History of Dictionary Searches using Damerau-Levenshtein distance in T-SQL
Fuzzy-string Searches
(up to 100 most recent)
for
"looseness"
Num | Started At (CA time) | Searched Word | Change Limit | Words Checked | Words Matched | Seconds | Words Per Sec |
282 | 2024-04-11 00:24:11 | looseness | 1 | 81242 | 2 | 1.423 | 57092.1 |
281 | 2024-04-08 11:28:09 | looseness | 3 | 148641 | 108 | 17.796 | 8352.5 |
280 | 2024-04-08 11:28:11 | looseness | 2 | 121436 | 14 | 5.346 | 22715.3 |
279 | 2024-04-08 10:57:24 | looseness | 1 | 81242 | 2 | 2.700 | 30089.6 |
278 | 2024-03-28 15:03:21 | looseness | 1 | 81242 | 2 | 1.313 | 61875.1 |
277 | 2024-03-06 03:02:08 | looseness | 1 | 81242 | 2 | 2.966 | 27391.1 |
276 | 2024-03-05 17:19:15 | looseness | 1 | 81242 | 2 | 1.516 | 53589.7 |
275 | 2024-02-27 11:09:39 | looseness | 1 | 81242 | 2 | 1.406 | 57782.4 |
274 | 2024-02-05 08:34:48 | looseness | 2 | 121436 | 14 | 3.720 | 32644.1 |
273 | 2024-02-02 05:30:15 | looseness | 1 | 81242 | 2 | 1.343 | 60492.9 |
272 | 2024-01-26 22:39:57 | looseness | 1 | 81242 | 2 | 2.843 | 28576.2 |
271 | 2024-01-09 22:58:25 | looseness | 1 | 81242 | 2 | 1.233 | 65889.7 |
270 | 2024-01-08 01:55:35 | looseness | 3 | 148641 | 108 | 6.093 | 24395.4 |
269 | 2023-12-16 15:03:22 | looseness | 3 | 148641 | 108 | 6.720 | 22119.2 |
268 | 2023-12-16 15:03:21 | looseness | 2 | 121436 | 14 | 3.516 | 34538.1 |
267 | 2023-12-03 23:50:19 | looseness | 3 | 148641 | 108 | 6.860 | 21667.8 |
266 | 2023-12-03 23:50:21 | looseness | 2 | 121436 | 14 | 3.576 | 33958.6 |
265 | 2023-11-16 02:02:00 | looseness | 2 | 121436 | 14 | 8.236 | 14744.5 |
264 | 2023-11-16 02:01:56 | looseness | 3 | 148641 | 108 | 8.733 | 17020.6 |
263 | 2023-11-15 03:37:36 | looseness | 1 | 81242 | 2 | 1.373 | 59171.2 |
262 | 2023-11-12 11:46:37 | looseness | 1 | 81242 | 2 | 1.186 | 68500.8 |
261 | 2023-11-11 19:50:39 | looseness | 1 | 81242 | 2 | 1.390 | 58447.5 |
260 | 2023-11-11 06:39:39 | looseness | 2 | 121436 | 14 | 2.986 | 40668.5 |
259 | 2023-11-10 09:20:17 | looseness | 1 | 81242 | 2 | 1.216 | 66810.9 |
258 | 2023-11-02 09:07:45 | looseness | 1 | 81242 | 2 | 1.390 | 58447.5 |
257 | 2023-10-26 22:01:32 | looseness | 1 | 81242 | 2 | 1.283 | 63321.9 |
256 | 2023-10-20 14:49:25 | looseness | 1 | 81242 | 2 | 1.360 | 59736.8 |
255 | 2023-10-17 10:50:39 | looseness | 1 | 81242 | 2 | 1.376 | 59042.2 |
254 | 2023-10-17 10:39:27 | looseness | 3 | 148641 | 108 | 19.580 | 7591.5 |
253 | 2023-10-14 14:53:11 | looseness | 3 | 148641 | 108 | 6.310 | 23556.4 |
252 | 2023-10-11 17:51:43 | looseness | 1 | 81242 | 2 | 1.390 | 58447.5 |
251 | 2023-10-04 03:11:45 | looseness | 1 | 81242 | 2 | 1.220 | 66591.8 |
250 | 2023-09-22 23:15:42 | looseness | 1 | 81242 | 2 | 1.203 | 67532.8 |
249 | 2023-09-10 21:26:20 | looseness | 1 | 81242 | 2 | 1.233 | 65889.7 |
248 | 2023-08-26 05:59:57 | looseness | 1 | 81242 | 2 | 1.250 | 64993.6 |
247 | 2023-08-13 20:19:28 | looseness | 2 | 121436 | 14 | 5.126 | 23690.2 |
246 | 2023-07-26 00:07:38 | looseness | 3 | 148641 | 108 | 6.813 | 21817.3 |
245 | 2023-07-21 03:00:08 | looseness | 1 | 81242 | 2 | 1.390 | 58447.5 |
244 | 2023-05-28 03:36:43 | looseness | 1 | 81242 | 2 | 1.220 | 66591.8 |
243 | 2023-04-25 05:56:47 | looseness | 2 | 121436 | 14 | 3.016 | 40263.9 |
242 | 2023-04-12 06:09:15 | looseness | 3 | 148641 | 108 | 7.110 | 20905.9 |
241 | 2023-04-02 02:41:45 | looseness | 1 | 81242 | 2 | 1.190 | 68270.6 |
240 | 2023-03-24 16:27:06 | looseness | 1 | 81242 | 2 | 1.220 | 66591.8 |
239 | 2023-01-27 20:54:01 | looseness | 2 | 121436 | 14 | 3.076 | 39478.5 |
238 | 2023-01-18 22:19:49 | looseness | 3 | 148641 | 108 | 5.860 | 25365.4 |
237 | 2023-01-08 21:45:55 | looseness | 1 | 81242 | 2 | 1.186 | 68500.8 |
236 | 2022-12-17 04:11:19 | looseness | 1 | 81242 | 2 | 1.390 | 58447.5 |
235 | 2022-11-09 23:26:05 | looseness | 2 | 121436 | 14 | 2.983 | 40709.4 |
234 | 2022-10-29 06:36:26 | looseness | 3 | 148641 | 108 | 6.233 | 23847.4 |
233 | 2022-10-14 07:48:49 | looseness | 1 | 81242 | 2 | 1.220 | 66591.8 |
232 | 2022-08-13 19:49:11 | looseness | 1 | 81242 | 2 | 1.233 | 65889.7 |
231 | 2022-07-15 18:57:44 | looseness | 3 | 148641 | 108 | 5.906 | 25167.8 |
230 | 2022-06-12 13:33:01 | looseness | 2 | 121436 | 14 | 3.046 | 39867.4 |
229 | 2022-06-04 23:49:08 | looseness | 1 | 81242 | 2 | 1.203 | 67532.8 |
228 | 2022-06-02 17:54:30 | looseness | 1 | 81242 | 2 | 1.216 | 66810.9 |
227 | 2022-05-14 14:07:45 | looseness | 3 | 148641 | 108 | 6.016 | 24707.6 |
226 | 2022-04-09 11:09:16 | looseness | 1 | 81242 | 2 | 1.373 | 59171.2 |
225 | 2022-02-10 12:13:03 | looseness | 1 | 81242 | 2 | 1.360 | 59736.8 |
224 | 2021-12-28 11:20:02 | looseness | 1 | 81242 | 2 | 2.686 | 30246.5 |
223 | 2021-12-02 03:04:12 | looseness | 1 | 81242 | 2 | 1.470 | 55266.7 |
222 | 2021-11-30 01:17:20 | looseness | 1 | 81242 | 2 | 1.266 | 64172.2 |
221 | 2021-10-27 23:16:21 | looseness | 1 | 81242 | 2 | 1.203 | 67532.8 |
220 | 2021-09-18 03:18:09 | looseness | 1 | 81242 | 2 | 1.203 | 67532.8 |
219 | 2021-07-25 17:21:10 | looseness | 1 | 81242 | 2 | 1.203 | 67532.8 |
218 | 2021-06-18 07:08:42 | looseness | 1 | 81242 | 2 | 1.280 | 63470.3 |
217 | 2021-05-30 23:44:27 | looseness | 1 | 81242 | 2 | 1.360 | 59736.8 |
216 | 2021-05-16 02:30:07 | looseness | 1 | 81242 | 2 | 1.420 | 57212.7 |
215 | 2021-04-15 15:40:20 | looseness | 1 | 81242 | 2 | 1.423 | 57092.1 |
214 | 2021-03-19 02:08:14 | looseness | 1 | 81242 | 2 | 1.220 | 66591.8 |
213 | 2021-02-21 18:03:00 | looseness | 1 | 81242 | 2 | 1.216 | 66810.9 |
212 | 2021-01-28 17:10:33 | looseness | 1 | 81242 | 2 | 1.343 | 60492.9 |
211 | 2020-12-31 02:24:50 | looseness | 1 | 81242 | 2 | 1.236 | 65729.8 |
210 | 2020-12-16 05:01:15 | looseness | 1 | 81242 | 2 | 1.233 | 65889.7 |
209 | 2020-12-04 02:05:15 | looseness | 1 | 81242 | 2 | 1.376 | 59042.2 |
208 | 2020-11-02 07:29:13 | looseness | 1 | 81242 | 2 | 1.436 | 56575.2 |
207 | 2020-09-15 19:12:37 | looseness | 1 | 81242 | 2 | 1.203 | 67532.8 |
206 | 2020-09-04 11:34:50 | looseness | 1 | 81242 | 2 | 1.250 | 64993.6 |
205 | 2020-08-29 14:45:39 | looseness | 1 | 81242 | 2 | 1.360 | 59736.8 |
204 | 2020-08-19 09:12:30 | looseness | 1 | 81242 | 2 | 1.280 | 63470.3 |
203 | 2020-06-06 11:33:44 | looseness | 1 | 81242 | 2 | 1.406 | 57782.4 |
202 | 2020-03-29 23:32:04 | looseness | 1 | 81242 | 2 | 1.233 | 65889.7 |
201 | 2020-03-28 14:16:17 | looseness | 1 | 81242 | 2 | 1.390 | 58447.5 |
200 | 2020-03-28 00:47:36 | looseness | 1 | 81242 | 2 | 1.690 | 48072.2 |
199 | 2020-03-21 11:39:01 | looseness | 1 | 81242 | 2 | 1.236 | 65729.8 |
198 | 2020-03-04 23:05:10 | looseness | 1 | 81242 | 2 | 1.373 | 59171.2 |
197 | 2020-02-28 09:45:29 | looseness | 1 | 81242 | 2 | 3.000 | 27080.7 |
196 | 2020-02-19 05:36:12 | looseness | 1 | 81242 | 2 | 1.516 | 53589.7 |
195 | 2020-02-18 18:10:51 | looseness | 1 | 81242 | 2 | 1.533 | 52995.4 |
194 | 2020-02-08 18:49:10 | looseness | 1 | 81242 | 2 | 1.500 | 54161.3 |
193 | 2020-02-03 02:14:36 | looseness | 1 | 81242 | 2 | 3.406 | 23852.6 |
192 | 2020-02-02 21:16:49 | looseness | 1 | 81242 | 2 | 1.483 | 54782.2 |
191 | 2020-02-02 19:55:09 | looseness | 1 | 81242 | 2 | 1.406 | 57782.4 |
190 | 2020-01-23 16:34:35 | looseness | 1 | 81242 | 2 | 3.203 | 25364.3 |
189 | 2020-01-21 11:39:03 | looseness | 1 | 81242 | 2 | 1.516 | 53589.7 |
188 | 2020-01-17 06:55:21 | looseness | 1 | 81242 | 2 | 1.466 | 55417.5 |
187 | 2020-01-12 02:54:56 | looseness | 1 | 81242 | 2 | 1.530 | 53099.3 |
186 | 2020-01-03 02:21:39 | looseness | 1 | 81242 | 2 | 1.343 | 60492.9 |
185 | 2019-12-31 05:52:16 | looseness | 1 | 81242 | 2 | 1.423 | 57092.1 |
184 | 2019-12-26 06:35:45 | looseness | 1 | 81242 | 2 | 1.470 | 55266.7 |
183 | 2019-12-25 22:43:50 | looseness | 1 | 81242 | 2 | 1.390 | 58447.5 |