History of Dictionary Searches using Damerau-Levenshtein distance in T-SQL
Fuzzy-string Searches
(up to 100 most recent)
for
"thorniness"
Num | Started At (CA time) | Searched Word | Change Limit | Words Checked | Words Matched | Seconds | Words Per Sec |
301 | 2024-05-25 23:38:58 | thorniness | 2 | 108824 | 8 | 8.030 | 13552.2 |
300 | 2024-05-25 23:38:52 | thorniness | 3 | 140603 | 61 | 11.626 | 12093.8 |
299 | 2024-05-25 23:37:39 | thorniness | 1 | 67641 | 2 | 3.406 | 19859.4 |
298 | 2024-05-19 19:38:30 | thorniness | 4 | 161450 | 406 | 48.093 | 3357.0 |
297 | 2024-05-18 21:12:31 | thorniness | 4 | 161450 | 406 | 38.486 | 4195.0 |
296 | 2024-05-18 00:48:30 | thorniness | 3 | 140603 | 61 | 16.033 | 8769.6 |
295 | 2024-05-17 00:56:45 | thorniness | 3 | 140603 | 61 | 14.203 | 9899.5 |
294 | 2024-05-17 00:56:44 | thorniness | 2 | 108824 | 8 | 11.376 | 9566.1 |
293 | 2024-05-16 04:52:53 | thorniness | 4 | 161450 | 406 | 28.423 | 5680.3 |
292 | 2024-05-16 04:52:49 | thorniness | 3 | 140603 | 61 | 19.233 | 7310.5 |
291 | 2024-05-16 04:52:53 | thorniness | 2 | 108824 | 8 | 3.593 | 30287.8 |
290 | 2024-05-16 04:30:13 | thorniness | 1 | 67641 | 2 | 1.203 | 56226.9 |
289 | 2024-05-09 14:35:53 | thorniness | 1 | 67641 | 2 | 1.186 | 57032.9 |
288 | 2024-05-06 00:56:36 | thorniness | 1 | 67641 | 2 | 5.030 | 13447.5 |
287 | 2024-05-02 02:30:22 | thorniness | 1 | 67641 | 2 | 1.580 | 42810.8 |
286 | 2024-04-25 23:17:26 | thorniness | 1 | 67641 | 2 | 1.280 | 52844.5 |
285 | 2024-04-18 12:43:12 | thorniness | 4 | 161450 | 406 | 15.940 | 10128.6 |
284 | 2024-04-18 04:52:44 | thorniness | 4 | 161450 | 406 | 15.813 | 10210.0 |
283 | 2024-04-16 06:19:42 | thorniness | 1 | 67641 | 2 | 1.280 | 52844.5 |
282 | 2024-04-16 05:29:54 | thorniness | 4 | 161450 | 406 | 17.690 | 9126.6 |
281 | 2024-04-16 02:34:22 | thorniness | 4 | 161450 | 406 | 41.253 | 3913.7 |
280 | 2024-04-16 02:34:26 | thorniness | 2 | 108824 | 8 | 11.563 | 9411.4 |
279 | 2024-04-16 02:34:25 | thorniness | 3 | 140603 | 61 | 7.763 | 18111.9 |
278 | 2024-04-16 01:05:48 | thorniness | 1 | 67641 | 2 | 0.983 | 68810.8 |
277 | 2024-04-11 08:15:07 | thorniness | 1 | 67641 | 2 | 1.206 | 56087.1 |
276 | 2024-04-09 09:06:41 | thorniness | 2 | 108824 | 8 | 2.903 | 37486.7 |
275 | 2024-03-28 14:51:31 | thorniness | 1 | 67641 | 2 | 1.143 | 59178.5 |
274 | 2024-03-14 13:19:15 | thorniness | 1 | 67641 | 2 | 0.983 | 68810.8 |
273 | 2024-03-11 22:14:25 | thorniness | 1 | 67641 | 2 | 1.186 | 57032.9 |
272 | 2024-03-10 22:55:41 | thorniness | 1 | 67641 | 2 | 1.236 | 54725.7 |
271 | 2024-03-07 14:20:19 | thorniness | 1 | 67641 | 2 | 1.030 | 65670.9 |
270 | 2024-02-27 05:34:48 | thorniness | 1 | 67641 | 2 | 1.190 | 56841.2 |
269 | 2024-02-06 00:20:10 | thorniness | 1 | 67641 | 2 | 1.423 | 47534.1 |
268 | 2024-02-05 00:13:35 | thorniness | 1 | 67641 | 2 | 2.376 | 28468.4 |
267 | 2024-02-02 02:34:39 | thorniness | 1 | 67641 | 2 | 0.983 | 68810.8 |
266 | 2024-01-27 09:18:39 | thorniness | 1 | 67641 | 2 | 1.203 | 56226.9 |
265 | 2024-01-27 09:18:35 | thorniness | 1 | 67641 | 2 | 1.093 | 61885.6 |
264 | 2024-01-21 23:41:56 | thorniness | 1 | 67641 | 2 | 1.216 | 55625.8 |
263 | 2024-01-05 13:31:38 | thorniness | 1 | 67641 | 2 | 1.000 | 67641.0 |
262 | 2023-12-19 13:34:41 | thorniness | 1 | 67641 | 2 | 1.000 | 67641.0 |
261 | 2023-12-10 02:57:39 | thorniness | 2 | 108824 | 8 | 3.046 | 35726.9 |
260 | 2023-10-29 10:14:57 | thorniness | 1 | 67641 | 2 | 1.140 | 59334.2 |
259 | 2023-09-18 20:22:20 | thorniness | 1 | 67641 | 2 | 0.986 | 68601.4 |
258 | 2023-09-17 21:38:28 | thorniness | 1 | 67641 | 2 | 1.076 | 62863.4 |
257 | 2023-09-07 20:54:19 | thorniness | 2 | 108824 | 8 | 2.563 | 42459.6 |
256 | 2023-08-22 15:39:20 | thorniness | 1 | 67641 | 2 | 1.063 | 63632.2 |
255 | 2023-07-14 06:07:21 | thorniness | 1 | 67641 | 2 | 1.093 | 61885.6 |
254 | 2023-05-28 03:31:23 | thorniness | 2 | 108824 | 8 | 2.593 | 41968.4 |
253 | 2023-05-23 13:20:29 | thorniness | 1 | 67641 | 2 | 0.966 | 70021.7 |
252 | 2023-03-22 23:47:29 | thorniness | 1 | 67641 | 2 | 1.060 | 63812.3 |
251 | 2023-03-20 19:55:57 | thorniness | 1 | 67641 | 2 | 1.080 | 62630.6 |
250 | 2023-03-19 18:22:49 | thorniness | 1 | 67641 | 2 | 0.970 | 69733.0 |
249 | 2023-03-08 15:28:21 | thorniness | 2 | 108824 | 8 | 2.906 | 37448.0 |
248 | 2023-01-07 12:37:19 | thorniness | 1 | 67641 | 2 | 0.966 | 70021.7 |
247 | 2022-12-14 04:59:53 | thorniness | 2 | 108824 | 8 | 2.876 | 37838.7 |
246 | 2022-10-31 08:34:00 | thorniness | 1 | 67641 | 2 | 1.313 | 51516.4 |
245 | 2022-10-08 12:16:47 | thorniness | 1 | 67641 | 2 | 1.080 | 62630.6 |
244 | 2022-07-30 12:34:13 | thorniness | 2 | 108824 | 8 | 2.580 | 42179.8 |
243 | 2022-06-01 07:34:48 | thorniness | 1 | 67641 | 2 | 1.030 | 65670.9 |
242 | 2022-05-24 13:46:23 | thorniness | 1 | 67641 | 2 | 1.063 | 63632.2 |
241 | 2022-02-08 00:41:59 | thorniness | 1 | 67641 | 2 | 1.093 | 61885.6 |
240 | 2022-01-07 17:42:21 | thorniness | 1 | 67641 | 2 | 1.233 | 54858.9 |
239 | 2021-12-16 11:08:04 | thorniness | 1 | 67641 | 2 | 1.096 | 61716.2 |
238 | 2021-09-05 21:37:46 | thorniness | 1 | 67641 | 2 | 1.000 | 67641.0 |
237 | 2021-05-19 13:26:47 | thorniness | 1 | 67641 | 2 | 1.123 | 60232.4 |
236 | 2021-03-23 00:28:06 | thorniness | 1 | 67641 | 2 | 1.013 | 66773.0 |
235 | 2021-02-03 10:25:08 | thorniness | 1 | 67641 | 2 | 0.983 | 68810.8 |
234 | 2021-01-24 12:55:51 | thorniness | 1 | 67641 | 2 | 1.093 | 61885.6 |
233 | 2021-01-04 22:47:44 | thorniness | 1 | 67641 | 2 | 0.983 | 68810.8 |
232 | 2020-11-06 17:15:07 | thorniness | 1 | 67641 | 2 | 1.220 | 55443.4 |
231 | 2020-11-06 02:49:39 | thorniness | 1 | 67641 | 2 | 1.110 | 60937.8 |
230 | 2020-10-26 15:12:47 | thorniness | 1 | 67641 | 2 | 1.000 | 67641.0 |
229 | 2020-10-17 19:22:23 | thorniness | 1 | 67641 | 2 | 0.966 | 70021.7 |
228 | 2020-08-27 00:36:32 | thorniness | 1 | 67641 | 2 | 1.016 | 66575.8 |
227 | 2020-06-19 02:07:15 | thorniness | 1 | 67641 | 2 | 1.093 | 61885.6 |
226 | 2020-03-29 22:34:34 | thorniness | 1 | 67641 | 2 | 2.530 | 26735.6 |
225 | 2020-03-26 07:58:41 | thorniness | 1 | 67641 | 2 | 2.313 | 29243.8 |
224 | 2020-03-14 04:02:37 | thorniness | 1 | 67641 | 2 | 0.983 | 68810.8 |
223 | 2020-02-28 10:19:48 | thorniness | 1 | 67641 | 2 | 2.296 | 29460.4 |
222 | 2020-02-25 08:02:17 | thorniness | 1 | 67641 | 2 | 2.483 | 27241.6 |
221 | 2020-02-08 17:27:33 | thorniness | 1 | 67641 | 2 | 3.750 | 18037.6 |
220 | 2020-02-06 12:07:13 | thorniness | 1 | 67641 | 2 | 2.220 | 30468.9 |
219 | 2020-02-01 12:03:52 | thorniness | 1 | 67641 | 2 | 3.580 | 18894.1 |
218 | 2020-01-31 10:45:58 | thorniness | 1 | 67641 | 2 | 2.406 | 28113.5 |
217 | 2020-01-29 08:46:25 | thorniness | 1 | 67641 | 2 | 1.203 | 56226.9 |
216 | 2020-01-20 10:47:17 | thorniness | 1 | 67641 | 2 | 1.050 | 64420.0 |
215 | 2020-01-15 19:41:22 | thorniness | 1 | 67641 | 2 | 1.190 | 56841.2 |
214 | 2020-01-08 21:35:55 | thorniness | 1 | 67641 | 2 | 2.546 | 26567.6 |
213 | 2020-01-02 07:13:44 | thorniness | 1 | 67641 | 2 | 1.203 | 56226.9 |
212 | 2019-12-02 14:50:04 | thorniness | 1 | 67641 | 2 | 0.986 | 68601.4 |
211 | 2019-10-07 11:26:32 | thorniness | 1 | 67641 | 2 | 0.983 | 68810.8 |
210 | 2019-10-05 17:47:23 | thorniness | 1 | 67641 | 2 | 0.926 | 73046.4 |
209 | 2019-10-03 17:36:43 | thorniness | 1 | 67641 | 2 | 0.920 | 73522.8 |
208 | 2019-10-01 09:41:47 | thorniness | 1 | 67641 | 2 | 0.883 | 76603.6 |
207 | 2019-09-27 14:53:47 | thorniness | 1 | 67641 | 2 | 0.906 | 74658.9 |
206 | 2019-09-24 06:12:10 | thorniness | 1 | 67641 | 2 | 1.086 | 62284.5 |
205 | 2019-09-21 15:38:31 | thorniness | 1 | 67641 | 2 | 1.026 | 65926.9 |
204 | 2019-09-15 12:14:22 | thorniness | 1 | 67641 | 2 | 0.890 | 76001.1 |
203 | 2019-09-03 08:22:59 | thorniness | 1 | 67641 | 2 | 1.143 | 59178.5 |
202 | 2019-08-31 17:18:23 | thorniness | 1 | 67641 | 2 | 0.930 | 72732.3 |