History of Dictionary Searches using Damerau-Levenshtein distance in T-SQL
Fuzzy-string Searches
(up to 100 most recent)
for
"proneness"
| Num | Started At (CA time) | Searched Word | Change Limit | Words Checked | Words Matched | Seconds | Words Per Sec |
| 366 | 2025-10-24 03:21:37 | proneness | 1 | 81242 | 1 | 1.300 | 62493.8 |
| 365 | 2025-10-14 05:10:17 | proneness | 1 | 81242 | 1 | 1.310 | 62016.8 |
| 364 | 2025-10-12 06:56:12 | proneness | 1 | 81242 | 1 | 1.436 | 56575.2 |
| 363 | 2025-10-05 10:24:08 | proneness | 1 | 81242 | 1 | 1.360 | 59736.8 |
| 362 | 2025-10-04 15:47:25 | proneness | 1 | 81242 | 1 | 1.580 | 51419.0 |
| 361 | 2025-10-04 00:28:08 | proneness | 1 | 81242 | 1 | 1.343 | 60492.9 |
| 360 | 2025-09-26 07:23:08 | proneness | 1 | 81242 | 1 | 1.423 | 57092.1 |
| 359 | 2025-09-20 05:44:09 | proneness | 1 | 81242 | 1 | 1.406 | 57782.4 |
| 358 | 2025-09-16 16:31:42 | proneness | 1 | 81242 | 1 | 1.310 | 62016.8 |
| 357 | 2025-09-10 21:48:47 | proneness | 1 | 81242 | 1 | 1.436 | 56575.2 |
| 356 | 2025-09-02 11:49:08 | proneness | 1 | 81242 | 1 | 1.310 | 62016.8 |
| 355 | 2025-08-25 15:58:32 | proneness | 1 | 81242 | 1 | 3.593 | 22611.2 |
| 354 | 2025-08-19 09:22:32 | proneness | 1 | 81242 | 1 | 6.406 | 12682.2 |
| 353 | 2025-08-19 05:09:13 | proneness | 1 | 81242 | 1 | 4.936 | 16459.1 |
| 352 | 2025-08-12 07:48:39 | proneness | 1 | 81242 | 1 | 6.000 | 13540.3 |
| 351 | 2025-08-09 04:36:40 | proneness | 1 | 81242 | 1 | 8.360 | 9717.9 |
| 350 | 2025-08-07 08:36:55 | proneness | 2 | 121436 | 17 | 10.593 | 11463.8 |
| 349 | 2025-08-04 06:42:00 | proneness | 1 | 81242 | 1 | 10.393 | 7817.0 |
| 348 | 2025-08-01 00:48:00 | proneness | 1 | 81242 | 1 | 6.800 | 11947.4 |
| 347 | 2025-07-30 16:40:03 | proneness | 2 | 121436 | 17 | 18.596 | 6530.2 |
| 346 | 2025-07-28 17:20:00 | proneness | 1 | 81242 | 1 | 8.686 | 9353.2 |
| 345 | 2025-07-25 20:04:21 | proneness | 2 | 121436 | 17 | 4.046 | 30013.8 |
| 344 | 2025-07-24 11:37:57 | proneness | 2 | 121436 | 17 | 8.953 | 13563.7 |
| 343 | 2025-07-18 10:07:15 | proneness | 1 | 81242 | 1 | 3.656 | 22221.6 |
| 342 | 2025-07-18 09:50:22 | proneness | 1 | 81242 | 1 | 4.470 | 18174.9 |
| 341 | 2025-07-16 23:48:42 | proneness | 1 | 81242 | 1 | 3.140 | 25873.2 |
| 340 | 2025-07-16 01:13:09 | proneness | 2 | 121436 | 17 | 3.890 | 31217.5 |
| 339 | 2025-07-13 14:51:29 | proneness | 1 | 81242 | 1 | 1.470 | 55266.7 |
| 338 | 2025-07-12 10:09:12 | proneness | 3 | 148641 | 139 | 11.873 | 12519.2 |
| 337 | 2025-07-11 11:47:10 | proneness | 3 | 148641 | 139 | 40.050 | 3711.4 |
| 336 | 2025-07-10 17:05:11 | proneness | 3 | 148641 | 139 | 36.563 | 4065.3 |
| 335 | 2025-07-10 12:14:13 | proneness | 1 | 81242 | 1 | 6.986 | 11629.3 |
| 334 | 2025-07-07 21:04:16 | proneness | 3 | 148641 | 139 | 46.740 | 3180.2 |
| 333 | 2025-07-07 04:18:22 | proneness | 1 | 81242 | 1 | 3.470 | 23412.7 |
| 332 | 2025-07-04 02:26:00 | proneness | 1 | 81242 | 1 | 8.530 | 9524.3 |
| 331 | 2025-07-03 16:37:17 | proneness | 3 | 148641 | 139 | 7.420 | 20032.5 |
| 330 | 2025-07-03 05:44:15 | proneness | 1 | 81242 | 1 | 5.390 | 15072.7 |
| 329 | 2025-06-27 19:51:28 | proneness | 1 | 81242 | 1 | 1.563 | 51978.2 |
| 328 | 2025-06-22 17:00:40 | proneness | 1 | 81242 | 1 | 6.953 | 11684.5 |
| 327 | 2025-06-22 03:07:42 | proneness | 1 | 81242 | 1 | 3.673 | 22118.7 |
| 326 | 2025-06-16 15:27:08 | proneness | 1 | 81242 | 1 | 6.436 | 12623.1 |
| 325 | 2025-06-15 21:29:37 | proneness | 1 | 81242 | 1 | 4.390 | 18506.2 |
| 324 | 2025-06-13 05:03:09 | proneness | 3 | 148641 | 139 | 20.643 | 7200.6 |
| 323 | 2025-06-12 20:19:18 | proneness | 3 | 148641 | 139 | 31.720 | 4686.0 |
| 322 | 2025-06-11 02:07:32 | proneness | 3 | 148641 | 139 | 31.956 | 4651.4 |
| 321 | 2025-06-10 22:42:05 | proneness | 1 | 81242 | 1 | 1.250 | 64993.6 |
| 320 | 2025-06-10 18:23:06 | proneness | 1 | 81242 | 1 | 6.780 | 11982.6 |
| 319 | 2025-06-10 14:43:30 | proneness | 3 | 148641 | 139 | 35.376 | 4201.7 |
| 318 | 2025-06-10 08:39:39 | proneness | 3 | 148641 | 139 | 23.953 | 6205.5 |
| 317 | 2025-06-08 21:03:47 | proneness | 2 | 121436 | 17 | 3.920 | 30978.6 |
| 316 | 2025-06-08 19:05:11 | proneness | 2 | 121436 | 17 | 17.906 | 6781.9 |
| 315 | 2025-06-08 06:43:54 | proneness | 1 | 81242 | 1 | 6.826 | 11901.8 |
| 314 | 2025-06-07 21:00:38 | proneness | 3 | 148641 | 139 | 28.796 | 5161.9 |
| 313 | 2025-06-06 16:08:33 | proneness | 1 | 81242 | 1 | 6.703 | 12120.2 |
| 312 | 2025-06-05 13:27:05 | proneness | 2 | 121436 | 17 | 9.046 | 13424.3 |
| 311 | 2025-06-03 16:14:22 | proneness | 3 | 148641 | 139 | 31.733 | 4684.1 |
| 310 | 2025-06-03 04:53:52 | proneness | 2 | 121436 | 17 | 17.546 | 6921.0 |
| 309 | 2025-06-02 14:41:48 | proneness | 1 | 81242 | 1 | 6.093 | 13333.7 |
| 308 | 2025-06-01 21:28:00 | proneness | 2 | 121436 | 17 | 24.126 | 5033.4 |
| 307 | 2025-05-28 05:37:39 | proneness | 1 | 81242 | 1 | 1.406 | 57782.4 |
| 306 | 2025-05-26 05:42:59 | proneness | 1 | 81242 | 1 | 7.170 | 11330.8 |
| 305 | 2025-05-19 05:57:03 | proneness | 3 | 148641 | 139 | 18.690 | 7953.0 |
| 304 | 2025-05-19 04:58:04 | proneness | 1 | 81242 | 1 | 3.923 | 20709.2 |
| 303 | 2025-05-18 17:34:01 | proneness | 1 | 81242 | 1 | 10.313 | 7877.6 |
| 302 | 2025-05-17 05:54:42 | proneness | 3 | 148641 | 139 | 20.126 | 7385.5 |
| 301 | 2025-05-14 18:53:51 | proneness | 1 | 81242 | 1 | 1.250 | 64993.6 |
| 300 | 2025-05-10 23:32:57 | proneness | 3 | 148641 | 139 | 36.313 | 4093.3 |
| 299 | 2025-05-10 09:13:39 | proneness | 3 | 148641 | 139 | 23.360 | 6363.1 |
| 298 | 2025-05-06 05:52:07 | proneness | 3 | 148641 | 139 | 19.580 | 7591.5 |
| 297 | 2025-05-06 04:55:23 | proneness | 2 | 121436 | 17 | 14.393 | 8437.2 |
| 296 | 2025-05-05 20:43:56 | proneness | 3 | 148641 | 139 | 33.046 | 4498.0 |
| 295 | 2025-05-05 10:01:00 | proneness | 2 | 121436 | 17 | 18.703 | 6492.9 |
| 294 | 2025-05-05 05:17:00 | proneness | 1 | 81242 | 1 | 1.783 | 45564.8 |
| 293 | 2025-05-04 20:32:48 | proneness | 3 | 148641 | 139 | 7.220 | 20587.4 |
| 292 | 2025-05-04 17:53:37 | proneness | 3 | 148641 | 139 | 46.236 | 3214.8 |
| 291 | 2025-05-01 04:18:24 | proneness | 1 | 81242 | 1 | 7.373 | 11018.9 |
| 290 | 2025-04-28 07:17:45 | proneness | 1 | 81242 | 1 | 7.033 | 11551.5 |
| 289 | 2025-04-18 17:49:13 | proneness | 1 | 81242 | 1 | 6.716 | 12096.8 |
| 288 | 2025-04-13 21:20:25 | proneness | 2 | 121436 | 17 | 19.063 | 6370.2 |
| 287 | 2025-04-12 07:11:33 | proneness | 2 | 121436 | 17 | 9.250 | 13128.2 |
| 286 | 2025-04-09 21:09:16 | proneness | 3 | 148641 | 139 | 8.640 | 17203.8 |
| 285 | 2025-04-07 04:45:50 | proneness | 3 | 148641 | 139 | 35.330 | 4207.2 |
| 284 | 2025-04-02 09:02:59 | proneness | 1 | 81242 | 1 | 7.233 | 11232.1 |
| 283 | 2025-03-25 19:52:35 | proneness | 1 | 81242 | 1 | 10.030 | 8099.9 |
| 282 | 2025-03-24 05:16:36 | proneness | 1 | 81242 | 1 | 6.640 | 12235.2 |
| 281 | 2025-03-20 21:41:12 | proneness | 3 | 148641 | 139 | 44.093 | 3371.1 |
| 280 | 2025-03-20 07:11:37 | proneness | 1 | 81242 | 1 | 3.533 | 22995.2 |
| 279 | 2025-03-19 21:45:37 | proneness | 3 | 148641 | 139 | 31.423 | 4730.3 |
| 278 | 2025-03-16 21:21:10 | proneness | 1 | 81242 | 1 | 5.986 | 13572.0 |
| 277 | 2025-03-16 11:17:58 | proneness | 3 | 148641 | 139 | 39.576 | 3755.8 |
| 276 | 2025-03-16 09:58:34 | proneness | 3 | 148641 | 139 | 39.456 | 3767.3 |
| 275 | 2025-03-16 09:58:28 | proneness | 2 | 121436 | 17 | 12.016 | 10106.2 |
| 274 | 2025-03-16 09:54:31 | proneness | 1 | 81242 | 1 | 6.080 | 13362.2 |
| 273 | 2025-03-02 10:32:49 | proneness | 1 | 81242 | 1 | 4.780 | 16996.2 |
| 272 | 2025-03-01 11:03:02 | proneness | 1 | 81242 | 1 | 10.126 | 8023.1 |
| 271 | 2025-02-28 20:46:32 | proneness | 1 | 81242 | 1 | 6.860 | 11842.9 |
| 270 | 2025-01-25 13:41:25 | proneness | 1 | 81242 | 1 | 7.376 | 11014.4 |
| 269 | 2025-01-05 21:38:45 | proneness | 1 | 81242 | 1 | 9.736 | 8344.5 |
| 268 | 2025-01-01 20:45:05 | proneness | 1 | 81242 | 1 | 1.470 | 55266.7 |
| 267 | 2024-12-26 07:31:14 | proneness | 1 | 81242 | 1 | 3.030 | 26812.5 |