06-02 02:39:35 | trained | 1 | 69583 | 11 | 2.796 | 24886.6 |
488 | 2025-06-01 08:44:55 | trained | 1 | 69583 | 11 | 5.313 | 13096.7 |
487 | 2025-06-01 02:07:52 | trained | 1 | 69583 | 11 | 5.780 | 12038.6 |
486 | 2025-05-31 19:26:30 | trained | 1 | 69583 | 11 | 5.966 | 11663.3 |
485 | 2025-05-30 08:23:24 | trained | 3 | 134027 | 755 | 41.346 | 3241.6 |
484 | 2025-05-30 00:38:47 | trained | 3 | 134027 | 755 | 11.123 | 12049.5 |
483 | 2025-05-28 05:11:03 | trained | 3 | 134027 | 755 | 6.530 | 20524.8 |
482 | 2025-05-26 23:27:09 | trained | 3 | 134027 | 755 | 18.923 | 7082.8 |
481 | 2025-05-25 16:08:04 | trained | 3 | 134027 | 755 | 6.280 | 21341.9 |
480 | 2025-05-22 21:40:57 | trained | 2 | 107671 | 69 | 3.390 | 31761.4 |
479 | 2025-05-21 00:28:27 | trained | 1 | 69583 | 11 | 1.250 | 55666.4 |
478 | 2025-05-12 16:26:42 | trained | 2 | 107671 | 69 | 13.470 | 7993.4 |
477 | 2025-05-10 23:33:58 | trained | 1 | 69583 | 11 | 3.030 | 22964.7 |
476 | 2025-05-10 16:14:49 | trained | 1 | 69583 | 11 | 7.376 | 9433.7 |
475 | 2025-05-10 05:03:05 | trained | 1 | 69583 | 11 | 4.093 | 17000.5 |
474 | 2025-05-09 21:40:32 | trained | 3 | 134027 | 755 | 34.113 | 3928.9 |
473 | 2025-05-09 01:01:45 | trained | 3 | 134027 | 755 | 11.016 | 12166.6 |
472 | 2025-05-06 03:21:17 | trained | 1 | 69583 | 11 | 7.530 | 9240.8 |
471 | 2025-05-04 23:33:19 | trained | 1 | 69583 | 11 | 1.300 | 53525.4 |
470 | 2025-05-04 00:09:38 | trained | 1 | 69583 | 11 | 5.766 | 12067.8 |
469 | 2025-05-02 02:36:24 | trained | 1 | 69583 | 11 | 6.970 | 9983.2 |
468 | 2025-04-26 09:07:34 | trained | 3 | 134027 | 755 | 52.940 | 2531.7 |
467 | 2025-04-25 23:24:46 | trained | 3 | 134027 | 755 | 32.266 | 4153.8 |
466 | 2025-04-25 17:42:28 | trained | 3 | 134027 | 755 | 7.266 | 18445.8 |
465 | 2025-04-25 13:11:42 | trained | 2 | 107671 | 69 | 3.516 | 30623.2 |
464 | 2025-04-25 08:28:55 | trained | 3 | 134027 | 755 | 32.390 | 4137.9 |
463 | 2025-04-23 20:57:21 | trained | 1 | 69583 | 11 | 6.970 | 9983.2 |
462 | 2025-04-23 04:15:02 | trained | 1 | 69583 | 11 | 7.876 | 8834.8 |
461 | 2025-04-20 00:14:29 | trained | 1 | 69583 | 11 | 8.080 | 8611.8 |
460 | 2025-04-11 17:22:11 | trained | 2 | 107671 | 69 | 19.406 | 5548.3 |
459 | 2025-04-08 23:47:07 | trained | 2 | 107671 | 69 | 13.190 | 8163.1 |
458 | 2025-04-08 23:24:09 | trained | 1 | 69583 | 11 | 3.750 | 18555.5 |
457 | 2025-04-07 21:21:26 | trained | 2 | 107671 | 69 | 25.376 | 4243.0 |
456 | 2025-04-03 23:36:01 | trained | 1 | 69583 | 11 | 4.156 | 16742.8 |
455 | 2025-04-02 02:08:47 | trained | 1 | 69583 | 11 | 5.330 | 13055.0 |
454 | 2025-03-21 05:25:35 | trained | 2 | 107671 | 69 | 30.263 | 3557.8 |
453 | 2025-03-21 03:54:55 | trained | 3 | 134027 | 755 | 38.350 | 3494.8 |
452 | 2025-03-20 01:39:04 | trained | 1 | 69583 | 11 | 4.733 | 14701.7 |
451 | 2025-03-20 01:01:58 | trained | 3 | 134027 | 755 | 30.800 | 4351.5 |
450 | 2025-03-19 22:17:40 | trained | 3 | 134027 | 755 | 36.266 | 3695.7 |
449 | 2025-03-19 19:17:17 | trained | 3 | 134027 | 755 | 5.860 | 22871.5 |
448 | 2025-03-19 10:50:17 | trained | 3 | 134027 | 755 | 35.470 | 3778.6 |
447 | 2025-03-18 01:24:26 | trained | 3 | 134027 | 755 | 46.283 | 2895.8 |
446 | 2025-03-18 01:24:26 | trained | 2 | 107671 | 69 | 14.453 | 7449.7 |
445 | 2025-03-10 17:08:49 | trained | 2 | 107671 | 69 | 17.186 | 6265.0 |
444 | 2025-03-10 10:10:01 | trained | 2 | 107671 | 69 | 7.953 | 13538.4 |
443 | 2025-03-09 22:15:56 | trained | 1 | 69583 | 11 | 7.780 | 8943.8 |