History of Dictionary Searches using Damerau-Levenshtein distance in T-SQL
Fuzzy-string Searches
(up to 100 most recent)
for
"biases"
| Num | Started At (CA time) | Searched Word | Change Limit | Words Checked | Words Matched | Seconds | Words Per Sec |
| 651 | 2025-11-22 20:16:32 | biases | 1 | 48755 | 7 | 0.780 | 62506.4 |
| 650 | 2025-11-21 08:51:34 | biases | 1 | 48755 | 7 | 2.156 | 22613.6 |
| 649 | 2025-11-20 23:43:39 | biases | 1 | 48755 | 7 | 0.893 | 54596.9 |
| 648 | 2025-11-19 22:35:46 | biases | 2 | 82551 | 135 | 2.576 | 32046.2 |
| 647 | 2025-11-18 19:05:25 | biases | 1 | 48755 | 7 | 0.953 | 51159.5 |
| 646 | 2025-11-16 03:42:40 | biases | 1 | 48755 | 7 | 0.846 | 57630.0 |
| 645 | 2025-11-15 19:18:19 | biases | 1 | 48755 | 7 | 0.763 | 63899.1 |
| 644 | 2025-11-13 01:47:18 | biases | 1 | 48755 | 7 | 0.783 | 62266.9 |
| 643 | 2025-11-11 10:51:42 | biases | 1 | 48755 | 7 | 0.750 | 65006.7 |
| 642 | 2025-10-25 21:32:42 | biases | 1 | 48755 | 7 | 0.826 | 59025.4 |
| 641 | 2025-10-25 01:54:43 | biases | 1 | 48755 | 7 | 0.846 | 57630.0 |
| 640 | 2025-10-21 14:02:03 | biases | 2 | 82551 | 135 | 8.106 | 10183.9 |
| 639 | 2025-10-21 13:04:27 | biases | 1 | 48755 | 7 | 3.860 | 12630.8 |
| 638 | 2025-10-17 20:02:11 | biases | 1 | 48755 | 7 | 0.876 | 55656.4 |
| 637 | 2025-10-17 07:34:46 | biases | 1 | 48755 | 7 | 0.923 | 52822.3 |
| 636 | 2025-10-16 01:46:38 | biases | 1 | 48755 | 7 | 0.830 | 58741.0 |
| 635 | 2025-10-07 06:36:27 | biases | 2 | 82551 | 135 | 2.500 | 33020.4 |
| 634 | 2025-09-30 18:11:25 | biases | 1 | 48755 | 7 | 0.766 | 63648.8 |
| 633 | 2025-09-24 23:38:12 | biases | 1 | 48755 | 7 | 2.516 | 19378.0 |
| 632 | 2025-09-23 21:35:43 | biases | 1 | 48755 | 7 | 0.860 | 56691.9 |
| 631 | 2025-09-20 21:05:13 | biases | 1 | 48755 | 7 | 0.893 | 54596.9 |
| 630 | 2025-09-19 09:49:44 | biases | 1 | 48755 | 7 | 0.843 | 57835.1 |
| 629 | 2025-09-19 00:54:22 | biases | 1 | 48755 | 7 | 0.860 | 56691.9 |
| 628 | 2025-09-16 07:40:03 | biases | 1 | 48755 | 7 | 0.876 | 55656.4 |
| 627 | 2025-09-15 18:29:44 | biases | 1 | 48755 | 7 | 0.830 | 58741.0 |
| 626 | 2025-09-15 16:54:00 | biases | 1 | 48755 | 7 | 0.843 | 57835.1 |
| 625 | 2025-09-15 03:50:44 | biases | 1 | 48755 | 7 | 0.783 | 62266.9 |
| 624 | 2025-09-14 21:02:40 | biases | 1 | 48755 | 7 | 0.903 | 53992.2 |
| 623 | 2025-09-14 06:10:23 | biases | 1 | 48755 | 7 | 0.893 | 54596.9 |
| 622 | 2025-09-12 09:35:41 | biases | 1 | 48755 | 7 | 0.876 | 55656.4 |
| 621 | 2025-09-11 17:39:32 | biases | 1 | 48755 | 7 | 0.843 | 57835.1 |
| 620 | 2025-09-09 01:53:46 | biases | 1 | 48755 | 7 | 0.796 | 61250.0 |
| 619 | 2025-09-05 18:52:27 | biases | 1 | 48755 | 7 | 0.860 | 56691.9 |
| 618 | 2025-09-02 12:00:01 | biases | 1 | 48755 | 7 | 0.843 | 57835.1 |
| 617 | 2025-08-30 04:05:59 | biases | 1 | 48755 | 7 | 1.550 | 31454.8 |
| 616 | 2025-08-26 21:06:54 | biases | 1 | 48755 | 7 | 0.766 | 63648.8 |
| 615 | 2025-08-26 11:39:55 | biases | 1 | 48755 | 7 | 0.860 | 56691.9 |
| 614 | 2025-08-22 21:45:28 | biases | 1 | 48755 | 7 | 2.343 | 20808.8 |
| 613 | 2025-08-20 04:38:04 | biases | 1 | 48755 | 7 | 0.766 | 63648.8 |
| 612 | 2025-08-19 09:45:36 | biases | 1 | 48755 | 7 | 3.593 | 13569.4 |
| 611 | 2025-08-14 12:50:11 | biases | 1 | 48755 | 7 | 0.860 | 56691.9 |
| 610 | 2025-08-13 20:31:34 | biases | 1 | 48755 | 7 | 0.826 | 59025.4 |
| 609 | 2025-08-13 11:30:40 | biases | 1 | 48755 | 7 | 4.080 | 11949.8 |
| 608 | 2025-08-10 23:35:14 | biases | 1 | 48755 | 7 | 1.716 | 28412.0 |
| 607 | 2025-08-10 03:08:47 | biases | 1 | 48755 | 7 | 1.716 | 28412.0 |
| 606 | 2025-08-10 02:23:31 | biases | 1 | 48755 | 7 | 2.030 | 24017.2 |
| 605 | 2025-08-09 10:06:20 | biases | 1 | 48755 | 7 | 1.796 | 27146.4 |
| 604 | 2025-08-03 09:18:49 | biases | 1 | 48755 | 7 | 0.860 | 56691.9 |
| 603 | 2025-08-01 12:21:17 | biases | 1 | 48755 | 7 | 4.313 | 11304.2 |
| 602 | 2025-08-01 06:56:40 | biases | 2 | 82551 | 135 | 6.833 | 12081.2 |
| 601 | 2025-08-01 03:53:47 | biases | 1 | 48755 | 7 | 1.736 | 28084.7 |
| 600 | 2025-07-31 01:05:11 | biases | 1 | 48755 | 7 | 0.906 | 53813.5 |
| 599 | 2025-07-30 20:37:21 | biases | 1 | 48755 | 7 | 3.750 | 13001.3 |
| 598 | 2025-07-24 01:23:46 | biases | 1 | 48755 | 7 | 7.733 | 6304.8 |
| 597 | 2025-07-22 16:32:01 | biases | 1 | 48755 | 7 | 2.046 | 23829.4 |
| 596 | 2025-07-21 16:01:18 | biases | 1 | 48755 | 7 | 5.873 | 8301.5 |
| 595 | 2025-07-21 00:20:53 | biases | 1 | 48755 | 7 | 0.766 | 63648.8 |
| 594 | 2025-07-19 01:30:23 | biases | 1 | 48755 | 7 | 0.780 | 62506.4 |
| 593 | 2025-07-17 14:09:14 | biases | 1 | 48755 | 7 | 1.906 | 25579.7 |
| 592 | 2025-07-12 18:15:25 | biases | 1 | 48755 | 7 | 0.903 | 53992.2 |
| 591 | 2025-07-12 15:47:34 | biases | 2 | 82551 | 135 | 4.466 | 18484.3 |
| 590 | 2025-07-11 19:13:28 | biases | 2 | 82551 | 135 | 11.986 | 6887.3 |
| 589 | 2025-07-10 14:29:07 | biases | 2 | 82551 | 135 | 10.563 | 7815.1 |
| 588 | 2025-07-10 08:36:42 | biases | 1 | 48755 | 7 | 0.843 | 57835.1 |
| 587 | 2025-07-07 09:04:16 | biases | 1 | 48755 | 7 | 4.483 | 10875.5 |
| 586 | 2025-06-30 23:59:07 | biases | 1 | 48755 | 7 | 0.780 | 62506.4 |
| 585 | 2025-06-30 05:44:52 | biases | 2 | 82551 | 135 | 15.563 | 5304.3 |
| 584 | 2025-06-28 20:30:33 | biases | 1 | 48755 | 7 | 0.766 | 63648.8 |
| 583 | 2025-06-11 21:43:59 | biases | 1 | 48755 | 7 | 1.953 | 24964.2 |
| 582 | 2025-06-10 10:59:29 | biases | 2 | 82551 | 135 | 13.033 | 6334.0 |
| 581 | 2025-06-10 02:14:27 | biases | 1 | 48755 | 7 | 3.016 | 16165.5 |
| 580 | 2025-06-08 19:59:07 | biases | 1 | 48755 | 7 | 3.936 | 12386.9 |
| 579 | 2025-06-08 08:57:40 | biases | 2 | 82551 | 135 | 21.140 | 3905.0 |
| 578 | 2025-06-07 07:57:57 | biases | 1 | 48755 | 7 | 0.826 | 59025.4 |
| 577 | 2025-05-31 04:37:43 | biases | 2 | 82551 | 135 | 12.860 | 6419.2 |
| 576 | 2025-05-29 20:10:28 | biases | 1 | 48755 | 7 | 0.826 | 59025.4 |
| 575 | 2025-05-28 13:44:54 | biases | 1 | 48755 | 7 | 0.923 | 52822.3 |
| 574 | 2025-05-27 14:05:22 | biases | 2 | 82551 | 135 | 9.060 | 9111.6 |
| 573 | 2025-05-25 11:11:47 | biases | 2 | 82551 | 135 | 2.686 | 30733.8 |
| 572 | 2025-05-23 11:10:13 | biases | 1 | 48755 | 7 | 0.860 | 56691.9 |
| 571 | 2025-05-19 11:50:44 | biases | 2 | 82551 | 135 | 2.440 | 33832.4 |
| 570 | 2025-05-17 02:59:24 | biases | 1 | 48755 | 7 | 0.906 | 53813.5 |
| 569 | 2025-05-11 22:24:19 | biases | 1 | 48755 | 7 | 4.156 | 11731.2 |
| 568 | 2025-05-10 02:06:44 | biases | 1 | 48755 | 7 | 2.720 | 17924.6 |
| 567 | 2025-05-08 12:49:38 | biases | 1 | 48755 | 7 | 2.626 | 18566.3 |
| 566 | 2025-05-08 00:15:49 | biases | 1 | 48755 | 7 | 3.796 | 12843.8 |
| 565 | 2025-05-07 08:25:08 | biases | 1 | 48755 | 7 | 0.890 | 54780.9 |
| 564 | 2025-05-05 07:42:35 | biases | 1 | 48755 | 7 | 0.906 | 53813.5 |
| 563 | 2025-04-28 20:10:34 | biases | 1 | 48755 | 7 | 0.920 | 52994.6 |
| 562 | 2025-04-22 15:00:44 | biases | 1 | 48755 | 7 | 0.876 | 55656.4 |
| 561 | 2025-04-16 09:07:55 | biases | 1 | 48755 | 7 | 4.016 | 12140.2 |
| 560 | 2025-04-13 12:48:38 | biases | 1 | 48755 | 7 | 0.766 | 63648.8 |
| 559 | 2025-04-10 22:02:58 | biases | 1 | 48755 | 7 | 4.736 | 10294.6 |
| 558 | 2025-04-09 10:30:31 | biases | 2 | 82551 | 135 | 17.173 | 4807.0 |
| 557 | 2025-04-08 07:47:58 | biases | 2 | 82551 | 135 | 2.703 | 30540.5 |
| 556 | 2025-04-08 01:48:22 | biases | 1 | 48755 | 7 | 3.940 | 12374.4 |
| 555 | 2025-04-07 07:15:26 | biases | 1 | 48755 | 7 | 0.840 | 58041.7 |
| 554 | 2025-04-06 00:09:47 | biases | 1 | 48755 | 7 | 4.483 | 10875.5 |
| 553 | 2025-03-28 21:25:40 | biases | 1 | 48755 | 7 | 4.080 | 11949.8 |
| 552 | 2025-03-27 21:11:33 | biases | 1 | 48755 | 7 | 1.656 | 29441.4 |