History of Dictionary Searches using Damerau-Levenshtein distance in T-SQL
Fuzzy-string Searches
(up to 100 most recent)
for
"plots"
| Num | Started At (CA time) | Searched Word | Change Limit | Words Checked | Words Matched | Seconds | Words Per Sec |
| 1083 | 2025-12-07 08:15:31 | plots | 2 | 53800 | 230 | 1.623 | 33148.5 |
| 1082 | 2025-12-05 03:44:35 | plots | 1 | 28756 | 15 | 0.516 | 55728.7 |
| 1081 | 2025-12-02 23:51:52 | plots | 1 | 28756 | 15 | 1.296 | 22188.3 |
| 1080 | 2025-12-02 23:51:27 | plots | 1 | 28756 | 15 | 1.610 | 17860.9 |
| 1079 | 2025-11-30 16:57:48 | plots | 1 | 28756 | 15 | 0.483 | 59536.2 |
| 1078 | 2025-11-28 18:41:01 | plots | 2 | 53800 | 230 | 3.500 | 15371.4 |
| 1077 | 2025-11-28 09:32:44 | plots | 1 | 28756 | 15 | 0.516 | 55728.7 |
| 1076 | 2025-11-27 14:14:43 | plots | 1 | 28756 | 15 | 0.546 | 52666.7 |
| 1075 | 2025-11-25 14:13:53 | plots | 1 | 28756 | 15 | 0.516 | 55728.7 |
| 1074 | 2025-11-25 00:07:48 | plots | 1 | 28756 | 15 | 0.953 | 30174.2 |
| 1073 | 2025-11-24 23:39:31 | plots | 1 | 28756 | 15 | 0.546 | 52666.7 |
| 1072 | 2025-11-24 19:44:16 | plots | 1 | 28756 | 15 | 0.516 | 55728.7 |
| 1071 | 2025-11-23 20:06:26 | plots | 1 | 28756 | 15 | 0.470 | 61183.0 |
| 1070 | 2025-11-23 03:29:51 | plots | 2 | 53800 | 230 | 1.593 | 33772.8 |
| 1069 | 2025-11-21 19:27:15 | plots | 1 | 28756 | 15 | 0.513 | 56054.6 |
| 1068 | 2025-11-21 18:39:08 | plots | 1 | 28756 | 15 | 0.516 | 55728.7 |
| 1067 | 2025-11-20 18:52:08 | plots | 1 | 28756 | 15 | 0.546 | 52666.7 |
| 1066 | 2025-11-20 18:52:07 | plots | 1 | 28756 | 15 | 0.533 | 53951.2 |
| 1065 | 2025-11-20 01:43:47 | plots | 1 | 28756 | 15 | 1.063 | 27051.7 |
| 1064 | 2025-11-19 16:15:27 | plots | 1 | 28756 | 15 | 0.593 | 48492.4 |
| 1063 | 2025-11-19 05:50:27 | plots | 1 | 28756 | 15 | 0.533 | 53951.2 |
| 1062 | 2025-11-18 20:18:43 | plots | 1 | 28756 | 15 | 0.530 | 54256.6 |
| 1061 | 2025-11-18 20:12:48 | plots | 1 | 28756 | 15 | 0.500 | 57512.0 |
| 1060 | 2025-11-16 14:24:25 | plots | 1 | 28756 | 15 | 0.516 | 55728.7 |
| 1059 | 2025-11-16 10:57:53 | plots | 2 | 53800 | 230 | 1.610 | 33416.1 |
| 1058 | 2025-11-15 11:14:26 | plots | 1 | 28756 | 15 | 0.546 | 52666.7 |
| 1057 | 2025-11-15 03:35:16 | plots | 1 | 28756 | 15 | 1.250 | 23004.8 |
| 1056 | 2025-11-11 14:23:08 | plots | 1 | 28756 | 15 | 0.550 | 52283.6 |
| 1055 | 2025-11-03 13:55:00 | plots | 1 | 28756 | 15 | 0.453 | 63479.0 |
| 1054 | 2025-11-01 19:32:53 | plots | 2 | 53800 | 230 | 1.576 | 34137.1 |
| 1053 | 2025-10-31 23:30:20 | plots | 2 | 53800 | 230 | 1.670 | 32215.6 |
| 1052 | 2025-10-30 05:55:19 | plots | 1 | 28756 | 15 | 0.606 | 47452.1 |
| 1051 | 2025-10-29 15:06:29 | plots | 1 | 28756 | 15 | 0.516 | 55728.7 |
| 1050 | 2025-10-27 22:29:07 | plots | 2 | 53800 | 230 | 1.706 | 31535.8 |
| 1049 | 2025-10-27 05:10:50 | plots | 1 | 28756 | 15 | 0.533 | 53951.2 |
| 1048 | 2025-10-25 20:45:31 | plots | 2 | 53800 | 230 | 1.373 | 39184.3 |
| 1047 | 2025-10-25 03:59:48 | plots | 2 | 53800 | 230 | 1.500 | 35866.7 |
| 1046 | 2025-10-22 15:09:04 | plots | 1 | 28756 | 15 | 1.393 | 20643.2 |
| 1045 | 2025-10-20 16:26:33 | plots | 1 | 28756 | 15 | 1.310 | 21951.1 |
| 1044 | 2025-10-20 12:22:39 | plots | 1 | 28756 | 15 | 0.686 | 41918.4 |
| 1043 | 2025-10-19 15:44:29 | plots | 1 | 28756 | 15 | 1.513 | 19005.9 |
| 1042 | 2025-10-18 23:28:55 | plots | 2 | 53800 | 230 | 1.436 | 37465.2 |
| 1041 | 2025-10-17 21:01:35 | plots | 1 | 28756 | 15 | 0.500 | 57512.0 |
| 1040 | 2025-10-12 17:36:33 | plots | 1 | 28756 | 15 | 0.500 | 57512.0 |
| 1039 | 2025-10-12 08:18:32 | plots | 1 | 28756 | 15 | 0.470 | 61183.0 |
| 1038 | 2025-10-08 01:57:05 | plots | 2 | 53800 | 230 | 1.483 | 36277.8 |
| 1037 | 2025-10-07 05:05:10 | plots | 2 | 53800 | 230 | 1.656 | 32487.9 |
| 1036 | 2025-10-03 17:29:47 | plots | 1 | 28756 | 15 | 0.530 | 54256.6 |
| 1035 | 2025-10-01 05:32:57 | plots | 2 | 53800 | 230 | 1.703 | 31591.3 |
| 1034 | 2025-09-28 07:46:30 | plots | 1 | 28756 | 15 | 0.500 | 57512.0 |
| 1033 | 2025-09-27 22:44:06 | plots | 2 | 53800 | 230 | 1.563 | 34421.0 |
| 1032 | 2025-09-27 12:23:25 | plots | 1 | 28756 | 15 | 0.486 | 59168.7 |
| 1031 | 2025-09-27 11:57:45 | plots | 1 | 28756 | 15 | 0.500 | 57512.0 |
| 1030 | 2025-09-27 11:37:44 | plots | 1 | 28756 | 15 | 0.530 | 54256.6 |
| 1029 | 2025-09-27 11:37:40 | plots | 1 | 28756 | 15 | 0.453 | 63479.0 |
| 1028 | 2025-09-26 21:40:22 | plots | 1 | 28756 | 15 | 0.546 | 52666.7 |
| 1027 | 2025-09-26 10:08:46 | plots | 1 | 28756 | 15 | 0.483 | 59536.2 |
| 1026 | 2025-09-25 11:17:02 | plots | 2 | 53800 | 230 | 10.813 | 4975.5 |
| 1025 | 2025-09-25 04:05:32 | plots | 1 | 28756 | 15 | 0.453 | 63479.0 |
| 1024 | 2025-09-22 01:19:12 | plots | 1 | 28756 | 15 | 0.436 | 65954.1 |
| 1023 | 2025-09-20 12:39:38 | plots | 1 | 28756 | 15 | 0.450 | 63902.2 |
| 1022 | 2025-09-20 06:02:01 | plots | 2 | 53800 | 230 | 1.643 | 32745.0 |
| 1021 | 2025-09-20 02:48:33 | plots | 2 | 53800 | 230 | 1.533 | 35094.6 |
| 1020 | 2025-09-19 11:43:34 | plots | 1 | 28756 | 15 | 0.450 | 63902.2 |
| 1019 | 2025-09-19 00:16:23 | plots | 2 | 53800 | 230 | 1.673 | 32157.8 |
| 1018 | 2025-09-17 16:11:04 | plots | 2 | 53800 | 230 | 1.436 | 37465.2 |
| 1017 | 2025-09-17 03:16:31 | plots | 2 | 53800 | 230 | 1.826 | 29463.3 |
| 1016 | 2025-09-17 02:55:04 | plots | 1 | 28756 | 15 | 0.530 | 54256.6 |
| 1015 | 2025-09-12 05:47:38 | plots | 1 | 28756 | 15 | 0.516 | 55728.7 |
| 1014 | 2025-09-12 00:34:13 | plots | 2 | 53800 | 230 | 1.716 | 31352.0 |
| 1013 | 2025-09-10 01:07:23 | plots | 1 | 28756 | 15 | 0.436 | 65954.1 |
| 1012 | 2025-09-08 15:03:39 | plots | 2 | 53800 | 230 | 1.516 | 35488.1 |
| 1011 | 2025-09-07 23:51:43 | plots | 1 | 28756 | 15 | 0.453 | 63479.0 |
| 1010 | 2025-09-07 09:30:21 | plots | 1 | 28756 | 15 | 0.533 | 53951.2 |
| 1009 | 2025-09-03 22:39:10 | plots | 1 | 28756 | 15 | 0.500 | 57512.0 |
| 1008 | 2025-09-01 11:04:58 | plots | 2 | 53800 | 230 | 1.436 | 37465.2 |
| 1007 | 2025-08-29 09:31:18 | plots | 1 | 28756 | 15 | 0.470 | 61183.0 |
| 1006 | 2025-08-27 12:25:17 | plots | 1 | 28756 | 15 | 0.500 | 57512.0 |
| 1005 | 2025-08-26 22:04:36 | plots | 2 | 53800 | 230 | 1.733 | 31044.4 |
| 1004 | 2025-08-26 08:26:39 | plots | 2 | 53800 | 230 | 3.373 | 15950.2 |
| 1003 | 2025-08-24 22:10:53 | plots | 1 | 28756 | 15 | 3.313 | 8679.7 |
| 1002 | 2025-08-22 22:16:43 | plots | 1 | 28756 | 15 | 3.546 | 8109.4 |
| 1001 | 2025-08-19 12:24:35 | plots | 1 | 28756 | 15 | 1.610 | 17860.9 |
| 1000 | 2025-08-17 20:55:58 | plots | 2 | 53800 | 230 | 7.546 | 7129.6 |
| 999 | 2025-08-15 23:59:26 | plots | 1 | 28756 | 15 | 1.000 | 28756.0 |
| 998 | 2025-08-01 02:33:51 | plots | 1 | 28756 | 15 | 3.313 | 8679.7 |
| 997 | 2025-08-01 02:33:27 | plots | 2 | 53800 | 230 | 4.626 | 11629.9 |
| 996 | 2025-07-31 11:49:09 | plots | 1 | 28756 | 15 | 0.826 | 34813.6 |
| 995 | 2025-07-31 08:10:42 | plots | 1 | 28756 | 15 | 3.343 | 8601.9 |
| 994 | 2025-07-28 00:22:23 | plots | 2 | 53800 | 230 | 4.313 | 12473.9 |
| 993 | 2025-07-27 13:29:29 | plots | 1 | 28756 | 15 | 2.000 | 14378.0 |
| 992 | 2025-07-27 07:05:07 | plots | 2 | 53800 | 230 | 8.953 | 6009.2 |
| 991 | 2025-07-25 22:59:39 | plots | 2 | 53800 | 230 | 1.763 | 30516.2 |
| 990 | 2025-07-25 22:39:22 | plots | 1 | 28756 | 15 | 0.516 | 55728.7 |
| 989 | 2025-07-23 10:46:44 | plots | 2 | 53800 | 230 | 8.203 | 6558.6 |
| 988 | 2025-07-22 20:51:52 | plots | 2 | 53800 | 230 | 7.846 | 6857.0 |
| 987 | 2025-07-22 11:13:23 | plots | 1 | 28756 | 15 | 2.330 | 12341.6 |
| 986 | 2025-07-20 00:03:26 | plots | 2 | 53800 | 230 | 7.796 | 6901.0 |
| 985 | 2025-07-19 20:26:17 | plots | 1 | 28756 | 15 | 1.483 | 19390.4 |
| 984 | 2025-07-19 20:26:15 | plots | 1 | 28756 | 15 | 1.143 | 25158.4 |