History of Dictionary Searches using Damerau-Levenshtein distance in T-SQL
    
        
    
    
    
    
    
    
    
    
        
    Fuzzy-string Searches
        (up to 100 most recent)
        for
        "bred"
        
    
	
		| Num | Started At (CA time) | Searched Word | Change Limit | Words Checked | Words Matched | Seconds | Words Per Sec | 
	
		| 1069 | 2025-10-16 19:33:14 | bred | 1 | 13983 | 15 | 0.250 | 55932.0 | 
	
		| 1068 | 2025-09-30 19:38:39 | bred | 1 | 13983 | 15 | 0.250 | 55932.0 | 
	
		| 1067 | 2025-09-24 22:27:09 | bred | 1 | 13983 | 15 | 0.250 | 55932.0 | 
	
		| 1066 | 2025-09-24 22:17:33 | bred | 2 | 29872 | 357 | 2.140 | 13958.9 | 
	
		| 1065 | 2025-09-24 22:17:04 | bred | 2 | 29872 | 357 | 3.906 | 7647.7 | 
	
		| 1064 | 2025-09-24 22:16:31 | bred | 2 | 29872 | 357 | 2.046 | 14600.2 | 
	
		| 1063 | 2025-09-24 22:16:01 | bred | 2 | 29872 | 357 | 3.096 | 9648.6 | 
	
		| 1062 | 2025-09-23 14:10:03 | bred | 2 | 29872 | 357 | 0.876 | 34100.5 | 
	
		| 1061 | 2025-09-21 13:05:53 | bred | 1 | 13983 | 15 | 0.266 | 52567.7 | 
	
		| 1060 | 2025-09-19 04:25:51 | bred | 2 | 29872 | 357 | 0.876 | 34100.5 | 
	
		| 1059 | 2025-09-13 00:14:39 | bred | 1 | 13983 | 15 | 0.250 | 55932.0 | 
	
		| 1058 | 2025-09-07 19:18:30 | bred | 1 | 13983 | 15 | 0.250 | 55932.0 | 
	
		| 1057 | 2025-09-06 05:53:43 | bred | 1 | 13983 | 15 | 0.500 | 27966.0 | 
	
		| 1056 | 2025-09-03 19:56:05 | bred | 1 | 13983 | 15 | 0.233 | 60012.9 | 
	
		| 1055 | 2025-09-03 18:59:21 | bred | 1 | 13983 | 15 | 0.250 | 55932.0 | 
	
		| 1054 | 2025-09-01 03:22:36 | bred | 1 | 13983 | 15 | 0.263 | 53167.3 | 
	
		| 1053 | 2025-08-31 08:36:27 | bred | 1 | 13983 | 15 | 0.236 | 59250.0 | 
	
		| 1052 | 2025-08-30 21:35:11 | bred | 1 | 13983 | 15 | 0.640 | 21848.4 | 
	
		| 1051 | 2025-08-24 07:35:55 | bred | 1 | 13983 | 15 | 0.250 | 55932.0 | 
	
		| 1050 | 2025-08-09 05:49:18 | bred | 1 | 13983 | 15 | 1.736 | 8054.7 | 
	
		| 1049 | 2025-08-04 15:14:38 | bred | 2 | 29872 | 357 | 0.903 | 33080.8 | 
	
		| 1048 | 2025-08-03 02:23:24 | bred | 2 | 29872 | 357 | 4.453 | 6708.3 | 
	
		| 1047 | 2025-08-01 18:33:33 | bred | 1 | 13983 | 15 | 1.080 | 12947.2 | 
	
		| 1046 | 2025-08-01 09:52:18 | bred | 2 | 29872 | 357 | 2.296 | 13010.5 | 
	
		| 1045 | 2025-08-01 02:36:03 | bred | 1 | 13983 | 15 | 0.560 | 24969.6 | 
	
		| 1044 | 2025-07-31 12:34:17 | bred | 1 | 13983 | 15 | 0.280 | 49939.3 | 
	
		| 1043 | 2025-07-31 03:52:08 | bred | 1 | 13983 | 15 | 0.500 | 27966.0 | 
	
		| 1042 | 2025-07-28 21:49:31 | bred | 2 | 29872 | 357 | 4.220 | 7078.7 | 
	
		| 1041 | 2025-07-28 01:53:35 | bred | 2 | 29872 | 357 | 4.060 | 7357.6 | 
	
		| 1040 | 2025-07-24 14:08:22 | bred | 1 | 13983 | 15 | 1.343 | 10411.8 | 
	
		| 1039 | 2025-07-23 04:06:22 | bred | 1 | 13983 | 15 | 1.376 | 10162.1 | 
	
		| 1038 | 2025-07-14 11:46:35 | bred | 2 | 29872 | 357 | 6.266 | 4767.3 | 
	
		| 1037 | 2025-07-08 04:21:53 | bred | 1 | 13983 | 15 | 0.920 | 15198.9 | 
	
		| 1036 | 2025-07-02 01:24:48 | bred | 1 | 13983 | 15 | 1.403 | 9966.5 | 
	
		| 1035 | 2025-07-01 08:18:20 | bred | 1 | 13983 | 15 | 0.250 | 55932.0 | 
	
		| 1034 | 2025-06-22 12:15:00 | bred | 1 | 13983 | 15 | 1.623 | 8615.5 | 
	
		| 1033 | 2025-06-18 01:36:51 | bred | 2 | 29872 | 357 | 2.313 | 12914.8 | 
	
		| 1032 | 2025-06-17 12:49:27 | bred | 1 | 13983 | 15 | 0.233 | 60012.9 | 
	
		| 1031 | 2025-06-16 15:07:49 | bred | 1 | 13983 | 15 | 0.780 | 17926.9 | 
	
		| 1030 | 2025-06-10 09:04:51 | bred | 1 | 13983 | 15 | 1.126 | 12418.3 | 
	
		| 1029 | 2025-06-08 03:56:52 | bred | 1 | 13983 | 15 | 0.763 | 18326.3 | 
	
		| 1028 | 2025-06-02 00:34:03 | bred | 1 | 13983 | 15 | 1.186 | 11790.1 | 
	
		| 1027 | 2025-06-01 05:31:43 | bred | 1 | 13983 | 15 | 1.390 | 10059.7 | 
	
		| 1026 | 2025-05-31 08:05:21 | bred | 1 | 13983 | 15 | 0.343 | 40766.8 | 
	
		| 1025 | 2025-05-30 11:22:53 | bred | 1 | 13983 | 15 | 1.326 | 10545.2 | 
	
		| 1024 | 2025-05-27 19:22:29 | bred | 1 | 13983 | 15 | 0.250 | 55932.0 | 
	
		| 1023 | 2025-05-21 08:39:34 | bred | 1 | 13983 | 15 | 0.236 | 59250.0 | 
	
		| 1022 | 2025-05-16 13:54:39 | bred | 1 | 13983 | 15 | 1.500 | 9322.0 | 
	
		| 1021 | 2025-05-10 09:21:14 | bred | 2 | 29872 | 357 | 4.500 | 6638.2 | 
	
		| 1020 | 2025-05-09 08:35:18 | bred | 1 | 13983 | 15 | 0.250 | 55932.0 | 
	
		| 1019 | 2025-05-08 08:29:02 | bred | 1 | 13983 | 15 | 1.483 | 9428.9 | 
	
		| 1018 | 2025-05-08 08:24:42 | bred | 1 | 13983 | 15 | 0.266 | 52567.7 | 
	
		| 1017 | 2025-05-06 03:14:51 | bred | 1 | 13983 | 15 | 2.486 | 5624.7 | 
	
		| 1016 | 2025-05-04 12:51:43 | bred | 1 | 13983 | 15 | 1.106 | 12642.9 | 
	
		| 1015 | 2025-05-03 22:39:32 | bred | 2 | 29872 | 357 | 3.936 | 7589.4 | 
	
		| 1014 | 2025-05-02 14:42:34 | bred | 2 | 29872 | 357 | 3.626 | 8238.3 | 
	
		| 1013 | 2025-05-02 00:26:02 | bred | 1 | 13983 | 15 | 1.593 | 8777.8 | 
	
		| 1012 | 2025-04-30 09:15:57 | bred | 2 | 29872 | 357 | 4.516 | 6614.7 | 
	
		| 1011 | 2025-04-30 08:13:21 | bred | 1 | 13983 | 15 | 1.360 | 10281.6 | 
	
		| 1010 | 2025-04-29 11:35:03 | bred | 1 | 13983 | 15 | 0.250 | 55932.0 | 
	
		| 1009 | 2025-04-15 14:07:03 | bred | 1 | 13983 | 15 | 0.843 | 16587.2 | 
	
		| 1008 | 2025-04-10 20:21:17 | bred | 2 | 29872 | 357 | 5.593 | 5341.0 | 
	
		| 1007 | 2025-04-09 07:09:54 | bred | 2 | 29872 | 357 | 2.326 | 12842.6 | 
	
		| 1006 | 2025-04-08 08:04:50 | bred | 1 | 13983 | 15 | 0.720 | 19420.8 | 
	
		| 1005 | 2025-04-03 10:27:40 | bred | 1 | 13983 | 15 | 0.310 | 45106.5 | 
	
		| 1004 | 2025-04-03 05:42:14 | bred | 1 | 13983 | 15 | 0.250 | 55932.0 | 
	
		| 1003 | 2025-03-31 01:23:27 | bred | 1 | 13983 | 15 | 0.893 | 15658.5 | 
	
		| 1002 | 2025-03-29 10:11:21 | bred | 1 | 13983 | 15 | 0.936 | 14939.1 | 
	
		| 1001 | 2025-03-27 14:18:27 | bred | 1 | 13983 | 15 | 1.513 | 9241.9 | 
	
		| 1000 | 2025-03-18 00:43:18 | bred | 1 | 13983 | 15 | 1.313 | 10649.7 | 
	
		| 999 | 2025-03-15 16:25:27 | bred | 1 | 13983 | 15 | 0.250 | 55932.0 | 
	
		| 998 | 2025-03-13 08:37:17 | bred | 2 | 29872 | 357 | 1.750 | 17069.7 | 
	
		| 997 | 2025-03-08 03:38:59 | bred | 1 | 13983 | 15 | 0.280 | 49939.3 | 
	
		| 996 | 2025-03-06 23:26:43 | bred | 2 | 29872 | 357 | 2.220 | 13455.9 | 
	
		| 995 | 2025-03-06 23:07:09 | bred | 1 | 13983 | 15 | 0.233 | 60012.9 | 
	
		| 994 | 2025-03-01 06:43:24 | bred | 1 | 13983 | 15 | 0.576 | 24276.0 | 
	
		| 993 | 2025-02-25 23:53:56 | bred | 2 | 29872 | 357 | 6.500 | 4595.7 | 
	
		| 992 | 2025-02-25 20:16:10 | bred | 2 | 29872 | 357 | 6.186 | 4829.0 | 
	
		| 991 | 2025-02-25 12:13:15 | bred | 2 | 29872 | 357 | 4.236 | 7051.9 | 
	
		| 990 | 2025-02-25 11:52:32 | bred | 1 | 13983 | 15 | 0.690 | 20265.2 | 
	
		| 989 | 2025-02-25 08:27:54 | bred | 1 | 13983 | 15 | 0.686 | 20383.4 | 
	
		| 988 | 2025-02-24 09:30:19 | bred | 1 | 13983 | 15 | 0.280 | 49939.3 | 
	
		| 987 | 2025-02-23 19:28:22 | bred | 1 | 13983 | 15 | 0.280 | 49939.3 | 
	
		| 986 | 2025-02-04 19:40:35 | bred | 1 | 13983 | 15 | 0.250 | 55932.0 | 
	
		| 985 | 2025-01-26 11:33:50 | bred | 1 | 13983 | 15 | 0.233 | 60012.9 | 
	
		| 984 | 2025-01-25 23:31:29 | bred | 2 | 29872 | 357 | 2.500 | 11948.8 | 
	
		| 983 | 2025-01-25 08:57:44 | bred | 2 | 29872 | 357 | 4.140 | 7215.5 | 
	
		| 982 | 2025-01-25 01:46:15 | bred | 2 | 29872 | 357 | 4.313 | 6926.0 | 
	
		| 981 | 2025-01-25 01:31:49 | bred | 2 | 29872 | 357 | 3.000 | 9957.3 | 
	
		| 980 | 2025-01-25 01:26:05 | bred | 1 | 13983 | 15 | 0.250 | 55932.0 | 
	
		| 979 | 2025-01-24 17:14:56 | bred | 1 | 13983 | 15 | 0.936 | 14939.1 | 
	
		| 978 | 2025-01-18 08:20:16 | bred | 1 | 13983 | 15 | 1.360 | 10281.6 | 
	
		| 977 | 2025-01-05 18:49:05 | bred | 1 | 13983 | 15 | 0.876 | 15962.3 | 
	
		| 976 | 2024-12-30 19:00:58 | bred | 1 | 13983 | 15 | 0.250 | 55932.0 | 
	
		| 975 | 2024-12-27 07:29:00 | bred | 1 | 13983 | 15 | 0.856 | 16335.3 | 
	
		| 974 | 2024-12-25 15:28:48 | bred | 1 | 13983 | 15 | 0.686 | 20383.4 | 
	
		| 973 | 2024-12-25 10:08:12 | bred | 1 | 13983 | 15 | 0.216 | 64736.1 | 
	
		| 972 | 2024-12-06 19:10:32 | bred | 2 | 29872 | 357 | 2.263 | 13200.2 | 
	
		| 971 | 2024-12-06 14:29:46 | bred | 2 | 29872 | 357 | 4.173 | 7158.4 | 
	
		| 970 | 2024-12-06 14:23:09 | bred | 1 | 13983 | 15 | 0.936 | 14939.1 |