History of Dictionary Searches using Damerau-Levenshtein distance in T-SQL
Fuzzy-string Searches
(up to 100 most recent)
for
"precisions"
Num | Started At (CA time) | Searched Word | Change Limit | Words Checked | Words Matched | Seconds | Words Per Sec |
483 | 2025-09-16 03:21:15 | precisions | 1 | 67641 | 5 | 1.173 | 57665.0 |
482 | 2025-09-15 13:28:35 | precisions | 1 | 67641 | 5 | 1.220 | 55443.4 |
481 | 2025-09-09 08:18:35 | precisions | 1 | 67641 | 5 | 1.220 | 55443.4 |
480 | 2025-09-08 22:31:26 | precisions | 1 | 67641 | 5 | 1.093 | 61885.6 |
479 | 2025-09-05 15:38:29 | precisions | 1 | 67641 | 5 | 1.080 | 62630.6 |
478 | 2025-09-02 08:34:12 | precisions | 1 | 67641 | 5 | 1.173 | 57665.0 |
477 | 2025-08-30 00:48:33 | precisions | 1 | 67641 | 5 | 1.233 | 54858.9 |
476 | 2025-08-28 03:29:16 | precisions | 1 | 67641 | 5 | 1.266 | 53428.9 |
475 | 2025-08-23 08:48:20 | precisions | 4 | 161450 | 403 | 41.923 | 3851.1 |
474 | 2025-08-23 02:49:55 | precisions | 1 | 67641 | 5 | 8.486 | 7970.9 |
473 | 2025-08-20 01:15:08 | precisions | 1 | 67641 | 5 | 2.250 | 30062.7 |
472 | 2025-08-19 13:22:00 | precisions | 4 | 161450 | 403 | 27.733 | 5821.6 |
471 | 2025-08-19 12:26:46 | precisions | 1 | 67641 | 5 | 5.376 | 12582.0 |
470 | 2025-08-17 07:04:53 | precisions | 4 | 161450 | 403 | 27.140 | 5948.8 |
469 | 2025-08-17 04:40:57 | precisions | 4 | 161450 | 403 | 56.766 | 2844.1 |
468 | 2025-08-16 16:37:11 | precisions | 1 | 67641 | 5 | 1.140 | 59334.2 |
467 | 2025-08-15 07:23:35 | precisions | 4 | 161450 | 403 | 43.330 | 3726.1 |
466 | 2025-08-11 23:33:15 | precisions | 4 | 161450 | 403 | 28.110 | 5743.5 |
465 | 2025-08-09 13:31:45 | precisions | 1 | 67641 | 5 | 5.076 | 13325.7 |
464 | 2025-08-02 03:20:30 | precisions | 1 | 67641 | 5 | 2.736 | 24722.6 |
463 | 2025-07-29 02:30:24 | precisions | 1 | 67641 | 5 | 6.266 | 10794.9 |
462 | 2025-07-24 06:15:50 | precisions | 1 | 67641 | 5 | 2.923 | 23141.0 |
461 | 2025-07-23 16:35:53 | precisions | 1 | 67641 | 5 | 5.830 | 11602.2 |
460 | 2025-07-23 16:09:34 | precisions | 1 | 67641 | 5 | 3.593 | 18825.8 |
459 | 2025-07-23 01:29:47 | precisions | 1 | 67641 | 5 | 5.076 | 13325.7 |
458 | 2025-07-22 15:49:55 | precisions | 1 | 67641 | 5 | 5.796 | 11670.3 |
457 | 2025-07-22 12:19:46 | precisions | 1 | 67641 | 5 | 7.593 | 8908.3 |
456 | 2025-07-22 12:19:26 | precisions | 1 | 67641 | 5 | 3.156 | 21432.5 |
455 | 2025-07-21 14:32:15 | precisions | 4 | 161450 | 403 | 22.126 | 7296.8 |
454 | 2025-07-20 22:02:14 | precisions | 4 | 161450 | 403 | 11.720 | 13775.6 |
453 | 2025-07-20 20:57:04 | precisions | 1 | 67641 | 5 | 1.263 | 53555.8 |
452 | 2025-07-20 20:55:29 | precisions | 1 | 67641 | 5 | 1.123 | 60232.4 |
451 | 2025-07-18 17:52:42 | precisions | 4 | 161450 | 403 | 77.160 | 2092.4 |
450 | 2025-07-18 04:32:47 | precisions | 4 | 161450 | 403 | 30.203 | 5345.5 |
449 | 2025-07-17 22:47:51 | precisions | 4 | 161450 | 403 | 53.940 | 2993.1 |
448 | 2025-07-17 09:14:28 | precisions | 4 | 161450 | 403 | 44.046 | 3665.5 |
447 | 2025-07-16 11:44:36 | precisions | 4 | 161450 | 403 | 44.766 | 3606.5 |
446 | 2025-07-11 12:35:29 | precisions | 4 | 161450 | 403 | 81.426 | 1982.8 |
445 | 2025-07-11 10:21:30 | precisions | 2 | 108824 | 18 | 16.953 | 6419.2 |
444 | 2025-07-10 14:10:11 | precisions | 4 | 161450 | 403 | 52.626 | 3067.9 |
443 | 2025-07-10 13:45:51 | precisions | 1 | 67641 | 5 | 1.906 | 35488.5 |
442 | 2025-07-10 12:38:58 | precisions | 1 | 67641 | 5 | 6.030 | 11217.4 |
441 | 2025-07-09 23:47:28 | precisions | 4 | 161450 | 403 | 54.253 | 2975.9 |
440 | 2025-07-09 08:43:34 | precisions | 4 | 161450 | 403 | 17.516 | 9217.3 |
439 | 2025-07-08 14:26:43 | precisions | 4 | 161450 | 403 | 50.453 | 3200.0 |
438 | 2025-07-07 07:53:38 | precisions | 4 | 161450 | 403 | 45.596 | 3540.9 |
437 | 2025-07-02 03:23:14 | precisions | 1 | 67641 | 5 | 5.076 | 13325.7 |
436 | 2025-06-22 04:33:25 | precisions | 1 | 67641 | 5 | 8.200 | 8248.9 |
435 | 2025-06-09 16:02:30 | precisions | 1 | 67641 | 5 | 1.203 | 56226.9 |
434 | 2025-06-08 09:03:52 | precisions | 4 | 161450 | 403 | 50.460 | 3199.6 |
433 | 2025-06-06 10:59:50 | precisions | 4 | 161450 | 403 | 83.536 | 1932.7 |
432 | 2025-06-06 09:42:34 | precisions | 4 | 161450 | 403 | 69.973 | 2307.3 |
431 | 2025-06-06 02:36:37 | precisions | 1 | 67641 | 5 | 3.090 | 21890.3 |
430 | 2025-06-05 22:54:12 | precisions | 4 | 161450 | 403 | 79.830 | 2022.4 |
429 | 2025-06-04 04:15:27 | precisions | 4 | 161450 | 403 | 37.236 | 4335.9 |
428 | 2025-06-02 22:22:12 | precisions | 1 | 67641 | 5 | 1.250 | 54112.8 |
427 | 2025-06-01 09:56:32 | precisions | 1 | 67641 | 5 | 2.920 | 23164.7 |
426 | 2025-05-31 12:23:47 | precisions | 1 | 67641 | 5 | 3.783 | 17880.3 |
425 | 2025-05-28 09:42:15 | precisions | 1 | 67641 | 5 | 1.250 | 54112.8 |
424 | 2025-05-26 17:12:54 | precisions | 1 | 67641 | 5 | 2.733 | 24749.7 |
423 | 2025-05-21 05:28:17 | precisions | 1 | 67641 | 5 | 1.216 | 55625.8 |
422 | 2025-05-18 14:19:00 | precisions | 1 | 67641 | 5 | 4.110 | 16457.7 |
421 | 2025-05-04 19:55:05 | precisions | 3 | 140603 | 76 | 19.156 | 7339.9 |
420 | 2025-05-03 16:21:25 | precisions | 3 | 140603 | 76 | 6.486 | 21677.9 |
419 | 2025-05-03 04:42:21 | precisions | 2 | 108824 | 18 | 24.376 | 4464.4 |
418 | 2025-05-01 08:00:37 | precisions | 3 | 140603 | 76 | 26.003 | 5407.2 |
417 | 2025-05-01 07:44:21 | precisions | 2 | 108824 | 18 | 16.436 | 6621.1 |
416 | 2025-05-01 03:05:36 | precisions | 3 | 140603 | 76 | 33.923 | 4144.8 |
415 | 2025-04-29 03:20:29 | precisions | 1 | 67641 | 5 | 3.703 | 18266.5 |
414 | 2025-04-23 10:14:26 | precisions | 1 | 67641 | 5 | 3.140 | 21541.7 |
413 | 2025-04-10 22:42:06 | precisions | 1 | 67641 | 5 | 3.063 | 22083.3 |
412 | 2025-03-27 19:16:58 | precisions | 3 | 140603 | 76 | 33.580 | 4187.1 |
411 | 2025-03-24 10:11:46 | precisions | 3 | 140603 | 76 | 32.936 | 4269.0 |
410 | 2025-03-23 16:45:33 | precisions | 3 | 140603 | 76 | 35.736 | 3934.5 |
409 | 2025-03-23 10:12:48 | precisions | 2 | 108824 | 18 | 10.953 | 9935.5 |
408 | 2025-03-22 04:59:08 | precisions | 1 | 67641 | 5 | 6.673 | 10136.5 |
407 | 2025-03-21 03:03:41 | precisions | 3 | 140603 | 76 | 29.750 | 4726.2 |
406 | 2025-03-20 12:49:30 | precisions | 1 | 67641 | 5 | 4.876 | 13872.2 |
405 | 2025-03-20 04:49:52 | precisions | 1 | 67641 | 5 | 5.153 | 13126.5 |
404 | 2025-03-11 12:01:55 | precisions | 3 | 140603 | 76 | 22.046 | 6377.7 |
403 | 2025-03-06 17:38:43 | precisions | 1 | 67641 | 5 | 4.236 | 15968.1 |
402 | 2025-03-04 23:04:20 | precisions | 3 | 140603 | 76 | 31.626 | 4445.8 |
401 | 2025-03-04 16:24:27 | precisions | 3 | 140603 | 76 | 40.500 | 3471.7 |
400 | 2025-02-20 06:21:16 | precisions | 3 | 140603 | 76 | 31.656 | 4441.6 |
399 | 2025-02-20 06:18:31 | precisions | 1 | 67641 | 5 | 5.940 | 11387.4 |
398 | 2025-02-19 12:25:48 | precisions | 3 | 140603 | 76 | 33.406 | 4208.9 |
397 | 2025-02-18 21:09:28 | precisions | 3 | 140603 | 76 | 30.893 | 4551.3 |
396 | 2025-02-18 21:08:35 | precisions | 1 | 67641 | 5 | 5.703 | 11860.6 |
395 | 2025-02-16 09:48:17 | precisions | 3 | 140603 | 76 | 34.330 | 4095.6 |
394 | 2025-02-16 09:48:15 | precisions | 3 | 140603 | 76 | 34.343 | 4094.1 |
393 | 2025-02-16 09:48:11 | precisions | 2 | 108824 | 18 | 15.016 | 7247.2 |
392 | 2025-02-16 09:45:31 | precisions | 1 | 67641 | 5 | 4.796 | 14103.6 |
391 | 2025-02-15 18:00:04 | precisions | 3 | 140603 | 76 | 44.280 | 3175.3 |
390 | 2025-02-15 18:00:00 | precisions | 2 | 108824 | 18 | 16.046 | 6782.0 |
389 | 2025-02-15 17:59:28 | precisions | 3 | 140603 | 76 | 32.053 | 4386.6 |
388 | 2025-02-15 17:54:17 | precisions | 1 | 67641 | 5 | 1.220 | 55443.4 |
387 | 2025-01-22 03:53:08 | precisions | 2 | 108824 | 18 | 22.110 | 4921.9 |
386 | 2025-01-20 03:13:24 | precisions | 3 | 140603 | 76 | 42.673 | 3294.9 |
385 | 2025-01-19 04:29:22 | precisions | 2 | 108824 | 18 | 13.640 | 7978.3 |
384 | 2025-01-19 04:25:25 | precisions | 1 | 67641 | 5 | 5.580 | 12122.0 |