History of Dictionary Searches using Damerau-Levenshtein distance in T-SQL
Fuzzy-string Searches
(up to 100 most recent)
for
"prediction"
| Num | Started At (CA time) | Searched Word | Change Limit | Words Checked | Words Matched | Seconds | Words Per Sec |
| 478 | 2025-08-26 14:39:21 | prediction | 1 | 67641 | 3 | 1.173 | 57665.0 |
| 477 | 2025-08-09 22:51:28 | prediction | 1 | 67641 | 3 | 2.376 | 28468.4 |
| 476 | 2025-08-09 15:27:09 | prediction | 1 | 67641 | 3 | 3.310 | 20435.3 |
| 475 | 2025-08-04 12:22:48 | prediction | 1 | 67641 | 3 | 3.076 | 21989.9 |
| 474 | 2025-08-03 02:20:34 | prediction | 2 | 108824 | 15 | 12.800 | 8501.9 |
| 473 | 2025-08-03 02:18:49 | prediction | 3 | 140603 | 77 | 34.033 | 4131.4 |
| 472 | 2025-08-01 14:42:12 | prediction | 1 | 67641 | 3 | 5.826 | 11610.2 |
| 471 | 2025-07-30 22:31:25 | prediction | 1 | 67641 | 3 | 1.313 | 51516.4 |
| 470 | 2025-07-24 03:37:15 | prediction | 1 | 67641 | 3 | 5.576 | 12130.7 |
| 469 | 2025-07-22 15:37:44 | prediction | 1 | 67641 | 3 | 7.940 | 8519.0 |
| 468 | 2025-07-22 15:01:53 | prediction | 1 | 67641 | 3 | 3.250 | 20812.6 |
| 467 | 2025-07-18 21:48:32 | prediction | 1 | 67641 | 3 | 6.890 | 9817.3 |
| 466 | 2025-07-18 00:39:07 | prediction | 1 | 67641 | 3 | 3.453 | 19589.1 |
| 465 | 2025-07-11 07:15:49 | prediction | 1 | 67641 | 3 | 6.733 | 10046.2 |
| 464 | 2025-07-10 19:09:58 | prediction | 1 | 67641 | 3 | 5.766 | 11731.0 |
| 463 | 2025-07-09 12:08:56 | prediction | 1 | 67641 | 3 | 7.093 | 9536.3 |
| 462 | 2025-07-03 13:45:42 | prediction | 1 | 67641 | 3 | 2.640 | 25621.6 |
| 461 | 2025-06-17 18:24:32 | prediction | 1 | 67641 | 3 | 1.280 | 52844.5 |
| 460 | 2025-06-11 12:21:13 | prediction | 3 | 140603 | 77 | 29.410 | 4780.8 |
| 459 | 2025-06-10 09:38:33 | prediction | 3 | 140603 | 77 | 23.236 | 6051.1 |
| 458 | 2025-06-10 05:07:44 | prediction | 3 | 140603 | 77 | 40.453 | 3475.7 |
| 457 | 2025-06-10 02:25:19 | prediction | 1 | 67641 | 3 | 4.936 | 13703.6 |
| 456 | 2025-06-09 23:13:21 | prediction | 3 | 140603 | 77 | 32.316 | 4350.9 |
| 455 | 2025-06-08 02:32:28 | prediction | 3 | 140603 | 77 | 35.486 | 3962.2 |
| 454 | 2025-06-07 23:15:27 | prediction | 4 | 161450 | 318 | 55.800 | 2893.4 |
| 453 | 2025-06-06 22:24:51 | prediction | 1 | 67641 | 3 | 1.170 | 57812.8 |
| 452 | 2025-06-06 21:26:00 | prediction | 1 | 67641 | 3 | 2.830 | 23901.4 |
| 451 | 2025-05-31 21:23:53 | prediction | 1 | 67641 | 3 | 3.000 | 22547.0 |
| 450 | 2025-05-27 12:05:41 | prediction | 1 | 67641 | 3 | 3.250 | 20812.6 |
| 449 | 2025-05-20 02:31:56 | prediction | 1 | 67641 | 3 | 8.126 | 8324.0 |
| 448 | 2025-05-17 23:13:53 | prediction | 1 | 67641 | 3 | 2.780 | 24331.3 |
| 447 | 2025-05-09 19:56:11 | prediction | 1 | 67641 | 3 | 5.843 | 11576.4 |
| 446 | 2025-05-09 02:26:18 | prediction | 1 | 67641 | 3 | 1.126 | 60071.9 |
| 445 | 2025-05-08 16:02:48 | prediction | 1 | 67641 | 3 | 7.830 | 8638.7 |
| 444 | 2025-05-05 23:11:28 | prediction | 4 | 161450 | 318 | 45.176 | 3573.8 |
| 443 | 2025-05-05 21:50:39 | prediction | 1 | 67641 | 3 | 3.640 | 18582.7 |
| 442 | 2025-05-04 23:31:59 | prediction | 4 | 161450 | 318 | 47.876 | 3372.3 |
| 441 | 2025-05-04 23:11:45 | prediction | 4 | 161450 | 318 | 61.596 | 2621.1 |
| 440 | 2025-05-04 12:24:13 | prediction | 4 | 161450 | 318 | 58.380 | 2765.5 |
| 439 | 2025-05-03 12:13:51 | prediction | 3 | 140603 | 77 | 7.063 | 19907.0 |
| 438 | 2025-05-02 19:23:19 | prediction | 4 | 161450 | 318 | 11.953 | 13507.1 |
| 437 | 2025-04-30 05:35:21 | prediction | 4 | 161450 | 318 | 59.286 | 2723.2 |
| 436 | 2025-04-30 00:07:53 | prediction | 2 | 108824 | 15 | 16.813 | 6472.6 |
| 435 | 2025-04-29 09:59:32 | prediction | 3 | 140603 | 77 | 6.313 | 22272.0 |
| 434 | 2025-04-26 11:56:34 | prediction | 3 | 140603 | 77 | 41.643 | 3376.4 |
| 433 | 2025-04-26 02:46:55 | prediction | 2 | 108824 | 15 | 15.750 | 6909.5 |
| 432 | 2025-04-25 13:51:35 | prediction | 1 | 67641 | 3 | 3.000 | 22547.0 |
| 431 | 2025-04-22 15:26:52 | prediction | 1 | 67641 | 3 | 1.186 | 57032.9 |
| 430 | 2025-04-20 00:28:49 | prediction | 1 | 67641 | 3 | 5.390 | 12549.4 |
| 429 | 2025-04-03 21:11:29 | prediction | 1 | 67641 | 3 | 2.796 | 24192.1 |
| 428 | 2025-03-29 00:10:47 | prediction | 1 | 67641 | 3 | 5.436 | 12443.2 |
| 427 | 2025-03-23 18:16:46 | prediction | 2 | 108824 | 15 | 15.343 | 7092.7 |
| 426 | 2025-03-23 04:20:59 | prediction | 2 | 108824 | 15 | 15.516 | 7013.7 |
| 425 | 2025-03-22 15:34:18 | prediction | 1 | 67641 | 3 | 3.390 | 19953.1 |
| 424 | 2025-03-20 01:28:58 | prediction | 1 | 67641 | 3 | 5.376 | 12582.0 |
| 423 | 2025-03-18 13:32:40 | prediction | 2 | 108824 | 15 | 13.733 | 7924.3 |
| 422 | 2025-03-15 14:53:02 | prediction | 2 | 108824 | 15 | 15.516 | 7013.7 |
| 421 | 2025-03-14 23:25:02 | prediction | 1 | 67641 | 3 | 4.963 | 13629.1 |
| 420 | 2025-03-14 08:37:54 | prediction | 1 | 67641 | 3 | 3.860 | 17523.6 |
| 419 | 2025-03-10 19:34:17 | prediction | 3 | 140603 | 77 | 31.163 | 4511.9 |
| 418 | 2025-03-09 21:58:48 | prediction | 2 | 108824 | 15 | 8.186 | 13293.9 |
| 417 | 2025-03-09 21:56:06 | prediction | 1 | 67641 | 3 | 7.313 | 9249.4 |
| 416 | 2025-03-09 05:55:37 | prediction | 3 | 140603 | 77 | 33.376 | 4212.7 |
| 415 | 2025-03-06 15:36:08 | prediction | 3 | 140603 | 77 | 31.940 | 4402.1 |
| 414 | 2025-03-06 10:25:35 | prediction | 3 | 140603 | 77 | 34.376 | 4090.2 |
| 413 | 2025-03-05 07:16:24 | prediction | 3 | 140603 | 77 | 19.610 | 7170.0 |
| 412 | 2025-02-28 21:09:10 | prediction | 1 | 67641 | 3 | 5.360 | 12619.6 |
| 411 | 2025-02-24 09:52:59 | prediction | 2 | 108824 | 15 | 6.813 | 15973.0 |
| 410 | 2025-02-04 16:28:44 | prediction | 2 | 108824 | 15 | 16.593 | 6558.4 |
| 409 | 2025-02-03 05:14:58 | prediction | 2 | 108824 | 15 | 14.660 | 7423.2 |
| 408 | 2025-02-03 05:13:09 | prediction | 1 | 67641 | 3 | 2.890 | 23405.2 |
| 407 | 2025-02-03 05:11:20 | prediction | 3 | 140603 | 77 | 37.863 | 3713.5 |
| 406 | 2025-02-02 02:43:42 | prediction | 3 | 140603 | 77 | 36.206 | 3883.4 |
| 405 | 2025-02-02 02:43:53 | prediction | 2 | 108824 | 15 | 21.766 | 4999.7 |
| 404 | 2025-02-02 02:35:20 | prediction | 1 | 67641 | 3 | 5.626 | 12022.9 |
| 403 | 2025-01-30 12:59:00 | prediction | 4 | 161450 | 318 | 70.176 | 2300.6 |
| 402 | 2025-01-30 04:54:02 | prediction | 4 | 161450 | 318 | 57.276 | 2818.8 |
| 401 | 2025-01-30 04:33:12 | prediction | 4 | 161450 | 318 | 51.156 | 3156.0 |
| 400 | 2025-01-29 09:35:06 | prediction | 4 | 161450 | 318 | 72.020 | 2241.7 |
| 399 | 2025-01-26 07:18:59 | prediction | 4 | 161450 | 318 | 42.650 | 3785.5 |
| 398 | 2025-01-26 01:56:14 | prediction | 2 | 108824 | 15 | 8.266 | 13165.3 |
| 397 | 2025-01-26 01:55:15 | prediction | 1 | 67641 | 3 | 5.906 | 11452.9 |
| 396 | 2025-01-24 02:43:35 | prediction | 3 | 140603 | 77 | 25.283 | 5561.2 |
| 395 | 2025-01-20 05:01:27 | prediction | 1 | 67641 | 3 | 3.750 | 18037.6 |
| 394 | 2025-01-02 19:00:46 | prediction | 1 | 67641 | 3 | 1.376 | 49157.7 |
| 393 | 2025-01-02 01:26:21 | prediction | 2 | 108824 | 15 | 16.250 | 6696.9 |
| 392 | 2025-01-02 01:26:13 | prediction | 3 | 140603 | 77 | 20.296 | 6927.6 |
| 391 | 2025-01-01 10:34:48 | prediction | 2 | 108824 | 15 | 16.923 | 6430.5 |
| 390 | 2025-01-01 10:34:28 | prediction | 1 | 67641 | 3 | 5.483 | 12336.5 |
| 389 | 2024-12-31 20:02:12 | prediction | 3 | 140603 | 77 | 21.690 | 6482.4 |
| 388 | 2024-12-31 10:07:52 | prediction | 4 | 161450 | 318 | 51.673 | 3124.5 |
| 387 | 2024-12-29 23:18:24 | prediction | 4 | 161450 | 318 | 47.300 | 3413.3 |
| 386 | 2024-12-29 19:45:42 | prediction | 4 | 161450 | 318 | 58.956 | 2738.5 |
| 385 | 2024-12-26 19:27:32 | prediction | 3 | 140603 | 77 | 6.343 | 22166.6 |
| 384 | 2024-12-16 12:14:47 | prediction | 1 | 67641 | 3 | 1.860 | 36366.1 |
| 383 | 2024-12-16 00:28:33 | prediction | 1 | 67641 | 3 | 5.423 | 12473.0 |
| 382 | 2024-11-30 01:34:08 | prediction | 1 | 67641 | 3 | 6.923 | 9770.5 |
| 381 | 2024-11-28 23:45:28 | prediction | 2 | 108824 | 15 | 13.446 | 8093.4 |
| 380 | 2024-11-27 17:40:27 | prediction | 3 | 140603 | 77 | 46.766 | 3006.5 |
| 379 | 2024-11-27 17:40:22 | prediction | 3 | 140603 | 77 | 18.000 | 7811.3 |