History of Dictionary Searches using Damerau-Levenshtein distance in T-SQL
Fuzzy-string Searches
(up to 100 most recent)
for
"multilayer"
| Num | Started At (CA time) | Searched Word | Change Limit | Words Checked | Words Matched | Seconds | Words Per Sec |
| 333 | 2025-10-17 07:33:45 | multilayer | 4 | 161450 | 128 | 13.453 | 12001.0 |
| 332 | 2025-10-13 15:39:13 | multilayer | 1 | 67641 | 2 | 1.030 | 65670.9 |
| 331 | 2025-10-12 22:16:45 | multilayer | 4 | 161450 | 128 | 10.576 | 15265.7 |
| 330 | 2025-10-11 16:17:32 | multilayer | 1 | 67641 | 2 | 1.093 | 61885.6 |
| 329 | 2025-10-01 23:42:13 | multilayer | 1 | 67641 | 2 | 1.233 | 54858.9 |
| 328 | 2025-09-03 00:40:32 | multilayer | 3 | 140603 | 26 | 5.343 | 26315.4 |
| 327 | 2025-08-28 16:42:33 | multilayer | 1 | 67641 | 2 | 1.173 | 57665.0 |
| 326 | 2025-08-13 19:10:56 | multilayer | 1 | 67641 | 2 | 5.416 | 12489.1 |
| 325 | 2025-08-10 09:30:04 | multilayer | 2 | 108824 | 5 | 10.876 | 10005.9 |
| 324 | 2025-08-09 20:02:30 | multilayer | 3 | 140603 | 26 | 27.206 | 5168.1 |
| 323 | 2025-08-09 12:04:45 | multilayer | 1 | 67641 | 2 | 1.063 | 63632.2 |
| 322 | 2025-07-28 15:45:04 | multilayer | 1 | 67641 | 2 | 2.936 | 23038.5 |
| 321 | 2025-07-23 12:01:37 | multilayer | 1 | 67641 | 2 | 5.296 | 12772.1 |
| 320 | 2025-07-22 12:43:23 | multilayer | 1 | 67641 | 2 | 4.656 | 14527.7 |
| 319 | 2025-07-21 07:49:15 | multilayer | 1 | 67641 | 2 | 1.000 | 67641.0 |
| 318 | 2025-07-19 12:30:32 | multilayer | 1 | 67641 | 2 | 3.250 | 20812.6 |
| 317 | 2025-07-14 09:57:53 | multilayer | 1 | 67641 | 2 | 5.486 | 12329.7 |
| 316 | 2025-07-13 00:14:19 | multilayer | 1 | 67641 | 2 | 8.390 | 8062.1 |
| 315 | 2025-07-03 14:35:14 | multilayer | 1 | 67641 | 2 | 1.000 | 67641.0 |
| 314 | 2025-07-02 11:59:36 | multilayer | 1 | 67641 | 2 | 3.750 | 18037.6 |
| 313 | 2025-06-24 05:20:14 | multilayer | 1 | 67641 | 2 | 5.376 | 12582.0 |
| 312 | 2025-06-19 20:37:53 | multilayer | 1 | 67641 | 2 | 5.420 | 12479.9 |
| 311 | 2025-06-17 11:45:40 | multilayer | 1 | 67641 | 2 | 1.063 | 63632.2 |
| 310 | 2025-06-12 01:22:56 | multilayer | 1 | 67641 | 2 | 5.330 | 12690.6 |
| 309 | 2025-06-11 19:54:27 | multilayer | 1 | 67641 | 2 | 1.000 | 67641.0 |
| 308 | 2025-06-08 11:02:14 | multilayer | 1 | 67641 | 2 | 10.656 | 6347.7 |
| 307 | 2025-05-31 01:49:19 | multilayer | 1 | 67641 | 2 | 5.110 | 13237.0 |
| 306 | 2025-05-27 14:33:36 | multilayer | 3 | 140603 | 26 | 47.906 | 2935.0 |
| 305 | 2025-05-27 12:39:35 | multilayer | 3 | 140603 | 26 | 30.063 | 4676.9 |
| 304 | 2025-05-25 18:07:45 | multilayer | 1 | 67641 | 2 | 4.373 | 15467.9 |
| 303 | 2025-05-24 08:35:19 | multilayer | 1 | 67641 | 2 | 3.063 | 22083.3 |
| 302 | 2025-05-22 11:24:41 | multilayer | 1 | 67641 | 2 | 5.376 | 12582.0 |
| 301 | 2025-05-20 20:20:13 | multilayer | 1 | 67641 | 2 | 1.203 | 56226.9 |
| 300 | 2025-05-15 18:52:42 | multilayer | 1 | 67641 | 2 | 1.173 | 57665.0 |
| 299 | 2025-05-15 10:27:57 | multilayer | 1 | 67641 | 2 | 1.046 | 64666.3 |
| 298 | 2025-05-11 04:23:51 | multilayer | 1 | 67641 | 2 | 2.923 | 23141.0 |
| 297 | 2025-05-02 19:44:56 | multilayer | 4 | 161450 | 128 | 11.810 | 13670.6 |
| 296 | 2025-04-28 23:35:22 | multilayer | 4 | 161450 | 128 | 25.173 | 6413.6 |
| 295 | 2025-04-28 15:15:52 | multilayer | 1 | 67641 | 2 | 4.326 | 15635.9 |
| 294 | 2025-04-27 00:49:40 | multilayer | 4 | 161450 | 128 | 11.423 | 14133.8 |
| 293 | 2025-04-23 16:37:50 | multilayer | 1 | 67641 | 2 | 6.470 | 10454.6 |
| 292 | 2025-04-19 01:03:25 | multilayer | 1 | 67641 | 2 | 1.186 | 57032.9 |
| 291 | 2025-04-02 08:17:44 | multilayer | 1 | 67641 | 2 | 5.450 | 12411.2 |
| 290 | 2025-03-25 13:28:53 | multilayer | 1 | 67641 | 2 | 3.236 | 20902.7 |
| 289 | 2025-03-23 11:58:04 | multilayer | 1 | 67641 | 2 | 5.563 | 12159.1 |
| 288 | 2025-03-21 15:59:20 | multilayer | 4 | 161450 | 128 | 60.583 | 2664.9 |
| 287 | 2025-03-21 03:10:01 | multilayer | 4 | 161450 | 128 | 70.846 | 2278.9 |
| 286 | 2025-03-20 18:50:55 | multilayer | 1 | 67641 | 2 | 3.516 | 19238.1 |
| 285 | 2025-03-18 02:08:27 | multilayer | 4 | 161450 | 128 | 49.830 | 3240.0 |
| 284 | 2025-03-15 04:59:35 | multilayer | 4 | 161450 | 128 | 81.113 | 1990.4 |
| 283 | 2025-03-07 08:48:09 | multilayer | 4 | 161450 | 128 | 68.720 | 2349.4 |
| 282 | 2025-03-06 13:57:27 | multilayer | 4 | 161450 | 128 | 67.113 | 2405.6 |
| 281 | 2025-02-20 20:06:29 | multilayer | 2 | 108824 | 5 | 8.796 | 12372.0 |
| 280 | 2025-02-20 20:04:39 | multilayer | 1 | 67641 | 2 | 3.656 | 18501.4 |
| 279 | 2025-02-16 23:18:31 | multilayer | 2 | 108824 | 5 | 7.516 | 14479.0 |
| 278 | 2025-02-16 23:16:28 | multilayer | 1 | 67641 | 2 | 2.436 | 27767.2 |
| 277 | 2025-02-12 07:49:51 | multilayer | 4 | 161450 | 128 | 59.423 | 2717.0 |
| 276 | 2025-02-07 12:23:13 | multilayer | 1 | 67641 | 2 | 2.500 | 27056.4 |
| 275 | 2025-02-07 12:12:34 | multilayer | 4 | 161450 | 128 | 62.676 | 2575.9 |
| 274 | 2025-02-07 10:08:41 | multilayer | 4 | 161450 | 128 | 41.456 | 3894.5 |
| 273 | 2025-02-07 10:08:40 | multilayer | 2 | 108824 | 5 | 24.780 | 4391.6 |
| 272 | 2025-02-07 08:34:07 | multilayer | 3 | 140603 | 26 | 26.330 | 5340.0 |
| 271 | 2025-02-05 14:57:39 | multilayer | 3 | 140603 | 26 | 32.096 | 4380.7 |
| 270 | 2025-01-30 17:42:39 | multilayer | 3 | 140603 | 26 | 32.380 | 4342.3 |
| 269 | 2025-01-24 14:32:05 | multilayer | 3 | 140603 | 26 | 46.720 | 3009.5 |
| 268 | 2025-01-24 07:04:12 | multilayer | 3 | 140603 | 26 | 33.910 | 4146.4 |
| 267 | 2025-01-21 07:35:48 | multilayer | 1 | 67641 | 2 | 6.313 | 10714.6 |
| 266 | 2025-01-15 09:56:21 | multilayer | 1 | 67641 | 2 | 4.000 | 16910.3 |
| 265 | 2025-01-13 10:25:56 | multilayer | 2 | 108824 | 5 | 14.736 | 7384.9 |
| 264 | 2025-01-13 10:23:32 | multilayer | 1 | 67641 | 2 | 3.703 | 18266.5 |
| 263 | 2025-01-04 00:29:46 | multilayer | 3 | 140603 | 26 | 44.236 | 3178.5 |
| 262 | 2025-01-02 03:01:02 | multilayer | 2 | 108824 | 5 | 14.940 | 7284.1 |
| 261 | 2025-01-02 02:59:38 | multilayer | 1 | 67641 | 2 | 5.640 | 11993.1 |
| 260 | 2024-12-23 16:27:15 | multilayer | 3 | 140603 | 26 | 29.170 | 4820.1 |
| 259 | 2024-12-19 07:15:54 | multilayer | 4 | 161450 | 128 | 64.316 | 2510.3 |
| 258 | 2024-12-19 04:43:30 | multilayer | 4 | 161450 | 128 | 51.850 | 3113.8 |
| 257 | 2024-12-18 16:31:24 | multilayer | 4 | 161450 | 128 | 56.190 | 2873.3 |
| 256 | 2024-12-18 12:42:15 | multilayer | 2 | 108824 | 5 | 19.720 | 5518.5 |
| 255 | 2024-12-18 11:17:00 | multilayer | 1 | 67641 | 2 | 1.000 | 67641.0 |
| 254 | 2024-12-18 11:16:21 | multilayer | 3 | 140603 | 26 | 7.420 | 18949.2 |
| 253 | 2024-12-18 06:26:35 | multilayer | 3 | 140603 | 26 | 34.130 | 4119.6 |
| 252 | 2024-12-13 11:28:28 | multilayer | 1 | 67641 | 2 | 3.580 | 18894.1 |
| 251 | 2024-12-02 06:46:57 | multilayer | 1 | 67641 | 2 | 6.326 | 10692.5 |
| 250 | 2024-11-28 09:19:13 | multilayer | 1 | 67641 | 2 | 2.436 | 27767.2 |
| 249 | 2024-11-23 00:36:10 | multilayer | 2 | 108824 | 5 | 18.406 | 5912.4 |
| 248 | 2024-11-21 04:26:56 | multilayer | 3 | 140603 | 26 | 31.206 | 4505.6 |
| 247 | 2024-11-20 08:09:45 | multilayer | 3 | 140603 | 26 | 44.076 | 3190.0 |
| 246 | 2024-11-17 12:09:11 | multilayer | 2 | 108824 | 5 | 22.626 | 4809.7 |
| 245 | 2024-11-17 12:05:46 | multilayer | 1 | 67641 | 2 | 1.283 | 52721.0 |
| 244 | 2024-11-17 06:46:34 | multilayer | 4 | 161450 | 128 | 55.380 | 2915.3 |
| 243 | 2024-11-17 01:23:00 | multilayer | 4 | 161450 | 128 | 60.956 | 2648.6 |
| 242 | 2024-11-15 15:28:24 | multilayer | 4 | 161450 | 128 | 53.813 | 3000.2 |
| 241 | 2024-11-15 14:01:08 | multilayer | 3 | 140603 | 26 | 27.183 | 5172.5 |
| 240 | 2024-11-14 02:43:07 | multilayer | 3 | 140603 | 26 | 50.096 | 2806.7 |
| 239 | 2024-10-28 14:31:02 | multilayer | 1 | 67641 | 2 | 1.030 | 65670.9 |
| 238 | 2024-10-20 05:22:00 | multilayer | 3 | 140603 | 26 | 31.923 | 4404.4 |
| 237 | 2024-10-17 16:44:59 | multilayer | 1 | 67641 | 2 | 8.236 | 8212.8 |
| 236 | 2024-10-08 21:29:07 | multilayer | 3 | 140603 | 26 | 64.720 | 2172.5 |
| 235 | 2024-10-05 13:18:06 | multilayer | 3 | 140603 | 26 | 48.423 | 2903.6 |
| 234 | 2024-10-05 02:02:31 | multilayer | 2 | 108824 | 5 | 17.546 | 6202.2 |