History of Dictionary Searches using Damerau-Levenshtein distance in T-SQL
    
        
    
    
    
    
    
    
    
    
        
    Fuzzy-string Searches
        (up to 100 most recent)
        for
        "plot"
        
    
	
		| Num | Started At (CA time) | Searched Word | Change Limit | Words Checked | Words Matched | Seconds | Words Per Sec | 
		| 912 | 2025-10-25 06:14:54 | plot | 1 | 13983 | 15 | 0.436 | 32071.1 | 
		| 911 | 2025-10-25 02:39:55 | plot | 1 | 13983 | 15 | 0.220 | 63559.1 | 
		| 910 | 2025-10-24 14:14:43 | plot | 1 | 13983 | 15 | 0.250 | 55932.0 | 
		| 909 | 2025-10-23 04:24:45 | plot | 1 | 13983 | 15 | 1.516 | 9223.6 | 
		| 908 | 2025-10-21 06:41:35 | plot | 1 | 13983 | 15 | 1.050 | 13317.1 | 
		| 907 | 2025-10-20 04:12:58 | plot | 1 | 13983 | 15 | 0.250 | 55932.0 | 
		| 906 | 2025-10-18 05:53:11 | plot | 1 | 13983 | 15 | 0.236 | 59250.0 | 
		| 905 | 2025-10-08 05:54:00 | plot | 1 | 13983 | 15 | 0.236 | 59250.0 | 
		| 904 | 2025-10-06 06:46:22 | plot | 1 | 13983 | 15 | 0.220 | 63559.1 | 
		| 903 | 2025-09-30 05:54:24 | plot | 1 | 13983 | 15 | 0.250 | 55932.0 | 
		| 902 | 2025-09-29 04:20:05 | plot | 2 | 29872 | 232 | 1.876 | 15923.2 | 
		| 901 | 2025-09-27 02:18:02 | plot | 1 | 13983 | 15 | 0.233 | 60012.9 | 
		| 900 | 2025-09-25 11:51:38 | plot | 2 | 29872 | 232 | 0.860 | 34734.9 | 
		| 899 | 2025-09-25 09:50:55 | plot | 1 | 13983 | 15 | 0.940 | 14875.5 | 
		| 898 | 2025-09-25 09:50:52 | plot | 1 | 13983 | 15 | 1.126 | 12418.3 | 
		| 897 | 2025-09-25 09:50:47 | plot | 1 | 13983 | 15 | 0.796 | 17566.6 | 
		| 896 | 2025-09-25 09:50:43 | plot | 1 | 13983 | 15 | 1.843 | 7587.1 | 
		| 895 | 2025-09-23 23:30:58 | plot | 2 | 29872 | 232 | 1.656 | 18038.6 | 
		| 894 | 2025-09-19 10:05:24 | plot | 1 | 13983 | 15 | 0.220 | 63559.1 | 
		| 893 | 2025-09-13 01:33:20 | plot | 1 | 13983 | 15 | 0.250 | 55932.0 | 
		| 892 | 2025-09-11 23:12:14 | plot | 1 | 13983 | 15 | 0.263 | 53167.3 | 
		| 891 | 2025-09-08 21:26:52 | plot | 2 | 29872 | 232 | 0.860 | 34734.9 | 
		| 890 | 2025-09-08 15:47:52 | plot | 2 | 29872 | 232 | 1.860 | 16060.2 | 
		| 889 | 2025-09-08 02:36:43 | plot | 2 | 29872 | 232 | 0.860 | 34734.9 | 
		| 888 | 2025-09-04 17:27:28 | plot | 1 | 13983 | 15 | 0.216 | 64736.1 | 
		| 887 | 2025-09-01 05:48:56 | plot | 1 | 13983 | 15 | 0.233 | 60012.9 | 
		| 886 | 2025-08-29 00:48:29 | plot | 1 | 13983 | 15 | 0.266 | 52567.7 | 
		| 885 | 2025-08-27 01:25:00 | plot | 1 | 13983 | 15 | 0.250 | 55932.0 | 
		| 884 | 2025-08-17 15:16:07 | plot | 1 | 13983 | 15 | 0.656 | 21315.5 | 
		| 883 | 2025-08-05 05:40:42 | plot | 1 | 13983 | 15 | 0.626 | 22337.1 | 
		| 882 | 2025-08-04 11:02:25 | plot | 1 | 13983 | 15 | 0.576 | 24276.0 | 
		| 881 | 2025-08-01 14:25:48 | plot | 1 | 13983 | 15 | 0.453 | 30867.5 | 
		| 880 | 2025-07-31 11:26:59 | plot | 1 | 13983 | 15 | 0.250 | 55932.0 | 
		| 879 | 2025-07-28 23:19:15 | plot | 2 | 29872 | 232 | 2.376 | 12572.4 | 
		| 878 | 2025-07-28 06:26:52 | plot | 2 | 29872 | 232 | 2.203 | 13559.7 | 
		| 877 | 2025-07-27 01:55:37 | plot | 1 | 13983 | 15 | 1.156 | 12096.0 | 
		| 876 | 2025-07-26 06:04:18 | plot | 2 | 29872 | 232 | 1.983 | 15064.0 | 
		| 875 | 2025-07-24 14:05:52 | plot | 1 | 13983 | 15 | 0.280 | 49939.3 | 
		| 874 | 2025-07-24 11:50:50 | plot | 2 | 29872 | 232 | 8.033 | 3718.7 | 
		| 873 | 2025-07-23 01:31:17 | plot | 1 | 13983 | 15 | 0.876 | 15962.3 | 
		| 872 | 2025-07-21 17:08:46 | plot | 1 | 13983 | 15 | 0.250 | 55932.0 | 
		| 871 | 2025-07-20 23:56:35 | plot | 2 | 29872 | 232 | 0.843 | 35435.3 | 
		| 870 | 2025-07-20 07:14:00 | plot | 1 | 13983 | 15 | 0.250 | 55932.0 | 
		| 869 | 2025-07-17 19:31:28 | plot | 1 | 13983 | 15 | 1.296 | 10789.4 | 
		| 868 | 2025-07-11 14:42:11 | plot | 1 | 13983 | 15 | 0.923 | 15149.5 | 
		| 867 | 2025-07-07 05:33:17 | plot | 2 | 29872 | 232 | 2.093 | 14272.3 | 
		| 866 | 2025-07-06 05:10:28 | plot | 1 | 13983 | 15 | 0.470 | 29751.1 | 
		| 865 | 2025-07-06 04:20:40 | plot | 1 | 13983 | 15 | 0.940 | 14875.5 | 
		| 864 | 2025-07-04 05:23:18 | plot | 1 | 13983 | 15 | 1.356 | 10311.9 | 
		| 863 | 2025-07-04 03:06:41 | plot | 2 | 29872 | 232 | 4.813 | 6206.5 | 
		| 862 | 2025-07-03 10:21:44 | plot | 1 | 13983 | 15 | 0.236 | 59250.0 | 
		| 861 | 2025-06-30 05:35:45 | plot | 1 | 13983 | 15 | 1.656 | 8443.8 | 
		| 860 | 2025-06-28 10:58:50 | plot | 1 | 13983 | 15 | 1.280 | 10924.2 | 
		| 859 | 2025-06-23 20:08:26 | plot | 1 | 13983 | 15 | 1.953 | 7159.8 | 
		| 858 | 2025-06-20 13:24:55 | plot | 1 | 13983 | 15 | 0.250 | 55932.0 | 
		| 857 | 2025-06-19 20:49:40 | plot | 1 | 13983 | 15 | 1.843 | 7587.1 | 
		| 856 | 2025-06-18 01:49:39 | plot | 1 | 13983 | 15 | 1.346 | 10388.6 | 
		| 855 | 2025-06-14 19:16:39 | plot | 1 | 13983 | 15 | 1.060 | 13191.5 | 
		| 854 | 2025-06-11 02:00:01 | plot | 1 | 13983 | 15 | 0.250 | 55932.0 | 
		| 853 | 2025-06-06 21:56:50 | plot | 1 | 13983 | 15 | 0.500 | 27966.0 | 
		| 852 | 2025-06-06 03:46:40 | plot | 1 | 13983 | 15 | 1.850 | 7558.4 | 
		| 851 | 2025-06-03 15:00:21 | plot | 1 | 13983 | 15 | 0.516 | 27098.8 | 
		| 850 | 2025-06-02 10:14:12 | plot | 2 | 29872 | 232 | 4.453 | 6708.3 | 
		| 849 | 2025-06-02 09:00:41 | plot | 1 | 13983 | 15 | 1.060 | 13191.5 | 
		| 848 | 2025-06-02 02:20:39 | plot | 2 | 29872 | 232 | 4.406 | 6779.8 | 
		| 847 | 2025-06-01 08:20:04 | plot | 2 | 29872 | 232 | 2.220 | 13455.9 | 
		| 846 | 2025-06-01 07:53:37 | plot | 1 | 13983 | 15 | 0.673 | 20777.1 | 
		| 845 | 2025-05-31 10:07:42 | plot | 1 | 13983 | 15 | 0.936 | 14939.1 | 
		| 844 | 2025-05-31 04:57:38 | plot | 1 | 13983 | 15 | 1.500 | 9322.0 | 
		| 843 | 2025-05-30 12:33:36 | plot | 2 | 29872 | 232 | 2.250 | 13276.4 | 
		| 842 | 2025-05-29 09:59:26 | plot | 1 | 13983 | 15 | 0.656 | 21315.5 | 
		| 841 | 2025-05-28 19:22:44 | plot | 1 | 13983 | 15 | 0.266 | 52567.7 | 
		| 840 | 2025-05-26 23:40:39 | plot | 1 | 13983 | 15 | 0.280 | 49939.3 | 
		| 839 | 2025-05-20 08:39:21 | plot | 1 | 13983 | 15 | 1.283 | 10898.7 | 
		| 838 | 2025-05-16 15:35:57 | plot | 1 | 13983 | 15 | 1.296 | 10789.4 | 
		| 837 | 2025-05-07 22:08:33 | plot | 1 | 13983 | 15 | 0.783 | 17858.2 | 
		| 836 | 2025-05-06 03:13:02 | plot | 1 | 13983 | 15 | 0.923 | 15149.5 | 
		| 835 | 2025-05-02 16:32:13 | plot | 1 | 13983 | 15 | 0.950 | 14718.9 | 
		| 834 | 2025-05-02 13:12:57 | plot | 1 | 13983 | 15 | 0.690 | 20265.2 | 
		| 833 | 2025-05-02 09:39:43 | plot | 1 | 13983 | 15 | 1.000 | 13983.0 | 
		| 832 | 2025-04-29 12:35:36 | plot | 2 | 29872 | 232 | 0.890 | 33564.0 | 
		| 831 | 2025-04-28 09:51:22 | plot | 1 | 13983 | 15 | 0.330 | 42372.7 | 
		| 830 | 2025-04-27 18:04:14 | plot | 1 | 13983 | 15 | 0.250 | 55932.0 | 
		| 829 | 2025-04-27 18:01:43 | plot | 1 | 13983 | 15 | 0.250 | 55932.0 | 
		| 828 | 2025-04-20 07:42:54 | plot | 1 | 13983 | 15 | 1.406 | 9945.2 | 
		| 827 | 2025-04-14 15:13:54 | plot | 1 | 13983 | 15 | 0.640 | 21848.4 | 
		| 826 | 2025-04-06 02:44:21 | plot | 1 | 13983 | 15 | 0.686 | 20383.4 | 
		| 825 | 2025-04-02 08:45:59 | plot | 1 | 13983 | 15 | 1.576 | 8872.5 | 
		| 824 | 2025-03-29 06:09:17 | plot | 1 | 13983 | 15 | 0.656 | 21315.5 | 
		| 823 | 2025-03-20 09:48:40 | plot | 1 | 13983 | 15 | 1.140 | 12265.8 | 
		| 822 | 2025-03-17 09:07:09 | plot | 1 | 13983 | 15 | 1.970 | 7098.0 | 
		| 821 | 2025-03-14 20:42:04 | plot | 1 | 13983 | 15 | 1.406 | 9945.2 | 
		| 820 | 2025-03-09 23:57:52 | plot | 1 | 13983 | 15 | 1.343 | 10411.8 | 
		| 819 | 2025-03-06 23:40:13 | plot | 1 | 13983 | 15 | 2.140 | 6534.1 | 
		| 818 | 2025-02-26 17:39:04 | plot | 2 | 29872 | 232 | 2.030 | 14715.3 | 
		| 817 | 2025-02-26 17:24:39 | plot | 1 | 13983 | 15 | 1.153 | 12127.5 | 
		| 816 | 2025-02-25 12:04:19 | plot | 1 | 13983 | 15 | 1.140 | 12265.8 | 
		| 815 | 2025-02-25 09:10:26 | plot | 2 | 29872 | 232 | 6.453 | 4629.2 | 
		| 814 | 2025-02-25 08:51:31 | plot | 1 | 13983 | 15 | 0.233 | 60012.9 | 
		| 813 | 2025-02-24 22:24:04 | plot | 1 | 13983 | 15 | 0.810 | 17263.0 |