History of Dictionary Searches using Damerau-Levenshtein distance in T-SQL
Fuzzy-string Searches
(up to 100 most recent)
for
"coarsest"
Num | Started At (CA time) | Searched Word | Change Limit | Words Checked | Words Matched | Seconds | Words Per Sec |
315 | 2024-05-01 22:22:41 | coarsest | 1 | 82945 | 2 | 1.686 | 49196.3 |
314 | 2024-04-11 10:02:01 | coarsest | 2 | 121059 | 19 | 4.313 | 28068.4 |
313 | 2024-04-10 09:12:10 | coarsest | 2 | 121059 | 19 | 3.750 | 32282.4 |
312 | 2024-04-10 09:11:06 | coarsest | 1 | 82945 | 2 | 3.016 | 27501.7 |
311 | 2024-04-06 01:03:46 | coarsest | 3 | 146162 | 196 | 22.830 | 6402.2 |
310 | 2024-04-05 03:16:57 | coarsest | 3 | 146162 | 196 | 18.046 | 8099.4 |
309 | 2024-03-31 21:19:36 | coarsest | 3 | 146162 | 196 | 14.390 | 10157.2 |
308 | 2024-03-31 21:19:34 | coarsest | 2 | 121059 | 19 | 8.936 | 13547.3 |
307 | 2024-03-31 21:18:57 | coarsest | 1 | 82945 | 2 | 2.140 | 38759.3 |
306 | 2024-03-29 09:59:39 | coarsest | 3 | 146162 | 196 | 10.733 | 13618.0 |
305 | 2024-03-29 09:59:33 | coarsest | 1 | 82945 | 2 | 1.483 | 55930.5 |
304 | 2024-03-29 09:59:21 | coarsest | 3 | 146162 | 196 | 10.766 | 13576.3 |
303 | 2024-03-29 09:59:20 | coarsest | 2 | 121059 | 19 | 4.156 | 29128.7 |
302 | 2024-03-29 09:59:15 | coarsest | 1 | 82945 | 2 | 3.140 | 26415.6 |
301 | 2024-03-17 14:45:01 | coarsest | 3 | 146162 | 196 | 7.313 | 19986.6 |
300 | 2024-03-10 23:27:19 | coarsest | 1 | 82945 | 2 | 1.516 | 54713.1 |
299 | 2024-03-08 22:34:40 | coarsest | 1 | 82945 | 2 | 4.640 | 17876.1 |
298 | 2024-03-01 18:35:07 | coarsest | 3 | 146162 | 196 | 15.423 | 9476.9 |
297 | 2024-02-29 05:46:21 | coarsest | 2 | 121059 | 19 | 3.860 | 31362.4 |
296 | 2024-02-29 05:46:07 | coarsest | 3 | 146162 | 196 | 8.516 | 17163.2 |
295 | 2024-02-28 14:31:26 | coarsest | 1 | 82945 | 2 | 1.533 | 54106.3 |
294 | 2024-02-28 12:01:43 | coarsest | 2 | 121059 | 19 | 4.203 | 28803.0 |
293 | 2024-02-28 05:31:59 | coarsest | 3 | 146162 | 196 | 25.830 | 5658.6 |
292 | 2024-02-28 04:47:46 | coarsest | 3 | 146162 | 196 | 20.500 | 7129.9 |
291 | 2024-02-28 04:47:48 | coarsest | 2 | 121059 | 19 | 10.046 | 12050.5 |
290 | 2024-02-28 04:47:37 | coarsest | 1 | 82945 | 2 | 3.360 | 24686.0 |
289 | 2024-01-22 13:21:32 | coarsest | 1 | 82945 | 2 | 1.266 | 65517.4 |
288 | 2024-01-21 21:22:08 | coarsest | 2 | 121059 | 19 | 3.263 | 37100.5 |
287 | 2024-01-17 02:45:13 | coarsest | 3 | 146162 | 196 | 8.766 | 16673.7 |
286 | 2024-01-17 02:45:17 | coarsest | 2 | 121059 | 19 | 3.796 | 31891.2 |
285 | 2023-12-02 12:12:25 | coarsest | 1 | 82945 | 2 | 1.593 | 52068.4 |
284 | 2023-11-29 07:43:40 | coarsest | 3 | 146162 | 196 | 6.593 | 22169.3 |
283 | 2023-11-19 16:16:24 | coarsest | 1 | 82945 | 2 | 1.296 | 64000.8 |
282 | 2023-11-17 00:41:46 | coarsest | 1 | 82945 | 2 | 1.453 | 57085.3 |
281 | 2023-11-16 19:37:53 | coarsest | 1 | 82945 | 2 | 1.406 | 58993.6 |
280 | 2023-11-09 18:49:40 | coarsest | 1 | 82945 | 2 | 1.296 | 64000.8 |
279 | 2023-11-04 12:35:59 | coarsest | 1 | 82945 | 2 | 1.530 | 54212.4 |
278 | 2023-11-02 14:40:51 | coarsest | 2 | 121059 | 19 | 4.063 | 29795.5 |
277 | 2023-10-25 15:06:14 | coarsest | 1 | 82945 | 2 | 1.343 | 61761.0 |
276 | 2023-10-19 19:03:01 | coarsest | 1 | 82945 | 2 | 2.983 | 27805.9 |
275 | 2023-10-17 18:55:54 | coarsest | 1 | 82945 | 2 | 1.313 | 63172.1 |
274 | 2023-09-17 00:58:39 | coarsest | 1 | 82945 | 2 | 1.393 | 59544.1 |
273 | 2023-09-04 11:29:19 | coarsest | 1 | 82945 | 2 | 1.300 | 63803.8 |
272 | 2023-08-28 23:19:50 | coarsest | 3 | 146162 | 196 | 7.220 | 20244.0 |
271 | 2023-08-10 07:14:37 | coarsest | 2 | 121059 | 19 | 3.720 | 32542.7 |
270 | 2023-08-09 23:12:36 | coarsest | 1 | 82945 | 2 | 1.390 | 59672.7 |
269 | 2023-05-13 14:08:05 | coarsest | 3 | 146162 | 196 | 6.733 | 21708.3 |
268 | 2023-04-21 08:25:03 | coarsest | 1 | 82945 | 2 | 1.313 | 63172.1 |
267 | 2023-04-20 06:19:47 | coarsest | 2 | 121059 | 19 | 4.360 | 27765.8 |
266 | 2023-02-18 07:21:15 | coarsest | 3 | 146162 | 196 | 6.390 | 22873.6 |
265 | 2023-01-21 01:32:06 | coarsest | 2 | 121059 | 19 | 3.220 | 37596.0 |
264 | 2023-01-08 22:33:24 | coarsest | 1 | 82945 | 2 | 1.360 | 60989.0 |
263 | 2022-12-21 09:25:27 | coarsest | 1 | 82945 | 2 | 1.266 | 65517.4 |
262 | 2022-11-30 02:41:27 | coarsest | 3 | 146162 | 196 | 6.390 | 22873.6 |
261 | 2022-10-31 22:16:32 | coarsest | 2 | 121059 | 19 | 3.186 | 37997.2 |
260 | 2022-10-10 05:37:24 | coarsest | 1 | 82945 | 2 | 1.296 | 64000.8 |
259 | 2022-09-01 19:12:08 | coarsest | 1 | 82945 | 2 | 1.313 | 63172.1 |
258 | 2022-08-21 05:49:24 | coarsest | 1 | 82945 | 2 | 1.326 | 62552.8 |
257 | 2022-07-07 08:11:48 | coarsest | 3 | 146162 | 196 | 6.763 | 21612.0 |
256 | 2022-06-03 02:30:07 | coarsest | 2 | 121059 | 19 | 3.330 | 36354.1 |
255 | 2022-05-25 11:34:32 | coarsest | 1 | 82945 | 2 | 1.406 | 58993.6 |
254 | 2022-05-01 10:54:06 | coarsest | 1 | 82945 | 2 | 1.313 | 63172.1 |
253 | 2022-02-11 02:06:26 | coarsest | 1 | 82945 | 2 | 1.486 | 55817.6 |
252 | 2022-01-17 14:25:27 | coarsest | 1 | 82945 | 2 | 1.500 | 55296.7 |
251 | 2022-01-14 07:41:31 | coarsest | 1 | 82945 | 2 | 1.330 | 62364.7 |
250 | 2021-12-12 08:57:08 | coarsest | 1 | 82945 | 2 | 1.576 | 52630.1 |
249 | 2021-12-02 16:11:03 | coarsest | 1 | 82945 | 2 | 1.500 | 55296.7 |
248 | 2021-11-30 15:05:08 | coarsest | 1 | 82945 | 2 | 1.420 | 58412.0 |
247 | 2021-11-12 22:03:29 | coarsest | 1 | 82945 | 2 | 1.640 | 50576.2 |
246 | 2021-10-14 04:46:03 | coarsest | 1 | 82945 | 2 | 1.453 | 57085.3 |
245 | 2021-10-11 05:30:41 | coarsest | 1 | 82945 | 2 | 1.296 | 64000.8 |
244 | 2021-09-08 03:29:01 | coarsest | 1 | 82945 | 2 | 1.470 | 56425.2 |
243 | 2021-08-21 12:43:16 | coarsest | 1 | 82945 | 2 | 1.313 | 63172.1 |
242 | 2021-07-09 15:56:34 | coarsest | 1 | 82945 | 2 | 1.640 | 50576.2 |
241 | 2021-04-14 13:34:27 | coarsest | 1 | 82945 | 2 | 1.470 | 56425.2 |
240 | 2021-04-13 07:26:03 | coarsest | 3 | 146162 | 196 | 7.796 | 18748.3 |
239 | 2021-04-05 19:16:10 | coarsest | 1 | 82945 | 2 | 1.466 | 56579.1 |
238 | 2021-04-01 15:02:02 | coarsest | 1 | 82945 | 2 | 1.470 | 56425.2 |
237 | 2021-03-18 05:54:30 | coarsest | 1 | 82945 | 2 | 2.936 | 28251.0 |
236 | 2021-01-28 10:14:37 | coarsest | 1 | 82945 | 2 | 1.513 | 54821.5 |
235 | 2020-12-30 08:16:31 | coarsest | 1 | 82945 | 2 | 1.313 | 63172.1 |
234 | 2020-12-20 18:02:25 | coarsest | 1 | 82945 | 2 | 1.343 | 61761.0 |
233 | 2020-12-02 15:13:15 | coarsest | 1 | 82945 | 2 | 1.313 | 63172.1 |
232 | 2020-12-01 17:20:51 | coarsest | 3 | 146162 | 196 | 6.720 | 21750.3 |
231 | 2020-11-02 23:53:58 | coarsest | 1 | 82945 | 2 | 1.513 | 54821.5 |
230 | 2020-10-31 11:08:48 | coarsest | 1 | 82945 | 2 | 1.673 | 49578.6 |
229 | 2020-10-31 00:05:19 | coarsest | 1 | 82945 | 2 | 1.470 | 56425.2 |
228 | 2020-10-27 10:33:44 | coarsest | 3 | 146162 | 196 | 6.753 | 21644.0 |
227 | 2020-09-16 18:43:53 | coarsest | 1 | 82945 | 2 | 1.346 | 61623.3 |
226 | 2020-06-04 06:39:05 | coarsest | 1 | 82945 | 2 | 1.343 | 61761.0 |
225 | 2020-03-29 17:09:52 | coarsest | 1 | 82945 | 2 | 1.763 | 47047.6 |
224 | 2020-03-22 20:52:25 | coarsest | 1 | 82945 | 2 | 1.390 | 59672.7 |
223 | 2020-03-05 14:57:07 | coarsest | 1 | 82945 | 2 | 1.360 | 60989.0 |
222 | 2020-03-01 23:35:34 | coarsest | 1 | 82945 | 2 | 1.563 | 53067.8 |
221 | 2020-02-25 07:15:28 | coarsest | 1 | 82945 | 2 | 1.593 | 52068.4 |
220 | 2020-02-25 02:50:04 | coarsest | 1 | 82945 | 2 | 1.546 | 53651.4 |
219 | 2020-02-24 02:09:29 | coarsest | 1 | 82945 | 2 | 1.533 | 54106.3 |
218 | 2020-02-18 11:58:41 | coarsest | 1 | 82945 | 2 | 1.686 | 49196.3 |
217 | 2020-02-17 20:02:31 | coarsest | 1 | 82945 | 2 | 1.800 | 46080.6 |
216 | 2020-02-13 21:07:05 | coarsest | 1 | 82945 | 2 | 1.796 | 46183.2 |