History of Dictionary Searches using Damerau-Levenshtein distance in T-SQL
Fuzzy-string Searches
(up to 100 most recent)
for
"variables"
| Num | Started At (CA time) | Searched Word | Change Limit | Words Checked | Words Matched | Seconds | Words Per Sec |
| 481 | 2025-10-30 06:27:21 | variables | 4 | 165329 | 728 | 12.126 | 13634.3 |
| 480 | 2025-10-19 15:33:45 | variables | 1 | 81242 | 2 | 1.360 | 59736.8 |
| 479 | 2025-10-18 00:50:42 | variables | 2 | 121436 | 10 | 3.236 | 37526.6 |
| 478 | 2025-10-17 21:59:32 | variables | 4 | 165329 | 728 | 11.970 | 13811.9 |
| 477 | 2025-10-03 01:32:33 | variables | 1 | 81242 | 2 | 1.983 | 40969.2 |
| 476 | 2025-09-30 04:47:08 | variables | 1 | 81242 | 2 | 2.923 | 27794.0 |
| 475 | 2025-09-28 17:13:57 | variables | 4 | 165329 | 728 | 12.423 | 13308.3 |
| 474 | 2025-09-11 09:33:23 | variables | 4 | 165329 | 728 | 12.330 | 13408.7 |
| 473 | 2025-09-09 02:06:26 | variables | 1 | 81242 | 2 | 1.266 | 64172.2 |
| 472 | 2025-09-09 01:56:44 | variables | 1 | 81242 | 2 | 1.420 | 57212.7 |
| 471 | 2025-09-05 23:50:27 | variables | 2 | 121436 | 10 | 3.640 | 33361.5 |
| 470 | 2025-09-04 17:23:59 | variables | 3 | 148641 | 67 | 7.906 | 18801.0 |
| 469 | 2025-09-03 01:27:14 | variables | 1 | 81242 | 2 | 1.360 | 59736.8 |
| 468 | 2025-08-28 10:12:59 | variables | 3 | 148641 | 67 | 7.486 | 19855.9 |
| 467 | 2025-08-27 11:29:49 | variables | 1 | 81242 | 2 | 1.343 | 60492.9 |
| 466 | 2025-08-27 02:36:54 | variables | 2 | 121436 | 10 | 3.266 | 37181.9 |
| 465 | 2025-08-22 09:51:30 | variables | 1 | 81242 | 2 | 1.266 | 64172.2 |
| 464 | 2025-08-17 09:31:53 | variables | 1 | 81242 | 2 | 3.173 | 25604.2 |
| 463 | 2025-08-12 01:46:25 | variables | 1 | 81242 | 2 | 3.326 | 24426.3 |
| 462 | 2025-08-09 19:06:06 | variables | 1 | 81242 | 2 | 3.343 | 24302.1 |
| 461 | 2025-08-09 18:46:12 | variables | 1 | 81242 | 2 | 7.813 | 10398.3 |
| 460 | 2025-08-08 15:26:39 | variables | 1 | 81242 | 2 | 1.390 | 58447.5 |
| 459 | 2025-07-27 10:08:24 | variables | 1 | 81242 | 2 | 3.610 | 22504.7 |
| 458 | 2025-07-27 05:47:24 | variables | 4 | 165329 | 728 | 55.036 | 3004.0 |
| 457 | 2025-07-26 00:10:33 | variables | 4 | 165329 | 728 | 11.953 | 13831.6 |
| 456 | 2025-07-24 18:58:55 | variables | 4 | 165329 | 728 | 75.770 | 2182.0 |
| 455 | 2025-07-24 09:02:02 | variables | 4 | 165329 | 728 | 67.050 | 2465.8 |
| 454 | 2025-07-23 11:20:02 | variables | 4 | 165329 | 728 | 64.450 | 2565.2 |
| 453 | 2025-07-23 04:47:24 | variables | 4 | 165329 | 728 | 35.906 | 4604.5 |
| 452 | 2025-07-22 22:54:34 | variables | 4 | 165329 | 728 | 35.143 | 4704.5 |
| 451 | 2025-07-22 12:05:25 | variables | 4 | 165329 | 728 | 58.296 | 2836.0 |
| 450 | 2025-07-20 00:24:58 | variables | 4 | 165329 | 728 | 12.423 | 13308.3 |
| 449 | 2025-07-19 15:32:31 | variables | 4 | 165329 | 728 | 11.893 | 13901.4 |
| 448 | 2025-07-19 09:26:04 | variables | 4 | 165329 | 728 | 18.360 | 9004.8 |
| 447 | 2025-07-18 12:50:12 | variables | 2 | 121436 | 10 | 18.160 | 6687.0 |
| 446 | 2025-07-18 06:17:50 | variables | 4 | 165329 | 728 | 37.270 | 4436.0 |
| 445 | 2025-07-10 15:45:48 | variables | 1 | 81242 | 2 | 6.483 | 12531.5 |
| 444 | 2025-07-10 00:48:07 | variables | 3 | 148641 | 67 | 25.046 | 5934.7 |
| 443 | 2025-07-09 09:37:36 | variables | 1 | 81242 | 2 | 6.406 | 12682.2 |
| 442 | 2025-07-08 07:20:00 | variables | 2 | 121436 | 10 | 15.986 | 7596.4 |
| 441 | 2025-07-08 00:26:16 | variables | 3 | 148641 | 67 | 39.110 | 3800.6 |
| 440 | 2025-07-07 12:45:30 | variables | 1 | 81242 | 2 | 8.343 | 9737.7 |
| 439 | 2025-07-05 16:35:44 | variables | 2 | 121436 | 10 | 12.530 | 9691.6 |
| 438 | 2025-07-05 13:10:54 | variables | 3 | 148641 | 67 | 35.283 | 4212.8 |
| 437 | 2025-07-04 13:03:54 | variables | 1 | 81242 | 2 | 4.330 | 18762.6 |
| 436 | 2025-06-15 17:13:29 | variables | 2 | 121436 | 10 | 3.593 | 33797.9 |
| 435 | 2025-06-14 17:44:17 | variables | 1 | 81242 | 2 | 7.500 | 10832.3 |
| 434 | 2025-06-13 16:45:53 | variables | 1 | 81242 | 2 | 1.873 | 43375.3 |
| 433 | 2025-06-11 11:34:23 | variables | 4 | 165329 | 728 | 37.693 | 4386.2 |
| 432 | 2025-06-10 07:13:00 | variables | 4 | 165329 | 728 | 69.443 | 2380.8 |
| 431 | 2025-06-10 04:05:38 | variables | 4 | 165329 | 728 | 59.663 | 2771.0 |
| 430 | 2025-06-10 00:32:39 | variables | 4 | 165329 | 728 | 60.533 | 2731.2 |
| 429 | 2025-06-08 15:31:35 | variables | 4 | 165329 | 728 | 58.423 | 2829.9 |
| 428 | 2025-06-08 06:31:07 | variables | 1 | 81242 | 2 | 6.610 | 12290.8 |
| 427 | 2025-06-02 13:01:55 | variables | 1 | 81242 | 2 | 7.670 | 10592.2 |
| 426 | 2025-05-29 11:39:39 | variables | 1 | 81242 | 2 | 6.923 | 11735.1 |
| 425 | 2025-05-15 17:01:39 | variables | 1 | 81242 | 2 | 1.500 | 54161.3 |
| 424 | 2025-05-14 16:40:49 | variables | 1 | 81242 | 2 | 10.263 | 7916.0 |
| 423 | 2025-05-13 19:23:06 | variables | 1 | 81242 | 2 | 1.453 | 55913.3 |
| 422 | 2025-05-12 17:12:39 | variables | 1 | 81242 | 2 | 7.156 | 11353.0 |
| 421 | 2025-05-06 11:52:10 | variables | 4 | 165329 | 728 | 56.953 | 2902.9 |
| 420 | 2025-05-06 02:45:11 | variables | 4 | 165329 | 728 | 51.453 | 3213.2 |
| 419 | 2025-05-06 00:58:37 | variables | 4 | 165329 | 728 | 61.533 | 2686.8 |
| 418 | 2025-05-05 15:33:15 | variables | 2 | 121436 | 10 | 17.190 | 7064.3 |
| 417 | 2025-05-05 12:18:18 | variables | 3 | 148641 | 67 | 19.830 | 7495.8 |
| 416 | 2025-05-05 11:26:39 | variables | 4 | 165329 | 728 | 13.360 | 12374.9 |
| 415 | 2025-05-05 05:36:38 | variables | 1 | 81242 | 2 | 1.280 | 63470.3 |
| 414 | 2025-04-23 20:29:42 | variables | 3 | 148641 | 67 | 28.563 | 5204.0 |
| 413 | 2025-04-23 18:35:19 | variables | 2 | 121436 | 10 | 3.923 | 30954.9 |
| 412 | 2025-04-23 02:53:48 | variables | 3 | 148641 | 67 | 42.500 | 3497.4 |
| 411 | 2025-04-22 08:19:15 | variables | 1 | 81242 | 2 | 1.453 | 55913.3 |
| 410 | 2025-04-20 11:32:40 | variables | 1 | 81242 | 2 | 1.453 | 55913.3 |
| 409 | 2025-04-19 06:09:49 | variables | 1 | 81242 | 2 | 1.390 | 58447.5 |
| 408 | 2025-04-11 17:08:00 | variables | 1 | 81242 | 2 | 3.376 | 24064.6 |
| 407 | 2025-04-09 20:47:20 | variables | 1 | 81242 | 2 | 3.050 | 26636.7 |
| 406 | 2025-03-29 17:42:11 | variables | 2 | 121436 | 10 | 21.876 | 5551.1 |
| 405 | 2025-03-29 11:05:38 | variables | 1 | 81242 | 2 | 3.216 | 25261.8 |
| 404 | 2025-03-23 10:58:24 | variables | 2 | 121436 | 10 | 11.156 | 10885.3 |
| 403 | 2025-03-22 09:54:19 | variables | 1 | 81242 | 2 | 1.250 | 64993.6 |
| 402 | 2025-03-17 04:43:57 | variables | 1 | 81242 | 2 | 11.890 | 6832.8 |
| 401 | 2025-03-12 14:11:15 | variables | 1 | 81242 | 2 | 6.456 | 12584.0 |
| 400 | 2025-03-05 06:24:15 | variables | 1 | 81242 | 2 | 3.486 | 23305.2 |
| 399 | 2025-03-03 08:22:02 | variables | 1 | 81242 | 2 | 1.220 | 66591.8 |
| 398 | 2025-02-08 14:02:57 | variables | 1 | 81242 | 2 | 5.656 | 14363.9 |
| 397 | 2025-02-04 12:36:51 | variables | 1 | 81242 | 2 | 3.170 | 25628.4 |
| 396 | 2025-01-26 15:44:01 | variables | 1 | 81242 | 2 | 6.000 | 13540.3 |
| 395 | 2025-01-10 09:06:35 | variables | 1 | 81242 | 2 | 2.483 | 32719.3 |
| 394 | 2025-01-08 12:47:51 | variables | 1 | 81242 | 2 | 1.393 | 58321.6 |
| 393 | 2025-01-05 11:46:35 | variables | 1 | 81242 | 2 | 6.470 | 12556.7 |
| 392 | 2024-12-27 14:36:24 | variables | 1 | 81242 | 2 | 1.296 | 62686.7 |
| 391 | 2024-12-08 12:28:00 | variables | 2 | 121436 | 10 | 34.123 | 3558.8 |
| 390 | 2024-12-08 12:27:41 | variables | 3 | 148641 | 67 | 43.783 | 3394.9 |
| 389 | 2024-12-08 12:26:36 | variables | 1 | 81242 | 2 | 6.546 | 12410.9 |
| 388 | 2024-12-07 04:45:03 | variables | 3 | 148641 | 67 | 37.890 | 3923.0 |
| 387 | 2024-12-06 09:47:37 | variables | 3 | 148641 | 67 | 45.283 | 3282.5 |
| 386 | 2024-12-06 09:47:27 | variables | 3 | 148641 | 67 | 36.440 | 4079.1 |
| 385 | 2024-12-06 09:47:31 | variables | 2 | 121436 | 10 | 23.690 | 5126.0 |
| 384 | 2024-12-06 09:12:18 | variables | 1 | 81242 | 2 | 1.330 | 61084.2 |
| 383 | 2024-11-27 13:19:44 | variables | 1 | 81242 | 2 | 3.783 | 21475.5 |
| 382 | 2024-10-28 12:30:45 | variables | 1 | 81242 | 2 | 4.643 | 17497.7 |