History of Dictionary Searches using Damerau-Levenshtein distance in T-SQL
Fuzzy-string Searches
(up to 100 most recent)
for
"nosinesses"
Num | Started At (CA time) | Searched Word | Change Limit | Words Checked | Words Matched | Seconds | Words Per Sec |
355 | 2024-04-25 10:07:03 | nosinesses | 3 | 140603 | 253 | 22.093 | 6364.1 |
354 | 2024-04-25 10:07:04 | nosinesses | 2 | 108824 | 38 | 11.360 | 9579.6 |
353 | 2024-04-25 10:04:34 | nosinesses | 1 | 67641 | 4 | 3.296 | 20522.1 |
352 | 2024-04-20 20:01:39 | nosinesses | 2 | 108824 | 38 | 2.703 | 40260.5 |
351 | 2024-04-16 18:07:58 | nosinesses | 1 | 67641 | 4 | 4.563 | 14823.8 |
350 | 2024-04-14 04:55:16 | nosinesses | 1 | 67641 | 4 | 4.670 | 14484.2 |
349 | 2024-04-06 20:04:45 | nosinesses | 3 | 140603 | 253 | 12.903 | 10896.9 |
348 | 2024-04-05 11:29:42 | nosinesses | 3 | 140603 | 253 | 22.033 | 6381.5 |
347 | 2024-04-05 11:29:05 | nosinesses | 2 | 108824 | 38 | 8.436 | 12900.0 |
346 | 2024-04-05 11:18:05 | nosinesses | 1 | 67641 | 4 | 2.563 | 26391.3 |
345 | 2024-03-31 20:27:28 | nosinesses | 3 | 140603 | 253 | 17.766 | 7914.2 |
344 | 2024-03-31 20:27:27 | nosinesses | 2 | 108824 | 38 | 13.046 | 8341.6 |
343 | 2024-03-31 20:19:24 | nosinesses | 1 | 67641 | 4 | 2.283 | 29628.1 |
342 | 2024-03-28 04:48:53 | nosinesses | 1 | 67641 | 4 | 1.063 | 63632.2 |
341 | 2024-03-20 04:49:40 | nosinesses | 1 | 67641 | 4 | 1.140 | 59334.2 |
340 | 2024-03-16 17:21:29 | nosinesses | 3 | 140603 | 253 | 19.940 | 7051.3 |
339 | 2024-03-16 17:21:28 | nosinesses | 2 | 108824 | 38 | 10.690 | 10180.0 |
338 | 2024-03-16 17:11:32 | nosinesses | 1 | 67641 | 4 | 3.690 | 18330.9 |
337 | 2024-03-15 11:34:39 | nosinesses | 1 | 67641 | 4 | 3.453 | 19589.1 |
336 | 2024-03-11 10:15:30 | nosinesses | 1 | 67641 | 4 | 3.593 | 18825.8 |
335 | 2024-03-02 11:42:26 | nosinesses | 1 | 67641 | 4 | 1.153 | 58665.2 |
334 | 2024-03-01 12:39:34 | nosinesses | 1 | 67641 | 4 | 1.483 | 45610.9 |
333 | 2024-02-22 20:21:08 | nosinesses | 3 | 140603 | 253 | 12.703 | 11068.5 |
332 | 2024-02-15 19:27:40 | nosinesses | 3 | 140603 | 253 | 8.000 | 17575.4 |
331 | 2024-02-14 13:35:07 | nosinesses | 3 | 140603 | 253 | 9.966 | 14108.3 |
330 | 2024-02-14 13:35:10 | nosinesses | 2 | 108824 | 38 | 3.733 | 29151.9 |
329 | 2024-02-14 13:21:56 | nosinesses | 1 | 67641 | 4 | 1.046 | 64666.3 |
328 | 2024-02-10 01:09:11 | nosinesses | 1 | 67641 | 4 | 1.266 | 53428.9 |
327 | 2024-02-08 20:22:20 | nosinesses | 1 | 67641 | 4 | 1.250 | 54112.8 |
326 | 2024-01-31 15:30:08 | nosinesses | 1 | 67641 | 4 | 1.000 | 67641.0 |
325 | 2024-01-30 00:09:19 | nosinesses | 1 | 67641 | 4 | 1.156 | 58513.0 |
324 | 2024-01-30 00:09:17 | nosinesses | 1 | 67641 | 4 | 1.110 | 60937.8 |
323 | 2024-01-27 11:24:39 | nosinesses | 1 | 67641 | 4 | 1.076 | 62863.4 |
322 | 2024-01-22 01:20:37 | nosinesses | 3 | 140603 | 253 | 5.453 | 25784.5 |
321 | 2023-12-21 05:47:44 | nosinesses | 1 | 67641 | 4 | 1.186 | 57032.9 |
320 | 2023-12-19 09:02:49 | nosinesses | 1 | 67641 | 4 | 1.110 | 60937.8 |
319 | 2023-12-18 05:42:30 | nosinesses | 1 | 67641 | 4 | 1.000 | 67641.0 |
318 | 2023-12-17 19:04:15 | nosinesses | 2 | 108824 | 38 | 3.016 | 36082.2 |
317 | 2023-12-08 22:51:58 | nosinesses | 1 | 67641 | 4 | 1.123 | 60232.4 |
316 | 2023-12-07 22:26:08 | nosinesses | 1 | 67641 | 4 | 1.190 | 56841.2 |
315 | 2023-12-06 22:44:22 | nosinesses | 1 | 67641 | 4 | 1.016 | 66575.8 |
314 | 2023-12-03 06:14:52 | nosinesses | 1 | 67641 | 4 | 1.046 | 64666.3 |
313 | 2023-12-01 10:47:17 | nosinesses | 2 | 108824 | 38 | 3.080 | 35332.5 |
312 | 2023-11-30 22:59:47 | nosinesses | 3 | 140603 | 253 | 7.406 | 18985.0 |
311 | 2023-11-30 03:27:17 | nosinesses | 1 | 67641 | 4 | 1.076 | 62863.4 |
310 | 2023-11-29 02:02:47 | nosinesses | 1 | 67641 | 4 | 1.110 | 60937.8 |
309 | 2023-11-27 19:30:39 | nosinesses | 1 | 67641 | 4 | 1.140 | 59334.2 |
308 | 2023-11-14 23:45:49 | nosinesses | 3 | 140603 | 253 | 5.516 | 25490.0 |
307 | 2023-11-14 23:45:46 | nosinesses | 2 | 108824 | 38 | 3.076 | 35378.4 |
306 | 2023-11-11 15:03:36 | nosinesses | 1 | 67641 | 4 | 1.000 | 67641.0 |
305 | 2023-11-10 07:53:11 | nosinesses | 1 | 67641 | 4 | 1.000 | 67641.0 |
304 | 2023-11-02 15:05:13 | nosinesses | 3 | 140603 | 253 | 7.016 | 20040.3 |
303 | 2023-10-26 20:31:22 | nosinesses | 1 | 67641 | 4 | 1.123 | 60232.4 |
302 | 2023-10-23 15:01:56 | nosinesses | 1 | 67641 | 4 | 1.140 | 59334.2 |
301 | 2023-10-13 03:38:19 | nosinesses | 1 | 67641 | 4 | 1.123 | 60232.4 |
300 | 2023-10-09 07:57:18 | nosinesses | 1 | 67641 | 4 | 1.123 | 60232.4 |
299 | 2023-10-08 05:18:19 | nosinesses | 1 | 67641 | 4 | 1.110 | 60937.8 |
298 | 2023-09-29 08:20:30 | nosinesses | 1 | 67641 | 4 | 1.126 | 60071.9 |
297 | 2023-09-16 13:20:07 | nosinesses | 2 | 108824 | 38 | 5.966 | 18240.7 |
296 | 2023-09-01 07:28:11 | nosinesses | 1 | 67641 | 4 | 0.983 | 68810.8 |
295 | 2023-08-31 06:56:57 | nosinesses | 1 | 67641 | 4 | 1.140 | 59334.2 |
294 | 2023-08-30 06:32:44 | nosinesses | 1 | 67641 | 4 | 0.970 | 69733.0 |
293 | 2023-08-09 13:47:47 | nosinesses | 3 | 140603 | 253 | 6.313 | 22272.0 |
292 | 2023-08-04 21:16:45 | nosinesses | 1 | 67641 | 4 | 1.000 | 67641.0 |
291 | 2023-07-23 00:58:28 | nosinesses | 1 | 67641 | 4 | 1.156 | 58513.0 |
290 | 2023-06-20 22:34:02 | nosinesses | 1 | 67641 | 4 | 1.096 | 61716.2 |
289 | 2023-06-12 06:01:29 | nosinesses | 1 | 67641 | 4 | 1.000 | 67641.0 |
288 | 2023-06-08 22:54:33 | nosinesses | 1 | 67641 | 4 | 1.000 | 67641.0 |
287 | 2023-06-05 11:36:54 | nosinesses | 2 | 108824 | 38 | 2.593 | 41968.4 |
286 | 2023-05-27 14:14:59 | nosinesses | 1 | 67641 | 4 | 1.000 | 67641.0 |
285 | 2023-05-07 11:26:00 | nosinesses | 1 | 67641 | 4 | 1.033 | 65480.2 |
284 | 2023-05-02 11:23:51 | nosinesses | 1 | 67641 | 4 | 1.013 | 66773.0 |
283 | 2023-04-21 22:18:25 | nosinesses | 3 | 140603 | 253 | 6.250 | 22496.5 |
282 | 2023-04-07 19:17:40 | nosinesses | 1 | 67641 | 4 | 1.110 | 60937.8 |
281 | 2023-03-11 21:55:09 | nosinesses | 1 | 67641 | 4 | 0.983 | 68810.8 |
280 | 2023-03-08 19:34:55 | nosinesses | 2 | 108824 | 38 | 2.906 | 37448.0 |
279 | 2023-03-06 13:25:23 | nosinesses | 1 | 67641 | 4 | 1.076 | 62863.4 |
278 | 2023-03-03 01:04:33 | nosinesses | 1 | 67641 | 4 | 0.983 | 68810.8 |
277 | 2023-02-28 18:54:26 | nosinesses | 1 | 67641 | 4 | 1.096 | 61716.2 |
276 | 2023-02-14 00:58:42 | nosinesses | 1 | 67641 | 4 | 0.966 | 70021.7 |
275 | 2023-01-23 22:24:51 | nosinesses | 3 | 140603 | 253 | 5.470 | 25704.4 |
274 | 2023-01-18 01:47:28 | nosinesses | 1 | 67641 | 4 | 1.093 | 61885.6 |
273 | 2022-12-25 20:31:33 | nosinesses | 1 | 67641 | 4 | 0.983 | 68810.8 |
272 | 2022-12-25 03:02:31 | nosinesses | 1 | 67641 | 4 | 0.970 | 69733.0 |
271 | 2022-12-16 03:10:53 | nosinesses | 2 | 108824 | 38 | 3.250 | 33484.3 |
270 | 2022-12-04 02:56:08 | nosinesses | 1 | 67641 | 4 | 1.093 | 61885.6 |
269 | 2022-11-14 11:52:45 | nosinesses | 1 | 67641 | 4 | 1.013 | 66773.0 |
268 | 2022-11-10 19:10:56 | nosinesses | 1 | 67641 | 4 | 1.000 | 67641.0 |
267 | 2022-11-09 04:00:53 | nosinesses | 1 | 67641 | 4 | 1.093 | 61885.6 |
266 | 2022-11-09 02:36:31 | nosinesses | 1 | 67641 | 4 | 1.126 | 60071.9 |
265 | 2022-11-03 13:18:45 | nosinesses | 3 | 140603 | 253 | 5.983 | 23500.4 |
264 | 2022-09-25 05:04:10 | nosinesses | 1 | 67641 | 4 | 1.000 | 67641.0 |
263 | 2022-09-13 01:50:53 | nosinesses | 1 | 67641 | 4 | 1.000 | 67641.0 |
262 | 2022-09-04 10:15:39 | nosinesses | 1 | 67641 | 4 | 0.983 | 68810.8 |
261 | 2022-08-09 15:16:42 | nosinesses | 1 | 67641 | 4 | 0.983 | 68810.8 |
260 | 2022-08-05 14:50:12 | nosinesses | 2 | 108824 | 38 | 2.703 | 40260.5 |
259 | 2022-07-21 14:55:31 | nosinesses | 1 | 67641 | 4 | 1.123 | 60232.4 |
258 | 2022-07-19 07:34:21 | nosinesses | 1 | 67641 | 4 | 1.033 | 65480.2 |
257 | 2022-07-17 21:39:50 | nosinesses | 1 | 67641 | 4 | 1.030 | 65670.9 |
256 | 2022-07-14 09:58:52 | nosinesses | 1 | 67641 | 4 | 1.076 | 62863.4 |