History of Dictionary Searches using Damerau-Levenshtein distance in T-SQL
Fuzzy-string Searches
(up to 100 most recent)
for
"trap"
| Num | Started At (CA time) | Searched Word | Change Limit | Words Checked | Words Matched | Seconds | Words Per Sec |
| 1134 | 2026-02-09 01:12:10 | trap | 1 | 13983 | 16 | 0.263 | 53167.3 |
| 1133 | 2026-02-08 12:20:40 | trap | 1 | 13983 | 16 | 0.953 | 14672.6 |
| 1132 | 2026-02-07 06:19:20 | trap | 1 | 13983 | 16 | 0.250 | 55932.0 |
| 1131 | 2026-02-07 06:18:56 | trap | 1 | 13983 | 16 | 1.000 | 13983.0 |
| 1130 | 2026-02-05 09:03:13 | trap | 1 | 13983 | 16 | 0.283 | 49409.9 |
| 1129 | 2026-02-05 01:25:43 | trap | 1 | 13983 | 16 | 0.250 | 55932.0 |
| 1128 | 2026-02-04 07:54:16 | trap | 1 | 13983 | 16 | 0.263 | 53167.3 |
| 1127 | 2026-02-04 07:04:42 | trap | 1 | 13983 | 16 | 0.296 | 47239.9 |
| 1126 | 2026-02-03 15:05:11 | trap | 1 | 13983 | 16 | 0.250 | 55932.0 |
| 1125 | 2026-02-02 15:06:39 | trap | 1 | 13983 | 16 | 0.483 | 28950.3 |
| 1124 | 2026-02-01 19:32:25 | trap | 1 | 13983 | 16 | 0.283 | 49409.9 |
| 1123 | 2026-02-01 11:10:43 | trap | 1 | 13983 | 16 | 0.250 | 55932.0 |
| 1122 | 2026-01-31 15:05:01 | trap | 1 | 13983 | 16 | 0.250 | 55932.0 |
| 1121 | 2026-01-30 16:08:51 | trap | 1 | 13983 | 16 | 0.716 | 19529.3 |
| 1120 | 2026-01-30 16:08:17 | trap | 1 | 13983 | 16 | 0.300 | 46610.0 |
| 1119 | 2026-01-30 16:08:13 | trap | 1 | 13983 | 16 | 0.266 | 52567.7 |
| 1118 | 2026-01-29 12:13:57 | trap | 1 | 13983 | 16 | 0.233 | 60012.9 |
| 1117 | 2026-01-29 12:13:51 | trap | 1 | 13983 | 16 | 0.280 | 49939.3 |
| 1116 | 2026-01-28 08:09:00 | trap | 1 | 13983 | 16 | 0.233 | 60012.9 |
| 1115 | 2026-01-28 08:08:51 | trap | 1 | 13983 | 16 | 0.216 | 64736.1 |
| 1114 | 2026-01-25 23:30:06 | trap | 1 | 13983 | 16 | 0.923 | 15149.5 |
| 1113 | 2026-01-25 22:35:04 | trap | 1 | 13983 | 16 | 1.250 | 11186.4 |
| 1112 | 2026-01-19 22:43:16 | trap | 1 | 13983 | 16 | 0.546 | 25609.9 |
| 1111 | 2026-01-18 15:11:09 | trap | 1 | 13983 | 16 | 1.403 | 9966.5 |
| 1110 | 2026-01-16 07:37:38 | trap | 1 | 13983 | 16 | 0.296 | 47239.9 |
| 1109 | 2026-01-14 09:13:34 | trap | 1 | 13983 | 16 | 0.220 | 63559.1 |
| 1108 | 2026-01-12 11:48:20 | trap | 2 | 29872 | 244 | 0.780 | 38297.4 |
| 1107 | 2026-01-11 14:01:07 | trap | 1 | 13983 | 16 | 0.250 | 55932.0 |
| 1106 | 2026-01-07 23:48:46 | trap | 2 | 29872 | 244 | 0.906 | 32971.3 |
| 1105 | 2026-01-07 09:51:43 | trap | 1 | 13983 | 16 | 0.220 | 63559.1 |
| 1104 | 2026-01-06 02:29:03 | trap | 1 | 13983 | 16 | 0.516 | 27098.8 |
| 1103 | 2026-01-04 03:17:07 | trap | 1 | 13983 | 16 | 0.483 | 28950.3 |
| 1102 | 2026-01-03 20:41:19 | trap | 1 | 13983 | 16 | 0.266 | 52567.7 |
| 1101 | 2025-12-28 05:45:54 | trap | 1 | 13983 | 16 | 0.236 | 59250.0 |
| 1100 | 2025-12-27 11:05:00 | trap | 1 | 13983 | 16 | 0.220 | 63559.1 |
| 1099 | 2025-12-27 06:27:52 | trap | 1 | 13983 | 16 | 0.250 | 55932.0 |
| 1098 | 2025-12-27 02:25:25 | trap | 1 | 13983 | 16 | 0.216 | 64736.1 |
| 1097 | 2025-12-26 16:13:07 | trap | 1 | 13983 | 16 | 0.220 | 63559.1 |
| 1096 | 2025-12-25 08:36:15 | trap | 1 | 13983 | 16 | 0.250 | 55932.0 |
| 1095 | 2025-12-25 07:14:13 | trap | 1 | 13983 | 16 | 0.313 | 44674.1 |
| 1094 | 2025-12-24 06:00:06 | trap | 1 | 13983 | 16 | 0.360 | 38841.7 |
| 1093 | 2025-12-19 10:36:27 | trap | 2 | 29872 | 244 | 1.030 | 29001.9 |
| 1092 | 2025-12-17 16:45:47 | trap | 1 | 13983 | 16 | 0.250 | 55932.0 |
| 1091 | 2025-12-15 05:47:32 | trap | 1 | 13983 | 16 | 0.250 | 55932.0 |
| 1090 | 2025-12-09 23:59:34 | trap | 1 | 13983 | 16 | 0.250 | 55932.0 |
| 1089 | 2025-12-07 22:49:29 | trap | 1 | 13983 | 16 | 0.216 | 64736.1 |
| 1088 | 2025-12-03 13:17:29 | trap | 1 | 13983 | 16 | 0.250 | 55932.0 |
| 1087 | 2025-12-02 21:55:49 | trap | 1 | 13983 | 16 | 0.296 | 47239.9 |
| 1086 | 2025-12-02 12:48:36 | trap | 1 | 13983 | 16 | 0.266 | 52567.7 |
| 1085 | 2025-12-02 02:28:11 | trap | 1 | 13983 | 16 | 0.263 | 53167.3 |
| 1084 | 2025-11-25 19:30:16 | trap | 1 | 13983 | 16 | 0.250 | 55932.0 |
| 1083 | 2025-11-24 23:58:26 | trap | 1 | 13983 | 16 | 0.546 | 25609.9 |
| 1082 | 2025-11-23 18:42:18 | trap | 1 | 13983 | 16 | 0.440 | 31779.5 |
| 1081 | 2025-11-22 15:52:33 | trap | 2 | 29872 | 244 | 1.643 | 18181.4 |
| 1080 | 2025-11-18 22:03:27 | trap | 1 | 13983 | 16 | 0.250 | 55932.0 |
| 1079 | 2025-11-18 07:06:06 | trap | 1 | 13983 | 16 | 0.266 | 52567.7 |
| 1078 | 2025-11-16 00:26:27 | trap | 1 | 13983 | 16 | 0.233 | 60012.9 |
| 1077 | 2025-11-14 22:12:37 | trap | 1 | 13983 | 16 | 0.486 | 28771.6 |
| 1076 | 2025-11-14 13:08:34 | trap | 1 | 13983 | 16 | 0.233 | 60012.9 |
| 1075 | 2025-11-14 05:53:01 | trap | 1 | 13983 | 16 | 0.250 | 55932.0 |
| 1074 | 2025-11-13 17:59:03 | trap | 1 | 13983 | 16 | 0.216 | 64736.1 |
| 1073 | 2025-11-13 16:12:37 | trap | 1 | 13983 | 16 | 0.233 | 60012.9 |
| 1072 | 2025-11-13 02:38:58 | trap | 1 | 13983 | 16 | 0.250 | 55932.0 |
| 1071 | 2025-11-12 16:32:58 | trap | 1 | 13983 | 16 | 0.236 | 59250.0 |
| 1070 | 2025-11-10 21:57:53 | trap | 1 | 13983 | 16 | 0.250 | 55932.0 |
| 1069 | 2025-11-10 19:20:00 | trap | 1 | 13983 | 16 | 0.216 | 64736.1 |
| 1068 | 2025-10-27 07:10:08 | trap | 1 | 13983 | 16 | 0.250 | 55932.0 |
| 1067 | 2025-10-19 11:49:23 | trap | 1 | 13983 | 16 | 0.283 | 49409.9 |
| 1066 | 2025-10-19 11:49:20 | trap | 1 | 13983 | 16 | 0.686 | 20383.4 |
| 1065 | 2025-10-19 11:49:17 | trap | 1 | 13983 | 16 | 1.190 | 11750.4 |
| 1064 | 2025-10-19 11:49:13 | trap | 1 | 13983 | 16 | 0.940 | 14875.5 |
| 1063 | 2025-10-18 00:46:29 | trap | 1 | 13983 | 16 | 0.250 | 55932.0 |
| 1062 | 2025-10-11 23:15:32 | trap | 1 | 13983 | 16 | 0.250 | 55932.0 |
| 1061 | 2025-10-11 12:18:43 | trap | 1 | 13983 | 16 | 0.220 | 63559.1 |
| 1060 | 2025-10-11 10:05:09 | trap | 1 | 13983 | 16 | 0.220 | 63559.1 |
| 1059 | 2025-10-07 13:47:50 | trap | 1 | 13983 | 16 | 0.483 | 28950.3 |
| 1058 | 2025-10-03 16:37:16 | trap | 1 | 13983 | 16 | 0.233 | 60012.9 |
| 1057 | 2025-10-02 15:59:46 | trap | 1 | 13983 | 16 | 0.266 | 52567.7 |
| 1056 | 2025-09-25 13:05:42 | trap | 1 | 13983 | 16 | 0.563 | 24836.6 |
| 1055 | 2025-09-25 11:27:07 | trap | 1 | 13983 | 16 | 0.533 | 26234.5 |
| 1054 | 2025-09-25 11:27:02 | trap | 1 | 13983 | 16 | 0.656 | 21315.5 |
| 1053 | 2025-09-25 11:26:57 | trap | 1 | 13983 | 16 | 0.516 | 27098.8 |
| 1052 | 2025-09-25 11:26:52 | trap | 1 | 13983 | 16 | 0.796 | 17566.6 |
| 1051 | 2025-09-23 05:53:59 | trap | 1 | 13983 | 16 | 0.233 | 60012.9 |
| 1050 | 2025-09-22 01:02:44 | trap | 1 | 13983 | 16 | 0.250 | 55932.0 |
| 1049 | 2025-09-15 08:07:53 | trap | 1 | 13983 | 16 | 0.216 | 64736.1 |
| 1048 | 2025-09-14 19:54:29 | trap | 1 | 13983 | 16 | 0.250 | 55932.0 |
| 1047 | 2025-09-10 23:35:03 | trap | 1 | 13983 | 16 | 0.233 | 60012.9 |
| 1046 | 2025-09-07 12:46:00 | trap | 2 | 29872 | 244 | 0.813 | 36742.9 |
| 1045 | 2025-09-07 01:33:02 | trap | 1 | 13983 | 16 | 0.216 | 64736.1 |
| 1044 | 2025-09-06 14:02:17 | trap | 1 | 13983 | 16 | 0.233 | 60012.9 |
| 1043 | 2025-09-06 04:21:03 | trap | 1 | 13983 | 16 | 0.220 | 63559.1 |
| 1042 | 2025-09-03 07:41:54 | trap | 1 | 13983 | 16 | 0.200 | 69915.0 |
| 1041 | 2025-08-19 06:48:26 | trap | 1 | 13983 | 16 | 0.266 | 52567.7 |
| 1040 | 2025-08-18 17:39:26 | trap | 2 | 29872 | 244 | 0.780 | 38297.4 |
| 1039 | 2025-08-14 00:49:17 | trap | 1 | 13983 | 16 | 0.250 | 55932.0 |
| 1038 | 2025-08-10 02:14:53 | trap | 1 | 13983 | 16 | 0.546 | 25609.9 |
| 1037 | 2025-08-06 00:33:36 | trap | 2 | 29872 | 244 | 2.216 | 13480.1 |
| 1036 | 2025-08-04 14:50:22 | trap | 1 | 13983 | 16 | 0.216 | 64736.1 |
| 1035 | 2025-08-04 10:27:35 | trap | 1 | 13983 | 16 | 0.250 | 55932.0 |