History of Dictionary Searches using Damerau-Levenshtein distance in T-SQL
Fuzzy-string Searches
(up to 100 most recent)
for
"fit"
| Num | Started At (CA time) | Searched Word | Change Limit | Words Checked | Words Matched | Seconds | Words Per Sec |
| 2157 | 2026-02-13 06:56:08 | fit | 2 | 14084 | 472 | 0.703 | 20034.1 |
| 2156 | 2026-02-13 05:08:37 | fit | 2 | 14084 | 472 | 2.033 | 6927.7 |
| 2155 | 2026-02-13 05:06:40 | fit | 2 | 14084 | 472 | 1.656 | 8504.8 |
| 2154 | 2026-02-13 05:06:11 | fit | 2 | 14084 | 472 | 2.873 | 4902.2 |
| 2153 | 2026-02-12 13:05:34 | fit | 1 | 5146 | 32 | 0.093 | 55333.3 |
| 2152 | 2026-02-11 23:09:33 | fit | 1 | 5146 | 32 | 0.296 | 17385.1 |
| 2151 | 2026-02-11 23:09:23 | fit | 1 | 5146 | 32 | 0.596 | 8634.2 |
| 2150 | 2026-02-11 05:10:43 | fit | 2 | 14084 | 472 | 0.403 | 34947.9 |
| 2149 | 2026-02-10 22:59:03 | fit | 1 | 5146 | 32 | 0.376 | 13686.2 |
| 2148 | 2026-02-10 12:13:09 | fit | 1 | 5146 | 32 | 0.093 | 55333.3 |
| 2147 | 2026-02-06 22:39:56 | fit | 1 | 5146 | 32 | 0.076 | 67710.5 |
| 2146 | 2026-02-05 03:07:53 | fit | 1 | 5146 | 32 | 0.093 | 55333.3 |
| 2145 | 2026-02-03 20:57:08 | fit | 1 | 5146 | 32 | 0.076 | 67710.5 |
| 2144 | 2026-02-03 12:35:05 | fit | 2 | 14084 | 472 | 0.783 | 17987.2 |
| 2143 | 2026-02-02 12:23:12 | fit | 1 | 5146 | 32 | 0.080 | 64325.0 |
| 2142 | 2026-02-02 05:16:13 | fit | 1 | 5146 | 32 | 0.093 | 55333.3 |
| 2141 | 2026-02-01 03:49:15 | fit | 2 | 14084 | 472 | 0.423 | 33295.5 |
| 2140 | 2026-01-29 09:10:11 | fit | 1 | 5146 | 32 | 0.110 | 46781.8 |
| 2139 | 2026-01-27 18:46:52 | fit | 1 | 5146 | 32 | 0.076 | 67710.5 |
| 2138 | 2026-01-26 07:03:17 | fit | 1 | 5146 | 32 | 0.080 | 64325.0 |
| 2137 | 2026-01-26 06:54:43 | fit | 1 | 5146 | 32 | 0.170 | 30270.6 |
| 2136 | 2026-01-26 02:31:16 | fit | 1 | 5146 | 32 | 0.093 | 55333.3 |
| 2135 | 2026-01-18 16:18:35 | fit | 1 | 5146 | 32 | 0.090 | 57177.8 |
| 2134 | 2026-01-18 13:05:45 | fit | 1 | 5146 | 32 | 0.110 | 46781.8 |
| 2133 | 2026-01-17 04:03:13 | fit | 1 | 5146 | 32 | 0.093 | 55333.3 |
| 2132 | 2026-01-17 02:39:26 | fit | 1 | 5146 | 32 | 0.110 | 46781.8 |
| 2131 | 2026-01-17 02:37:33 | fit | 1 | 5146 | 32 | 0.093 | 55333.3 |
| 2130 | 2026-01-16 06:26:58 | fit | 1 | 5146 | 32 | 0.076 | 67710.5 |
| 2129 | 2026-01-16 00:34:44 | fit | 2 | 14084 | 472 | 2.220 | 6344.1 |
| 2128 | 2026-01-16 00:34:34 | fit | 2 | 14084 | 472 | 1.673 | 8418.4 |
| 2127 | 2026-01-13 00:26:31 | fit | 1 | 5146 | 32 | 0.076 | 67710.5 |
| 2126 | 2026-01-12 01:09:28 | fit | 1 | 5146 | 32 | 0.080 | 64325.0 |
| 2125 | 2026-01-11 19:41:52 | fit | 1 | 5146 | 32 | 0.373 | 13796.2 |
| 2124 | 2026-01-09 08:46:27 | fit | 1 | 5146 | 32 | 0.110 | 46781.8 |
| 2123 | 2026-01-08 04:31:15 | fit | 1 | 5146 | 32 | 0.390 | 13194.9 |
| 2122 | 2026-01-08 00:45:38 | fit | 1 | 5146 | 32 | 0.093 | 55333.3 |
| 2121 | 2026-01-05 11:20:28 | fit | 1 | 5146 | 32 | 0.080 | 64325.0 |
| 2120 | 2026-01-03 16:21:17 | fit | 1 | 5146 | 32 | 0.140 | 36757.1 |
| 2119 | 2026-01-03 16:20:23 | fit | 1 | 5146 | 32 | 0.093 | 55333.3 |
| 2118 | 2025-12-31 21:42:53 | fit | 1 | 5146 | 32 | 0.080 | 64325.0 |
| 2117 | 2025-12-28 00:39:52 | fit | 1 | 5146 | 32 | 0.076 | 67710.5 |
| 2116 | 2025-12-27 20:07:07 | fit | 1 | 5146 | 32 | 0.080 | 64325.0 |
| 2115 | 2025-12-26 05:57:41 | fit | 1 | 5146 | 32 | 0.310 | 16600.0 |
| 2114 | 2025-12-25 09:54:44 | fit | 1 | 5146 | 32 | 0.093 | 55333.3 |
| 2113 | 2025-12-24 20:12:44 | fit | 1 | 5146 | 32 | 0.173 | 29745.7 |
| 2112 | 2025-12-24 17:25:59 | fit | 1 | 5146 | 32 | 0.203 | 25349.8 |
| 2111 | 2025-12-22 01:30:27 | fit | 2 | 14084 | 472 | 1.063 | 13249.3 |
| 2110 | 2025-12-17 12:09:00 | fit | 1 | 5146 | 32 | 0.170 | 30270.6 |
| 2109 | 2025-12-16 02:39:52 | fit | 1 | 5146 | 32 | 0.500 | 10292.0 |
| 2108 | 2025-12-11 01:17:16 | fit | 1 | 5146 | 32 | 0.110 | 46781.8 |
| 2107 | 2025-12-10 18:19:14 | fit | 1 | 5146 | 32 | 0.093 | 55333.3 |
| 2106 | 2025-12-10 18:18:14 | fit | 1 | 5146 | 32 | 0.093 | 55333.3 |
| 2105 | 2025-12-09 23:51:04 | fit | 1 | 5146 | 32 | 0.080 | 64325.0 |
| 2104 | 2025-12-08 23:00:22 | fit | 1 | 5146 | 32 | 0.170 | 30270.6 |
| 2103 | 2025-12-05 00:59:09 | fit | 1 | 5146 | 32 | 0.203 | 25349.8 |
| 2102 | 2025-11-28 15:18:54 | fit | 2 | 14084 | 472 | 0.810 | 17387.7 |
| 2101 | 2025-11-23 05:37:43 | fit | 1 | 5146 | 32 | 0.093 | 55333.3 |
| 2100 | 2025-11-21 01:37:06 | fit | 2 | 14084 | 472 | 0.343 | 41061.2 |
| 2099 | 2025-11-17 00:25:10 | fit | 2 | 14084 | 472 | 0.783 | 17987.2 |
| 2098 | 2025-11-16 07:33:24 | fit | 1 | 5146 | 32 | 0.093 | 55333.3 |
| 2097 | 2025-11-16 06:48:16 | fit | 2 | 14084 | 472 | 0.343 | 41061.2 |
| 2096 | 2025-11-15 17:05:37 | fit | 2 | 14084 | 472 | 0.343 | 41061.2 |
| 2095 | 2025-11-13 15:06:32 | fit | 1 | 5146 | 32 | 0.076 | 67710.5 |
| 2094 | 2025-11-12 18:45:42 | fit | 1 | 5146 | 32 | 0.080 | 64325.0 |
| 2093 | 2025-11-12 16:05:05 | fit | 2 | 14084 | 472 | 0.343 | 41061.2 |
| 2092 | 2025-11-10 02:19:59 | fit | 1 | 5146 | 32 | 0.080 | 64325.0 |
| 2091 | 2025-11-09 08:58:00 | fit | 1 | 5146 | 32 | 0.080 | 64325.0 |
| 2090 | 2025-11-09 07:55:07 | fit | 1 | 5146 | 32 | 0.093 | 55333.3 |
| 2089 | 2025-10-29 16:54:07 | fit | 1 | 5146 | 32 | 0.093 | 55333.3 |
| 2088 | 2025-10-24 09:33:57 | fit | 1 | 5146 | 32 | 0.093 | 55333.3 |
| 2087 | 2025-10-22 15:42:29 | fit | 1 | 5146 | 32 | 0.093 | 55333.3 |
| 2086 | 2025-10-19 12:49:26 | fit | 1 | 5146 | 32 | 0.560 | 9189.3 |
| 2085 | 2025-10-19 12:49:24 | fit | 1 | 5146 | 32 | 0.186 | 27666.7 |
| 2084 | 2025-10-19 12:49:19 | fit | 1 | 5146 | 32 | 0.093 | 55333.3 |
| 2083 | 2025-10-15 23:55:34 | fit | 1 | 5146 | 32 | 0.093 | 55333.3 |
| 2082 | 2025-10-13 21:54:53 | fit | 1 | 5146 | 32 | 0.096 | 53604.2 |
| 2081 | 2025-10-11 08:59:11 | fit | 1 | 5146 | 32 | 0.873 | 5894.6 |
| 2080 | 2025-10-11 08:58:21 | fit | 1 | 5146 | 32 | 0.453 | 11359.8 |
| 2079 | 2025-10-11 08:57:42 | fit | 1 | 5146 | 32 | 0.096 | 53604.2 |
| 2078 | 2025-10-08 06:17:39 | fit | 1 | 5146 | 32 | 0.093 | 55333.3 |
| 2077 | 2025-10-08 00:29:49 | fit | 1 | 5146 | 32 | 0.076 | 67710.5 |
| 2076 | 2025-10-06 03:03:12 | fit | 1 | 5146 | 32 | 0.093 | 55333.3 |
| 2075 | 2025-10-06 00:06:42 | fit | 1 | 5146 | 32 | 0.093 | 55333.3 |
| 2074 | 2025-10-05 11:16:00 | fit | 1 | 5146 | 32 | 0.080 | 64325.0 |
| 2073 | 2025-10-04 21:39:10 | fit | 1 | 5146 | 32 | 0.093 | 55333.3 |
| 2072 | 2025-10-02 10:19:19 | fit | 1 | 5146 | 32 | 0.096 | 53604.2 |
| 2071 | 2025-10-02 10:19:14 | fit | 1 | 5146 | 32 | 0.093 | 55333.3 |
| 2070 | 2025-09-25 00:16:02 | fit | 1 | 5146 | 32 | 0.093 | 55333.3 |
| 2069 | 2025-09-24 18:51:57 | fit | 2 | 14084 | 472 | 0.390 | 36112.8 |
| 2068 | 2025-09-22 19:03:22 | fit | 1 | 5146 | 32 | 0.076 | 67710.5 |
| 2067 | 2025-09-21 19:58:15 | fit | 1 | 5146 | 32 | 0.093 | 55333.3 |
| 2066 | 2025-09-20 16:30:03 | fit | 1 | 5146 | 32 | 0.093 | 55333.3 |
| 2065 | 2025-09-19 18:38:51 | fit | 1 | 5146 | 32 | 0.093 | 55333.3 |
| 2064 | 2025-09-15 12:10:00 | fit | 1 | 5146 | 32 | 0.093 | 55333.3 |
| 2063 | 2025-09-08 13:38:55 | fit | 2 | 14084 | 472 | 0.360 | 39122.2 |
| 2062 | 2025-09-07 13:46:03 | fit | 2 | 14084 | 472 | 0.703 | 20034.1 |
| 2061 | 2025-09-06 19:46:17 | fit | 1 | 5146 | 32 | 0.093 | 55333.3 |
| 2060 | 2025-09-06 06:47:18 | fit | 2 | 14084 | 472 | 0.356 | 39561.8 |
| 2059 | 2025-09-05 22:46:01 | fit | 2 | 14084 | 472 | 0.406 | 34689.7 |
| 2058 | 2025-09-05 00:53:23 | fit | 2 | 14084 | 472 | 0.376 | 37457.4 |