History of Dictionary Searches using Damerau-Levenshtein distance in T-SQL
Fuzzy-string Searches
(up to 100 most recent)
for
"subset"
Num | Started At (CA time) | Searched Word | Change Limit | Words Checked | Words Matched | Seconds | Words Per Sec |
1124 | 2025-10-17 17:32:19 | subset | 3 | 112716 | 519 | 6.500 | 17340.9 |
1123 | 2025-10-13 12:48:13 | subset | 1 | 48755 | 7 | 0.780 | 62506.4 |
1122 | 2025-10-09 20:12:59 | subset | 2 | 82551 | 38 | 2.233 | 36968.7 |
1121 | 2025-10-09 09:11:47 | subset | 1 | 48755 | 7 | 0.906 | 53813.5 |
1120 | 2025-10-08 20:00:31 | subset | 2 | 82551 | 38 | 2.560 | 32246.5 |
1119 | 2025-10-06 16:58:45 | subset | 1 | 48755 | 7 | 0.876 | 55656.4 |
1118 | 2025-10-06 10:39:33 | subset | 2 | 82551 | 38 | 2.203 | 37472.1 |
1117 | 2025-10-06 07:33:19 | subset | 2 | 82551 | 38 | 2.470 | 33421.5 |
1116 | 2025-10-05 10:27:06 | subset | 1 | 48755 | 7 | 0.876 | 55656.4 |
1115 | 2025-10-05 10:15:09 | subset | 2 | 82551 | 38 | 2.440 | 33832.4 |
1114 | 2025-10-05 03:11:24 | subset | 1 | 48755 | 7 | 0.876 | 55656.4 |
1113 | 2025-10-02 04:14:00 | subset | 3 | 112716 | 519 | 5.236 | 21527.1 |
1112 | 2025-09-30 11:54:19 | subset | 1 | 48755 | 7 | 1.233 | 39541.8 |
1111 | 2025-09-29 06:42:59 | subset | 2 | 82551 | 38 | 2.533 | 32590.2 |
1110 | 2025-09-28 22:29:09 | subset | 2 | 82551 | 38 | 2.516 | 32810.4 |
1109 | 2025-09-28 09:33:35 | subset | 3 | 112716 | 519 | 5.456 | 20659.1 |
1108 | 2025-09-28 02:08:13 | subset | 3 | 112716 | 519 | 6.140 | 18357.7 |
1107 | 2025-09-27 16:10:16 | subset | 3 | 112716 | 519 | 5.033 | 22395.4 |
1106 | 2025-09-26 22:14:02 | subset | 1 | 48755 | 7 | 0.843 | 57835.1 |
1105 | 2025-09-26 10:59:28 | subset | 3 | 112716 | 519 | 5.296 | 21283.2 |
1104 | 2025-09-25 22:48:05 | subset | 3 | 112716 | 519 | 30.780 | 3662.0 |
1103 | 2025-09-25 22:32:20 | subset | 3 | 112716 | 519 | 29.283 | 3849.2 |
1102 | 2025-09-25 16:33:37 | subset | 1 | 48755 | 7 | 2.173 | 22436.7 |
1101 | 2025-09-25 16:09:06 | subset | 3 | 112716 | 519 | 6.126 | 18399.6 |
1100 | 2025-09-23 08:54:01 | subset | 3 | 112716 | 519 | 6.533 | 17253.3 |
1099 | 2025-09-23 07:25:10 | subset | 3 | 112716 | 519 | 4.940 | 22817.0 |
1098 | 2025-09-23 00:24:36 | subset | 2 | 82551 | 38 | 2.296 | 35954.3 |
1097 | 2025-09-22 19:54:11 | subset | 2 | 82551 | 38 | 2.406 | 34310.5 |
1096 | 2025-09-22 11:41:49 | subset | 1 | 48755 | 7 | 0.970 | 50262.9 |
1095 | 2025-09-22 01:05:05 | subset | 1 | 48755 | 7 | 0.873 | 55847.7 |
1094 | 2025-09-20 07:03:41 | subset | 3 | 112716 | 519 | 4.923 | 22895.8 |
1093 | 2025-09-19 04:37:30 | subset | 3 | 112716 | 519 | 5.110 | 22057.9 |
1092 | 2025-09-12 13:15:08 | subset | 1 | 48755 | 7 | 0.920 | 52994.6 |
1091 | 2025-09-09 18:13:19 | subset | 2 | 82551 | 38 | 2.263 | 36478.6 |
1090 | 2025-09-09 18:13:02 | subset | 3 | 112716 | 519 | 4.843 | 23274.0 |
1089 | 2025-09-07 13:27:11 | subset | 1 | 48755 | 7 | 0.856 | 56956.8 |
1088 | 2025-09-05 14:41:27 | subset | 1 | 48755 | 7 | 0.860 | 56691.9 |
1087 | 2025-09-04 10:37:37 | subset | 1 | 48755 | 7 | 0.876 | 55656.4 |
1086 | 2025-09-04 03:13:57 | subset | 1 | 48755 | 7 | 0.780 | 62506.4 |
1085 | 2025-09-01 03:08:43 | subset | 3 | 112716 | 519 | 5.453 | 20670.5 |
1084 | 2025-08-31 22:31:44 | subset | 1 | 48755 | 7 | 0.780 | 62506.4 |
1083 | 2025-08-31 06:50:21 | subset | 3 | 112716 | 519 | 4.950 | 22770.9 |
1082 | 2025-08-29 18:02:49 | subset | 2 | 82551 | 38 | 2.610 | 31628.7 |
1081 | 2025-08-29 11:04:52 | subset | 2 | 82551 | 38 | 3.876 | 21298.0 |
1080 | 2025-08-28 22:46:22 | subset | 2 | 82551 | 38 | 2.516 | 32810.4 |
1079 | 2025-08-28 15:38:25 | subset | 3 | 112716 | 519 | 5.860 | 19234.8 |
1078 | 2025-08-28 14:38:55 | subset | 2 | 82551 | 38 | 2.250 | 36689.3 |
1077 | 2025-08-28 09:37:28 | subset | 3 | 112716 | 519 | 6.033 | 18683.2 |
1076 | 2025-08-28 07:28:36 | subset | 2 | 82551 | 38 | 2.266 | 36430.3 |
1075 | 2025-08-28 05:29:16 | subset | 3 | 112716 | 519 | 4.783 | 23566.0 |
1074 | 2025-08-28 01:53:42 | subset | 3 | 112716 | 519 | 5.186 | 21734.7 |
1073 | 2025-08-27 21:48:44 | subset | 1 | 48755 | 7 | 0.796 | 61250.0 |
1072 | 2025-08-27 19:59:24 | subset | 3 | 112716 | 519 | 5.640 | 19985.1 |
1071 | 2025-08-27 19:12:02 | subset | 3 | 112716 | 519 | 28.720 | 3924.7 |
1070 | 2025-08-27 10:26:06 | subset | 3 | 112716 | 519 | 5.186 | 21734.7 |
1069 | 2025-08-26 21:39:22 | subset | 3 | 112716 | 519 | 5.533 | 20371.6 |
1068 | 2025-08-25 16:42:14 | subset | 1 | 48755 | 7 | 6.250 | 7800.8 |
1067 | 2025-08-25 16:39:48 | subset | 3 | 112716 | 519 | 26.656 | 4228.5 |
1066 | 2025-08-23 07:13:40 | subset | 3 | 112716 | 519 | 28.686 | 3929.3 |
1065 | 2025-08-22 20:45:45 | subset | 2 | 82551 | 38 | 18.300 | 4511.0 |
1064 | 2025-08-22 11:26:44 | subset | 1 | 48755 | 7 | 2.266 | 21515.9 |
1063 | 2025-08-22 01:41:04 | subset | 1 | 48755 | 7 | 0.890 | 54780.9 |
1062 | 2025-08-09 00:37:17 | subset | 1 | 48755 | 7 | 3.953 | 12333.7 |
1061 | 2025-08-05 17:07:27 | subset | 1 | 48755 | 7 | 3.780 | 12898.1 |
1060 | 2025-08-04 13:50:30 | subset | 1 | 48755 | 7 | 2.390 | 20399.6 |
1059 | 2025-07-27 00:27:45 | subset | 1 | 48755 | 7 | 3.250 | 15001.5 |
1058 | 2025-07-24 22:11:35 | subset | 1 | 48755 | 7 | 1.546 | 31536.2 |
1057 | 2025-07-23 11:39:13 | subset | 1 | 48755 | 7 | 3.373 | 14454.5 |
1056 | 2025-07-23 08:08:26 | subset | 1 | 48755 | 7 | 4.203 | 11600.0 |
1055 | 2025-07-22 14:11:21 | subset | 1 | 48755 | 7 | 2.076 | 23485.1 |
1054 | 2025-07-20 21:21:56 | subset | 1 | 48755 | 7 | 0.920 | 52994.6 |
1053 | 2025-07-10 21:17:09 | subset | 2 | 82551 | 38 | 9.440 | 8744.8 |
1052 | 2025-07-09 14:44:53 | subset | 1 | 48755 | 7 | 0.876 | 55656.4 |
1051 | 2025-07-08 21:56:24 | subset | 1 | 48755 | 7 | 0.796 | 61250.0 |
1050 | 2025-07-07 10:17:01 | subset | 3 | 112716 | 519 | 38.316 | 2941.7 |
1049 | 2025-07-07 02:25:50 | subset | 3 | 112716 | 519 | 19.673 | 5729.5 |
1048 | 2025-07-07 00:13:04 | subset | 2 | 82551 | 38 | 17.656 | 4675.5 |
1047 | 2025-07-05 16:55:37 | subset | 3 | 112716 | 519 | 30.063 | 3749.3 |
1046 | 2025-07-05 10:28:24 | subset | 2 | 82551 | 38 | 12.813 | 6442.8 |
1045 | 2025-07-04 12:17:20 | subset | 1 | 48755 | 7 | 4.720 | 10329.4 |
1044 | 2025-06-29 06:37:06 | subset | 1 | 48755 | 7 | 3.716 | 13120.3 |
1043 | 2025-06-26 23:15:47 | subset | 1 | 48755 | 7 | 3.983 | 12240.8 |
1042 | 2025-06-20 20:52:03 | subset | 1 | 48755 | 7 | 4.436 | 10990.8 |
1041 | 2025-06-18 11:58:32 | subset | 1 | 48755 | 7 | 1.813 | 26891.9 |
1040 | 2025-06-13 21:06:16 | subset | 2 | 82551 | 38 | 13.703 | 6024.3 |
1039 | 2025-06-13 01:13:45 | subset | 1 | 48755 | 7 | 4.436 | 10990.8 |
1038 | 2025-06-08 13:56:27 | subset | 1 | 48755 | 7 | 5.140 | 9485.4 |
1037 | 2025-06-04 11:06:42 | subset | 1 | 48755 | 7 | 1.860 | 26212.4 |
1036 | 2025-05-30 05:16:12 | subset | 1 | 48755 | 7 | 0.890 | 54780.9 |
1035 | 2025-05-26 08:43:44 | subset | 1 | 48755 | 7 | 2.093 | 23294.3 |
1034 | 2025-05-26 00:19:20 | subset | 3 | 112716 | 519 | 30.286 | 3721.7 |
1033 | 2025-05-24 16:10:35 | subset | 3 | 112716 | 519 | 28.830 | 3909.7 |
1032 | 2025-05-24 02:09:10 | subset | 3 | 112716 | 519 | 28.176 | 4000.4 |
1031 | 2025-05-23 15:48:54 | subset | 3 | 112716 | 519 | 23.360 | 4825.2 |
1030 | 2025-05-22 21:16:57 | subset | 3 | 112716 | 519 | 5.453 | 20670.5 |
1029 | 2025-05-18 14:11:39 | subset | 1 | 48755 | 7 | 4.060 | 12008.6 |
1028 | 2025-05-12 02:12:14 | subset | 1 | 48755 | 7 | 4.046 | 12050.2 |
1027 | 2025-05-06 14:11:23 | subset | 1 | 48755 | 7 | 3.983 | 12240.8 |
1026 | 2025-05-01 23:39:39 | subset | 2 | 82551 | 38 | 16.533 | 4993.1 |
1025 | 2025-05-01 11:12:28 | subset | 1 | 48755 | 7 | 2.063 | 23633.1 |