History of Dictionary Searches using Damerau-Levenshtein distance in T-SQL
Fuzzy-string Searches
(up to 100 most recent)
for
"optimality"
| Num | Started At (CA time) | Searched Word | Change Limit | Words Checked | Words Matched | Seconds | Words Per Sec |
| 372 | 2026-02-15 18:40:23 | optimality | 1 | 67641 | 1 | 1.156 | 58513.0 |
| 371 | 2026-02-15 01:09:36 | optimality | 3 | 140603 | 12 | 11.580 | 12141.9 |
| 370 | 2026-02-14 23:26:05 | optimality | 4 | 161450 | 80 | 41.313 | 3908.0 |
| 369 | 2026-02-12 11:25:08 | optimality | 1 | 67641 | 1 | 5.516 | 12262.7 |
| 368 | 2026-02-12 11:24:43 | optimality | 1 | 67641 | 1 | 5.530 | 12231.6 |
| 367 | 2026-02-08 13:17:57 | optimality | 4 | 161450 | 80 | 14.346 | 11254.0 |
| 366 | 2026-02-06 23:48:06 | optimality | 4 | 161450 | 80 | 15.530 | 10396.0 |
| 365 | 2026-02-05 10:47:07 | optimality | 3 | 140603 | 12 | 5.906 | 23806.8 |
| 364 | 2026-02-04 09:28:38 | optimality | 3 | 140603 | 12 | 6.546 | 21479.2 |
| 363 | 2026-02-03 16:00:15 | optimality | 4 | 161450 | 80 | 10.220 | 15797.5 |
| 362 | 2026-02-01 15:02:17 | optimality | 3 | 140603 | 12 | 5.890 | 23871.5 |
| 361 | 2026-01-26 15:58:29 | optimality | 5 | 173545 | 428 | 16.953 | 10236.8 |
| 360 | 2026-01-18 16:26:05 | optimality | 1 | 67641 | 1 | 1.060 | 63812.3 |
| 359 | 2026-01-15 13:06:24 | optimality | 3 | 140603 | 12 | 5.893 | 23859.3 |
| 358 | 2026-01-14 22:36:28 | optimality | 4 | 161450 | 80 | 11.310 | 14275.0 |
| 357 | 2026-01-14 17:10:21 | optimality | 3 | 140603 | 12 | 23.516 | 5979.0 |
| 356 | 2026-01-14 15:30:58 | optimality | 3 | 140603 | 12 | 14.030 | 10021.6 |
| 355 | 2026-01-14 12:13:40 | optimality | 2 | 108824 | 4 | 3.156 | 34481.6 |
| 354 | 2026-01-13 20:14:49 | optimality | 4 | 161450 | 80 | 11.156 | 14472.0 |
| 353 | 2026-01-11 12:53:20 | optimality | 2 | 108824 | 4 | 2.640 | 41221.2 |
| 352 | 2026-01-11 03:45:04 | optimality | 2 | 108824 | 4 | 3.093 | 35184.0 |
| 351 | 2026-01-10 22:51:46 | optimality | 4 | 161450 | 80 | 18.703 | 8632.3 |
| 350 | 2026-01-10 02:04:42 | optimality | 1 | 67641 | 1 | 1.063 | 63632.2 |
| 349 | 2026-01-09 09:30:25 | optimality | 1 | 67641 | 1 | 1.156 | 58513.0 |
| 348 | 2026-01-09 00:09:03 | optimality | 5 | 173545 | 428 | 17.406 | 9970.4 |
| 347 | 2026-01-08 04:08:51 | optimality | 1 | 67641 | 1 | 1.033 | 65480.2 |
| 346 | 2026-01-07 15:18:58 | optimality | 2 | 108824 | 4 | 5.923 | 18373.1 |
| 345 | 2026-01-07 03:28:07 | optimality | 1 | 67641 | 1 | 1.096 | 61716.2 |
| 344 | 2026-01-05 00:59:01 | optimality | 5 | 173545 | 428 | 18.143 | 9565.4 |
| 343 | 2026-01-03 22:09:33 | optimality | 5 | 173545 | 428 | 19.546 | 8878.8 |
| 342 | 2026-01-03 04:05:54 | optimality | 4 | 161450 | 80 | 15.436 | 10459.3 |
| 341 | 2025-12-31 03:40:44 | optimality | 2 | 108824 | 4 | 2.780 | 39145.3 |
| 340 | 2025-12-24 21:19:46 | optimality | 1 | 67641 | 1 | 1.060 | 63812.3 |
| 339 | 2025-12-08 20:41:24 | optimality | 1 | 67641 | 1 | 1.033 | 65480.2 |
| 338 | 2025-12-07 16:56:36 | optimality | 1 | 67641 | 1 | 1.153 | 58665.2 |
| 337 | 2025-11-30 02:00:37 | optimality | 1 | 67641 | 1 | 1.206 | 56087.1 |
| 336 | 2025-11-26 23:24:51 | optimality | 1 | 67641 | 1 | 1.156 | 58513.0 |
| 335 | 2025-11-12 07:56:43 | optimality | 1 | 67641 | 1 | 1.123 | 60232.4 |
| 334 | 2025-11-02 01:10:45 | optimality | 1 | 67641 | 1 | 1.186 | 57032.9 |
| 333 | 2025-10-28 18:05:28 | optimality | 1 | 67641 | 1 | 1.076 | 62863.4 |
| 332 | 2025-10-11 17:45:11 | optimality | 3 | 140603 | 12 | 6.766 | 20780.8 |
| 331 | 2025-10-11 11:36:10 | optimality | 2 | 108824 | 4 | 2.626 | 41441.0 |
| 330 | 2025-10-08 18:25:53 | optimality | 4 | 161450 | 80 | 10.500 | 15376.2 |
| 329 | 2025-09-12 01:45:17 | optimality | 4 | 161450 | 80 | 10.343 | 15609.6 |
| 328 | 2025-09-07 07:17:41 | optimality | 1 | 67641 | 1 | 1.186 | 57032.9 |
| 327 | 2025-09-06 05:41:43 | optimality | 2 | 108824 | 4 | 2.736 | 39774.9 |
| 326 | 2025-09-05 14:27:19 | optimality | 3 | 140603 | 12 | 5.483 | 25643.4 |
| 325 | 2025-08-26 02:55:48 | optimality | 4 | 161450 | 80 | 46.786 | 3450.8 |
| 324 | 2025-08-25 00:36:59 | optimality | 2 | 108824 | 4 | 15.060 | 7226.0 |
| 323 | 2025-08-24 12:51:13 | optimality | 1 | 67641 | 1 | 1.016 | 66575.8 |
| 322 | 2025-08-22 20:03:32 | optimality | 3 | 140603 | 12 | 20.983 | 6700.8 |
| 321 | 2025-08-21 03:52:49 | optimality | 4 | 161450 | 80 | 47.580 | 3393.2 |
| 320 | 2025-08-20 12:48:07 | optimality | 2 | 108824 | 4 | 6.173 | 17629.0 |
| 319 | 2025-08-20 06:49:10 | optimality | 1 | 67641 | 1 | 1.126 | 60071.9 |
| 318 | 2025-08-19 06:16:22 | optimality | 4 | 161450 | 80 | 34.923 | 4623.0 |
| 317 | 2025-08-18 22:18:43 | optimality | 3 | 140603 | 12 | 19.126 | 7351.4 |
| 316 | 2025-08-15 16:42:12 | optimality | 4 | 161450 | 80 | 44.846 | 3600.1 |
| 315 | 2025-08-13 20:37:55 | optimality | 1 | 67641 | 1 | 3.843 | 17601.1 |
| 314 | 2025-08-05 14:37:35 | optimality | 2 | 108824 | 4 | 15.550 | 6998.3 |
| 313 | 2025-08-05 11:05:56 | optimality | 3 | 140603 | 12 | 16.206 | 8676.0 |
| 312 | 2025-08-04 09:55:46 | optimality | 1 | 67641 | 1 | 2.110 | 32057.3 |
| 311 | 2025-07-28 20:26:02 | optimality | 3 | 140603 | 12 | 31.503 | 4463.2 |
| 310 | 2025-07-26 11:45:49 | optimality | 1 | 67641 | 1 | 1.220 | 55443.4 |
| 309 | 2025-07-25 17:26:48 | optimality | 1 | 67641 | 1 | 2.733 | 24749.7 |
| 308 | 2025-07-25 09:59:31 | optimality | 1 | 67641 | 1 | 3.920 | 17255.4 |
| 307 | 2025-07-24 18:05:39 | optimality | 1 | 67641 | 1 | 4.283 | 15792.9 |
| 306 | 2025-07-20 20:40:31 | optimality | 3 | 140603 | 12 | 9.643 | 14580.8 |
| 305 | 2025-07-19 07:24:47 | optimality | 1 | 67641 | 1 | 1.096 | 61716.2 |
| 304 | 2025-07-12 15:56:13 | optimality | 1 | 67641 | 1 | 2.720 | 24868.0 |
| 303 | 2025-07-04 09:53:28 | optimality | 1 | 67641 | 1 | 2.626 | 25758.2 |
| 302 | 2025-06-27 15:30:00 | optimality | 2 | 108824 | 4 | 10.940 | 9947.3 |
| 301 | 2025-06-17 14:15:32 | optimality | 1 | 67641 | 1 | 5.156 | 13118.9 |
| 300 | 2025-06-10 13:24:16 | optimality | 1 | 67641 | 1 | 5.140 | 13159.7 |
| 299 | 2025-05-31 19:36:48 | optimality | 1 | 67641 | 1 | 5.453 | 12404.4 |
| 298 | 2025-05-30 23:18:15 | optimality | 1 | 67641 | 1 | 7.470 | 9055.0 |
| 297 | 2025-05-22 13:21:31 | optimality | 1 | 67641 | 1 | 5.720 | 11825.3 |
| 296 | 2025-05-07 04:20:33 | optimality | 1 | 67641 | 1 | 1.190 | 56841.2 |
| 295 | 2025-04-26 13:00:46 | optimality | 1 | 67641 | 1 | 5.640 | 11993.1 |
| 294 | 2025-04-24 09:08:39 | optimality | 3 | 140603 | 12 | 31.486 | 4465.6 |
| 293 | 2025-04-17 07:56:10 | optimality | 3 | 140603 | 12 | 32.546 | 4320.1 |
| 292 | 2025-04-06 03:42:09 | optimality | 3 | 140603 | 12 | 25.566 | 5499.6 |
| 291 | 2025-03-29 15:38:14 | optimality | 3 | 140603 | 12 | 31.003 | 4535.1 |
| 290 | 2025-03-29 12:16:10 | optimality | 1 | 67641 | 1 | 5.890 | 11484.0 |
| 289 | 2025-03-29 05:33:54 | optimality | 3 | 140603 | 12 | 42.173 | 3334.0 |
| 288 | 2025-03-29 02:18:52 | optimality | 2 | 108824 | 4 | 11.080 | 9821.7 |
| 287 | 2025-03-28 21:22:30 | optimality | 3 | 140603 | 12 | 31.783 | 4423.8 |
| 286 | 2025-03-28 15:17:44 | optimality | 1 | 67641 | 1 | 1.190 | 56841.2 |
| 285 | 2025-03-26 15:20:51 | optimality | 1 | 67641 | 1 | 8.250 | 8198.9 |
| 284 | 2025-03-25 04:54:11 | optimality | 1 | 67641 | 1 | 7.830 | 8638.7 |
| 283 | 2025-03-13 12:22:45 | optimality | 1 | 67641 | 1 | 5.423 | 12473.0 |
| 282 | 2025-03-09 09:40:20 | optimality | 1 | 67641 | 1 | 4.830 | 14004.3 |
| 281 | 2025-02-20 20:22:17 | optimality | 3 | 140603 | 12 | 32.343 | 4347.2 |
| 280 | 2025-02-18 17:10:51 | optimality | 4 | 161450 | 80 | 45.423 | 3554.4 |
| 279 | 2025-02-15 19:44:24 | optimality | 1 | 67641 | 1 | 5.280 | 12810.8 |
| 278 | 2025-02-15 02:23:06 | optimality | 1 | 67641 | 1 | 5.376 | 12582.0 |
| 277 | 2025-02-13 14:42:38 | optimality | 3 | 140603 | 12 | 27.516 | 5109.9 |
| 276 | 2025-02-13 14:42:33 | optimality | 2 | 108824 | 4 | 21.173 | 5139.8 |
| 275 | 2025-02-13 14:41:40 | optimality | 4 | 161450 | 80 | 49.033 | 3292.7 |
| 274 | 2025-02-13 14:40:34 | optimality | 1 | 67641 | 1 | 5.966 | 11337.7 |
| 273 | 2025-02-13 12:42:08 | optimality | 4 | 161450 | 80 | 57.710 | 2797.6 |