History of Dictionary Searches using Damerau-Levenshtein distance in T-SQL
Fuzzy-string Searches
(up to 100 most recent)
for
"cohorts"
Num | Started At (CA time) | Searched Word | Change Limit | Words Checked | Words Matched | Seconds | Words Per Sec |
491 | 2025-07-12 08:51:02 | cohorts | 2 | 107671 | 29 | 4.470 | 24087.5 |
490 | 2025-07-09 09:38:56 | cohorts | 1 | 69583 | 3 | 1.233 | 56433.9 |
489 | 2025-07-03 20:49:56 | cohorts | 2 | 107671 | 29 | 3.466 | 31064.9 |
488 | 2025-07-01 21:43:06 | cohorts | 2 | 107671 | 29 | 10.843 | 9930.0 |
487 | 2025-06-30 23:46:35 | cohorts | 1 | 69583 | 3 | 1.173 | 59320.5 |
486 | 2025-06-29 17:08:03 | cohorts | 1 | 69583 | 3 | 1.233 | 56433.9 |
485 | 2025-06-29 15:21:54 | cohorts | 3 | 134027 | 326 | 6.760 | 19826.5 |
484 | 2025-06-28 01:37:23 | cohorts | 3 | 134027 | 326 | 26.690 | 5021.6 |
483 | 2025-06-27 02:45:38 | cohorts | 3 | 134027 | 326 | 17.580 | 7623.8 |
482 | 2025-06-25 10:01:36 | cohorts | 1 | 69583 | 3 | 7.280 | 9558.1 |
481 | 2025-06-25 03:08:12 | cohorts | 3 | 134027 | 326 | 26.516 | 5054.6 |
480 | 2025-06-24 19:59:35 | cohorts | 2 | 107671 | 29 | 3.263 | 32997.5 |
479 | 2025-06-24 11:07:05 | cohorts | 1 | 69583 | 3 | 3.296 | 21111.3 |
478 | 2025-06-23 12:44:35 | cohorts | 3 | 134027 | 326 | 24.690 | 5428.4 |
477 | 2025-06-22 06:04:24 | cohorts | 1 | 69583 | 3 | 3.970 | 17527.2 |
476 | 2025-06-20 21:31:40 | cohorts | 1 | 69583 | 3 | 4.876 | 14270.5 |
475 | 2025-06-16 05:52:45 | cohorts | 1 | 69583 | 3 | 6.750 | 10308.6 |
474 | 2025-06-15 15:11:51 | cohorts | 3 | 134027 | 326 | 11.690 | 11465.1 |
473 | 2025-06-13 21:44:58 | cohorts | 3 | 134027 | 326 | 35.733 | 3750.8 |
472 | 2025-06-11 12:56:21 | cohorts | 1 | 69583 | 3 | 3.766 | 18476.6 |
471 | 2025-06-08 10:12:23 | cohorts | 1 | 69583 | 3 | 2.893 | 24052.2 |
470 | 2025-06-06 05:13:47 | cohorts | 2 | 107671 | 29 | 11.750 | 9163.5 |
469 | 2025-06-03 05:55:24 | cohorts | 2 | 107671 | 29 | 10.643 | 10116.6 |
468 | 2025-06-02 23:39:02 | cohorts | 3 | 134027 | 326 | 33.113 | 4047.6 |
467 | 2025-06-01 18:28:31 | cohorts | 1 | 69583 | 3 | 2.763 | 25183.9 |
466 | 2025-05-31 17:33:45 | cohorts | 2 | 107671 | 29 | 9.783 | 11005.9 |
465 | 2025-05-30 17:06:30 | cohorts | 1 | 69583 | 3 | 1.153 | 60349.5 |
464 | 2025-05-22 02:47:01 | cohorts | 3 | 134027 | 326 | 34.360 | 3900.7 |
463 | 2025-05-21 07:05:59 | cohorts | 1 | 69583 | 3 | 8.796 | 7910.8 |
462 | 2025-05-20 16:09:00 | cohorts | 3 | 134027 | 326 | 33.703 | 3976.7 |
461 | 2025-05-20 03:42:19 | cohorts | 3 | 134027 | 326 | 22.596 | 5931.4 |
460 | 2025-05-19 01:39:49 | cohorts | 3 | 134027 | 326 | 6.050 | 22153.2 |
459 | 2025-05-17 08:51:47 | cohorts | 3 | 134027 | 326 | 18.263 | 7338.7 |
458 | 2025-05-12 05:36:07 | cohorts | 1 | 69583 | 3 | 5.390 | 12909.6 |
457 | 2025-04-22 12:50:57 | cohorts | 2 | 107671 | 29 | 2.856 | 37699.9 |
456 | 2025-04-21 07:27:14 | cohorts | 2 | 107671 | 29 | 12.266 | 8778.0 |
455 | 2025-04-20 11:54:37 | cohorts | 3 | 134027 | 326 | 15.953 | 8401.4 |
454 | 2025-04-20 09:47:16 | cohorts | 1 | 69583 | 3 | 1.266 | 54962.9 |
453 | 2025-04-19 18:54:11 | cohorts | 1 | 69583 | 3 | 1.266 | 54962.9 |
452 | 2025-04-18 23:58:38 | cohorts | 3 | 134027 | 326 | 15.766 | 8501.0 |
451 | 2025-04-18 09:30:17 | cohorts | 1 | 69583 | 3 | 5.110 | 13617.0 |
450 | 2025-04-18 04:03:22 | cohorts | 2 | 107671 | 29 | 7.766 | 13864.4 |
449 | 2025-04-17 13:17:34 | cohorts | 2 | 107671 | 29 | 3.470 | 31029.1 |
448 | 2025-04-17 11:51:01 | cohorts | 3 | 134027 | 326 | 6.516 | 20568.9 |
447 | 2025-04-16 04:50:43 | cohorts | 1 | 69583 | 3 | 6.186 | 11248.5 |
446 | 2025-04-11 07:41:07 | cohorts | 1 | 69583 | 3 | 7.190 | 9677.7 |
445 | 2025-04-06 11:18:17 | cohorts | 1 | 69583 | 3 | 6.296 | 11051.9 |
444 | 2025-03-20 12:15:05 | cohorts | 1 | 69583 | 3 | 6.156 | 11303.3 |
443 | 2025-03-18 19:51:41 | cohorts | 1 | 69583 | 3 | 1.060 | 65644.3 |
442 | 2025-03-17 19:23:54 | cohorts | 1 | 69583 | 3 | 8.060 | 8633.1 |
441 | 2025-03-15 00:31:00 | cohorts | 1 | 69583 | 3 | 6.533 | 10651.0 |
440 | 2025-03-08 18:24:18 | cohorts | 1 | 69583 | 3 | 4.593 | 15149.8 |
439 | 2025-03-04 03:34:30 | cohorts | 1 | 69583 | 3 | 5.830 | 11935.3 |
438 | 2025-02-19 17:42:25 | cohorts | 1 | 69583 | 3 | 5.546 | 12546.5 |
437 | 2025-02-04 20:48:12 | cohorts | 1 | 69583 | 3 | 6.796 | 10238.8 |
436 | 2025-01-29 22:07:19 | cohorts | 1 | 69583 | 3 | 2.940 | 23667.7 |
435 | 2024-12-29 14:01:59 | cohorts | 1 | 69583 | 3 | 3.110 | 22374.0 |
434 | 2024-12-26 18:23:40 | cohorts | 1 | 69583 | 3 | 3.296 | 21111.3 |
433 | 2024-11-28 18:15:34 | cohorts | 1 | 69583 | 3 | 7.483 | 9298.8 |
432 | 2024-11-26 12:18:11 | cohorts | 1 | 69583 | 3 | 4.096 | 16988.0 |
431 | 2024-11-09 17:21:37 | cohorts | 1 | 69583 | 3 | 5.390 | 12909.6 |
430 | 2024-11-02 10:28:14 | cohorts | 1 | 69583 | 3 | 1.296 | 53690.6 |
429 | 2024-10-28 13:22:16 | cohorts | 1 | 69583 | 3 | 7.953 | 8749.3 |
428 | 2024-10-21 18:31:58 | cohorts | 3 | 134027 | 326 | 32.330 | 4145.6 |
427 | 2024-10-20 23:59:35 | cohorts | 3 | 134027 | 326 | 37.020 | 3620.4 |
426 | 2024-10-20 10:48:14 | cohorts | 3 | 134027 | 326 | 30.313 | 4421.4 |
425 | 2024-10-18 14:27:19 | cohorts | 3 | 134027 | 326 | 34.546 | 3879.7 |
424 | 2024-10-18 14:27:21 | cohorts | 2 | 107671 | 29 | 13.736 | 7838.6 |
423 | 2024-10-18 14:25:51 | cohorts | 1 | 69583 | 3 | 5.483 | 12690.7 |
422 | 2024-10-11 10:10:20 | cohorts | 1 | 69583 | 3 | 3.656 | 19032.5 |
421 | 2024-09-26 03:13:33 | cohorts | 1 | 69583 | 3 | 7.813 | 8906.1 |
420 | 2024-09-22 08:21:07 | cohorts | 1 | 69583 | 3 | 10.876 | 6397.8 |
419 | 2024-09-09 02:49:58 | cohorts | 1 | 69583 | 3 | 4.360 | 15959.4 |
418 | 2024-08-13 03:45:33 | cohorts | 1 | 69583 | 3 | 6.016 | 11566.3 |
417 | 2024-08-11 22:55:45 | cohorts | 1 | 69583 | 3 | 3.233 | 21522.7 |
416 | 2024-08-02 23:55:38 | cohorts | 3 | 134027 | 326 | 37.160 | 3606.8 |
415 | 2024-08-02 06:35:34 | cohorts | 3 | 134027 | 326 | 31.986 | 4190.2 |
414 | 2024-08-02 02:26:04 | cohorts | 3 | 134027 | 326 | 24.283 | 5519.4 |
413 | 2024-08-02 00:01:49 | cohorts | 3 | 134027 | 326 | 13.423 | 9984.9 |
412 | 2024-08-02 00:01:45 | cohorts | 2 | 107671 | 29 | 14.953 | 7200.6 |
411 | 2024-08-01 23:57:03 | cohorts | 1 | 69583 | 3 | 5.753 | 12095.1 |
410 | 2024-08-01 23:16:20 | cohorts | 1 | 69583 | 3 | 5.373 | 12950.5 |
409 | 2024-07-31 04:39:30 | cohorts | 1 | 69583 | 3 | 4.640 | 14996.3 |
408 | 2024-07-29 22:41:15 | cohorts | 1 | 69583 | 3 | 1.250 | 55666.4 |
407 | 2024-07-18 20:29:27 | cohorts | 1 | 69583 | 3 | 1.343 | 51811.6 |
406 | 2024-07-13 23:18:26 | cohorts | 1 | 69583 | 3 | 6.766 | 10284.2 |
405 | 2024-07-01 20:13:18 | cohorts | 1 | 69583 | 3 | 5.466 | 12730.2 |
404 | 2024-07-01 16:24:31 | cohorts | 1 | 69583 | 3 | 3.843 | 18106.4 |
403 | 2024-07-01 02:46:53 | cohorts | 1 | 69583 | 3 | 21.236 | 3276.7 |
402 | 2024-06-30 08:00:41 | cohorts | 1 | 69583 | 3 | 5.893 | 11807.7 |
401 | 2024-06-26 21:21:23 | cohorts | 1 | 69583 | 3 | 6.686 | 10407.3 |
400 | 2024-06-19 20:58:58 | cohorts | 1 | 69583 | 3 | 2.736 | 25432.4 |
399 | 2024-05-31 07:53:29 | cohorts | 1 | 69583 | 3 | 4.406 | 15792.8 |
398 | 2024-05-29 13:42:09 | cohorts | 1 | 69583 | 3 | 2.186 | 31831.2 |
397 | 2024-05-16 10:41:16 | cohorts | 3 | 134027 | 326 | 15.393 | 8707.0 |
396 | 2024-05-15 14:06:56 | cohorts | 3 | 134027 | 326 | 9.703 | 13812.9 |
395 | 2024-05-14 04:45:35 | cohorts | 2 | 107671 | 29 | 3.326 | 32372.5 |
394 | 2024-05-14 04:45:13 | cohorts | 3 | 134027 | 326 | 7.610 | 17612.0 |
393 | 2024-05-11 17:02:18 | cohorts | 3 | 134027 | 326 | 16.093 | 8328.3 |
392 | 2024-05-11 13:00:25 | cohorts | 3 | 134027 | 326 | 26.440 | 5069.1 |