History of Dictionary Searches using Damerau-Levenshtein distance in T-SQL
Fuzzy-string Searches
(up to 100 most recent)
for
"propensity"
| Num | Started At (CA time) | Searched Word | Change Limit | Words Checked | Words Matched | Seconds | Words Per Sec |
| 378 | 2025-11-05 14:43:34 | propensity | 4 | 161450 | 91 | 11.970 | 13487.9 |
| 377 | 2025-11-03 03:04:13 | propensity | 4 | 161450 | 91 | 12.140 | 13299.0 |
| 376 | 2025-10-29 17:06:18 | propensity | 4 | 161450 | 91 | 11.220 | 14389.5 |
| 375 | 2025-10-04 21:01:32 | propensity | 4 | 161450 | 91 | 15.080 | 10706.2 |
| 374 | 2025-09-14 17:26:04 | propensity | 4 | 161450 | 91 | 10.830 | 14907.7 |
| 373 | 2025-09-14 15:51:59 | propensity | 1 | 67641 | 1 | 1.203 | 56226.9 |
| 372 | 2025-08-27 08:03:40 | propensity | 1 | 67641 | 1 | 1.156 | 58513.0 |
| 371 | 2025-08-16 22:04:30 | propensity | 1 | 67641 | 1 | 2.500 | 27056.4 |
| 370 | 2025-08-10 14:56:14 | propensity | 1 | 67641 | 1 | 2.923 | 23141.0 |
| 369 | 2025-07-25 07:57:41 | propensity | 1 | 67641 | 1 | 2.906 | 23276.3 |
| 368 | 2025-07-24 22:40:38 | propensity | 1 | 67641 | 1 | 2.953 | 22905.9 |
| 367 | 2025-07-24 17:58:38 | propensity | 1 | 67641 | 1 | 2.390 | 28301.7 |
| 366 | 2025-07-19 09:41:04 | propensity | 1 | 67641 | 1 | 1.046 | 64666.3 |
| 365 | 2025-06-28 14:30:02 | propensity | 1 | 67641 | 1 | 6.046 | 11187.7 |
| 364 | 2025-06-16 13:05:15 | propensity | 1 | 67641 | 1 | 4.780 | 14150.8 |
| 363 | 2025-06-14 02:48:58 | propensity | 3 | 140603 | 12 | 20.376 | 6900.4 |
| 362 | 2025-06-12 17:06:27 | propensity | 1 | 67641 | 1 | 1.233 | 54858.9 |
| 361 | 2025-05-31 09:34:41 | propensity | 1 | 67641 | 1 | 4.923 | 13739.8 |
| 360 | 2025-05-20 23:22:23 | propensity | 1 | 67641 | 1 | 1.250 | 54112.8 |
| 359 | 2025-05-17 13:13:25 | propensity | 2 | 108824 | 1 | 8.843 | 12306.2 |
| 358 | 2025-05-15 17:25:45 | propensity | 3 | 140603 | 12 | 7.126 | 19731.0 |
| 357 | 2025-05-09 12:01:21 | propensity | 3 | 140603 | 12 | 8.313 | 16913.6 |
| 356 | 2025-05-08 17:04:46 | propensity | 1 | 67641 | 1 | 4.500 | 15031.3 |
| 355 | 2025-05-06 13:35:46 | propensity | 1 | 67641 | 1 | 3.123 | 21659.0 |
| 354 | 2025-05-06 05:44:54 | propensity | 2 | 108824 | 1 | 16.873 | 6449.6 |
| 353 | 2025-05-04 23:25:56 | propensity | 3 | 140603 | 12 | 8.376 | 16786.4 |
| 352 | 2025-04-29 01:54:55 | propensity | 3 | 140603 | 12 | 32.830 | 4282.8 |
| 351 | 2025-04-25 22:34:01 | propensity | 4 | 161450 | 91 | 66.286 | 2435.7 |
| 350 | 2025-04-24 11:16:30 | propensity | 4 | 161450 | 91 | 51.050 | 3162.6 |
| 349 | 2025-04-23 07:27:19 | propensity | 3 | 140603 | 12 | 29.343 | 4791.7 |
| 348 | 2025-04-23 07:06:24 | propensity | 4 | 161450 | 91 | 35.376 | 4563.8 |
| 347 | 2025-04-23 03:35:29 | propensity | 4 | 161450 | 91 | 51.440 | 3138.6 |
| 346 | 2025-04-23 01:42:34 | propensity | 2 | 108824 | 1 | 11.716 | 9288.5 |
| 345 | 2025-04-22 03:33:34 | propensity | 1 | 67641 | 1 | 1.170 | 57812.8 |
| 344 | 2025-04-06 11:35:15 | propensity | 1 | 67641 | 1 | 6.813 | 9928.2 |
| 343 | 2025-03-29 19:08:25 | propensity | 1 | 67641 | 1 | 5.576 | 12130.7 |
| 342 | 2025-03-27 12:22:05 | propensity | 1 | 67641 | 1 | 4.376 | 15457.3 |
| 341 | 2025-03-18 01:57:47 | propensity | 3 | 140603 | 12 | 27.720 | 5072.3 |
| 340 | 2025-03-10 06:17:10 | propensity | 3 | 140603 | 12 | 17.563 | 8005.6 |
| 339 | 2025-03-08 06:55:06 | propensity | 3 | 140603 | 12 | 36.440 | 3858.5 |
| 338 | 2025-03-02 09:13:06 | propensity | 3 | 140603 | 12 | 31.850 | 4414.5 |
| 337 | 2025-02-28 17:28:39 | propensity | 1 | 67641 | 1 | 7.266 | 9309.2 |
| 336 | 2025-02-26 14:19:39 | propensity | 1 | 67641 | 1 | 4.186 | 16158.9 |
| 335 | 2025-02-17 21:55:36 | propensity | 1 | 67641 | 1 | 5.313 | 12731.2 |
| 334 | 2025-02-08 02:42:25 | propensity | 3 | 140603 | 12 | 32.600 | 4313.0 |
| 333 | 2025-02-03 00:05:41 | propensity | 3 | 140603 | 12 | 41.113 | 3419.9 |
| 332 | 2025-01-30 05:49:00 | propensity | 3 | 140603 | 12 | 42.813 | 3284.1 |
| 331 | 2025-01-27 22:18:45 | propensity | 1 | 67641 | 1 | 2.796 | 24192.1 |
| 330 | 2025-01-25 16:31:58 | propensity | 1 | 67641 | 1 | 1.106 | 61158.2 |
| 329 | 2025-01-22 22:16:56 | propensity | 3 | 140603 | 12 | 33.266 | 4226.6 |
| 328 | 2025-01-03 05:57:42 | propensity | 3 | 140603 | 12 | 33.750 | 4166.0 |
| 327 | 2025-01-02 18:08:48 | propensity | 1 | 67641 | 1 | 3.063 | 22083.3 |
| 326 | 2024-12-26 15:07:05 | propensity | 1 | 67641 | 1 | 1.093 | 61885.6 |
| 325 | 2024-12-26 03:45:15 | propensity | 3 | 140603 | 12 | 39.096 | 3596.4 |
| 324 | 2024-12-20 21:40:55 | propensity | 3 | 140603 | 12 | 35.970 | 3908.9 |
| 323 | 2024-12-03 16:05:09 | propensity | 3 | 140603 | 12 | 37.066 | 3793.3 |
| 322 | 2024-11-25 07:07:00 | propensity | 3 | 140603 | 12 | 36.113 | 3893.4 |
| 321 | 2024-11-23 22:40:10 | propensity | 1 | 67641 | 1 | 5.673 | 11923.3 |
| 320 | 2024-11-23 16:06:39 | propensity | 3 | 140603 | 12 | 49.330 | 2850.3 |
| 319 | 2024-11-22 20:40:23 | propensity | 1 | 67641 | 1 | 5.190 | 13032.9 |
| 318 | 2024-11-05 17:00:55 | propensity | 3 | 140603 | 12 | 36.830 | 3817.6 |
| 317 | 2024-10-26 16:47:17 | propensity | 3 | 140603 | 12 | 46.770 | 3006.3 |
| 316 | 2024-10-26 16:47:18 | propensity | 2 | 108824 | 1 | 15.720 | 6922.6 |
| 315 | 2024-10-26 16:46:48 | propensity | 3 | 140603 | 12 | 32.483 | 4328.5 |
| 314 | 2024-10-26 16:46:46 | propensity | 3 | 140603 | 12 | 29.093 | 4832.9 |
| 313 | 2024-10-26 16:44:01 | propensity | 1 | 67641 | 1 | 2.580 | 26217.4 |
| 312 | 2024-10-20 09:55:01 | propensity | 1 | 67641 | 1 | 2.750 | 24596.7 |
| 311 | 2024-10-17 00:35:43 | propensity | 3 | 140603 | 12 | 31.690 | 4436.8 |
| 310 | 2024-10-14 06:30:41 | propensity | 3 | 140603 | 12 | 36.783 | 3822.5 |
| 309 | 2024-10-14 06:30:44 | propensity | 2 | 108824 | 1 | 19.673 | 5531.6 |
| 308 | 2024-10-14 06:30:21 | propensity | 3 | 140603 | 12 | 37.236 | 3776.0 |
| 307 | 2024-10-14 06:30:17 | propensity | 3 | 140603 | 12 | 29.846 | 4710.9 |
| 306 | 2024-10-14 06:22:35 | propensity | 1 | 67641 | 1 | 2.500 | 27056.4 |
| 305 | 2024-10-03 06:14:21 | propensity | 1 | 67641 | 1 | 7.203 | 9390.7 |
| 304 | 2024-09-30 23:15:11 | propensity | 1 | 67641 | 1 | 8.843 | 7649.1 |
| 303 | 2024-09-05 03:17:18 | propensity | 2 | 108824 | 1 | 10.783 | 10092.2 |
| 302 | 2024-09-04 04:21:44 | propensity | 1 | 67641 | 1 | 13.046 | 5184.8 |
| 301 | 2024-09-03 09:49:26 | propensity | 1 | 67641 | 1 | 8.530 | 7929.8 |
| 300 | 2024-09-03 09:49:18 | propensity | 1 | 67641 | 1 | 4.390 | 15408.0 |
| 299 | 2024-08-29 23:57:37 | propensity | 1 | 67641 | 1 | 3.640 | 18582.7 |
| 298 | 2024-08-23 10:35:43 | propensity | 2 | 108824 | 1 | 34.613 | 3144.0 |
| 297 | 2024-08-23 10:35:23 | propensity | 3 | 140603 | 12 | 34.413 | 4085.8 |
| 296 | 2024-08-23 10:34:23 | propensity | 3 | 140603 | 12 | 50.203 | 2800.7 |
| 295 | 2024-08-23 10:33:42 | propensity | 1 | 67641 | 1 | 5.113 | 13229.2 |
| 294 | 2024-08-01 21:32:45 | propensity | 3 | 140603 | 12 | 34.330 | 4095.6 |
| 293 | 2024-07-30 03:17:51 | propensity | 3 | 140603 | 12 | 28.373 | 4955.5 |
| 292 | 2024-07-28 16:47:32 | propensity | 3 | 140603 | 12 | 25.780 | 5454.0 |
| 291 | 2024-07-19 09:02:54 | propensity | 3 | 140603 | 12 | 36.690 | 3832.2 |
| 290 | 2024-07-19 02:30:46 | propensity | 1 | 67641 | 1 | 4.623 | 14631.4 |
| 289 | 2024-07-18 09:48:41 | propensity | 1 | 67641 | 1 | 3.456 | 19572.0 |
| 288 | 2024-07-17 17:33:25 | propensity | 4 | 161450 | 91 | 65.173 | 2477.3 |
| 287 | 2024-07-11 16:57:13 | propensity | 4 | 161450 | 91 | 58.533 | 2758.3 |
| 286 | 2024-07-11 16:57:30 | propensity | 3 | 140603 | 12 | 25.156 | 5589.2 |
| 285 | 2024-07-11 16:57:16 | propensity | 4 | 161450 | 91 | 34.860 | 4631.4 |
| 284 | 2024-07-11 16:57:35 | propensity | 2 | 108824 | 1 | 10.626 | 10241.3 |
| 283 | 2024-07-11 16:51:30 | propensity | 1 | 67641 | 1 | 1.250 | 54112.8 |
| 282 | 2024-07-11 15:21:01 | propensity | 4 | 161450 | 91 | 47.453 | 3402.3 |
| 281 | 2024-07-11 05:00:42 | propensity | 4 | 161450 | 91 | 20.486 | 7881.0 |
| 280 | 2024-07-10 13:55:23 | propensity | 4 | 161450 | 91 | 46.600 | 3464.6 |
| 279 | 2024-07-09 02:28:47 | propensity | 4 | 161450 | 91 | 71.816 | 2248.1 |