History of Dictionary Searches using Damerau-Levenshtein distance in T-SQL
Fuzzy-string Searches
(up to 100 most recent)
for
"linearized"
| Num | Started At (CA time) | Searched Word | Change Limit | Words Checked | Words Matched | Seconds | Words Per Sec |
| 396 | 2025-10-28 12:40:50 | linearized | 1 | 67641 | 4 | 1.016 | 66575.8 |
| 395 | 2025-10-28 07:15:12 | linearized | 4 | 161450 | 164 | 10.843 | 14889.8 |
| 394 | 2025-10-26 08:44:06 | linearized | 4 | 161450 | 164 | 10.360 | 15584.0 |
| 393 | 2025-10-26 05:04:30 | linearized | 4 | 161450 | 164 | 12.016 | 13436.3 |
| 392 | 2025-10-25 18:02:12 | linearized | 1 | 67641 | 4 | 1.000 | 67641.0 |
| 391 | 2025-10-25 14:27:54 | linearized | 1 | 67641 | 4 | 1.030 | 65670.9 |
| 390 | 2025-10-25 10:07:01 | linearized | 1 | 67641 | 4 | 1.080 | 62630.6 |
| 389 | 2025-10-23 01:02:21 | linearized | 4 | 161450 | 164 | 74.993 | 2152.9 |
| 388 | 2025-10-21 22:07:40 | linearized | 1 | 67641 | 4 | 5.450 | 12411.2 |
| 387 | 2025-10-17 22:10:40 | linearized | 4 | 161450 | 164 | 13.313 | 12127.2 |
| 386 | 2025-10-17 09:25:04 | linearized | 4 | 161450 | 164 | 31.563 | 5115.2 |
| 385 | 2025-10-09 20:49:37 | linearized | 3 | 140603 | 23 | 6.423 | 21890.5 |
| 384 | 2025-10-09 07:34:25 | linearized | 1 | 67641 | 4 | 1.236 | 54725.7 |
| 383 | 2025-10-04 08:29:29 | linearized | 4 | 161450 | 164 | 10.406 | 15515.1 |
| 382 | 2025-10-03 18:14:40 | linearized | 1 | 67641 | 4 | 1.030 | 65670.9 |
| 381 | 2025-09-25 23:46:15 | linearized | 1 | 67641 | 4 | 5.390 | 12549.4 |
| 380 | 2025-09-24 18:29:42 | linearized | 4 | 161450 | 164 | 11.700 | 13799.1 |
| 379 | 2025-09-18 00:01:18 | linearized | 1 | 67641 | 4 | 1.093 | 61885.6 |
| 378 | 2025-09-16 13:23:37 | linearized | 4 | 161450 | 164 | 12.173 | 13263.0 |
| 377 | 2025-09-15 09:04:03 | linearized | 2 | 108824 | 6 | 2.626 | 41441.0 |
| 376 | 2025-09-11 08:25:43 | linearized | 2 | 108824 | 6 | 3.123 | 34846.0 |
| 375 | 2025-09-09 22:07:28 | linearized | 4 | 161450 | 164 | 11.080 | 14571.3 |
| 374 | 2025-09-07 19:35:42 | linearized | 4 | 161450 | 164 | 10.670 | 15131.2 |
| 373 | 2025-09-07 13:25:22 | linearized | 1 | 67641 | 4 | 1.250 | 54112.8 |
| 372 | 2025-09-06 07:44:13 | linearized | 1 | 67641 | 4 | 1.123 | 60232.4 |
| 371 | 2025-09-05 17:19:12 | linearized | 3 | 140603 | 23 | 5.500 | 25564.2 |
| 370 | 2025-09-01 13:11:50 | linearized | 2 | 108824 | 6 | 2.890 | 37655.4 |
| 369 | 2025-09-01 03:40:50 | linearized | 4 | 161450 | 164 | 11.080 | 14571.3 |
| 368 | 2025-08-31 05:19:18 | linearized | 4 | 161450 | 164 | 11.640 | 13870.3 |
| 367 | 2025-08-29 19:58:12 | linearized | 4 | 161450 | 164 | 13.486 | 11971.7 |
| 366 | 2025-08-25 23:09:04 | linearized | 3 | 140603 | 23 | 6.546 | 21479.2 |
| 365 | 2025-08-24 12:36:29 | linearized | 1 | 67641 | 4 | 1.236 | 54725.7 |
| 364 | 2025-08-23 09:24:55 | linearized | 1 | 67641 | 4 | 7.690 | 8796.0 |
| 363 | 2025-08-20 19:47:59 | linearized | 1 | 67641 | 4 | 2.830 | 23901.4 |
| 362 | 2025-08-18 13:56:36 | linearized | 1 | 67641 | 4 | 1.170 | 57812.8 |
| 361 | 2025-08-15 15:30:16 | linearized | 1 | 67641 | 4 | 5.376 | 12582.0 |
| 360 | 2025-08-10 07:32:08 | linearized | 2 | 108824 | 6 | 6.986 | 15577.4 |
| 359 | 2025-08-09 16:36:34 | linearized | 1 | 67641 | 4 | 1.153 | 58665.2 |
| 358 | 2025-08-09 10:57:18 | linearized | 1 | 67641 | 4 | 5.716 | 11833.6 |
| 357 | 2025-07-29 22:00:40 | linearized | 3 | 140603 | 23 | 42.203 | 3331.6 |
| 356 | 2025-07-22 08:51:17 | linearized | 1 | 67641 | 4 | 1.140 | 59334.2 |
| 355 | 2025-07-22 02:22:23 | linearized | 4 | 161450 | 164 | 47.736 | 3382.1 |
| 354 | 2025-07-20 00:18:37 | linearized | 4 | 161450 | 164 | 12.110 | 13332.0 |
| 353 | 2025-07-19 08:10:02 | linearized | 4 | 161450 | 164 | 12.236 | 13194.7 |
| 352 | 2025-07-18 17:36:08 | linearized | 4 | 161450 | 164 | 53.520 | 3016.6 |
| 351 | 2025-07-16 10:27:59 | linearized | 1 | 67641 | 4 | 5.423 | 12473.0 |
| 350 | 2025-07-14 11:20:59 | linearized | 3 | 140603 | 23 | 27.703 | 5075.4 |
| 349 | 2025-07-14 01:47:22 | linearized | 4 | 161450 | 164 | 61.096 | 2642.6 |
| 348 | 2025-07-13 10:39:22 | linearized | 1 | 67641 | 4 | 2.046 | 33060.1 |
| 347 | 2025-07-09 18:47:44 | linearized | 1 | 67641 | 4 | 1.186 | 57032.9 |
| 346 | 2025-07-09 08:07:07 | linearized | 1 | 67641 | 4 | 1.296 | 52192.1 |
| 345 | 2025-07-07 03:22:42 | linearized | 1 | 67641 | 4 | 2.670 | 25333.7 |
| 344 | 2025-07-04 11:52:21 | linearized | 1 | 67641 | 4 | 1.233 | 54858.9 |
| 343 | 2025-07-03 11:55:02 | linearized | 3 | 140603 | 23 | 8.330 | 16879.1 |
| 342 | 2025-07-02 15:38:42 | linearized | 1 | 67641 | 4 | 5.530 | 12231.6 |
| 341 | 2025-07-02 11:10:27 | linearized | 1 | 67641 | 4 | 3.546 | 19075.3 |
| 340 | 2025-06-27 12:44:47 | linearized | 1 | 67641 | 4 | 1.203 | 56226.9 |
| 339 | 2025-06-20 11:20:19 | linearized | 1 | 67641 | 4 | 8.203 | 8245.9 |
| 338 | 2025-06-19 17:47:12 | linearized | 1 | 67641 | 4 | 1.186 | 57032.9 |
| 337 | 2025-06-18 12:20:24 | linearized | 1 | 67641 | 4 | 5.390 | 12549.4 |
| 336 | 2025-06-16 22:00:53 | linearized | 1 | 67641 | 4 | 8.473 | 7983.1 |
| 335 | 2025-06-06 10:29:04 | linearized | 1 | 67641 | 4 | 5.156 | 13118.9 |
| 334 | 2025-05-18 10:01:23 | linearized | 1 | 67641 | 4 | 4.640 | 14577.8 |
| 333 | 2025-05-14 10:28:52 | linearized | 1 | 67641 | 4 | 5.420 | 12479.9 |
| 332 | 2025-05-07 21:23:12 | linearized | 1 | 67641 | 4 | 4.626 | 14621.9 |
| 331 | 2025-04-16 08:12:27 | linearized | 1 | 67641 | 4 | 8.266 | 8183.0 |
| 330 | 2025-04-14 09:50:22 | linearized | 1 | 67641 | 4 | 5.953 | 11362.5 |
| 329 | 2025-03-28 21:31:24 | linearized | 1 | 67641 | 4 | 4.606 | 14685.4 |
| 328 | 2025-03-14 19:29:07 | linearized | 1 | 67641 | 4 | 5.390 | 12549.4 |
| 327 | 2025-03-05 03:35:37 | linearized | 1 | 67641 | 4 | 4.830 | 14004.3 |
| 326 | 2025-03-03 10:12:59 | linearized | 1 | 67641 | 4 | 1.013 | 66773.0 |
| 325 | 2025-02-18 06:14:58 | linearized | 1 | 67641 | 4 | 2.766 | 24454.4 |
| 324 | 2025-02-18 01:19:58 | linearized | 3 | 140603 | 23 | 55.143 | 2549.8 |
| 323 | 2025-02-18 01:20:00 | linearized | 3 | 140603 | 23 | 19.156 | 7339.9 |
| 322 | 2025-02-18 01:19:56 | linearized | 2 | 108824 | 6 | 14.266 | 7628.2 |
| 321 | 2025-02-18 01:19:45 | linearized | 1 | 67641 | 4 | 2.546 | 26567.6 |
| 320 | 2025-01-31 05:20:57 | linearized | 3 | 140603 | 23 | 31.173 | 4510.4 |
| 319 | 2025-01-29 18:36:26 | linearized | 1 | 67641 | 4 | 1.156 | 58513.0 |
| 318 | 2025-01-27 17:17:37 | linearized | 3 | 140603 | 23 | 37.923 | 3707.6 |
| 317 | 2025-01-27 17:17:39 | linearized | 3 | 140603 | 23 | 33.250 | 4228.7 |
| 316 | 2025-01-27 17:17:38 | linearized | 2 | 108824 | 6 | 22.953 | 4741.2 |
| 315 | 2025-01-27 16:05:16 | linearized | 1 | 67641 | 4 | 1.153 | 58665.2 |
| 314 | 2025-01-17 05:27:07 | linearized | 3 | 140603 | 23 | 33.220 | 4232.5 |
| 313 | 2025-01-17 05:27:16 | linearized | 2 | 108824 | 6 | 15.080 | 7216.4 |
| 312 | 2025-01-17 05:24:17 | linearized | 1 | 67641 | 4 | 5.283 | 12803.5 |
| 311 | 2025-01-17 02:21:25 | linearized | 3 | 140603 | 23 | 37.970 | 3703.0 |
| 310 | 2025-01-17 02:21:26 | linearized | 2 | 108824 | 6 | 15.250 | 7136.0 |
| 309 | 2025-01-17 02:13:25 | linearized | 1 | 67641 | 4 | 5.576 | 12130.7 |
| 308 | 2024-12-26 12:34:15 | linearized | 1 | 67641 | 4 | 1.126 | 60071.9 |
| 307 | 2024-12-21 11:19:40 | linearized | 3 | 140603 | 23 | 29.673 | 4738.4 |
| 306 | 2024-12-21 01:20:59 | linearized | 3 | 140603 | 23 | 32.690 | 4301.1 |
| 305 | 2024-12-21 01:20:57 | linearized | 2 | 108824 | 6 | 18.666 | 5830.1 |
| 304 | 2024-12-21 00:59:11 | linearized | 3 | 140603 | 23 | 46.753 | 3007.4 |
| 303 | 2024-12-21 00:59:01 | linearized | 2 | 108824 | 6 | 14.936 | 7286.0 |
| 302 | 2024-12-21 00:55:38 | linearized | 1 | 67641 | 4 | 2.406 | 28113.5 |
| 301 | 2024-12-08 14:45:16 | linearized | 2 | 108824 | 6 | 15.456 | 7040.9 |
| 300 | 2024-12-08 14:42:34 | linearized | 1 | 67641 | 4 | 6.046 | 11187.7 |
| 299 | 2024-11-25 14:00:00 | linearized | 3 | 140603 | 23 | 29.710 | 4732.5 |
| 298 | 2024-11-25 14:00:03 | linearized | 3 | 140603 | 23 | 26.240 | 5358.3 |
| 297 | 2024-11-25 14:00:01 | linearized | 2 | 108824 | 6 | 15.066 | 7223.2 |