History of Dictionary Searches using Damerau-Levenshtein distance in T-SQL
Fuzzy-string Searches
(up to 100 most recent)
for
"predictive"
| Num | Started At (CA time) | Searched Word | Change Limit | Words Checked | Words Matched | Seconds | Words Per Sec |
| 524 | 2025-11-05 08:08:28 | predictive | 3 | 140603 | 46 | 6.906 | 20359.5 |
| 523 | 2025-11-05 01:48:43 | predictive | 4 | 161450 | 199 | 12.546 | 12868.6 |
| 522 | 2025-11-04 16:34:48 | predictive | 4 | 161450 | 199 | 10.110 | 15969.3 |
| 521 | 2025-10-31 18:56:40 | predictive | 3 | 140603 | 46 | 6.576 | 21381.2 |
| 520 | 2025-10-29 06:36:52 | predictive | 3 | 140603 | 46 | 6.766 | 20780.8 |
| 519 | 2025-10-28 16:17:06 | predictive | 3 | 140603 | 46 | 8.440 | 16659.1 |
| 518 | 2025-10-28 07:13:18 | predictive | 2 | 108824 | 7 | 2.906 | 37448.0 |
| 517 | 2025-10-28 06:23:29 | predictive | 4 | 161450 | 199 | 12.093 | 13350.7 |
| 516 | 2025-10-27 23:47:57 | predictive | 2 | 108824 | 7 | 3.486 | 31217.4 |
| 515 | 2025-10-26 22:02:48 | predictive | 1 | 67641 | 2 | 1.280 | 52844.5 |
| 514 | 2025-10-25 21:53:35 | predictive | 1 | 67641 | 2 | 1.170 | 57812.8 |
| 513 | 2025-09-12 03:03:44 | predictive | 3 | 140603 | 46 | 7.063 | 19907.0 |
| 512 | 2025-09-10 23:37:04 | predictive | 2 | 108824 | 7 | 3.216 | 33838.3 |
| 511 | 2025-09-10 02:58:10 | predictive | 4 | 161450 | 199 | 11.143 | 14488.9 |
| 510 | 2025-09-10 01:24:44 | predictive | 2 | 108824 | 7 | 3.156 | 34481.6 |
| 509 | 2025-09-05 16:31:11 | predictive | 3 | 140603 | 46 | 5.860 | 23993.7 |
| 508 | 2025-09-05 12:07:43 | predictive | 1 | 67641 | 2 | 1.186 | 57032.9 |
| 507 | 2025-08-19 00:21:44 | predictive | 1 | 67641 | 2 | 4.420 | 15303.4 |
| 506 | 2025-08-18 21:09:04 | predictive | 1 | 67641 | 2 | 4.906 | 13787.4 |
| 505 | 2025-08-09 11:00:44 | predictive | 1 | 67641 | 2 | 7.903 | 8558.9 |
| 504 | 2025-08-09 01:44:31 | predictive | 1 | 67641 | 2 | 4.343 | 15574.7 |
| 503 | 2025-07-27 16:06:35 | predictive | 1 | 67641 | 2 | 2.826 | 23935.2 |
| 502 | 2025-07-26 11:53:28 | predictive | 1 | 67641 | 2 | 1.170 | 57812.8 |
| 501 | 2025-07-24 03:54:07 | predictive | 1 | 67641 | 2 | 4.110 | 16457.7 |
| 500 | 2025-07-15 06:41:28 | predictive | 3 | 140603 | 46 | 29.283 | 4801.5 |
| 499 | 2025-07-14 02:53:01 | predictive | 2 | 108824 | 7 | 7.970 | 13654.2 |
| 498 | 2025-07-11 20:41:50 | predictive | 2 | 108824 | 7 | 23.126 | 4705.7 |
| 497 | 2025-07-11 19:26:08 | predictive | 3 | 140603 | 46 | 17.186 | 8181.3 |
| 496 | 2025-07-11 15:19:11 | predictive | 2 | 108824 | 7 | 20.236 | 5377.7 |
| 495 | 2025-07-11 02:27:39 | predictive | 1 | 67641 | 2 | 6.016 | 11243.5 |
| 494 | 2025-07-10 09:37:25 | predictive | 1 | 67641 | 2 | 1.170 | 57812.8 |
| 493 | 2025-07-05 12:59:54 | predictive | 2 | 108824 | 7 | 8.766 | 12414.3 |
| 492 | 2025-07-02 00:55:24 | predictive | 2 | 108824 | 7 | 12.736 | 8544.6 |
| 491 | 2025-06-30 23:05:26 | predictive | 1 | 67641 | 2 | 1.250 | 54112.8 |
| 490 | 2025-06-26 00:11:39 | predictive | 1 | 67641 | 2 | 4.716 | 14342.9 |
| 489 | 2025-06-24 21:35:05 | predictive | 1 | 67641 | 2 | 1.170 | 57812.8 |
| 488 | 2025-06-24 15:01:46 | predictive | 1 | 67641 | 2 | 5.013 | 13493.1 |
| 487 | 2025-06-16 02:15:00 | predictive | 1 | 67641 | 2 | 6.093 | 11101.4 |
| 486 | 2025-06-13 05:23:10 | predictive | 3 | 140603 | 46 | 35.020 | 4014.9 |
| 485 | 2025-06-12 01:21:03 | predictive | 2 | 108824 | 7 | 10.483 | 10381.0 |
| 484 | 2025-06-10 20:38:45 | predictive | 1 | 67641 | 2 | 1.123 | 60232.4 |
| 483 | 2025-06-08 10:53:58 | predictive | 3 | 140603 | 46 | 34.190 | 4112.4 |
| 482 | 2025-06-08 03:55:50 | predictive | 4 | 161450 | 199 | 61.363 | 2631.1 |
| 481 | 2025-06-06 08:32:10 | predictive | 3 | 140603 | 46 | 24.390 | 5764.8 |
| 480 | 2025-06-02 15:39:45 | predictive | 3 | 140603 | 46 | 37.923 | 3707.6 |
| 479 | 2025-06-02 00:25:45 | predictive | 1 | 67641 | 2 | 5.686 | 11896.1 |
| 478 | 2025-05-31 13:50:52 | predictive | 4 | 161450 | 199 | 55.176 | 2926.1 |
| 477 | 2025-05-31 00:15:22 | predictive | 3 | 140603 | 46 | 27.796 | 5058.4 |
| 476 | 2025-05-30 19:55:20 | predictive | 4 | 161450 | 199 | 59.706 | 2704.1 |
| 475 | 2025-05-28 20:07:43 | predictive | 4 | 161450 | 199 | 35.300 | 4573.7 |
| 474 | 2025-05-28 18:00:58 | predictive | 4 | 161450 | 199 | 11.186 | 14433.2 |
| 473 | 2025-05-28 17:41:37 | predictive | 3 | 140603 | 46 | 8.170 | 17209.7 |
| 472 | 2025-05-28 03:02:12 | predictive | 4 | 161450 | 199 | 10.406 | 15515.1 |
| 471 | 2025-05-25 13:28:25 | predictive | 1 | 67641 | 2 | 1.156 | 58513.0 |
| 470 | 2025-05-23 23:55:10 | predictive | 1 | 67641 | 2 | 4.873 | 13880.8 |
| 469 | 2025-05-20 15:31:35 | predictive | 1 | 67641 | 2 | 8.093 | 8358.0 |
| 468 | 2025-05-02 01:32:48 | predictive | 1 | 67641 | 2 | 6.110 | 11070.5 |
| 467 | 2025-04-16 13:54:08 | predictive | 1 | 67641 | 2 | 6.190 | 10927.5 |
| 466 | 2025-04-04 05:52:09 | predictive | 4 | 161450 | 199 | 52.910 | 3051.4 |
| 465 | 2025-04-01 00:50:26 | predictive | 1 | 67641 | 2 | 3.530 | 19161.8 |
| 464 | 2025-03-29 15:16:46 | predictive | 2 | 108824 | 7 | 14.000 | 7773.1 |
| 463 | 2025-03-26 21:32:12 | predictive | 4 | 161450 | 199 | 66.553 | 2425.9 |
| 462 | 2025-03-26 21:14:49 | predictive | 4 | 161450 | 199 | 36.033 | 4480.6 |
| 461 | 2025-03-25 19:01:41 | predictive | 2 | 108824 | 7 | 17.173 | 6336.9 |
| 460 | 2025-03-25 16:21:31 | predictive | 4 | 161450 | 199 | 68.566 | 2354.7 |
| 459 | 2025-03-25 01:07:06 | predictive | 1 | 67641 | 2 | 2.983 | 22675.5 |
| 458 | 2025-03-24 01:54:16 | predictive | 1 | 67641 | 2 | 4.530 | 14931.8 |
| 457 | 2025-03-24 00:18:14 | predictive | 3 | 140603 | 46 | 7.220 | 19474.1 |
| 456 | 2025-03-19 21:43:01 | predictive | 1 | 67641 | 2 | 5.533 | 12225.0 |
| 455 | 2025-03-15 14:53:42 | predictive | 3 | 140603 | 46 | 36.690 | 3832.2 |
| 454 | 2025-03-15 14:53:46 | predictive | 3 | 140603 | 46 | 19.046 | 7382.3 |
| 453 | 2025-03-15 14:53:37 | predictive | 2 | 108824 | 7 | 16.376 | 6645.3 |
| 452 | 2025-03-15 14:46:57 | predictive | 1 | 67641 | 2 | 2.406 | 28113.5 |
| 451 | 2025-03-09 09:57:05 | predictive | 1 | 67641 | 2 | 5.250 | 12884.0 |
| 450 | 2025-02-14 15:34:39 | predictive | 1 | 67641 | 2 | 5.563 | 12159.1 |
| 449 | 2025-02-12 23:43:34 | predictive | 3 | 140603 | 46 | 42.926 | 3275.5 |
| 448 | 2025-02-12 20:09:44 | predictive | 3 | 140603 | 46 | 24.516 | 5735.2 |
| 447 | 2025-02-12 18:08:51 | predictive | 3 | 140603 | 46 | 33.673 | 4175.5 |
| 446 | 2025-02-12 18:08:43 | predictive | 3 | 140603 | 46 | 31.030 | 4531.2 |
| 445 | 2025-02-12 18:08:43 | predictive | 2 | 108824 | 7 | 15.953 | 6821.5 |
| 444 | 2025-02-12 15:31:22 | predictive | 3 | 140603 | 46 | 36.473 | 3855.0 |
| 443 | 2025-02-12 15:31:19 | predictive | 2 | 108824 | 7 | 20.050 | 5427.6 |
| 442 | 2025-02-12 13:59:33 | predictive | 1 | 67641 | 2 | 3.140 | 21541.7 |
| 441 | 2025-02-10 12:41:22 | predictive | 1 | 67641 | 2 | 4.110 | 16457.7 |
| 440 | 2025-02-04 20:17:50 | predictive | 1 | 67641 | 2 | 1.186 | 57032.9 |
| 439 | 2025-01-23 00:34:21 | predictive | 1 | 67641 | 2 | 8.406 | 8046.8 |
| 438 | 2025-01-11 23:38:33 | predictive | 1 | 67641 | 2 | 3.110 | 21749.5 |
| 437 | 2025-01-07 11:24:45 | predictive | 3 | 140603 | 46 | 37.610 | 3738.4 |
| 436 | 2025-01-07 11:24:43 | predictive | 3 | 140603 | 46 | 38.890 | 3615.4 |
| 435 | 2025-01-07 11:24:46 | predictive | 2 | 108824 | 7 | 24.813 | 4385.8 |
| 434 | 2025-01-07 11:24:40 | predictive | 1 | 67641 | 2 | 5.846 | 11570.5 |
| 433 | 2024-12-30 17:45:09 | predictive | 1 | 67641 | 2 | 1.186 | 57032.9 |
| 432 | 2024-12-21 10:24:46 | predictive | 1 | 67641 | 2 | 8.653 | 7817.1 |
| 431 | 2024-12-01 20:11:22 | predictive | 2 | 108824 | 7 | 11.923 | 9127.2 |
| 430 | 2024-11-29 10:25:57 | predictive | 3 | 140603 | 46 | 42.003 | 3347.5 |
| 429 | 2024-11-28 23:45:22 | predictive | 3 | 140603 | 46 | 42.176 | 3333.7 |
| 428 | 2024-11-28 23:45:22 | predictive | 3 | 140603 | 46 | 40.286 | 3490.1 |
| 427 | 2024-11-28 23:45:28 | predictive | 2 | 108824 | 7 | 23.393 | 4652.0 |
| 426 | 2024-11-28 22:08:16 | predictive | 1 | 67641 | 2 | 1.670 | 40503.6 |
| 425 | 2024-11-26 10:49:38 | predictive | 1 | 67641 | 2 | 1.063 | 63632.2 |