History of Dictionary Searches using Damerau-Levenshtein distance in T-SQL
Fuzzy-string Searches
(up to 100 most recent)
for
"attractors"
| Num | Started At (CA time) | Searched Word | Change Limit | Words Checked | Words Matched | Seconds | Words Per Sec |
| 409 | 2026-03-03 04:38:37 | attractors | 1 | 67641 | 3 | 1.156 | 58513.0 |
| 408 | 2026-03-01 22:32:34 | attractors | 1 | 67641 | 3 | 1.220 | 55443.4 |
| 407 | 2026-02-15 15:20:55 | attractors | 1 | 67641 | 3 | 1.186 | 57032.9 |
| 406 | 2026-02-05 09:20:02 | attractors | 1 | 67641 | 3 | 1.126 | 60071.9 |
| 405 | 2026-02-03 05:16:33 | attractors | 1 | 67641 | 3 | 1.186 | 57032.9 |
| 404 | 2026-02-03 00:09:30 | attractors | 1 | 67641 | 3 | 4.686 | 14434.7 |
| 403 | 2026-01-29 17:38:03 | attractors | 1 | 67641 | 3 | 7.783 | 8690.9 |
| 402 | 2026-01-28 17:21:21 | attractors | 1 | 67641 | 3 | 1.110 | 60937.8 |
| 401 | 2026-01-23 02:05:29 | attractors | 1 | 67641 | 3 | 1.186 | 57032.9 |
| 400 | 2026-01-22 17:24:39 | attractors | 1 | 67641 | 3 | 2.923 | 23141.0 |
| 399 | 2026-01-22 17:24:28 | attractors | 1 | 67641 | 3 | 3.030 | 22323.8 |
| 398 | 2026-01-22 17:24:19 | attractors | 1 | 67641 | 3 | 3.470 | 19493.1 |
| 397 | 2026-01-22 05:00:51 | attractors | 1 | 67641 | 3 | 1.186 | 57032.9 |
| 396 | 2026-01-20 14:16:11 | attractors | 1 | 67641 | 3 | 1.140 | 59334.2 |
| 395 | 2026-01-19 01:16:21 | attractors | 2 | 108824 | 11 | 8.703 | 12504.2 |
| 394 | 2026-01-17 21:31:30 | attractors | 1 | 67641 | 3 | 2.686 | 25182.8 |
| 393 | 2026-01-17 21:31:18 | attractors | 1 | 67641 | 3 | 4.406 | 15352.0 |
| 392 | 2026-01-17 15:33:33 | attractors | 1 | 67641 | 3 | 1.173 | 57665.0 |
| 391 | 2026-01-15 04:01:51 | attractors | 1 | 67641 | 3 | 1.173 | 57665.0 |
| 390 | 2026-01-10 13:02:58 | attractors | 1 | 67641 | 3 | 1.046 | 64666.3 |
| 389 | 2026-01-04 08:58:49 | attractors | 1 | 67641 | 3 | 1.216 | 55625.8 |
| 388 | 2026-01-03 21:10:21 | attractors | 1 | 67641 | 3 | 1.156 | 58513.0 |
| 387 | 2026-01-03 00:18:37 | attractors | 1 | 67641 | 3 | 1.106 | 61158.2 |
| 386 | 2025-12-29 23:16:15 | attractors | 1 | 67641 | 3 | 5.830 | 11602.2 |
| 385 | 2025-12-26 10:11:59 | attractors | 1 | 67641 | 3 | 1.486 | 45518.8 |
| 384 | 2025-12-25 21:39:39 | attractors | 1 | 67641 | 3 | 1.156 | 58513.0 |
| 383 | 2025-12-25 03:21:46 | attractors | 1 | 67641 | 3 | 3.830 | 17660.8 |
| 382 | 2025-12-19 00:15:20 | attractors | 1 | 67641 | 3 | 1.313 | 51516.4 |
| 381 | 2025-12-18 09:52:41 | attractors | 1 | 67641 | 3 | 2.123 | 31861.0 |
| 380 | 2025-12-17 23:11:05 | attractors | 1 | 67641 | 3 | 2.250 | 30062.7 |
| 379 | 2025-12-14 05:04:38 | attractors | 1 | 67641 | 3 | 1.173 | 57665.0 |
| 378 | 2025-12-08 22:20:26 | attractors | 1 | 67641 | 3 | 2.343 | 28869.4 |
| 377 | 2025-11-27 15:06:08 | attractors | 1 | 67641 | 3 | 1.593 | 42461.4 |
| 376 | 2025-11-22 00:04:04 | attractors | 1 | 67641 | 3 | 1.763 | 38367.0 |
| 375 | 2025-11-10 09:55:42 | attractors | 2 | 108824 | 11 | 2.656 | 40972.9 |
| 374 | 2025-11-01 16:04:48 | attractors | 1 | 67641 | 3 | 1.030 | 65670.9 |
| 373 | 2025-10-31 04:44:29 | attractors | 1 | 67641 | 3 | 1.046 | 64666.3 |
| 372 | 2025-10-25 20:09:50 | attractors | 1 | 67641 | 3 | 1.126 | 60071.9 |
| 371 | 2025-10-20 06:05:07 | attractors | 2 | 108824 | 11 | 12.906 | 8432.0 |
| 370 | 2025-10-17 12:33:54 | attractors | 4 | 161450 | 182 | 14.906 | 10831.2 |
| 369 | 2025-10-16 16:30:36 | attractors | 1 | 67641 | 3 | 1.046 | 64666.3 |
| 368 | 2025-10-16 15:41:03 | attractors | 1 | 67641 | 3 | 1.063 | 63632.2 |
| 367 | 2025-10-04 19:47:30 | attractors | 1 | 67641 | 3 | 1.173 | 57665.0 |
| 366 | 2025-09-26 21:43:34 | attractors | 1 | 67641 | 3 | 1.653 | 40920.1 |
| 365 | 2025-09-24 01:53:46 | attractors | 1 | 67641 | 3 | 1.123 | 60232.4 |
| 364 | 2025-09-14 19:11:35 | attractors | 1 | 67641 | 3 | 1.826 | 37043.3 |
| 363 | 2025-09-14 14:12:43 | attractors | 1 | 67641 | 3 | 1.110 | 60937.8 |
| 362 | 2025-09-03 09:17:36 | attractors | 1 | 67641 | 3 | 1.173 | 57665.0 |
| 361 | 2025-08-29 03:58:23 | attractors | 1 | 67641 | 3 | 1.046 | 64666.3 |
| 360 | 2025-08-28 10:42:37 | attractors | 1 | 67641 | 3 | 1.110 | 60937.8 |
| 359 | 2025-08-20 20:30:00 | attractors | 1 | 67641 | 3 | 4.516 | 14978.1 |
| 358 | 2025-08-15 14:33:28 | attractors | 1 | 67641 | 3 | 4.936 | 13703.6 |
| 357 | 2025-08-15 05:36:39 | attractors | 1 | 67641 | 3 | 2.500 | 27056.4 |
| 356 | 2025-08-09 17:27:25 | attractors | 1 | 67641 | 3 | 5.623 | 12029.3 |
| 355 | 2025-07-28 05:40:48 | attractors | 1 | 67641 | 3 | 3.826 | 17679.3 |
| 354 | 2025-07-28 03:31:32 | attractors | 1 | 67641 | 3 | 2.890 | 23405.2 |
| 353 | 2025-07-28 02:23:06 | attractors | 1 | 67641 | 3 | 4.686 | 14434.7 |
| 352 | 2025-07-26 09:21:25 | attractors | 1 | 67641 | 3 | 2.466 | 27429.4 |
| 351 | 2025-07-24 04:32:17 | attractors | 1 | 67641 | 3 | 4.673 | 14474.9 |
| 350 | 2025-07-19 06:30:38 | attractors | 1 | 67641 | 3 | 1.170 | 57812.8 |
| 349 | 2025-07-12 23:06:04 | attractors | 1 | 67641 | 3 | 3.126 | 21638.2 |
| 348 | 2025-07-09 19:05:11 | attractors | 1 | 67641 | 3 | 1.190 | 56841.2 |
| 347 | 2025-07-08 16:23:31 | attractors | 1 | 67641 | 3 | 5.436 | 12443.2 |
| 346 | 2025-07-05 02:21:50 | attractors | 4 | 161450 | 182 | 48.113 | 3355.6 |
| 345 | 2025-06-26 05:52:43 | attractors | 1 | 67641 | 3 | 5.343 | 12659.7 |
| 344 | 2025-06-23 17:51:27 | attractors | 2 | 108824 | 11 | 3.250 | 33484.3 |
| 343 | 2025-06-14 05:40:03 | attractors | 1 | 67641 | 3 | 2.733 | 24749.7 |
| 342 | 2025-06-12 21:17:08 | attractors | 1 | 67641 | 3 | 4.966 | 13620.8 |
| 341 | 2025-06-10 02:50:48 | attractors | 1 | 67641 | 3 | 4.250 | 15915.5 |
| 340 | 2025-06-03 06:54:41 | attractors | 1 | 67641 | 3 | 4.720 | 14330.7 |
| 339 | 2025-05-29 09:08:31 | attractors | 1 | 67641 | 3 | 8.783 | 7701.4 |
| 338 | 2025-05-27 10:47:27 | attractors | 2 | 108824 | 11 | 15.423 | 7056.0 |
| 337 | 2025-05-27 03:02:25 | attractors | 3 | 140603 | 41 | 28.516 | 4930.7 |
| 336 | 2025-05-26 14:50:47 | attractors | 4 | 161450 | 182 | 62.223 | 2594.7 |
| 335 | 2025-05-26 06:08:16 | attractors | 1 | 67641 | 3 | 6.250 | 10822.6 |
| 334 | 2025-05-25 20:11:02 | attractors | 1 | 67641 | 3 | 1.140 | 59334.2 |
| 333 | 2025-05-24 14:49:07 | attractors | 4 | 161450 | 182 | 49.866 | 3237.7 |
| 332 | 2025-05-22 14:29:42 | attractors | 4 | 161450 | 182 | 48.940 | 3298.9 |
| 331 | 2025-05-17 04:40:43 | attractors | 1 | 67641 | 3 | 1.173 | 57665.0 |
| 330 | 2025-05-15 05:48:09 | attractors | 1 | 67641 | 3 | 5.310 | 12738.4 |
| 329 | 2025-05-07 03:28:04 | attractors | 1 | 67641 | 3 | 1.123 | 60232.4 |
| 328 | 2025-05-06 02:41:11 | attractors | 1 | 67641 | 3 | 8.110 | 8340.4 |
| 327 | 2025-04-25 13:16:27 | attractors | 4 | 161450 | 182 | 19.610 | 8233.0 |
| 326 | 2025-04-13 03:00:03 | attractors | 1 | 67641 | 3 | 1.030 | 65670.9 |
| 325 | 2025-04-12 15:25:27 | attractors | 1 | 67641 | 3 | 6.733 | 10046.2 |
| 324 | 2025-04-09 06:48:31 | attractors | 3 | 140603 | 41 | 28.656 | 4906.6 |
| 323 | 2025-04-09 06:07:51 | attractors | 1 | 67641 | 3 | 8.390 | 8062.1 |
| 322 | 2025-04-09 03:54:45 | attractors | 3 | 140603 | 41 | 30.453 | 4617.0 |
| 321 | 2025-04-07 12:56:10 | attractors | 4 | 161450 | 182 | 53.986 | 2990.6 |
| 320 | 2025-04-04 13:50:17 | attractors | 4 | 161450 | 182 | 66.113 | 2442.0 |
| 319 | 2025-04-04 08:26:39 | attractors | 2 | 108824 | 11 | 20.003 | 5440.4 |
| 318 | 2025-04-04 03:13:35 | attractors | 3 | 140603 | 41 | 15.986 | 8795.4 |
| 317 | 2025-04-02 20:20:33 | attractors | 1 | 67641 | 3 | 2.623 | 25787.6 |
| 316 | 2025-03-21 03:14:32 | attractors | 1 | 67641 | 3 | 2.796 | 24192.1 |
| 315 | 2025-03-18 05:29:22 | attractors | 1 | 67641 | 3 | 5.330 | 12690.6 |
| 314 | 2025-03-17 01:22:04 | attractors | 1 | 67641 | 3 | 7.906 | 8555.7 |
| 313 | 2025-03-07 12:00:10 | attractors | 1 | 67641 | 3 | 5.530 | 12231.6 |
| 312 | 2025-02-27 19:08:00 | attractors | 1 | 67641 | 3 | 3.390 | 19953.1 |
| 311 | 2025-02-27 04:33:33 | attractors | 1 | 67641 | 3 | 5.390 | 12549.4 |
| 310 | 2025-02-05 22:28:42 | attractors | 2 | 108824 | 11 | 3.140 | 34657.3 |