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 |
455 | 2025-08-29 12:21:33 | coarsest | 1 | 82945 | 2 | 1.470 | 56425.2 |
454 | 2025-08-25 01:05:18 | coarsest | 1 | 82945 | 2 | 5.860 | 14154.4 |
453 | 2025-08-12 11:02:06 | coarsest | 1 | 82945 | 2 | 6.346 | 13070.4 |
452 | 2025-08-10 00:59:26 | coarsest | 2 | 121059 | 19 | 9.873 | 12261.6 |
451 | 2025-08-09 23:36:38 | coarsest | 1 | 82945 | 2 | 2.830 | 29309.2 |
450 | 2025-08-09 23:36:31 | coarsest | 1 | 82945 | 2 | 6.640 | 12491.7 |
449 | 2025-08-09 11:35:18 | coarsest | 1 | 82945 | 2 | 7.733 | 10726.1 |
448 | 2025-08-08 23:01:16 | coarsest | 1 | 82945 | 2 | 4.313 | 19231.4 |
447 | 2025-08-05 19:25:03 | coarsest | 1 | 82945 | 2 | 3.736 | 22201.6 |
446 | 2025-08-05 11:04:25 | coarsest | 1 | 82945 | 2 | 6.436 | 12887.7 |
445 | 2025-07-29 17:59:12 | coarsest | 3 | 146162 | 196 | 56.953 | 2566.4 |
444 | 2025-07-27 20:32:36 | coarsest | 1 | 82945 | 2 | 3.343 | 24811.5 |
443 | 2025-07-25 19:18:11 | coarsest | 1 | 82945 | 2 | 1.593 | 52068.4 |
442 | 2025-07-24 23:19:03 | coarsest | 1 | 82945 | 2 | 5.656 | 14665.0 |
441 | 2025-07-22 09:12:24 | coarsest | 3 | 146162 | 196 | 7.936 | 18417.6 |
440 | 2025-07-19 11:11:46 | coarsest | 3 | 146162 | 196 | 7.800 | 18738.7 |
439 | 2025-07-17 23:27:37 | coarsest | 2 | 121059 | 19 | 8.686 | 13937.3 |
438 | 2025-07-17 21:06:22 | coarsest | 3 | 146162 | 196 | 18.266 | 8001.9 |
437 | 2025-07-17 10:39:33 | coarsest | 2 | 121059 | 19 | 11.203 | 10805.9 |
436 | 2025-07-16 15:56:32 | coarsest | 1 | 82945 | 2 | 1.576 | 52630.1 |
435 | 2025-07-14 05:32:24 | coarsest | 2 | 121059 | 19 | 17.923 | 6754.4 |
434 | 2025-07-12 22:19:56 | coarsest | 2 | 121059 | 19 | 3.936 | 30756.9 |
433 | 2025-07-12 07:48:54 | coarsest | 1 | 82945 | 2 | 1.470 | 56425.2 |
432 | 2025-07-10 20:54:20 | coarsest | 1 | 82945 | 2 | 7.890 | 10512.7 |
431 | 2025-07-08 01:51:57 | coarsest | 1 | 82945 | 2 | 4.080 | 20329.7 |
430 | 2025-07-06 16:01:42 | coarsest | 1 | 82945 | 2 | 1.563 | 53067.8 |
429 | 2025-07-06 11:27:59 | coarsest | 1 | 82945 | 2 | 1.313 | 63172.1 |
428 | 2025-07-02 10:30:35 | coarsest | 1 | 82945 | 2 | 3.266 | 25396.5 |
427 | 2025-06-29 15:25:24 | coarsest | 1 | 82945 | 2 | 1.500 | 55296.7 |
426 | 2025-06-11 11:33:54 | coarsest | 3 | 146162 | 196 | 22.300 | 6554.3 |
425 | 2025-06-10 23:19:40 | coarsest | 3 | 146162 | 196 | 32.826 | 4452.6 |
424 | 2025-06-10 14:27:16 | coarsest | 3 | 146162 | 196 | 49.690 | 2941.5 |
423 | 2025-06-10 10:53:30 | coarsest | 3 | 146162 | 196 | 58.613 | 2493.7 |
422 | 2025-06-08 19:13:21 | coarsest | 3 | 146162 | 196 | 38.346 | 3811.7 |
421 | 2025-06-08 01:31:12 | coarsest | 1 | 82945 | 2 | 6.983 | 11878.1 |
420 | 2025-06-05 21:49:34 | coarsest | 1 | 82945 | 2 | 5.326 | 15573.6 |
419 | 2025-06-05 05:25:28 | coarsest | 1 | 82945 | 2 | 10.846 | 7647.5 |
418 | 2025-06-04 13:11:24 | coarsest | 2 | 121059 | 19 | 14.533 | 8329.9 |
417 | 2025-05-21 10:25:16 | coarsest | 1 | 82945 | 2 | 1.576 | 52630.1 |
416 | 2025-05-20 14:57:07 | coarsest | 1 | 82945 | 2 | 9.250 | 8967.0 |
415 | 2025-05-18 03:17:14 | coarsest | 1 | 82945 | 2 | 5.813 | 14268.9 |
414 | 2025-05-10 22:35:10 | coarsest | 3 | 146162 | 196 | 21.436 | 6818.5 |
413 | 2025-05-10 18:30:25 | coarsest | 3 | 146162 | 196 | 42.766 | 3417.7 |
412 | 2025-05-10 14:26:31 | coarsest | 3 | 146162 | 196 | 39.093 | 3738.8 |
411 | 2025-05-10 10:29:20 | coarsest | 2 | 121059 | 19 | 22.033 | 5494.4 |
410 | 2025-05-08 22:27:14 | coarsest | 3 | 146162 | 196 | 37.626 | 3884.6 |
409 | 2025-05-08 22:23:36 | coarsest | 2 | 121059 | 19 | 3.766 | 32145.2 |
408 | 2025-05-08 08:42:04 | coarsest | 3 | 146162 | 196 | 42.283 | 3456.8 |
407 | 2025-05-07 00:54:38 | coarsest | 1 | 82945 | 2 | 1.500 | 55296.7 |
406 | 2025-05-06 11:38:04 | coarsest | 1 | 82945 | 2 | 7.110 | 11666.0 |
405 | 2025-05-05 22:39:50 | coarsest | 1 | 82945 | 2 | 6.390 | 12980.4 |
404 | 2025-05-02 17:21:12 | coarsest | 1 | 82945 | 2 | 1.546 | 53651.4 |
403 | 2025-05-02 05:19:42 | coarsest | 1 | 82945 | 2 | 7.140 | 11616.9 |
402 | 2025-04-20 14:06:01 | coarsest | 1 | 82945 | 2 | 9.830 | 8437.9 |
401 | 2025-04-15 15:40:33 | coarsest | 1 | 82945 | 2 | 1.330 | 62364.7 |
400 | 2025-04-13 04:13:58 | coarsest | 3 | 146162 | 196 | 8.126 | 17987.0 |
399 | 2025-04-07 23:31:01 | coarsest | 3 | 146162 | 196 | 38.410 | 3805.3 |
398 | 2025-04-04 00:02:31 | coarsest | 2 | 121059 | 19 | 17.596 | 6879.9 |
397 | 2025-04-03 14:44:51 | coarsest | 2 | 121059 | 19 | 3.233 | 37444.8 |
396 | 2025-04-03 14:44:17 | coarsest | 3 | 146162 | 196 | 11.970 | 12210.7 |
395 | 2025-04-02 23:50:18 | coarsest | 1 | 82945 | 2 | 2.203 | 37650.9 |
394 | 2025-04-02 21:55:04 | coarsest | 1 | 82945 | 2 | 1.550 | 53512.9 |
393 | 2025-03-25 19:55:13 | coarsest | 3 | 146162 | 196 | 10.430 | 14013.6 |
392 | 2025-03-25 16:10:11 | coarsest | 3 | 146162 | 196 | 38.656 | 3781.1 |
391 | 2025-03-23 19:01:11 | coarsest | 3 | 146162 | 196 | 36.813 | 3970.4 |
390 | 2025-03-23 09:58:29 | coarsest | 2 | 121059 | 19 | 17.736 | 6825.6 |
389 | 2025-03-22 17:44:27 | coarsest | 2 | 121059 | 19 | 3.563 | 33976.7 |
388 | 2025-03-22 13:19:14 | coarsest | 1 | 82945 | 2 | 4.530 | 18310.2 |
387 | 2025-03-20 19:19:07 | coarsest | 1 | 82945 | 2 | 1.516 | 54713.1 |
386 | 2025-03-20 10:47:31 | coarsest | 1 | 82945 | 2 | 3.483 | 23814.2 |
385 | 2025-03-20 02:29:10 | coarsest | 1 | 82945 | 2 | 3.640 | 22787.1 |
384 | 2025-02-25 18:08:32 | coarsest | 1 | 82945 | 2 | 3.623 | 22894.0 |
383 | 2025-02-11 13:29:40 | coarsest | 3 | 146162 | 196 | 37.766 | 3870.2 |
382 | 2025-02-10 11:10:29 | coarsest | 3 | 146162 | 196 | 38.440 | 3802.3 |
381 | 2025-02-10 07:00:22 | coarsest | 3 | 146162 | 196 | 35.113 | 4162.6 |
380 | 2025-02-09 09:35:50 | coarsest | 3 | 146162 | 196 | 31.580 | 4628.3 |
379 | 2025-02-09 09:24:59 | coarsest | 1 | 82945 | 2 | 1.313 | 63172.1 |
378 | 2025-02-09 03:28:13 | coarsest | 1 | 82945 | 2 | 3.923 | 21143.3 |
377 | 2025-02-07 15:14:08 | coarsest | 1 | 82945 | 2 | 7.016 | 11822.3 |
376 | 2025-02-06 18:23:20 | coarsest | 2 | 121059 | 19 | 22.156 | 5463.9 |
375 | 2025-02-05 03:16:43 | coarsest | 3 | 146162 | 196 | 38.736 | 3773.3 |
374 | 2025-02-01 14:26:16 | coarsest | 2 | 121059 | 19 | 21.126 | 5730.3 |
373 | 2025-02-01 14:25:48 | coarsest | 1 | 82945 | 2 | 10.690 | 7759.1 |
372 | 2025-01-11 19:30:01 | coarsest | 3 | 146162 | 196 | 34.190 | 4275.0 |
371 | 2025-01-09 14:32:51 | coarsest | 3 | 146162 | 196 | 29.986 | 4874.3 |
370 | 2025-01-09 11:33:24 | coarsest | 3 | 146162 | 196 | 53.080 | 2753.6 |
369 | 2025-01-07 17:01:26 | coarsest | 3 | 146162 | 196 | 50.656 | 2885.4 |
368 | 2025-01-07 17:01:26 | coarsest | 2 | 121059 | 19 | 12.626 | 9588.1 |
367 | 2025-01-07 14:49:36 | coarsest | 1 | 82945 | 2 | 4.470 | 18555.9 |
366 | 2025-01-01 18:16:47 | coarsest | 1 | 82945 | 2 | 6.780 | 12233.8 |
365 | 2024-12-29 17:42:04 | coarsest | 1 | 82945 | 2 | 6.856 | 12098.2 |
364 | 2024-12-28 13:22:16 | coarsest | 1 | 82945 | 2 | 7.360 | 11269.7 |
363 | 2024-11-09 15:54:24 | coarsest | 1 | 82945 | 2 | 6.063 | 13680.5 |
362 | 2024-11-08 05:27:46 | coarsest | 1 | 82945 | 2 | 5.500 | 15080.9 |
361 | 2024-10-29 02:53:21 | coarsest | 1 | 82945 | 2 | 5.423 | 15295.0 |
360 | 2024-10-28 20:17:42 | coarsest | 1 | 82945 | 2 | 5.563 | 14910.1 |
359 | 2024-10-10 09:49:52 | coarsest | 1 | 82945 | 2 | 4.030 | 20581.9 |
358 | 2024-10-08 17:44:33 | coarsest | 1 | 82945 | 2 | 5.626 | 14743.2 |
357 | 2024-09-27 10:12:20 | coarsest | 1 | 82945 | 2 | 13.360 | 6208.5 |
356 | 2024-09-12 23:38:05 | coarsest | 2 | 121059 | 19 | 25.003 | 4841.8 |