History of Dictionary Searches using Damerau-Levenshtein distance in T-SQL
Fuzzy-string Searches
(up to 100 most recent)
for
"lidar"
| Num | Started At (CA time) | Searched Word | Change Limit | Words Checked | Words Matched | Seconds | Words Per Sec |
| 1121 | 2025-12-11 19:50:41 | lidar | 3 | 83667 | 970 | 18.640 | 4488.6 |
| 1120 | 2025-12-10 15:41:54 | lidar | 3 | 83667 | 970 | 7.376 | 11343.1 |
| 1119 | 2025-12-09 13:16:15 | lidar | 1 | 28756 | 3 | 0.596 | 48248.3 |
| 1118 | 2025-12-08 22:24:51 | lidar | 3 | 83667 | 970 | 3.453 | 24230.2 |
| 1117 | 2025-12-08 09:24:06 | lidar | 1 | 28756 | 3 | 0.530 | 54256.6 |
| 1116 | 2025-12-07 15:35:50 | lidar | 1 | 28756 | 3 | 0.516 | 55728.7 |
| 1115 | 2025-12-07 15:34:17 | lidar | 1 | 28756 | 3 | 0.500 | 57512.0 |
| 1114 | 2025-12-06 08:35:16 | lidar | 1 | 28756 | 3 | 0.546 | 52666.7 |
| 1113 | 2025-12-03 03:48:51 | lidar | 1 | 28756 | 3 | 0.576 | 49923.6 |
| 1112 | 2025-12-02 23:18:02 | lidar | 1 | 28756 | 3 | 2.453 | 11722.8 |
| 1111 | 2025-12-02 23:17:38 | lidar | 1 | 28756 | 3 | 3.313 | 8679.7 |
| 1110 | 2025-12-02 09:43:03 | lidar | 1 | 28756 | 3 | 0.436 | 65954.1 |
| 1109 | 2025-12-02 00:21:31 | lidar | 1 | 28756 | 3 | 1.123 | 25606.4 |
| 1108 | 2025-12-01 07:39:40 | lidar | 1 | 28756 | 3 | 0.456 | 63061.4 |
| 1107 | 2025-11-30 07:26:02 | lidar | 1 | 28756 | 3 | 0.453 | 63479.0 |
| 1106 | 2025-11-30 01:25:53 | lidar | 1 | 28756 | 3 | 1.080 | 26625.9 |
| 1105 | 2025-11-29 08:53:53 | lidar | 1 | 28756 | 3 | 0.516 | 55728.7 |
| 1104 | 2025-11-29 03:50:48 | lidar | 1 | 28756 | 3 | 1.376 | 20898.3 |
| 1103 | 2025-11-28 09:49:48 | lidar | 1 | 28756 | 3 | 0.516 | 55728.7 |
| 1102 | 2025-11-26 08:53:30 | lidar | 1 | 28756 | 3 | 1.173 | 24514.9 |
| 1101 | 2025-11-23 12:19:54 | lidar | 3 | 83667 | 970 | 3.593 | 23286.1 |
| 1100 | 2025-11-23 12:15:18 | lidar | 2 | 53800 | 67 | 1.656 | 32487.9 |
| 1099 | 2025-11-23 08:06:08 | lidar | 1 | 28756 | 3 | 0.513 | 56054.6 |
| 1098 | 2025-11-17 23:23:43 | lidar | 1 | 28756 | 3 | 0.500 | 57512.0 |
| 1097 | 2025-11-15 19:20:05 | lidar | 1 | 28756 | 3 | 0.516 | 55728.7 |
| 1096 | 2025-11-10 07:18:31 | lidar | 1 | 28756 | 3 | 0.453 | 63479.0 |
| 1095 | 2025-11-05 03:44:02 | lidar | 1 | 28756 | 3 | 0.500 | 57512.0 |
| 1094 | 2025-11-04 00:01:44 | lidar | 1 | 28756 | 3 | 0.500 | 57512.0 |
| 1093 | 2025-11-02 18:11:37 | lidar | 1 | 28756 | 3 | 0.500 | 57512.0 |
| 1092 | 2025-11-02 01:51:11 | lidar | 1 | 28756 | 3 | 0.500 | 57512.0 |
| 1091 | 2025-11-01 17:31:20 | lidar | 1 | 28756 | 3 | 0.486 | 59168.7 |
| 1090 | 2025-10-31 15:48:26 | lidar | 1 | 28756 | 3 | 0.560 | 51350.0 |
| 1089 | 2025-10-24 20:40:06 | lidar | 1 | 28756 | 3 | 0.516 | 55728.7 |
| 1088 | 2025-10-24 18:08:17 | lidar | 1 | 28756 | 3 | 0.436 | 65954.1 |
| 1087 | 2025-10-23 21:52:19 | lidar | 1 | 28756 | 3 | 0.513 | 56054.6 |
| 1086 | 2025-10-23 10:44:55 | lidar | 1 | 28756 | 3 | 1.266 | 22714.1 |
| 1085 | 2025-10-21 17:21:41 | lidar | 1 | 28756 | 3 | 2.096 | 13719.5 |
| 1084 | 2025-10-20 02:00:11 | lidar | 1 | 28756 | 3 | 3.016 | 9534.5 |
| 1083 | 2025-10-19 10:50:16 | lidar | 3 | 83667 | 970 | 20.486 | 4084.1 |
| 1082 | 2025-10-19 10:49:51 | lidar | 3 | 83667 | 970 | 17.686 | 4730.7 |
| 1081 | 2025-10-19 10:49:34 | lidar | 3 | 83667 | 970 | 10.296 | 8126.2 |
| 1080 | 2025-10-19 10:49:23 | lidar | 3 | 83667 | 970 | 19.390 | 4315.0 |
| 1079 | 2025-10-18 22:05:22 | lidar | 3 | 83667 | 970 | 3.780 | 22134.1 |
| 1078 | 2025-10-10 14:02:11 | lidar | 3 | 83667 | 970 | 4.110 | 20356.9 |
| 1077 | 2025-10-05 15:16:00 | lidar | 1 | 28756 | 3 | 0.860 | 33437.2 |
| 1076 | 2025-10-04 19:38:54 | lidar | 1 | 28756 | 3 | 0.513 | 56054.6 |
| 1075 | 2025-09-29 21:46:40 | lidar | 1 | 28756 | 3 | 0.500 | 57512.0 |
| 1074 | 2025-09-26 14:20:22 | lidar | 1 | 28756 | 3 | 0.513 | 56054.6 |
| 1073 | 2025-09-24 20:37:05 | lidar | 1 | 28756 | 3 | 0.546 | 52666.7 |
| 1072 | 2025-09-24 11:01:26 | lidar | 1 | 28756 | 3 | 0.500 | 57512.0 |
| 1071 | 2025-09-24 01:07:56 | lidar | 1 | 28756 | 3 | 0.436 | 65954.1 |
| 1070 | 2025-09-23 01:09:18 | lidar | 1 | 28756 | 3 | 0.500 | 57512.0 |
| 1069 | 2025-09-22 01:15:48 | lidar | 1 | 28756 | 3 | 1.033 | 27837.4 |
| 1068 | 2025-09-21 10:52:48 | lidar | 1 | 28756 | 3 | 0.453 | 63479.0 |
| 1067 | 2025-09-21 10:30:52 | lidar | 1 | 28756 | 3 | 0.453 | 63479.0 |
| 1066 | 2025-09-21 00:59:38 | lidar | 1 | 28756 | 3 | 0.516 | 55728.7 |
| 1065 | 2025-09-20 01:00:56 | lidar | 1 | 28756 | 3 | 0.500 | 57512.0 |
| 1064 | 2025-09-19 11:18:27 | lidar | 1 | 28756 | 3 | 0.500 | 57512.0 |
| 1063 | 2025-09-19 01:07:52 | lidar | 1 | 28756 | 3 | 1.530 | 18794.8 |
| 1062 | 2025-09-09 01:21:26 | lidar | 1 | 28756 | 3 | 0.500 | 57512.0 |
| 1061 | 2025-09-08 18:21:54 | lidar | 1 | 28756 | 3 | 0.450 | 63902.2 |
| 1060 | 2025-09-08 05:08:33 | lidar | 1 | 28756 | 3 | 0.436 | 65954.1 |
| 1059 | 2025-09-07 19:28:44 | lidar | 1 | 28756 | 3 | 1.033 | 27837.4 |
| 1058 | 2025-09-06 18:02:22 | lidar | 1 | 28756 | 3 | 0.453 | 63479.0 |
| 1057 | 2025-09-03 09:18:59 | lidar | 1 | 28756 | 3 | 0.530 | 54256.6 |
| 1056 | 2025-09-01 17:44:28 | lidar | 1 | 28756 | 3 | 0.436 | 65954.1 |
| 1055 | 2025-08-31 00:29:06 | lidar | 2 | 53800 | 67 | 1.390 | 38705.0 |
| 1054 | 2025-08-24 10:32:01 | lidar | 1 | 28756 | 3 | 2.330 | 12341.6 |
| 1053 | 2025-08-24 06:18:57 | lidar | 1 | 28756 | 3 | 2.076 | 13851.6 |
| 1052 | 2025-08-19 06:31:56 | lidar | 1 | 28756 | 3 | 1.326 | 21686.3 |
| 1051 | 2025-08-17 13:13:22 | lidar | 1 | 28756 | 3 | 0.953 | 30174.2 |
| 1050 | 2025-08-13 04:18:03 | lidar | 2 | 53800 | 67 | 1.393 | 38621.7 |
| 1049 | 2025-08-11 18:54:22 | lidar | 3 | 83667 | 970 | 24.816 | 3371.5 |
| 1048 | 2025-08-11 13:53:10 | lidar | 3 | 83667 | 970 | 12.360 | 6769.2 |
| 1047 | 2025-08-11 12:54:15 | lidar | 3 | 83667 | 970 | 8.046 | 10398.6 |
| 1046 | 2025-08-11 08:20:29 | lidar | 1 | 28756 | 3 | 0.486 | 59168.7 |
| 1045 | 2025-08-09 17:41:18 | lidar | 3 | 83667 | 970 | 19.393 | 4314.3 |
| 1044 | 2025-08-08 16:56:27 | lidar | 3 | 83667 | 970 | 3.500 | 23904.9 |
| 1043 | 2025-08-08 06:46:09 | lidar | 1 | 28756 | 3 | 0.516 | 55728.7 |
| 1042 | 2025-08-02 20:39:37 | lidar | 3 | 83667 | 970 | 16.766 | 4990.3 |
| 1041 | 2025-08-02 20:39:26 | lidar | 3 | 83667 | 970 | 19.550 | 4279.6 |
| 1040 | 2025-08-02 13:42:35 | lidar | 3 | 83667 | 970 | 9.376 | 8923.5 |
| 1039 | 2025-07-31 22:14:31 | lidar | 3 | 83667 | 970 | 11.093 | 7542.3 |
| 1038 | 2025-07-31 08:40:03 | lidar | 1 | 28756 | 3 | 1.296 | 22188.3 |
| 1037 | 2025-07-30 20:42:14 | lidar | 3 | 83667 | 970 | 17.030 | 4912.9 |
| 1036 | 2025-07-27 18:28:24 | lidar | 2 | 53800 | 67 | 4.843 | 11108.8 |
| 1035 | 2025-07-27 16:37:24 | lidar | 1 | 28756 | 3 | 1.093 | 26309.2 |
| 1034 | 2025-07-24 07:19:58 | lidar | 1 | 28756 | 3 | 1.356 | 21206.5 |
| 1033 | 2025-07-23 18:41:07 | lidar | 1 | 28756 | 3 | 2.890 | 9950.2 |
| 1032 | 2025-07-22 10:26:22 | lidar | 1 | 28756 | 3 | 2.110 | 13628.4 |
| 1031 | 2025-07-18 19:26:11 | lidar | 1 | 28756 | 3 | 1.376 | 20898.3 |
| 1030 | 2025-07-17 07:59:16 | lidar | 1 | 28756 | 3 | 1.640 | 17534.1 |
| 1029 | 2025-07-16 08:53:18 | lidar | 1 | 28756 | 3 | 0.500 | 57512.0 |
| 1028 | 2025-07-15 22:36:53 | lidar | 1 | 28756 | 3 | 1.046 | 27491.4 |
| 1027 | 2025-07-14 15:26:14 | lidar | 1 | 28756 | 3 | 1.140 | 25224.6 |
| 1026 | 2025-07-10 13:54:28 | lidar | 1 | 28756 | 3 | 0.516 | 55728.7 |
| 1025 | 2025-07-10 12:37:51 | lidar | 1 | 28756 | 3 | 2.186 | 13154.6 |
| 1024 | 2025-07-10 12:15:53 | lidar | 1 | 28756 | 3 | 2.516 | 11429.3 |
| 1023 | 2025-07-06 20:30:51 | lidar | 3 | 83667 | 970 | 3.673 | 22778.9 |
| 1022 | 2025-07-04 22:27:24 | lidar | 3 | 83667 | 970 | 20.766 | 4029.0 |