History of Dictionary Searches using Damerau-Levenshtein distance in T-SQL
Fuzzy-string Searches
(up to 100 most recent)
for
"echelon"
| Num | Started At (CA time) | Searched Word | Change Limit | Words Checked | Words Matched | Seconds | Words Per Sec |
| 757 | 2025-12-24 08:26:46 | echelon | 1 | 69583 | 2 | 1.296 | 53690.6 |
| 756 | 2025-12-21 15:23:13 | echelon | 1 | 69583 | 2 | 4.736 | 14692.4 |
| 755 | 2025-12-21 15:21:19 | echelon | 1 | 69583 | 2 | 2.623 | 26528.0 |
| 754 | 2025-12-21 15:21:04 | echelon | 1 | 69583 | 2 | 1.390 | 50059.7 |
| 753 | 2025-12-21 14:30:35 | echelon | 1 | 69583 | 2 | 1.250 | 55666.4 |
| 752 | 2025-12-19 13:15:12 | echelon | 2 | 107671 | 4 | 3.170 | 33965.6 |
| 751 | 2025-12-15 04:31:19 | echelon | 1 | 69583 | 2 | 1.250 | 55666.4 |
| 750 | 2025-12-14 14:50:03 | echelon | 4 | 151207 | 768 | 20.766 | 7281.5 |
| 749 | 2025-12-14 04:34:05 | echelon | 1 | 69583 | 2 | 1.390 | 50059.7 |
| 748 | 2025-12-14 03:02:38 | echelon | 1 | 69583 | 2 | 1.233 | 56433.9 |
| 747 | 2025-12-13 09:29:32 | echelon | 1 | 69583 | 2 | 1.296 | 53690.6 |
| 746 | 2025-12-13 08:29:23 | echelon | 1 | 69583 | 2 | 3.216 | 21636.5 |
| 745 | 2025-12-13 00:58:20 | echelon | 1 | 69583 | 2 | 1.236 | 56296.9 |
| 744 | 2025-12-12 15:06:31 | echelon | 4 | 151207 | 768 | 52.706 | 2868.9 |
| 743 | 2025-12-11 03:11:49 | echelon | 4 | 151207 | 768 | 11.296 | 13385.9 |
| 742 | 2025-12-07 08:15:10 | echelon | 4 | 151207 | 768 | 10.703 | 14127.5 |
| 741 | 2025-12-05 06:32:13 | echelon | 1 | 69583 | 2 | 1.186 | 58670.3 |
| 740 | 2025-12-02 16:34:43 | echelon | 1 | 69583 | 2 | 1.263 | 55093.4 |
| 739 | 2025-11-28 22:35:18 | echelon | 3 | 134027 | 60 | 17.233 | 7777.3 |
| 738 | 2025-11-27 02:16:04 | echelon | 4 | 151207 | 768 | 13.626 | 11096.9 |
| 737 | 2025-11-25 05:59:24 | echelon | 1 | 69583 | 2 | 2.813 | 24736.2 |
| 736 | 2025-11-23 07:56:01 | echelon | 3 | 134027 | 60 | 8.250 | 16245.7 |
| 735 | 2025-11-19 22:14:15 | echelon | 1 | 69583 | 2 | 1.203 | 57841.2 |
| 734 | 2025-11-16 06:10:36 | echelon | 1 | 69583 | 2 | 1.170 | 59472.6 |
| 733 | 2025-11-16 02:36:49 | echelon | 4 | 151207 | 768 | 10.080 | 15000.7 |
| 732 | 2025-11-12 15:27:50 | echelon | 1 | 69583 | 2 | 1.216 | 57222.9 |
| 731 | 2025-11-07 10:56:26 | echelon | 2 | 107671 | 4 | 3.670 | 29338.1 |
| 730 | 2025-11-06 16:05:18 | echelon | 3 | 134027 | 60 | 13.486 | 9938.2 |
| 729 | 2025-11-06 13:41:36 | echelon | 1 | 69583 | 2 | 2.436 | 28564.4 |
| 728 | 2025-11-05 04:54:54 | echelon | 3 | 134027 | 60 | 5.936 | 22578.7 |
| 727 | 2025-11-04 12:33:39 | echelon | 3 | 134027 | 60 | 6.436 | 20824.6 |
| 726 | 2025-11-04 05:01:00 | echelon | 4 | 151207 | 768 | 15.063 | 10038.3 |
| 725 | 2025-11-02 22:25:35 | echelon | 3 | 134027 | 60 | 6.390 | 20974.5 |
| 724 | 2025-11-02 22:25:23 | echelon | 4 | 151207 | 768 | 11.393 | 13271.9 |
| 723 | 2025-11-02 09:57:03 | echelon | 2 | 107671 | 4 | 3.030 | 35535.0 |
| 722 | 2025-10-06 13:53:56 | echelon | 1 | 69583 | 2 | 1.216 | 57222.9 |
| 721 | 2025-09-29 16:21:36 | echelon | 1 | 69583 | 2 | 1.296 | 53690.6 |
| 720 | 2025-09-05 00:10:03 | echelon | 1 | 69583 | 2 | 1.233 | 56433.9 |
| 719 | 2025-08-30 04:59:35 | echelon | 4 | 151207 | 768 | 11.690 | 12934.7 |
| 718 | 2025-08-27 09:08:50 | echelon | 1 | 69583 | 2 | 2.140 | 32515.4 |
| 717 | 2025-08-17 02:08:34 | echelon | 1 | 69583 | 2 | 8.876 | 7839.5 |
| 716 | 2025-08-10 14:36:45 | echelon | 4 | 151207 | 768 | 35.690 | 4236.7 |
| 715 | 2025-08-06 23:08:55 | echelon | 4 | 151207 | 768 | 31.536 | 4794.7 |
| 714 | 2025-08-06 22:19:15 | echelon | 4 | 151207 | 768 | 46.940 | 3221.3 |
| 713 | 2025-08-05 18:28:33 | echelon | 1 | 69583 | 2 | 7.063 | 9851.8 |
| 712 | 2025-08-05 11:58:43 | echelon | 2 | 107671 | 4 | 6.550 | 16438.3 |
| 711 | 2025-08-04 05:19:54 | echelon | 1 | 69583 | 2 | 4.453 | 15626.1 |
| 710 | 2025-07-31 11:07:32 | echelon | 1 | 69583 | 2 | 1.250 | 55666.4 |
| 709 | 2025-07-27 07:19:11 | echelon | 1 | 69583 | 2 | 4.546 | 15306.4 |
| 708 | 2025-07-26 09:49:56 | echelon | 1 | 69583 | 2 | 1.220 | 57035.2 |
| 707 | 2025-07-26 01:13:28 | echelon | 4 | 151207 | 768 | 27.546 | 5489.3 |
| 706 | 2025-07-24 16:00:03 | echelon | 4 | 151207 | 768 | 28.640 | 5279.6 |
| 705 | 2025-07-22 05:03:11 | echelon | 4 | 151207 | 768 | 56.863 | 2659.1 |
| 704 | 2025-07-20 17:50:41 | echelon | 1 | 69583 | 2 | 1.266 | 54962.9 |
| 703 | 2025-07-19 16:04:24 | echelon | 4 | 151207 | 768 | 11.266 | 13421.5 |
| 702 | 2025-07-18 19:41:19 | echelon | 4 | 151207 | 768 | 49.813 | 3035.5 |
| 701 | 2025-07-18 03:08:22 | echelon | 2 | 107671 | 4 | 7.966 | 13516.3 |
| 700 | 2025-07-16 20:06:01 | echelon | 1 | 69583 | 2 | 1.283 | 54234.6 |
| 699 | 2025-07-16 12:47:25 | echelon | 1 | 69583 | 2 | 5.890 | 11813.8 |
| 698 | 2025-07-14 04:44:04 | echelon | 3 | 134027 | 60 | 21.423 | 6256.2 |
| 697 | 2025-07-13 01:19:45 | echelon | 1 | 69583 | 2 | 2.330 | 29863.9 |
| 696 | 2025-07-10 14:37:50 | echelon | 3 | 134027 | 60 | 28.953 | 4629.1 |
| 695 | 2025-07-08 12:51:36 | echelon | 3 | 134027 | 60 | 45.893 | 2920.4 |
| 694 | 2025-07-05 01:43:14 | echelon | 3 | 134027 | 60 | 34.813 | 3849.9 |
| 693 | 2025-07-04 23:56:17 | echelon | 2 | 107671 | 4 | 18.860 | 5709.0 |
| 692 | 2025-07-04 22:17:39 | echelon | 3 | 134027 | 60 | 32.440 | 4131.5 |
| 691 | 2025-07-04 16:12:05 | echelon | 1 | 69583 | 2 | 3.533 | 19695.2 |
| 690 | 2025-06-14 10:57:34 | echelon | 1 | 69583 | 2 | 5.580 | 12470.1 |
| 689 | 2025-06-10 06:24:19 | echelon | 3 | 134027 | 60 | 36.690 | 3653.0 |
| 688 | 2025-06-10 01:29:01 | echelon | 3 | 134027 | 60 | 25.283 | 5301.1 |
| 687 | 2025-06-08 18:52:28 | echelon | 3 | 134027 | 60 | 39.656 | 3379.7 |
| 686 | 2025-05-30 21:23:19 | echelon | 1 | 69583 | 2 | 2.720 | 25582.0 |
| 685 | 2025-05-30 21:17:59 | echelon | 1 | 69583 | 2 | 4.106 | 16946.7 |
| 684 | 2025-05-30 21:13:42 | echelon | 1 | 69583 | 2 | 3.186 | 21840.2 |
| 683 | 2025-05-29 15:25:21 | echelon | 1 | 69583 | 2 | 2.546 | 27330.3 |
| 682 | 2025-05-29 09:23:23 | echelon | 1 | 69583 | 2 | 6.470 | 10754.7 |
| 681 | 2025-05-27 09:49:29 | echelon | 1 | 69583 | 2 | 3.483 | 19977.9 |
| 680 | 2025-05-24 17:56:31 | echelon | 2 | 107671 | 4 | 11.563 | 9311.7 |
| 679 | 2025-05-24 04:45:52 | echelon | 3 | 134027 | 60 | 25.186 | 5321.5 |
| 678 | 2025-05-23 06:24:35 | echelon | 1 | 69583 | 2 | 5.906 | 11781.7 |
| 677 | 2025-05-19 18:41:24 | echelon | 1 | 69583 | 2 | 1.170 | 59472.6 |
| 676 | 2025-05-12 06:29:38 | echelon | 2 | 107671 | 4 | 16.813 | 6404.0 |
| 675 | 2025-05-11 10:19:31 | echelon | 1 | 69583 | 2 | 1.220 | 57035.2 |
| 674 | 2025-05-09 21:21:46 | echelon | 1 | 69583 | 2 | 3.873 | 17966.2 |
| 673 | 2025-05-08 08:30:03 | echelon | 3 | 134027 | 60 | 50.236 | 2667.9 |
| 672 | 2025-05-08 06:44:46 | echelon | 3 | 134027 | 60 | 25.000 | 5361.1 |
| 671 | 2025-05-05 03:41:01 | echelon | 3 | 134027 | 60 | 31.423 | 4265.3 |
| 670 | 2025-05-03 23:32:21 | echelon | 1 | 69583 | 2 | 3.093 | 22496.9 |
| 669 | 2025-04-30 00:23:27 | echelon | 1 | 69583 | 2 | 7.173 | 9700.7 |
| 668 | 2025-04-28 21:51:33 | echelon | 1 | 69583 | 2 | 1.216 | 57222.9 |
| 667 | 2025-04-28 01:38:04 | echelon | 3 | 134027 | 60 | 47.063 | 2847.8 |
| 666 | 2025-04-23 19:45:55 | echelon | 2 | 107671 | 4 | 11.986 | 8983.1 |
| 665 | 2025-04-22 05:40:59 | echelon | 1 | 69583 | 2 | 7.296 | 9537.1 |
| 664 | 2025-04-21 04:23:52 | echelon | 3 | 134027 | 60 | 28.686 | 4672.2 |
| 663 | 2025-04-17 22:17:51 | echelon | 2 | 107671 | 4 | 11.890 | 9055.6 |
| 662 | 2025-04-17 03:16:28 | echelon | 3 | 134027 | 60 | 7.203 | 18607.1 |
| 661 | 2025-04-16 16:50:54 | echelon | 1 | 69583 | 2 | 6.063 | 11476.7 |
| 660 | 2025-04-16 01:48:18 | echelon | 1 | 69583 | 2 | 5.030 | 13833.6 |
| 659 | 2025-04-10 22:15:04 | echelon | 3 | 134027 | 60 | 30.373 | 4412.7 |
| 658 | 2025-04-06 03:39:16 | echelon | 2 | 107671 | 4 | 15.906 | 6769.2 |