History of Dictionary Searches using Damerau-Levenshtein distance in T-SQL
    
        
    
    
    
    
    
    
    
    
        
    Fuzzy-string Searches
        (up to 100 most recent)
        for
        "sparse"
        
    
	
		| Num | Started At (CA time) | Searched Word | Change Limit | Words Checked | Words Matched | Seconds | Words Per Sec | 
		| 735 | 2025-10-30 18:06:56 | sparse | 2 | 82551 | 101 | 2.560 | 32246.5 | 
		| 734 | 2025-10-30 04:04:04 | sparse | 2 | 82551 | 101 | 2.266 | 36430.3 | 
		| 733 | 2025-10-25 22:42:58 | sparse | 1 | 48755 | 7 | 0.796 | 61250.0 | 
		| 732 | 2025-10-25 13:53:56 | sparse | 1 | 48755 | 7 | 0.890 | 54780.9 | 
		| 731 | 2025-10-25 12:31:26 | sparse | 1 | 48755 | 7 | 0.796 | 61250.0 | 
		| 730 | 2025-10-25 10:00:28 | sparse | 1 | 48755 | 7 | 0.893 | 54596.9 | 
		| 729 | 2025-10-22 01:10:03 | sparse | 1 | 48755 | 7 | 3.313 | 14716.3 | 
		| 728 | 2025-10-19 18:53:53 | sparse | 1 | 48755 | 7 | 4.110 | 11862.5 | 
		| 727 | 2025-10-17 20:42:29 | sparse | 2 | 82551 | 101 | 2.436 | 33887.9 | 
		| 726 | 2025-10-14 22:55:30 | sparse | 1 | 48755 | 7 | 0.780 | 62506.4 | 
		| 725 | 2025-10-13 19:14:31 | sparse | 1 | 48755 | 7 | 0.876 | 55656.4 | 
		| 724 | 2025-10-13 07:56:43 | sparse | 2 | 82551 | 101 | 2.546 | 32423.8 | 
		| 723 | 2025-10-10 18:48:33 | sparse | 1 | 48755 | 7 | 0.906 | 53813.5 | 
		| 722 | 2025-10-09 23:07:15 | sparse | 2 | 82551 | 101 | 2.563 | 32208.7 | 
		| 721 | 2025-10-04 20:06:41 | sparse | 1 | 48755 | 7 | 0.843 | 57835.1 | 
		| 720 | 2025-10-02 08:01:00 | sparse | 1 | 48755 | 7 | 0.876 | 55656.4 | 
		| 719 | 2025-09-25 04:33:28 | sparse | 1 | 48755 | 7 | 2.733 | 17839.4 | 
		| 718 | 2025-09-24 15:36:47 | sparse | 2 | 82551 | 101 | 2.403 | 34353.3 | 
		| 717 | 2025-09-24 09:55:26 | sparse | 1 | 48755 | 7 | 0.780 | 62506.4 | 
		| 716 | 2025-09-22 14:39:34 | sparse | 1 | 48755 | 7 | 0.936 | 52088.7 | 
		| 715 | 2025-09-21 02:21:46 | sparse | 1 | 48755 | 7 | 0.923 | 52822.3 | 
		| 714 | 2025-09-19 13:42:30 | sparse | 1 | 48755 | 7 | 0.876 | 55656.4 | 
		| 713 | 2025-09-18 23:28:27 | sparse | 1 | 48755 | 7 | 1.406 | 34676.4 | 
		| 712 | 2025-09-18 18:11:50 | sparse | 1 | 48755 | 7 | 0.860 | 56691.9 | 
		| 711 | 2025-09-17 11:11:10 | sparse | 1 | 48755 | 7 | 0.830 | 58741.0 | 
		| 710 | 2025-09-13 22:22:14 | sparse | 1 | 48755 | 7 | 0.876 | 55656.4 | 
		| 709 | 2025-09-13 17:19:58 | sparse | 1 | 48755 | 7 | 0.843 | 57835.1 | 
		| 708 | 2025-09-10 05:23:12 | sparse | 2 | 82551 | 101 | 2.563 | 32208.7 | 
		| 707 | 2025-09-08 05:45:29 | sparse | 1 | 48755 | 7 | 0.766 | 63648.8 | 
		| 706 | 2025-09-07 13:14:47 | sparse | 1 | 48755 | 7 | 0.890 | 54780.9 | 
		| 705 | 2025-08-28 04:13:30 | sparse | 1 | 48755 | 7 | 0.876 | 55656.4 | 
		| 704 | 2025-08-23 09:17:48 | sparse | 1 | 48755 | 7 | 3.266 | 14928.0 | 
		| 703 | 2025-08-19 05:08:51 | sparse | 2 | 82551 | 101 | 5.406 | 15270.3 | 
		| 702 | 2025-08-18 19:07:09 | sparse | 2 | 82551 | 101 | 2.733 | 30205.3 | 
		| 701 | 2025-08-18 11:54:16 | sparse | 2 | 82551 | 101 | 2.470 | 33421.5 | 
		| 700 | 2025-08-18 09:30:12 | sparse | 1 | 48755 | 7 | 0.920 | 52994.6 | 
		| 699 | 2025-08-12 12:43:54 | sparse | 1 | 48755 | 7 | 3.813 | 12786.5 | 
		| 698 | 2025-07-31 14:20:56 | sparse | 1 | 48755 | 7 | 2.266 | 21515.9 | 
		| 697 | 2025-07-31 13:48:40 | sparse | 1 | 48755 | 7 | 2.470 | 19738.9 | 
		| 696 | 2025-07-31 07:01:44 | sparse | 1 | 48755 | 7 | 0.986 | 49447.3 | 
		| 695 | 2025-07-27 20:25:46 | sparse | 2 | 82551 | 101 | 10.940 | 7545.8 | 
		| 694 | 2025-07-23 11:07:23 | sparse | 1 | 48755 | 7 | 4.436 | 10990.8 | 
		| 693 | 2025-07-22 21:01:53 | sparse | 1 | 48755 | 7 | 4.736 | 10294.6 | 
		| 692 | 2025-07-20 11:22:48 | sparse | 1 | 48755 | 7 | 1.046 | 46610.9 | 
		| 691 | 2025-07-20 06:07:32 | sparse | 2 | 82551 | 101 | 2.716 | 30394.3 | 
		| 690 | 2025-07-18 20:46:16 | sparse | 1 | 48755 | 7 | 1.890 | 25796.3 | 
		| 689 | 2025-07-18 13:02:09 | sparse | 2 | 82551 | 101 | 10.770 | 7664.9 | 
		| 688 | 2025-07-18 09:39:59 | sparse | 1 | 48755 | 7 | 4.330 | 11259.8 | 
		| 687 | 2025-07-16 14:56:31 | sparse | 2 | 82551 | 101 | 6.640 | 12432.4 | 
		| 686 | 2025-07-16 11:11:51 | sparse | 2 | 82551 | 101 | 11.720 | 7043.6 | 
		| 685 | 2025-07-14 13:39:54 | sparse | 2 | 82551 | 101 | 6.633 | 12445.5 | 
		| 684 | 2025-07-13 11:34:25 | sparse | 1 | 48755 | 7 | 4.343 | 11226.1 | 
		| 683 | 2025-07-13 09:17:51 | sparse | 2 | 82551 | 101 | 5.000 | 16510.2 | 
		| 682 | 2025-07-11 00:18:39 | sparse | 1 | 48755 | 7 | 5.953 | 8190.0 | 
		| 681 | 2025-07-09 23:47:39 | sparse | 1 | 48755 | 7 | 4.076 | 11961.5 | 
		| 680 | 2025-07-09 17:21:55 | sparse | 1 | 48755 | 7 | 0.766 | 63648.8 | 
		| 679 | 2025-07-07 22:28:22 | sparse | 2 | 82551 | 101 | 6.063 | 13615.5 | 
		| 678 | 2025-07-02 14:18:21 | sparse | 2 | 82551 | 101 | 11.813 | 6988.1 | 
		| 677 | 2025-06-30 23:09:00 | sparse | 1 | 48755 | 7 | 1.813 | 26891.9 | 
		| 676 | 2025-06-30 06:24:21 | sparse | 1 | 48755 | 7 | 5.093 | 9572.9 | 
		| 675 | 2025-06-28 01:23:32 | sparse | 1 | 48755 | 7 | 4.186 | 11647.2 | 
		| 674 | 2025-06-24 23:48:25 | sparse | 2 | 82551 | 101 | 2.813 | 29346.2 | 
		| 673 | 2025-06-21 15:54:08 | sparse | 1 | 48755 | 7 | 4.453 | 10948.8 | 
		| 672 | 2025-06-19 19:54:29 | sparse | 1 | 48755 | 7 | 6.410 | 7606.1 | 
		| 671 | 2025-06-18 07:26:03 | sparse | 2 | 82551 | 101 | 7.873 | 10485.3 | 
		| 670 | 2025-06-17 03:35:56 | sparse | 2 | 82551 | 101 | 11.936 | 6916.1 | 
		| 669 | 2025-06-14 10:12:11 | sparse | 1 | 48755 | 7 | 1.970 | 24748.7 | 
		| 668 | 2025-06-13 12:34:20 | sparse | 2 | 82551 | 101 | 2.406 | 34310.5 | 
		| 667 | 2025-06-12 11:46:21 | sparse | 1 | 48755 | 7 | 4.190 | 11636.0 | 
		| 666 | 2025-06-10 17:26:40 | sparse | 2 | 82551 | 101 | 9.893 | 8344.4 | 
		| 665 | 2025-06-09 22:49:27 | sparse | 1 | 48755 | 7 | 2.203 | 22131.2 | 
		| 664 | 2025-06-09 11:19:16 | sparse | 2 | 82551 | 101 | 2.736 | 30172.1 | 
		| 663 | 2025-06-08 00:15:47 | sparse | 2 | 82551 | 101 | 16.953 | 4869.4 | 
		| 662 | 2025-06-04 07:25:58 | sparse | 1 | 48755 | 7 | 4.140 | 11776.6 | 
		| 661 | 2025-06-04 07:11:01 | sparse | 1 | 48755 | 7 | 4.440 | 10980.9 | 
		| 660 | 2025-05-31 10:28:41 | sparse | 1 | 48755 | 7 | 2.250 | 21668.9 | 
		| 659 | 2025-05-30 16:03:43 | sparse | 1 | 48755 | 7 | 3.716 | 13120.3 | 
		| 658 | 2025-05-29 15:34:44 | sparse | 2 | 82551 | 101 | 10.923 | 7557.5 | 
		| 657 | 2025-05-26 23:48:28 | sparse | 1 | 48755 | 7 | 4.440 | 10980.9 | 
		| 656 | 2025-05-23 11:03:08 | sparse | 1 | 48755 | 7 | 4.313 | 11304.2 | 
		| 655 | 2025-05-15 05:16:45 | sparse | 1 | 48755 | 7 | 0.813 | 59969.2 | 
		| 654 | 2025-05-15 02:48:08 | sparse | 1 | 48755 | 7 | 0.906 | 53813.5 | 
		| 653 | 2025-05-14 11:04:31 | sparse | 1 | 48755 | 7 | 2.170 | 22467.7 | 
		| 652 | 2025-05-10 01:17:50 | sparse | 1 | 48755 | 7 | 1.763 | 27654.6 | 
		| 651 | 2025-05-09 18:31:34 | sparse | 1 | 48755 | 7 | 0.890 | 54780.9 | 
		| 650 | 2025-05-03 18:30:46 | sparse | 1 | 48755 | 7 | 0.923 | 52822.3 | 
		| 649 | 2025-04-29 05:01:10 | sparse | 1 | 48755 | 7 | 4.110 | 11862.5 | 
		| 648 | 2025-04-26 12:52:42 | sparse | 1 | 48755 | 7 | 2.326 | 20960.9 | 
		| 647 | 2025-04-20 14:40:46 | sparse | 1 | 48755 | 7 | 2.750 | 17729.1 | 
		| 646 | 2025-04-20 04:47:16 | sparse | 1 | 48755 | 7 | 6.080 | 8018.9 | 
		| 645 | 2025-04-17 12:50:35 | sparse | 2 | 82551 | 101 | 2.420 | 34112.0 | 
		| 644 | 2025-04-15 06:25:14 | sparse | 1 | 48755 | 7 | 0.763 | 63899.1 | 
		| 643 | 2025-04-14 10:20:14 | sparse | 1 | 48755 | 7 | 2.203 | 22131.2 | 
		| 642 | 2025-04-11 11:54:00 | sparse | 1 | 48755 | 7 | 3.970 | 12280.9 | 
		| 641 | 2025-04-09 20:39:37 | sparse | 1 | 48755 | 7 | 1.826 | 26700.4 | 
		| 640 | 2025-04-07 22:46:03 | sparse | 1 | 48755 | 7 | 1.970 | 24748.7 | 
		| 639 | 2025-03-29 23:50:44 | sparse | 1 | 48755 | 7 | 0.843 | 57835.1 | 
		| 638 | 2025-03-29 06:39:23 | sparse | 1 | 48755 | 7 | 3.920 | 12437.5 | 
		| 637 | 2025-03-28 19:02:02 | sparse | 1 | 48755 | 7 | 0.890 | 54780.9 | 
		| 636 | 2025-03-19 17:29:27 | sparse | 1 | 48755 | 7 | 0.936 | 52088.7 |