History of Dictionary Searches using Damerau-Levenshtein distance in T-SQL
Fuzzy-string Searches
(up to 100 most recent)
for
"sharpness"
Num | Started At (CA time) | Searched Word | Change Limit | Words Checked | Words Matched | Seconds | Words Per Sec |
311 | 2025-08-05 13:12:11 | sharpness | 3 | 148641 | 124 | 24.863 | 5978.4 |
310 | 2025-08-05 11:29:48 | sharpness | 2 | 121436 | 18 | 18.236 | 6659.1 |
309 | 2025-08-04 14:45:51 | sharpness | 1 | 81242 | 1 | 7.046 | 11530.2 |
308 | 2025-07-27 00:43:59 | sharpness | 1 | 81242 | 1 | 3.203 | 25364.3 |
307 | 2025-07-26 12:46:14 | sharpness | 1 | 81242 | 1 | 1.423 | 57092.1 |
306 | 2025-07-21 03:26:50 | sharpness | 1 | 81242 | 1 | 1.513 | 53696.0 |
305 | 2025-07-15 22:03:42 | sharpness | 2 | 121436 | 18 | 7.610 | 15957.4 |
304 | 2025-07-15 04:07:27 | sharpness | 1 | 81242 | 1 | 3.420 | 23755.0 |
303 | 2025-07-13 14:04:37 | sharpness | 1 | 81242 | 1 | 2.953 | 27511.7 |
302 | 2025-07-11 04:14:27 | sharpness | 1 | 81242 | 1 | 3.546 | 22910.9 |
301 | 2025-07-10 21:37:48 | sharpness | 1 | 81242 | 1 | 8.813 | 9218.4 |
300 | 2025-07-08 15:42:46 | sharpness | 1 | 81242 | 1 | 6.140 | 13231.6 |
299 | 2025-07-08 06:54:04 | sharpness | 3 | 148641 | 124 | 31.813 | 4672.3 |
298 | 2025-07-07 13:28:24 | sharpness | 1 | 81242 | 1 | 7.423 | 10944.6 |
297 | 2025-07-05 08:20:22 | sharpness | 2 | 121436 | 18 | 10.813 | 11230.6 |
296 | 2025-07-05 05:04:56 | sharpness | 3 | 148641 | 124 | 18.783 | 7913.6 |
295 | 2025-07-04 04:32:53 | sharpness | 1 | 81242 | 1 | 10.440 | 7781.8 |
294 | 2025-06-22 02:40:18 | sharpness | 1 | 81242 | 1 | 6.813 | 11924.6 |
293 | 2025-06-21 18:33:07 | sharpness | 1 | 81242 | 1 | 1.420 | 57212.7 |
292 | 2025-06-16 00:22:02 | sharpness | 1 | 81242 | 1 | 4.016 | 20229.6 |
291 | 2025-06-15 12:34:41 | sharpness | 1 | 81242 | 1 | 1.420 | 57212.7 |
290 | 2025-06-14 03:28:19 | sharpness | 1 | 81242 | 1 | 3.406 | 23852.6 |
289 | 2025-06-14 00:15:49 | sharpness | 1 | 81242 | 1 | 7.326 | 11089.5 |
288 | 2025-05-30 22:43:04 | sharpness | 1 | 81242 | 1 | 5.873 | 13833.1 |
287 | 2025-05-29 03:41:13 | sharpness | 1 | 81242 | 1 | 5.093 | 15951.7 |
286 | 2025-05-27 16:13:34 | sharpness | 1 | 81242 | 1 | 10.093 | 8049.3 |
285 | 2025-05-20 18:12:01 | sharpness | 1 | 81242 | 1 | 10.453 | 7772.1 |
284 | 2025-05-14 18:13:08 | sharpness | 1 | 81242 | 1 | 4.580 | 17738.4 |
283 | 2025-05-10 03:03:16 | sharpness | 1 | 81242 | 1 | 5.123 | 15858.3 |
282 | 2025-05-10 00:06:35 | sharpness | 1 | 81242 | 1 | 6.720 | 12089.6 |
281 | 2025-05-08 06:01:59 | sharpness | 1 | 81242 | 1 | 7.750 | 10482.8 |
280 | 2025-05-08 02:17:49 | sharpness | 1 | 81242 | 1 | 10.080 | 8059.7 |
279 | 2025-05-07 07:30:57 | sharpness | 1 | 81242 | 1 | 1.330 | 61084.2 |
278 | 2025-04-28 04:12:34 | sharpness | 1 | 81242 | 1 | 7.673 | 10588.0 |
277 | 2025-04-22 22:16:42 | sharpness | 1 | 81242 | 1 | 9.173 | 8856.6 |
276 | 2025-04-22 21:59:05 | sharpness | 1 | 81242 | 1 | 4.906 | 16559.7 |
275 | 2025-04-15 17:41:40 | sharpness | 1 | 81242 | 1 | 1.280 | 63470.3 |
274 | 2025-04-08 05:01:56 | sharpness | 1 | 81242 | 1 | 6.813 | 11924.6 |
273 | 2025-04-06 02:44:12 | sharpness | 1 | 81242 | 1 | 7.986 | 10173.1 |
272 | 2025-03-24 01:42:39 | sharpness | 2 | 121436 | 18 | 7.486 | 16221.7 |
271 | 2025-03-23 04:52:58 | sharpness | 1 | 81242 | 1 | 8.546 | 9506.4 |
270 | 2025-03-22 05:08:30 | sharpness | 3 | 148641 | 124 | 7.190 | 20673.3 |
269 | 2025-03-22 03:18:08 | sharpness | 2 | 121436 | 18 | 18.373 | 6609.5 |
268 | 2025-03-20 22:26:38 | sharpness | 1 | 81242 | 1 | 1.326 | 61268.5 |
267 | 2025-03-20 05:11:29 | sharpness | 3 | 148641 | 124 | 24.143 | 6156.7 |
266 | 2025-03-14 22:44:11 | sharpness | 3 | 148641 | 124 | 34.516 | 4306.4 |
265 | 2025-03-12 18:45:00 | sharpness | 3 | 148641 | 124 | 30.376 | 4893.4 |
264 | 2025-03-08 23:29:39 | sharpness | 3 | 148641 | 124 | 46.443 | 3200.5 |
263 | 2025-03-08 18:46:31 | sharpness | 1 | 81242 | 1 | 5.250 | 15474.7 |
262 | 2025-03-08 15:08:32 | sharpness | 3 | 148641 | 124 | 33.660 | 4416.0 |
261 | 2025-03-01 07:31:01 | sharpness | 1 | 81242 | 1 | 6.893 | 11786.2 |
260 | 2025-02-10 17:54:38 | sharpness | 3 | 148641 | 124 | 47.140 | 3153.2 |
259 | 2025-02-10 04:58:11 | sharpness | 3 | 148641 | 124 | 34.110 | 4357.7 |
258 | 2025-02-09 13:59:31 | sharpness | 2 | 121436 | 18 | 18.093 | 6711.8 |
257 | 2025-02-08 08:48:31 | sharpness | 2 | 121436 | 18 | 34.360 | 3534.2 |
256 | 2025-02-07 09:43:39 | sharpness | 2 | 121436 | 18 | 26.406 | 4598.8 |
255 | 2025-02-07 09:43:38 | sharpness | 3 | 148641 | 124 | 18.000 | 8257.8 |
254 | 2025-02-07 09:00:28 | sharpness | 1 | 81242 | 1 | 1.343 | 60492.9 |
253 | 2025-01-29 19:44:16 | sharpness | 1 | 81242 | 1 | 3.376 | 24064.6 |
252 | 2025-01-22 15:45:03 | sharpness | 3 | 148641 | 124 | 48.343 | 3074.7 |
251 | 2025-01-22 15:45:11 | sharpness | 2 | 121436 | 18 | 15.873 | 7650.5 |
250 | 2025-01-22 15:40:36 | sharpness | 1 | 81242 | 1 | 3.190 | 25467.7 |
249 | 2025-01-09 14:01:25 | sharpness | 3 | 148641 | 124 | 37.063 | 4010.5 |
248 | 2025-01-09 09:42:46 | sharpness | 3 | 148641 | 124 | 37.050 | 4011.9 |
247 | 2025-01-08 22:18:12 | sharpness | 1 | 81242 | 1 | 4.216 | 19269.9 |
246 | 2025-01-07 16:00:53 | sharpness | 3 | 148641 | 124 | 35.623 | 4172.6 |
245 | 2025-01-07 16:01:01 | sharpness | 2 | 121436 | 18 | 17.800 | 6822.2 |
244 | 2025-01-07 15:58:51 | sharpness | 1 | 81242 | 1 | 1.610 | 50460.9 |
243 | 2024-12-26 20:06:11 | sharpness | 1 | 81242 | 1 | 1.453 | 55913.3 |
242 | 2024-12-16 14:19:39 | sharpness | 2 | 121436 | 18 | 16.030 | 7575.5 |
241 | 2024-12-15 07:23:50 | sharpness | 3 | 148641 | 124 | 40.723 | 3650.1 |
240 | 2024-12-15 07:23:52 | sharpness | 2 | 121436 | 18 | 27.906 | 4351.6 |
239 | 2024-12-15 07:22:18 | sharpness | 1 | 81242 | 1 | 4.343 | 18706.4 |
238 | 2024-12-06 16:03:20 | sharpness | 1 | 81242 | 1 | 1.450 | 56029.0 |
237 | 2024-12-02 08:59:16 | sharpness | 3 | 148641 | 124 | 38.766 | 3834.3 |
236 | 2024-12-02 08:59:14 | sharpness | 2 | 121436 | 18 | 27.203 | 4464.1 |
235 | 2024-12-02 08:51:11 | sharpness | 1 | 81242 | 1 | 6.046 | 13437.3 |
234 | 2024-11-26 11:05:55 | sharpness | 1 | 81242 | 1 | 8.846 | 9184.0 |
233 | 2024-11-18 16:35:11 | sharpness | 3 | 148641 | 124 | 35.893 | 4141.2 |
232 | 2024-11-10 16:12:51 | sharpness | 2 | 121436 | 18 | 4.280 | 28372.9 |
231 | 2024-11-09 01:00:47 | sharpness | 3 | 148641 | 124 | 36.876 | 4030.8 |
230 | 2024-11-09 01:00:47 | sharpness | 2 | 121436 | 18 | 18.956 | 6406.2 |
229 | 2024-11-07 20:03:35 | sharpness | 1 | 81242 | 1 | 1.466 | 55417.5 |
228 | 2024-11-06 03:21:09 | sharpness | 1 | 81242 | 1 | 1.343 | 60492.9 |
227 | 2024-11-02 20:07:30 | sharpness | 2 | 121436 | 18 | 15.516 | 7826.5 |
226 | 2024-11-02 12:08:28 | sharpness | 3 | 148641 | 124 | 46.220 | 3215.9 |
225 | 2024-11-02 01:23:52 | sharpness | 3 | 148641 | 124 | 36.326 | 4091.9 |
224 | 2024-11-02 01:23:50 | sharpness | 2 | 121436 | 18 | 18.360 | 6614.2 |
223 | 2024-11-02 01:22:58 | sharpness | 1 | 81242 | 1 | 6.860 | 11842.9 |
222 | 2024-10-21 16:11:10 | sharpness | 1 | 81242 | 1 | 9.576 | 8483.9 |
221 | 2024-09-28 06:02:36 | sharpness | 1 | 81242 | 1 | 12.780 | 6357.0 |
220 | 2024-09-10 13:50:15 | sharpness | 1 | 81242 | 1 | 4.656 | 17448.9 |
219 | 2024-09-08 19:31:51 | sharpness | 1 | 81242 | 1 | 9.970 | 8148.6 |
218 | 2024-07-27 20:11:27 | sharpness | 3 | 148641 | 124 | 30.050 | 4946.5 |
217 | 2024-07-27 20:11:13 | sharpness | 2 | 121436 | 18 | 19.440 | 6246.7 |
216 | 2024-07-24 14:08:12 | sharpness | 1 | 81242 | 1 | 2.783 | 29192.2 |
215 | 2024-07-24 14:01:36 | sharpness | 3 | 148641 | 124 | 26.860 | 5533.9 |
214 | 2024-07-24 14:01:35 | sharpness | 2 | 121436 | 18 | 13.546 | 8964.7 |
213 | 2024-07-23 21:40:06 | sharpness | 3 | 148641 | 124 | 30.520 | 4870.3 |
212 | 2024-07-23 19:43:41 | sharpness | 2 | 121436 | 18 | 17.483 | 6945.9 |