History of Dictionary Searches using Damerau-Levenshtein distance in T-SQL
Fuzzy-string Searches
(up to 100 most recent)
for
"pandas"
Num | Started At (CA time) | Searched Word | Change Limit | Words Checked | Words Matched | Seconds | Words Per Sec |
1597 | 2025-08-14 04:08:53 | pandas | 3 | 112716 | 1063 | 5.546 | 20323.8 |
1596 | 2025-08-12 18:09:06 | pandas | 1 | 48755 | 6 | 1.736 | 28084.7 |
1595 | 2025-08-06 00:08:13 | pandas | 3 | 112716 | 1063 | 13.986 | 8059.2 |
1594 | 2025-08-03 14:00:49 | pandas | 3 | 112716 | 1063 | 14.813 | 7609.3 |
1593 | 2025-08-01 22:21:11 | pandas | 3 | 112716 | 1063 | 22.613 | 4984.6 |
1592 | 2025-08-01 10:21:26 | pandas | 1 | 48755 | 6 | 4.126 | 11816.5 |
1591 | 2025-08-01 09:30:57 | pandas | 1 | 48755 | 6 | 5.170 | 9430.4 |
1590 | 2025-07-31 06:42:48 | pandas | 3 | 112716 | 1063 | 6.123 | 18408.6 |
1589 | 2025-07-29 14:39:48 | pandas | 1 | 48755 | 6 | 2.000 | 24377.5 |
1588 | 2025-07-24 07:20:48 | pandas | 1 | 48755 | 6 | 6.096 | 7997.9 |
1587 | 2025-07-23 22:10:21 | pandas | 3 | 112716 | 1063 | 25.783 | 4371.7 |
1586 | 2025-07-23 18:05:58 | pandas | 1 | 48755 | 6 | 5.843 | 8344.2 |
1585 | 2025-07-23 13:14:43 | pandas | 1 | 48755 | 6 | 6.203 | 7859.9 |
1584 | 2025-07-22 20:10:24 | pandas | 1 | 48755 | 6 | 3.126 | 15596.6 |
1583 | 2025-07-22 03:45:53 | pandas | 3 | 112716 | 1063 | 6.313 | 17854.6 |
1582 | 2025-07-19 11:57:30 | pandas | 1 | 48755 | 6 | 1.063 | 45865.5 |
1581 | 2025-07-18 19:05:43 | pandas | 3 | 112716 | 1063 | 14.686 | 7675.1 |
1580 | 2025-07-18 16:56:53 | pandas | 3 | 112716 | 1063 | 29.783 | 3784.6 |
1579 | 2025-07-17 22:00:55 | pandas | 3 | 112716 | 1063 | 28.560 | 3946.6 |
1578 | 2025-07-17 20:01:07 | pandas | 1 | 48755 | 6 | 4.220 | 11553.3 |
1577 | 2025-07-17 05:24:18 | pandas | 3 | 112716 | 1063 | 16.266 | 6929.5 |
1576 | 2025-07-17 00:52:06 | pandas | 2 | 82551 | 97 | 12.563 | 6571.0 |
1575 | 2025-07-16 11:29:24 | pandas | 3 | 112716 | 1063 | 27.640 | 4078.0 |
1574 | 2025-07-15 16:50:34 | pandas | 3 | 112716 | 1063 | 15.186 | 7422.4 |
1573 | 2025-07-15 13:32:36 | pandas | 2 | 82551 | 97 | 19.236 | 4291.5 |
1572 | 2025-07-14 18:00:11 | pandas | 3 | 112716 | 1063 | 20.813 | 5415.7 |
1571 | 2025-07-13 16:52:29 | pandas | 1 | 48755 | 6 | 0.843 | 57835.1 |
1570 | 2025-07-13 12:16:15 | pandas | 2 | 82551 | 97 | 2.843 | 29036.6 |
1569 | 2025-07-13 05:28:52 | pandas | 1 | 48755 | 6 | 0.906 | 53813.5 |
1568 | 2025-07-07 17:00:23 | pandas | 1 | 48755 | 6 | 1.983 | 24586.5 |
1567 | 2025-07-06 15:50:09 | pandas | 3 | 112716 | 1063 | 5.486 | 20546.1 |
1566 | 2025-07-02 20:42:01 | pandas | 1 | 48755 | 6 | 6.406 | 7610.8 |
1565 | 2025-07-02 05:13:28 | pandas | 1 | 48755 | 6 | 4.156 | 11731.2 |
1564 | 2025-07-01 05:42:27 | pandas | 1 | 48755 | 6 | 0.890 | 54780.9 |
1563 | 2025-06-29 07:17:17 | pandas | 1 | 48755 | 6 | 0.780 | 62506.4 |
1562 | 2025-06-26 09:20:15 | pandas | 2 | 82551 | 97 | 6.703 | 12315.5 |
1561 | 2025-06-25 20:36:00 | pandas | 1 | 48755 | 6 | 0.846 | 57630.0 |
1560 | 2025-06-24 20:35:23 | pandas | 3 | 112716 | 1063 | 5.876 | 19182.4 |
1559 | 2025-06-18 05:11:49 | pandas | 1 | 48755 | 6 | 4.173 | 11683.4 |
1558 | 2025-06-17 19:48:54 | pandas | 3 | 112716 | 1063 | 23.766 | 4742.7 |
1557 | 2025-06-17 05:33:47 | pandas | 3 | 112716 | 1063 | 13.703 | 8225.6 |
1556 | 2025-06-14 13:31:56 | pandas | 2 | 82551 | 97 | 18.266 | 4519.4 |
1555 | 2025-06-14 04:15:24 | pandas | 3 | 112716 | 1063 | 48.330 | 2332.2 |
1554 | 2025-06-13 16:21:24 | pandas | 3 | 112716 | 1063 | 7.470 | 15089.2 |
1553 | 2025-06-13 16:11:13 | pandas | 3 | 112716 | 1063 | 18.406 | 6123.9 |
1552 | 2025-06-13 12:51:20 | pandas | 3 | 112716 | 1063 | 11.440 | 9852.8 |
1551 | 2025-06-13 10:34:43 | pandas | 3 | 112716 | 1063 | 24.406 | 4618.4 |
1550 | 2025-06-12 15:12:12 | pandas | 3 | 112716 | 1063 | 19.010 | 5929.3 |
1549 | 2025-06-12 04:39:09 | pandas | 1 | 48755 | 6 | 4.810 | 10136.2 |
1548 | 2025-06-12 04:14:02 | pandas | 3 | 112716 | 1063 | 17.923 | 6288.9 |
1547 | 2025-06-10 16:15:37 | pandas | 3 | 112716 | 1063 | 26.126 | 4314.3 |
1546 | 2025-06-06 16:28:31 | pandas | 1 | 48755 | 6 | 3.453 | 14119.6 |
1545 | 2025-05-30 21:00:39 | pandas | 2 | 82551 | 97 | 8.626 | 9570.0 |
1544 | 2025-05-30 06:01:21 | pandas | 1 | 48755 | 6 | 0.903 | 53992.2 |
1543 | 2025-05-29 13:08:35 | pandas | 1 | 48755 | 6 | 4.470 | 10907.2 |
1542 | 2025-05-29 05:20:04 | pandas | 3 | 112716 | 1063 | 22.516 | 5006.0 |
1541 | 2025-05-28 13:03:34 | pandas | 1 | 48755 | 6 | 0.903 | 53992.2 |
1540 | 2025-05-25 06:56:35 | pandas | 1 | 48755 | 6 | 0.873 | 55847.7 |
1539 | 2025-05-23 19:16:48 | pandas | 1 | 48755 | 6 | 0.843 | 57835.1 |
1538 | 2025-05-22 23:08:59 | pandas | 3 | 112716 | 1063 | 5.890 | 19136.8 |
1537 | 2025-05-19 00:14:30 | pandas | 1 | 48755 | 6 | 0.843 | 57835.1 |
1536 | 2025-05-14 19:42:51 | pandas | 3 | 112716 | 1063 | 5.076 | 22205.7 |
1535 | 2025-05-12 13:44:13 | pandas | 3 | 112716 | 1063 | 28.783 | 3916.1 |
1534 | 2025-05-12 04:25:07 | pandas | 3 | 112716 | 1063 | 22.410 | 5029.7 |
1533 | 2025-05-11 19:32:28 | pandas | 3 | 112716 | 1063 | 26.516 | 4250.9 |
1532 | 2025-05-10 19:59:23 | pandas | 3 | 112716 | 1063 | 54.816 | 2056.3 |
1531 | 2025-05-09 18:55:30 | pandas | 2 | 82551 | 97 | 2.563 | 32208.7 |
1530 | 2025-05-09 15:29:45 | pandas | 3 | 112716 | 1063 | 6.283 | 17939.8 |
1529 | 2025-05-09 04:17:36 | pandas | 3 | 112716 | 1063 | 6.220 | 18121.5 |
1528 | 2025-05-08 23:35:11 | pandas | 3 | 112716 | 1063 | 4.953 | 22757.1 |
1527 | 2025-05-08 10:46:08 | pandas | 1 | 48755 | 6 | 2.140 | 22782.7 |
1526 | 2025-05-08 10:39:07 | pandas | 3 | 112716 | 1063 | 19.686 | 5725.7 |
1525 | 2025-05-07 23:35:29 | pandas | 1 | 48755 | 6 | 3.890 | 12533.4 |
1524 | 2025-05-06 16:15:00 | pandas | 1 | 48755 | 6 | 5.940 | 8207.9 |
1523 | 2025-05-03 18:59:54 | pandas | 1 | 48755 | 6 | 0.783 | 62266.9 |
1522 | 2025-04-29 06:35:49 | pandas | 1 | 48755 | 6 | 3.203 | 15221.7 |
1521 | 2025-04-25 03:31:22 | pandas | 1 | 48755 | 6 | 0.876 | 55656.4 |
1520 | 2025-04-21 23:57:32 | pandas | 3 | 112716 | 1063 | 5.233 | 21539.5 |
1519 | 2025-04-16 04:25:45 | pandas | 1 | 48755 | 6 | 2.033 | 23981.8 |
1518 | 2025-04-10 23:53:39 | pandas | 2 | 82551 | 97 | 12.706 | 6497.0 |
1517 | 2025-04-10 04:42:35 | pandas | 3 | 112716 | 1063 | 5.390 | 20912.1 |
1516 | 2025-04-09 14:49:27 | pandas | 2 | 82551 | 97 | 13.626 | 6058.3 |
1515 | 2025-04-08 06:42:05 | pandas | 1 | 48755 | 6 | 1.610 | 30282.6 |
1514 | 2025-04-06 15:38:04 | pandas | 1 | 48755 | 6 | 3.983 | 12240.8 |
1513 | 2025-04-06 10:29:09 | pandas | 1 | 48755 | 6 | 4.843 | 10067.1 |
1512 | 2025-04-04 15:10:58 | pandas | 3 | 112716 | 1063 | 26.330 | 4280.9 |
1511 | 2025-04-03 11:48:38 | pandas | 2 | 82551 | 97 | 9.173 | 8999.3 |
1510 | 2025-04-02 04:31:07 | pandas | 3 | 112716 | 1063 | 28.453 | 3961.5 |
1509 | 2025-04-01 17:49:54 | pandas | 3 | 112716 | 1063 | 6.750 | 16698.7 |
1508 | 2025-03-31 15:51:30 | pandas | 3 | 112716 | 1063 | 32.143 | 3506.7 |
1507 | 2025-03-31 04:25:50 | pandas | 3 | 112716 | 1063 | 28.033 | 4020.8 |
1506 | 2025-03-30 17:41:13 | pandas | 1 | 48755 | 6 | 0.826 | 59025.4 |
1505 | 2025-03-30 10:10:28 | pandas | 3 | 112716 | 1063 | 5.673 | 19868.9 |
1504 | 2025-03-29 07:56:38 | pandas | 1 | 48755 | 6 | 5.766 | 8455.6 |
1503 | 2025-03-16 12:34:12 | pandas | 1 | 48755 | 6 | 2.720 | 17924.6 |
1502 | 2025-03-14 19:23:25 | pandas | 1 | 48755 | 6 | 3.766 | 12946.1 |
1501 | 2025-03-12 13:54:52 | pandas | 1 | 48755 | 6 | 3.500 | 13930.0 |
1500 | 2025-03-11 09:55:57 | pandas | 1 | 48755 | 6 | 4.280 | 11391.4 |
1499 | 2025-03-10 12:36:53 | pandas | 3 | 112716 | 1063 | 5.736 | 19650.6 |
1498 | 2025-03-08 19:41:51 | pandas | 1 | 48755 | 6 | 6.860 | 7107.1 |