History of Dictionary Searches using Damerau-Levenshtein distance in T-SQL
    
        
    
    
    
    
    
    
    
    
        
    Fuzzy-string Searches
        (up to 100 most recent)
        for
        "table"
        
    
	
		| Num | Started At (CA time) | Searched Word | Change Limit | Words Checked | Words Matched | Seconds | Words Per Sec | 
		| 1023 | 2025-10-25 23:14:51 | table | 1 | 28756 | 12 | 0.453 | 63479.0 | 
		| 1022 | 2025-10-25 21:59:38 | table | 1 | 28756 | 12 | 0.500 | 57512.0 | 
		| 1021 | 2025-10-25 07:25:55 | table | 1 | 28756 | 12 | 0.483 | 59536.2 | 
		| 1020 | 2025-10-13 16:17:09 | table | 1 | 28756 | 12 | 0.453 | 63479.0 | 
		| 1019 | 2025-10-13 15:26:01 | table | 1 | 28756 | 12 | 0.453 | 63479.0 | 
		| 1018 | 2025-10-13 13:33:31 | table | 1 | 28756 | 12 | 0.470 | 61183.0 | 
		| 1017 | 2025-10-11 06:35:04 | table | 1 | 28756 | 12 | 1.173 | 24514.9 | 
		| 1016 | 2025-10-10 19:28:09 | table | 1 | 28756 | 12 | 0.513 | 56054.6 | 
		| 1015 | 2025-10-10 04:07:22 | table | 1 | 28756 | 12 | 0.516 | 55728.7 | 
		| 1014 | 2025-10-03 05:28:52 | table | 1 | 28756 | 12 | 0.560 | 51350.0 | 
		| 1013 | 2025-09-26 18:12:37 | table | 1 | 28756 | 12 | 0.500 | 57512.0 | 
		| 1012 | 2025-09-26 16:04:20 | table | 1 | 28756 | 12 | 0.483 | 59536.2 | 
		| 1011 | 2025-09-25 11:06:34 | table | 2 | 53800 | 185 | 8.576 | 6273.3 | 
		| 1010 | 2025-09-25 11:06:39 | table | 2 | 53800 | 185 | 4.156 | 12945.1 | 
		| 1009 | 2025-09-25 11:06:32 | table | 2 | 53800 | 185 | 8.953 | 6009.2 | 
		| 1008 | 2025-09-24 23:18:33 | table | 1 | 28756 | 12 | 1.686 | 17055.8 | 
		| 1007 | 2025-09-24 22:34:58 | table | 1 | 28756 | 12 | 0.483 | 59536.2 | 
		| 1006 | 2025-09-24 21:56:46 | table | 1 | 28756 | 12 | 1.203 | 23903.6 | 
		| 1005 | 2025-09-19 02:21:40 | table | 2 | 53800 | 185 | 1.703 | 31591.3 | 
		| 1004 | 2025-09-13 17:06:44 | table | 1 | 28756 | 12 | 0.513 | 56054.6 | 
		| 1003 | 2025-09-13 14:28:49 | table | 1 | 28756 | 12 | 0.516 | 55728.7 | 
		| 1002 | 2025-09-12 16:58:29 | table | 1 | 28756 | 12 | 0.546 | 52666.7 | 
		| 1001 | 2025-09-11 05:42:30 | table | 1 | 28756 | 12 | 0.563 | 51076.4 | 
		| 1000 | 2025-09-10 12:45:47 | table | 1 | 28756 | 12 | 0.483 | 59536.2 | 
		| 999 | 2025-09-10 10:51:15 | table | 1 | 28756 | 12 | 0.513 | 56054.6 | 
		| 998 | 2025-09-09 15:26:44 | table | 1 | 28756 | 12 | 0.453 | 63479.0 | 
		| 997 | 2025-09-09 15:26:37 | table | 1 | 28756 | 12 | 0.500 | 57512.0 | 
		| 996 | 2025-09-09 15:21:01 | table | 1 | 28756 | 12 | 0.453 | 63479.0 | 
		| 995 | 2025-09-09 08:24:53 | table | 1 | 28756 | 12 | 0.466 | 61708.2 | 
		| 994 | 2025-09-08 19:40:09 | table | 1 | 28756 | 12 | 0.516 | 55728.7 | 
		| 993 | 2025-09-07 10:30:45 | table | 1 | 28756 | 12 | 0.513 | 56054.6 | 
		| 992 | 2025-08-24 23:18:42 | table | 1 | 28756 | 12 | 2.063 | 13938.9 | 
		| 991 | 2025-08-24 22:10:13 | table | 1 | 28756 | 12 | 2.360 | 12184.7 | 
		| 990 | 2025-08-10 08:18:14 | table | 1 | 28756 | 12 | 1.390 | 20687.8 | 
		| 989 | 2025-08-05 04:35:56 | table | 2 | 53800 | 185 | 8.220 | 6545.0 | 
		| 988 | 2025-08-04 15:21:42 | table | 1 | 28756 | 12 | 0.563 | 51076.4 | 
		| 987 | 2025-08-03 20:17:05 | table | 1 | 28756 | 12 | 1.000 | 28756.0 | 
		| 986 | 2025-08-03 07:18:53 | table | 1 | 28756 | 12 | 0.516 | 55728.7 | 
		| 985 | 2025-08-01 15:51:01 | table | 1 | 28756 | 12 | 3.593 | 8003.3 | 
		| 984 | 2025-08-01 14:21:28 | table | 1 | 28756 | 12 | 1.160 | 24789.7 | 
		| 983 | 2025-07-26 12:23:10 | table | 2 | 53800 | 185 | 1.500 | 35866.7 | 
		| 982 | 2025-07-24 03:26:51 | table | 1 | 28756 | 12 | 1.953 | 14724.0 | 
		| 981 | 2025-07-23 10:09:01 | table | 1 | 28756 | 12 | 3.856 | 7457.5 | 
		| 980 | 2025-07-22 11:31:53 | table | 1 | 28756 | 12 | 1.250 | 23004.8 | 
		| 979 | 2025-07-22 08:13:19 | table | 1 | 28756 | 12 | 2.203 | 13053.1 | 
		| 978 | 2025-07-21 07:11:51 | table | 2 | 53800 | 185 | 1.546 | 34799.5 | 
		| 977 | 2025-07-15 15:35:51 | table | 1 | 28756 | 12 | 2.263 | 12707.0 | 
		| 976 | 2025-07-15 10:04:07 | table | 1 | 28756 | 12 | 2.500 | 11502.4 | 
		| 975 | 2025-07-10 20:47:16 | table | 1 | 28756 | 12 | 2.890 | 9950.2 | 
		| 974 | 2025-07-06 06:34:32 | table | 1 | 28756 | 12 | 0.546 | 52666.7 | 
		| 973 | 2025-07-04 02:41:36 | table | 2 | 53800 | 185 | 8.360 | 6435.4 | 
		| 972 | 2025-07-03 06:02:25 | table | 2 | 53800 | 185 | 1.626 | 33087.3 | 
		| 971 | 2025-07-02 13:38:08 | table | 1 | 28756 | 12 | 2.780 | 10343.9 | 
		| 970 | 2025-07-01 19:57:08 | table | 1 | 28756 | 12 | 0.450 | 63902.2 | 
		| 969 | 2025-07-01 04:09:46 | table | 1 | 28756 | 12 | 1.393 | 20643.2 | 
		| 968 | 2025-06-30 09:02:43 | table | 1 | 28756 | 12 | 2.186 | 13154.6 | 
		| 967 | 2025-06-29 17:08:30 | table | 1 | 28756 | 12 | 0.500 | 57512.0 | 
		| 966 | 2025-06-23 22:58:46 | table | 1 | 28756 | 12 | 3.453 | 8327.8 | 
		| 965 | 2025-06-22 00:34:16 | table | 1 | 28756 | 12 | 3.456 | 8320.6 | 
		| 964 | 2025-06-21 18:08:56 | table | 2 | 53800 | 185 | 1.720 | 31279.1 | 
		| 963 | 2025-06-19 10:46:15 | table | 1 | 28756 | 12 | 0.563 | 51076.4 | 
		| 962 | 2025-06-19 06:17:22 | table | 2 | 53800 | 185 | 1.690 | 31834.3 | 
		| 961 | 2025-06-16 00:18:05 | table | 1 | 28756 | 12 | 1.030 | 27918.4 | 
		| 960 | 2025-06-14 15:05:57 | table | 1 | 28756 | 12 | 2.546 | 11294.6 | 
		| 959 | 2025-06-13 23:16:06 | table | 1 | 28756 | 12 | 2.470 | 11642.1 | 
		| 958 | 2025-06-13 00:30:18 | table | 1 | 28756 | 12 | 1.030 | 27918.4 | 
		| 957 | 2025-06-10 06:43:49 | table | 1 | 28756 | 12 | 3.266 | 8804.7 | 
		| 956 | 2025-06-06 11:00:24 | table | 1 | 28756 | 12 | 2.360 | 12184.7 | 
		| 955 | 2025-06-03 05:59:10 | table | 2 | 53800 | 185 | 8.360 | 6435.4 | 
		| 954 | 2025-06-03 00:51:15 | table | 1 | 28756 | 12 | 2.843 | 10114.7 | 
		| 953 | 2025-06-02 12:39:20 | table | 1 | 28756 | 12 | 2.813 | 10222.5 | 
		| 952 | 2025-06-01 19:59:51 | table | 2 | 53800 | 185 | 4.953 | 10862.1 | 
		| 951 | 2025-05-31 19:44:34 | table | 2 | 53800 | 185 | 9.376 | 5738.1 | 
		| 950 | 2025-05-30 19:58:53 | table | 1 | 28756 | 12 | 3.266 | 8804.7 | 
		| 949 | 2025-05-30 18:46:47 | table | 1 | 28756 | 12 | 0.516 | 55728.7 | 
		| 948 | 2025-05-28 09:05:42 | table | 1 | 28756 | 12 | 2.656 | 10826.8 | 
		| 947 | 2025-05-26 01:38:26 | table | 1 | 28756 | 12 | 2.623 | 10963.0 | 
		| 946 | 2025-05-23 21:41:43 | table | 2 | 53800 | 185 | 7.126 | 7549.8 | 
		| 945 | 2025-05-21 18:35:17 | table | 1 | 28756 | 12 | 0.453 | 63479.0 | 
		| 944 | 2025-05-17 17:55:42 | table | 1 | 28756 | 12 | 0.530 | 54256.6 | 
		| 943 | 2025-05-15 09:00:52 | table | 1 | 28756 | 12 | 0.470 | 61183.0 | 
		| 942 | 2025-05-15 02:42:49 | table | 2 | 53800 | 185 | 1.673 | 32157.8 | 
		| 941 | 2025-05-14 21:52:11 | table | 2 | 53800 | 185 | 3.720 | 14462.4 | 
		| 940 | 2025-05-13 15:35:26 | table | 1 | 28756 | 12 | 5.206 | 5523.6 | 
		| 939 | 2025-05-12 22:09:24 | table | 1 | 28756 | 12 | 0.970 | 29645.4 | 
		| 938 | 2025-05-09 06:47:53 | table | 1 | 28756 | 12 | 0.483 | 59536.2 | 
		| 937 | 2025-05-09 03:09:49 | table | 1 | 28756 | 12 | 0.533 | 53951.2 | 
		| 936 | 2025-05-08 15:18:28 | table | 1 | 28756 | 12 | 3.640 | 7900.0 | 
		| 935 | 2025-05-03 00:32:44 | table | 1 | 28756 | 12 | 1.170 | 24577.8 | 
		| 934 | 2025-04-30 21:32:12 | table | 2 | 53800 | 185 | 4.326 | 12436.4 | 
		| 933 | 2025-04-30 05:01:23 | table | 2 | 53800 | 185 | 6.280 | 8566.9 | 
		| 932 | 2025-04-29 19:56:57 | table | 1 | 28756 | 12 | 3.500 | 8216.0 | 
		| 931 | 2025-04-29 03:49:05 | table | 1 | 28756 | 12 | 0.530 | 54256.6 | 
		| 930 | 2025-04-28 20:22:37 | table | 2 | 53800 | 185 | 4.326 | 12436.4 | 
		| 929 | 2025-04-28 19:38:35 | table | 1 | 28756 | 12 | 0.466 | 61708.2 | 
		| 928 | 2025-04-28 05:53:39 | table | 2 | 53800 | 185 | 5.203 | 10340.2 | 
		| 927 | 2025-04-26 17:20:56 | table | 2 | 53800 | 185 | 7.860 | 6844.8 | 
		| 926 | 2025-04-24 03:56:18 | table | 2 | 53800 | 185 | 12.766 | 4214.3 | 
		| 925 | 2025-04-22 08:15:43 | table | 2 | 53800 | 185 | 3.936 | 13668.7 | 
		| 924 | 2025-04-19 19:09:29 | table | 1 | 28756 | 12 | 1.076 | 26724.9 |