History of Dictionary Searches using Damerau-Levenshtein distance in T-SQL
Fuzzy-string Searches
(up to 100 most recent)
for
"coarsens"
Num | Started At (CA time) | Searched Word | Change Limit | Words Checked | Words Matched | Seconds | Words Per Sec |
425 | 2024-04-15 00:48:27 | coarsens | 3 | 146162 | 218 | 10.016 | 14592.9 |
424 | 2024-04-15 00:48:22 | coarsens | 3 | 146162 | 218 | 10.500 | 13920.2 |
423 | 2024-04-11 04:58:34 | coarsens | 3 | 146162 | 218 | 10.673 | 13694.6 |
422 | 2024-04-11 04:58:35 | coarsens | 2 | 121059 | 18 | 7.796 | 15528.3 |
421 | 2024-04-10 09:09:49 | coarsens | 2 | 121059 | 18 | 6.936 | 17453.7 |
420 | 2024-04-10 09:09:48 | coarsens | 3 | 146162 | 218 | 8.030 | 18202.0 |
419 | 2024-04-10 09:08:35 | coarsens | 1 | 82945 | 3 | 2.266 | 36604.1 |
418 | 2024-04-09 11:31:00 | coarsens | 2 | 121059 | 18 | 15.003 | 8069.0 |
417 | 2024-04-09 11:30:54 | coarsens | 3 | 146162 | 218 | 17.736 | 8241.0 |
416 | 2024-04-09 10:14:48 | coarsens | 1 | 82945 | 3 | 1.343 | 61761.0 |
415 | 2024-04-04 20:38:49 | coarsens | 3 | 146162 | 218 | 20.410 | 7161.3 |
414 | 2024-04-03 18:41:07 | coarsens | 3 | 146162 | 218 | 9.483 | 15413.1 |
413 | 2024-03-29 09:59:49 | coarsens | 1 | 82945 | 3 | 4.360 | 19024.1 |
412 | 2024-03-29 09:59:21 | coarsens | 2 | 121059 | 18 | 4.156 | 29128.7 |
411 | 2024-03-29 04:21:43 | coarsens | 3 | 146162 | 218 | 14.266 | 10245.5 |
410 | 2024-03-29 03:41:13 | coarsens | 3 | 146162 | 218 | 20.733 | 7049.7 |
409 | 2024-03-29 03:41:14 | coarsens | 2 | 121059 | 18 | 8.030 | 15075.8 |
408 | 2024-03-29 03:41:02 | coarsens | 1 | 82945 | 3 | 5.030 | 16490.1 |
407 | 2024-03-27 14:23:58 | coarsens | 1 | 82945 | 3 | 3.156 | 26281.7 |
406 | 2024-03-12 00:10:52 | coarsens | 2 | 121059 | 18 | 8.093 | 14958.5 |
405 | 2024-03-12 00:10:27 | coarsens | 3 | 146162 | 218 | 8.890 | 16441.2 |
404 | 2024-03-11 01:30:34 | coarsens | 3 | 146162 | 218 | 29.376 | 4975.6 |
403 | 2024-03-10 23:27:01 | coarsens | 2 | 121059 | 18 | 3.563 | 33976.7 |
402 | 2024-03-10 23:26:58 | coarsens | 1 | 82945 | 3 | 1.563 | 53067.8 |
401 | 2024-03-04 23:41:21 | coarsens | 1 | 82945 | 3 | 1.376 | 60279.8 |
400 | 2024-02-26 10:14:55 | coarsens | 1 | 82945 | 3 | 1.296 | 64000.8 |
399 | 2024-02-02 18:38:26 | coarsens | 1 | 82945 | 3 | 3.080 | 26930.2 |
398 | 2024-01-30 14:25:47 | coarsens | 3 | 146162 | 218 | 8.250 | 17716.6 |
397 | 2024-01-30 14:25:39 | coarsens | 2 | 121059 | 18 | 3.843 | 31501.2 |
396 | 2024-01-30 06:20:58 | coarsens | 1 | 82945 | 3 | 1.516 | 54713.1 |
395 | 2024-01-29 13:36:59 | coarsens | 2 | 121059 | 18 | 3.766 | 32145.2 |
394 | 2024-01-17 21:22:11 | coarsens | 2 | 121059 | 18 | 4.673 | 25906.1 |
393 | 2024-01-08 19:21:03 | coarsens | 3 | 146162 | 218 | 8.580 | 17035.2 |
392 | 2023-12-25 16:15:55 | coarsens | 1 | 82945 | 3 | 1.500 | 55296.7 |
391 | 2023-12-12 22:13:02 | coarsens | 3 | 146162 | 218 | 7.643 | 19123.6 |
390 | 2023-12-06 00:03:43 | coarsens | 2 | 121059 | 18 | 3.283 | 36874.5 |
389 | 2023-12-05 11:22:18 | coarsens | 3 | 146162 | 218 | 7.936 | 18417.6 |
388 | 2023-11-27 18:26:29 | coarsens | 1 | 82945 | 3 | 1.346 | 61623.3 |
387 | 2023-11-20 05:35:40 | coarsens | 1 | 82945 | 3 | 1.453 | 57085.3 |
386 | 2023-11-16 08:50:29 | coarsens | 3 | 146162 | 218 | 7.233 | 20207.7 |
385 | 2023-11-16 08:50:19 | coarsens | 2 | 121059 | 18 | 3.453 | 35059.1 |
384 | 2023-11-10 09:29:26 | coarsens | 1 | 82945 | 3 | 1.296 | 64000.8 |
383 | 2023-10-26 22:17:17 | coarsens | 1 | 82945 | 3 | 1.533 | 54106.3 |
382 | 2023-10-20 14:51:39 | coarsens | 1 | 82945 | 3 | 1.560 | 53169.9 |
381 | 2023-10-17 12:01:13 | coarsens | 1 | 82945 | 3 | 1.346 | 61623.3 |
380 | 2023-10-11 18:02:44 | coarsens | 1 | 82945 | 3 | 1.310 | 63316.8 |
379 | 2023-10-04 03:47:27 | coarsens | 1 | 82945 | 3 | 1.343 | 61761.0 |
378 | 2023-09-22 23:20:16 | coarsens | 1 | 82945 | 3 | 1.330 | 62364.7 |
377 | 2023-09-12 17:26:11 | coarsens | 1 | 82945 | 3 | 1.483 | 55930.5 |
376 | 2023-09-11 09:13:12 | coarsens | 3 | 146162 | 218 | 8.250 | 17716.6 |
375 | 2023-09-10 21:36:05 | coarsens | 1 | 82945 | 3 | 1.313 | 63172.1 |
374 | 2023-09-05 18:10:40 | coarsens | 1 | 82945 | 3 | 1.313 | 63172.1 |
373 | 2023-07-10 07:27:07 | coarsens | 3 | 146162 | 218 | 7.593 | 19249.6 |
372 | 2023-06-24 13:56:12 | coarsens | 1 | 82945 | 3 | 1.266 | 65517.4 |
371 | 2023-06-02 08:13:32 | coarsens | 3 | 146162 | 218 | 6.516 | 22431.2 |
370 | 2023-05-23 07:42:34 | coarsens | 1 | 82945 | 3 | 1.500 | 55296.7 |
369 | 2023-04-05 21:14:29 | coarsens | 1 | 82945 | 3 | 1.326 | 62552.8 |
368 | 2023-03-08 01:20:34 | coarsens | 3 | 146162 | 218 | 6.436 | 22710.1 |
367 | 2023-02-10 09:02:36 | coarsens | 1 | 82945 | 3 | 1.296 | 64000.8 |
366 | 2023-01-19 04:57:54 | coarsens | 1 | 82945 | 3 | 1.280 | 64800.8 |
365 | 2022-12-12 18:52:26 | coarsens | 3 | 146162 | 218 | 6.436 | 22710.1 |
364 | 2022-11-15 09:08:14 | coarsens | 1 | 82945 | 3 | 1.593 | 52068.4 |
363 | 2022-10-27 09:10:47 | coarsens | 1 | 82945 | 3 | 1.280 | 64800.8 |
362 | 2022-10-23 19:58:50 | coarsens | 1 | 82945 | 3 | 1.266 | 65517.4 |
361 | 2022-10-18 21:59:55 | coarsens | 3 | 146162 | 218 | 6.576 | 22226.6 |
360 | 2022-09-06 09:17:22 | coarsens | 3 | 146162 | 218 | 7.670 | 19056.3 |
359 | 2022-08-25 08:57:44 | coarsens | 3 | 146162 | 218 | 8.923 | 16380.4 |
358 | 2022-07-29 21:00:57 | coarsens | 3 | 146162 | 218 | 6.610 | 22112.3 |
357 | 2022-07-27 11:39:46 | coarsens | 3 | 146162 | 218 | 7.190 | 20328.5 |
356 | 2022-07-07 05:05:08 | coarsens | 1 | 82945 | 3 | 1.313 | 63172.1 |
355 | 2022-07-05 01:41:32 | coarsens | 1 | 82945 | 3 | 1.266 | 65517.4 |
354 | 2022-07-04 00:46:45 | coarsens | 1 | 82945 | 3 | 1.500 | 55296.7 |
353 | 2022-06-19 08:27:00 | coarsens | 3 | 146162 | 218 | 7.266 | 20115.9 |
352 | 2022-05-04 08:29:23 | coarsens | 3 | 146162 | 218 | 6.486 | 22535.0 |
351 | 2022-03-13 09:38:47 | coarsens | 1 | 82945 | 3 | 1.423 | 58288.8 |
350 | 2022-03-05 12:07:36 | coarsens | 1 | 82945 | 3 | 1.343 | 61761.0 |
349 | 2022-03-02 20:12:00 | coarsens | 3 | 146162 | 218 | 7.233 | 20207.7 |
348 | 2022-02-28 15:41:49 | coarsens | 3 | 146162 | 218 | 8.143 | 17949.4 |
347 | 2022-02-28 04:24:38 | coarsens | 1 | 82945 | 3 | 1.330 | 62364.7 |
346 | 2021-12-16 00:23:53 | coarsens | 1 | 82945 | 3 | 1.656 | 50087.6 |
345 | 2021-11-26 07:37:19 | coarsens | 1 | 82945 | 3 | 1.310 | 63316.8 |
344 | 2021-11-24 14:47:57 | coarsens | 3 | 146162 | 218 | 7.690 | 19006.8 |
343 | 2021-11-07 20:51:26 | coarsens | 1 | 82945 | 3 | 1.500 | 55296.7 |
342 | 2021-11-05 23:22:27 | coarsens | 1 | 82945 | 3 | 1.470 | 56425.2 |
341 | 2021-10-25 05:57:10 | coarsens | 1 | 82945 | 3 | 1.343 | 61761.0 |
340 | 2021-10-23 04:30:29 | coarsens | 1 | 82945 | 3 | 1.343 | 61761.0 |
339 | 2021-09-27 15:07:39 | coarsens | 1 | 82945 | 3 | 1.343 | 61761.0 |
338 | 2021-09-26 20:20:46 | coarsens | 1 | 82945 | 3 | 1.470 | 56425.2 |
337 | 2021-09-26 02:43:47 | coarsens | 1 | 82945 | 3 | 1.436 | 57761.1 |
336 | 2021-09-22 00:01:44 | coarsens | 1 | 82945 | 3 | 1.516 | 54713.1 |
335 | 2021-08-23 10:38:11 | coarsens | 1 | 82945 | 3 | 1.313 | 63172.1 |
334 | 2021-05-22 17:22:29 | coarsens | 1 | 82945 | 3 | 1.470 | 56425.2 |
333 | 2021-03-20 05:59:56 | coarsens | 1 | 82945 | 3 | 1.436 | 57761.1 |
332 | 2021-02-20 14:26:17 | coarsens | 1 | 82945 | 3 | 1.563 | 53067.8 |
331 | 2021-02-19 04:16:41 | coarsens | 1 | 82945 | 3 | 1.610 | 51518.6 |
330 | 2021-02-02 17:53:05 | coarsens | 1 | 82945 | 3 | 1.343 | 61761.0 |
329 | 2021-01-29 21:32:29 | coarsens | 1 | 82945 | 3 | 1.450 | 57203.4 |
328 | 2021-01-01 15:36:45 | coarsens | 1 | 82945 | 3 | 1.516 | 54713.1 |
327 | 2020-12-05 06:29:15 | coarsens | 1 | 82945 | 3 | 1.296 | 64000.8 |
326 | 2020-11-17 02:24:00 | coarsens | 1 | 82945 | 3 | 1.313 | 63172.1 |