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 |
| 1128 | 2026-02-02 10:18:02 | plots | 1 | 28756 | 15 | 2.406 | 11951.8 |
| 1127 | 2026-02-01 15:27:22 | plots | 2 | 53800 | 230 | 1.560 | 34487.2 |
| 1126 | 2026-01-30 04:13:49 | plots | 1 | 28756 | 15 | 0.500 | 57512.0 |
| 1125 | 2026-01-30 03:24:09 | plots | 1 | 28756 | 15 | 1.030 | 27918.4 |
| 1124 | 2026-01-25 19:19:50 | plots | 2 | 53800 | 230 | 1.656 | 32487.9 |
| 1123 | 2026-01-24 19:11:44 | plots | 1 | 28756 | 15 | 0.500 | 57512.0 |
| 1122 | 2026-01-24 02:18:14 | plots | 1 | 28756 | 15 | 0.873 | 32939.3 |
| 1121 | 2026-01-24 02:13:48 | plots | 1 | 28756 | 15 | 0.530 | 54256.6 |
| 1120 | 2026-01-23 03:25:18 | plots | 1 | 28756 | 15 | 0.546 | 52666.7 |
| 1119 | 2026-01-20 11:54:08 | plots | 2 | 53800 | 230 | 1.593 | 33772.8 |
| 1118 | 2026-01-17 16:09:57 | plots | 1 | 28756 | 15 | 1.046 | 27491.4 |
| 1117 | 2026-01-17 04:34:46 | plots | 1 | 28756 | 15 | 1.546 | 18600.3 |
| 1116 | 2026-01-16 13:26:59 | plots | 1 | 28756 | 15 | 0.500 | 57512.0 |
| 1115 | 2026-01-16 13:25:51 | plots | 1 | 28756 | 15 | 0.546 | 52666.7 |
| 1114 | 2026-01-16 13:09:24 | plots | 1 | 28756 | 15 | 0.686 | 41918.4 |
| 1113 | 2026-01-16 12:22:44 | plots | 1 | 28756 | 15 | 0.513 | 56054.6 |
| 1112 | 2026-01-14 21:41:07 | plots | 2 | 53800 | 230 | 1.923 | 27977.1 |
| 1111 | 2026-01-13 20:16:11 | plots | 1 | 28756 | 15 | 0.500 | 57512.0 |
| 1110 | 2026-01-13 01:50:28 | plots | 1 | 28756 | 15 | 0.453 | 63479.0 |
| 1109 | 2026-01-12 13:22:51 | plots | 2 | 53800 | 230 | 1.796 | 29955.5 |
| 1108 | 2026-01-11 13:15:06 | plots | 2 | 53800 | 230 | 7.516 | 7158.1 |
| 1107 | 2026-01-08 20:11:34 | plots | 2 | 53800 | 230 | 4.733 | 11367.0 |
| 1106 | 2026-01-08 14:26:32 | plots | 1 | 28756 | 15 | 0.563 | 51076.4 |
| 1105 | 2026-01-08 08:44:24 | plots | 1 | 28756 | 15 | 0.500 | 57512.0 |
| 1104 | 2026-01-08 05:53:24 | plots | 1 | 28756 | 15 | 0.500 | 57512.0 |
| 1103 | 2026-01-07 06:56:23 | plots | 1 | 28756 | 15 | 0.796 | 36125.6 |
| 1102 | 2026-01-07 05:39:32 | plots | 1 | 28756 | 15 | 0.500 | 57512.0 |
| 1101 | 2026-01-07 05:09:56 | plots | 1 | 28756 | 15 | 1.016 | 28303.1 |
| 1100 | 2026-01-06 21:58:54 | plots | 1 | 28756 | 15 | 1.046 | 27491.4 |
| 1099 | 2026-01-06 20:53:46 | plots | 2 | 53800 | 230 | 1.716 | 31352.0 |
| 1098 | 2026-01-02 16:02:13 | plots | 1 | 28756 | 15 | 0.546 | 52666.7 |
| 1097 | 2025-12-31 22:21:31 | plots | 2 | 53800 | 230 | 1.656 | 32487.9 |
| 1096 | 2025-12-28 03:18:15 | plots | 1 | 28756 | 15 | 0.483 | 59536.2 |
| 1095 | 2025-12-26 04:25:07 | plots | 1 | 28756 | 15 | 0.670 | 42919.4 |
| 1094 | 2025-12-26 04:24:37 | plots | 1 | 28756 | 15 | 0.513 | 56054.6 |
| 1093 | 2025-12-25 10:48:26 | plots | 2 | 53800 | 230 | 1.406 | 38264.6 |
| 1092 | 2025-12-23 03:41:20 | plots | 1 | 28756 | 15 | 0.530 | 54256.6 |
| 1091 | 2025-12-22 23:15:48 | plots | 1 | 28756 | 15 | 0.530 | 54256.6 |
| 1090 | 2025-12-20 15:36:46 | plots | 1 | 28756 | 15 | 0.530 | 54256.6 |
| 1089 | 2025-12-20 05:51:35 | plots | 2 | 53800 | 230 | 1.843 | 29191.5 |
| 1088 | 2025-12-17 16:27:26 | plots | 1 | 28756 | 15 | 0.530 | 54256.6 |
| 1087 | 2025-12-14 16:41:19 | plots | 2 | 53800 | 230 | 1.563 | 34421.0 |
| 1086 | 2025-12-11 05:24:35 | plots | 1 | 28756 | 15 | 0.466 | 61708.2 |
| 1085 | 2025-12-10 12:24:28 | plots | 2 | 53800 | 230 | 1.690 | 31834.3 |
| 1084 | 2025-12-10 11:59:33 | plots | 1 | 28756 | 15 | 0.453 | 63479.0 |
| 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 |