History of Dictionary Searches using Damerau-Levenshtein distance in T-SQL
Fuzzy-string Searches
(up to 100 most recent)
for
"meat"
Num | Started At (CA time) | Searched Word | Change Limit | Words Checked | Words Matched | Seconds | Words Per Sec |
1451 | 2024-05-10 04:23:15 | meat | 1 | 13983 | 21 | 0.266 | 52567.7 |
1450 | 2024-05-06 19:32:05 | meat | 1 | 13983 | 21 | 0.233 | 60012.9 |
1449 | 2024-04-30 02:36:06 | meat | 1 | 13983 | 21 | 0.610 | 22923.0 |
1448 | 2024-04-27 22:11:29 | meat | 1 | 13983 | 21 | 0.233 | 60012.9 |
1447 | 2024-04-26 23:15:16 | meat | 1 | 13983 | 21 | 0.266 | 52567.7 |
1446 | 2024-04-24 01:08:36 | meat | 1 | 13983 | 21 | 0.500 | 27966.0 |
1445 | 2024-04-19 14:47:40 | meat | 1 | 13983 | 21 | 0.233 | 60012.9 |
1444 | 2024-04-18 19:44:23 | meat | 1 | 13983 | 21 | 0.233 | 60012.9 |
1443 | 2024-04-05 16:47:30 | meat | 1 | 13983 | 21 | 0.266 | 52567.7 |
1442 | 2024-04-01 17:51:38 | meat | 2 | 29872 | 357 | 3.216 | 9288.6 |
1441 | 2024-04-01 16:08:37 | meat | 1 | 13983 | 21 | 0.250 | 55932.0 |
1440 | 2024-03-31 01:27:18 | meat | 2 | 29872 | 357 | 1.483 | 20143.0 |
1439 | 2024-03-31 01:05:47 | meat | 1 | 13983 | 21 | 0.436 | 32071.1 |
1438 | 2024-03-02 17:45:44 | meat | 1 | 13983 | 21 | 0.203 | 68881.8 |
1437 | 2024-03-02 14:35:26 | meat | 2 | 29872 | 357 | 3.033 | 9849.0 |
1436 | 2024-03-02 13:42:04 | meat | 1 | 13983 | 21 | 0.563 | 24836.6 |
1435 | 2024-03-01 11:13:24 | meat | 1 | 13983 | 21 | 0.263 | 53167.3 |
1434 | 2024-03-01 10:43:48 | meat | 1 | 13983 | 21 | 1.296 | 10789.4 |
1433 | 2024-02-20 07:19:39 | meat | 1 | 13983 | 21 | 0.283 | 49409.9 |
1432 | 2024-01-29 22:16:58 | meat | 1 | 13983 | 21 | 0.250 | 55932.0 |
1431 | 2024-01-28 15:21:11 | meat | 1 | 13983 | 21 | 0.203 | 68881.8 |
1430 | 2024-01-26 03:48:50 | meat | 1 | 13983 | 21 | 0.233 | 60012.9 |
1429 | 2024-01-25 18:58:13 | meat | 1 | 13983 | 21 | 0.236 | 59250.0 |
1428 | 2024-01-24 03:29:11 | meat | 1 | 13983 | 21 | 0.203 | 68881.8 |
1427 | 2023-12-26 12:23:46 | meat | 1 | 13983 | 21 | 0.220 | 63559.1 |
1426 | 2023-12-15 09:24:15 | meat | 1 | 13983 | 21 | 0.250 | 55932.0 |
1425 | 2023-12-13 09:05:19 | meat | 1 | 13983 | 21 | 0.233 | 60012.9 |
1424 | 2023-12-12 05:20:35 | meat | 2 | 29872 | 357 | 0.843 | 35435.3 |
1423 | 2023-12-03 00:44:56 | meat | 2 | 29872 | 357 | 1.813 | 16476.6 |
1422 | 2023-11-27 14:23:48 | meat | 1 | 13983 | 21 | 0.233 | 60012.9 |
1421 | 2023-11-22 13:29:14 | meat | 1 | 13983 | 21 | 0.203 | 68881.8 |
1420 | 2023-11-11 06:11:04 | meat | 1 | 13983 | 21 | 0.200 | 69915.0 |
1419 | 2023-11-10 12:57:16 | meat | 1 | 13983 | 21 | 0.203 | 68881.8 |
1418 | 2023-11-08 03:44:36 | meat | 1 | 13983 | 21 | 0.250 | 55932.0 |
1417 | 2023-11-02 02:42:21 | meat | 1 | 13983 | 21 | 0.233 | 60012.9 |
1416 | 2023-10-26 04:09:56 | meat | 2 | 29872 | 357 | 0.763 | 39150.7 |
1415 | 2023-10-26 00:01:25 | meat | 1 | 13983 | 21 | 0.236 | 59250.0 |
1414 | 2023-10-25 02:12:38 | meat | 2 | 29872 | 357 | 0.733 | 40753.1 |
1413 | 2023-10-19 18:49:32 | meat | 1 | 13983 | 21 | 0.220 | 63559.1 |
1412 | 2023-10-17 17:15:03 | meat | 1 | 13983 | 21 | 0.233 | 60012.9 |
1411 | 2023-10-14 10:50:24 | meat | 1 | 13983 | 21 | 0.546 | 25609.9 |
1410 | 2023-10-12 11:20:13 | meat | 2 | 29872 | 357 | 0.763 | 39150.7 |
1409 | 2023-10-12 10:37:34 | meat | 1 | 13983 | 21 | 0.220 | 63559.1 |
1408 | 2023-10-03 17:06:05 | meat | 1 | 13983 | 21 | 0.220 | 63559.1 |
1407 | 2023-09-25 13:03:19 | meat | 2 | 29872 | 357 | 0.873 | 34217.6 |
1406 | 2023-09-25 09:23:36 | meat | 1 | 13983 | 21 | 0.233 | 60012.9 |
1405 | 2023-09-24 13:04:14 | meat | 1 | 13983 | 21 | 0.203 | 68881.8 |
1404 | 2023-09-23 22:06:23 | meat | 1 | 13983 | 21 | 0.436 | 32071.1 |
1403 | 2023-09-13 20:00:20 | meat | 1 | 13983 | 21 | 0.233 | 60012.9 |
1402 | 2023-09-12 06:24:11 | meat | 1 | 13983 | 21 | 0.220 | 63559.1 |
1401 | 2023-08-20 21:06:25 | meat | 1 | 13983 | 21 | 0.250 | 55932.0 |
1400 | 2023-08-10 00:20:32 | meat | 1 | 13983 | 21 | 0.263 | 53167.3 |
1399 | 2023-07-25 06:27:51 | meat | 1 | 13983 | 21 | 0.250 | 55932.0 |
1398 | 2023-05-09 11:01:24 | meat | 1 | 13983 | 21 | 0.203 | 68881.8 |
1397 | 2023-04-20 17:54:36 | meat | 1 | 13983 | 21 | 0.220 | 63559.1 |
1396 | 2023-03-29 23:23:53 | meat | 1 | 13983 | 21 | 0.203 | 68881.8 |
1395 | 2023-03-04 09:23:37 | meat | 1 | 13983 | 21 | 0.250 | 55932.0 |
1394 | 2023-01-08 08:36:55 | meat | 1 | 13983 | 21 | 0.250 | 55932.0 |
1393 | 2022-12-29 22:44:07 | meat | 1 | 13983 | 21 | 0.220 | 63559.1 |
1392 | 2022-11-26 00:49:46 | meat | 1 | 13983 | 21 | 0.250 | 55932.0 |
1391 | 2022-09-28 04:32:59 | meat | 1 | 13983 | 21 | 0.220 | 63559.1 |
1390 | 2022-09-17 12:09:33 | meat | 1 | 13983 | 21 | 0.200 | 69915.0 |
1389 | 2022-09-12 06:57:02 | meat | 1 | 13983 | 21 | 0.236 | 59250.0 |
1388 | 2022-08-26 02:00:11 | meat | 1 | 13983 | 21 | 0.216 | 64736.1 |
1387 | 2022-08-15 09:49:31 | meat | 1 | 13983 | 21 | 0.236 | 59250.0 |
1386 | 2022-08-14 02:37:34 | meat | 1 | 13983 | 21 | 0.236 | 59250.0 |
1385 | 2022-07-29 05:06:00 | meat | 1 | 13983 | 21 | 0.250 | 55932.0 |
1384 | 2022-06-14 19:23:50 | meat | 1 | 13983 | 21 | 0.233 | 60012.9 |
1383 | 2022-05-18 18:02:08 | meat | 1 | 13983 | 21 | 0.233 | 60012.9 |
1382 | 2022-05-18 07:18:05 | meat | 1 | 13983 | 21 | 0.200 | 69915.0 |
1381 | 2022-05-17 16:53:49 | meat | 1 | 13983 | 21 | 0.296 | 47239.9 |
1380 | 2022-05-16 23:13:46 | meat | 1 | 13983 | 21 | 0.233 | 60012.9 |
1379 | 2022-05-16 11:02:25 | meat | 1 | 13983 | 21 | 0.250 | 55932.0 |
1378 | 2022-05-15 21:34:28 | meat | 1 | 13983 | 21 | 0.283 | 49409.9 |
1377 | 2022-05-14 04:19:54 | meat | 1 | 13983 | 21 | 0.250 | 55932.0 |
1376 | 2022-05-13 21:17:24 | meat | 1 | 13983 | 21 | 0.313 | 44674.1 |
1375 | 2022-05-13 11:20:12 | meat | 1 | 13983 | 21 | 0.263 | 53167.3 |
1374 | 2022-05-13 02:05:44 | meat | 1 | 13983 | 21 | 0.250 | 55932.0 |
1373 | 2022-05-12 12:57:12 | meat | 1 | 13983 | 21 | 0.250 | 55932.0 |
1372 | 2022-04-25 10:37:48 | meat | 1 | 13983 | 21 | 0.266 | 52567.7 |
1371 | 2022-04-23 04:17:20 | meat | 1 | 13983 | 21 | 0.220 | 63559.1 |
1370 | 2022-04-08 07:25:30 | meat | 1 | 13983 | 21 | 0.220 | 63559.1 |
1369 | 2022-04-07 09:17:55 | meat | 1 | 13983 | 21 | 0.326 | 42892.6 |
1368 | 2022-04-06 05:13:18 | meat | 1 | 13983 | 21 | 0.250 | 55932.0 |
1367 | 2022-04-05 10:30:52 | meat | 1 | 13983 | 21 | 0.296 | 47239.9 |
1366 | 2022-04-04 09:10:27 | meat | 1 | 13983 | 21 | 0.250 | 55932.0 |
1365 | 2022-04-03 14:33:41 | meat | 1 | 13983 | 21 | 0.266 | 52567.7 |
1364 | 2022-04-02 13:15:34 | meat | 1 | 13983 | 21 | 0.203 | 68881.8 |
1363 | 2022-04-01 06:39:31 | meat | 1 | 13983 | 21 | 0.500 | 27966.0 |
1362 | 2022-03-03 00:14:13 | meat | 1 | 13983 | 21 | 0.220 | 63559.1 |
1361 | 2022-02-10 05:40:53 | meat | 1 | 13983 | 21 | 0.250 | 55932.0 |
1360 | 2022-02-09 10:33:02 | meat | 1 | 13983 | 21 | 0.266 | 52567.7 |
1359 | 2022-02-08 10:25:56 | meat | 1 | 13983 | 21 | 0.233 | 60012.9 |
1358 | 2022-02-06 21:40:19 | meat | 1 | 13983 | 21 | 0.233 | 60012.9 |
1357 | 2022-02-06 08:34:43 | meat | 1 | 13983 | 21 | 0.220 | 63559.1 |
1356 | 2022-02-05 11:44:45 | meat | 1 | 13983 | 21 | 0.296 | 47239.9 |
1355 | 2022-02-04 20:02:55 | meat | 1 | 13983 | 21 | 0.220 | 63559.1 |
1354 | 2022-02-03 23:37:49 | meat | 1 | 13983 | 21 | 0.250 | 55932.0 |
1353 | 2022-02-03 11:12:11 | meat | 1 | 13983 | 21 | 0.483 | 28950.3 |
1352 | 2022-02-02 07:40:00 | meat | 1 | 13983 | 21 | 0.233 | 60012.9 |