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 |
| 1059 | 2025-12-13 07:15:32 | table | 1 | 28756 | 12 | 0.513 | 56054.6 |
| 1058 | 2025-12-13 05:10:48 | table | 2 | 53800 | 185 | 2.283 | 23565.5 |
| 1057 | 2025-12-12 01:18:21 | table | 2 | 53800 | 185 | 5.080 | 10590.6 |
| 1056 | 2025-12-12 01:18:15 | table | 2 | 53800 | 185 | 7.313 | 7356.8 |
| 1055 | 2025-12-11 02:57:01 | table | 1 | 28756 | 12 | 0.530 | 54256.6 |
| 1054 | 2025-12-07 22:58:56 | table | 2 | 53800 | 185 | 1.716 | 31352.0 |
| 1053 | 2025-12-03 19:37:41 | table | 1 | 28756 | 12 | 0.513 | 56054.6 |
| 1052 | 2025-12-03 19:29:55 | table | 1 | 28756 | 12 | 0.533 | 53951.2 |
| 1051 | 2025-12-03 19:25:34 | table | 1 | 28756 | 12 | 0.610 | 47141.0 |
| 1050 | 2025-12-03 19:08:05 | table | 1 | 28756 | 12 | 0.516 | 55728.7 |
| 1049 | 2025-12-02 11:04:02 | table | 1 | 28756 | 12 | 1.013 | 28387.0 |
| 1048 | 2025-12-01 17:43:42 | table | 1 | 28756 | 12 | 0.516 | 55728.7 |
| 1047 | 2025-11-28 00:21:47 | table | 2 | 53800 | 185 | 3.626 | 14837.3 |
| 1046 | 2025-11-27 02:16:42 | table | 2 | 53800 | 185 | 1.750 | 30742.9 |
| 1045 | 2025-11-25 21:45:47 | table | 1 | 28756 | 12 | 0.546 | 52666.7 |
| 1044 | 2025-11-25 20:59:57 | table | 1 | 28756 | 12 | 0.500 | 57512.0 |
| 1043 | 2025-11-24 02:38:01 | table | 2 | 53800 | 185 | 1.750 | 30742.9 |
| 1042 | 2025-11-23 00:53:29 | table | 1 | 28756 | 12 | 0.530 | 54256.6 |
| 1041 | 2025-11-21 22:30:57 | table | 2 | 53800 | 185 | 4.343 | 12387.8 |
| 1040 | 2025-11-20 03:46:17 | table | 1 | 28756 | 12 | 0.470 | 61183.0 |
| 1039 | 2025-11-18 15:46:26 | table | 2 | 53800 | 185 | 1.686 | 31909.8 |
| 1038 | 2025-11-18 14:30:49 | table | 1 | 28756 | 12 | 0.500 | 57512.0 |
| 1037 | 2025-11-14 19:33:23 | table | 1 | 28756 | 12 | 1.093 | 26309.2 |
| 1036 | 2025-11-14 01:33:30 | table | 1 | 28756 | 12 | 0.966 | 29768.1 |
| 1035 | 2025-11-13 17:07:53 | table | 1 | 28756 | 12 | 0.530 | 54256.6 |
| 1034 | 2025-11-13 16:20:31 | table | 1 | 28756 | 12 | 0.626 | 45936.1 |
| 1033 | 2025-11-13 16:13:49 | table | 1 | 28756 | 12 | 1.000 | 28756.0 |
| 1032 | 2025-11-13 11:58:49 | table | 1 | 28756 | 12 | 0.470 | 61183.0 |
| 1031 | 2025-11-12 20:45:49 | table | 1 | 28756 | 12 | 0.543 | 52957.6 |
| 1030 | 2025-11-12 01:16:24 | table | 1 | 28756 | 12 | 0.700 | 41080.0 |
| 1029 | 2025-11-11 05:49:58 | table | 1 | 28756 | 12 | 0.516 | 55728.7 |
| 1028 | 2025-11-10 18:36:53 | table | 1 | 28756 | 12 | 0.516 | 55728.7 |
| 1027 | 2025-11-10 03:00:29 | table | 1 | 28756 | 12 | 0.580 | 49579.3 |
| 1026 | 2025-11-02 21:04:45 | table | 1 | 28756 | 12 | 0.500 | 57512.0 |
| 1025 | 2025-11-02 08:49:38 | table | 1 | 28756 | 12 | 0.516 | 55728.7 |
| 1024 | 2025-11-02 01:35:48 | table | 1 | 28756 | 12 | 0.830 | 34645.8 |
| 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 |