History of Dictionary Searches using Damerau-Levenshtein distance in T-SQL
Fuzzy-string Searches
(up to 100 most recent)
for
"plots"
| Num | Started At (CA time) | Searched Word | Change Limit | Words Checked | Words Matched | Seconds | Words Per Sec |
| 1046 | 2025-10-22 15:09:04 | plots | 1 | 28756 | 15 | 1.393 | 20643.2 |
| 1045 | 2025-10-20 16:26:33 | plots | 1 | 28756 | 15 | 1.310 | 21951.1 |
| 1044 | 2025-10-20 12:22:39 | plots | 1 | 28756 | 15 | 0.686 | 41918.4 |
| 1043 | 2025-10-19 15:44:29 | plots | 1 | 28756 | 15 | 1.513 | 19005.9 |
| 1042 | 2025-10-18 23:28:55 | plots | 2 | 53800 | 230 | 1.436 | 37465.2 |
| 1041 | 2025-10-17 21:01:35 | plots | 1 | 28756 | 15 | 0.500 | 57512.0 |
| 1040 | 2025-10-12 17:36:33 | plots | 1 | 28756 | 15 | 0.500 | 57512.0 |
| 1039 | 2025-10-12 08:18:32 | plots | 1 | 28756 | 15 | 0.470 | 61183.0 |
| 1038 | 2025-10-08 01:57:05 | plots | 2 | 53800 | 230 | 1.483 | 36277.8 |
| 1037 | 2025-10-07 05:05:10 | plots | 2 | 53800 | 230 | 1.656 | 32487.9 |
| 1036 | 2025-10-03 17:29:47 | plots | 1 | 28756 | 15 | 0.530 | 54256.6 |
| 1035 | 2025-10-01 05:32:57 | plots | 2 | 53800 | 230 | 1.703 | 31591.3 |
| 1034 | 2025-09-28 07:46:30 | plots | 1 | 28756 | 15 | 0.500 | 57512.0 |
| 1033 | 2025-09-27 22:44:06 | plots | 2 | 53800 | 230 | 1.563 | 34421.0 |
| 1032 | 2025-09-27 12:23:25 | plots | 1 | 28756 | 15 | 0.486 | 59168.7 |
| 1031 | 2025-09-27 11:57:45 | plots | 1 | 28756 | 15 | 0.500 | 57512.0 |
| 1030 | 2025-09-27 11:37:44 | plots | 1 | 28756 | 15 | 0.530 | 54256.6 |
| 1029 | 2025-09-27 11:37:40 | plots | 1 | 28756 | 15 | 0.453 | 63479.0 |
| 1028 | 2025-09-26 21:40:22 | plots | 1 | 28756 | 15 | 0.546 | 52666.7 |
| 1027 | 2025-09-26 10:08:46 | plots | 1 | 28756 | 15 | 0.483 | 59536.2 |
| 1026 | 2025-09-25 11:17:02 | plots | 2 | 53800 | 230 | 10.813 | 4975.5 |
| 1025 | 2025-09-25 04:05:32 | plots | 1 | 28756 | 15 | 0.453 | 63479.0 |
| 1024 | 2025-09-22 01:19:12 | plots | 1 | 28756 | 15 | 0.436 | 65954.1 |
| 1023 | 2025-09-20 12:39:38 | plots | 1 | 28756 | 15 | 0.450 | 63902.2 |
| 1022 | 2025-09-20 06:02:01 | plots | 2 | 53800 | 230 | 1.643 | 32745.0 |
| 1021 | 2025-09-20 02:48:33 | plots | 2 | 53800 | 230 | 1.533 | 35094.6 |
| 1020 | 2025-09-19 11:43:34 | plots | 1 | 28756 | 15 | 0.450 | 63902.2 |
| 1019 | 2025-09-19 00:16:23 | plots | 2 | 53800 | 230 | 1.673 | 32157.8 |
| 1018 | 2025-09-17 16:11:04 | plots | 2 | 53800 | 230 | 1.436 | 37465.2 |
| 1017 | 2025-09-17 03:16:31 | plots | 2 | 53800 | 230 | 1.826 | 29463.3 |
| 1016 | 2025-09-17 02:55:04 | plots | 1 | 28756 | 15 | 0.530 | 54256.6 |
| 1015 | 2025-09-12 05:47:38 | plots | 1 | 28756 | 15 | 0.516 | 55728.7 |
| 1014 | 2025-09-12 00:34:13 | plots | 2 | 53800 | 230 | 1.716 | 31352.0 |
| 1013 | 2025-09-10 01:07:23 | plots | 1 | 28756 | 15 | 0.436 | 65954.1 |
| 1012 | 2025-09-08 15:03:39 | plots | 2 | 53800 | 230 | 1.516 | 35488.1 |
| 1011 | 2025-09-07 23:51:43 | plots | 1 | 28756 | 15 | 0.453 | 63479.0 |
| 1010 | 2025-09-07 09:30:21 | plots | 1 | 28756 | 15 | 0.533 | 53951.2 |
| 1009 | 2025-09-03 22:39:10 | plots | 1 | 28756 | 15 | 0.500 | 57512.0 |
| 1008 | 2025-09-01 11:04:58 | plots | 2 | 53800 | 230 | 1.436 | 37465.2 |
| 1007 | 2025-08-29 09:31:18 | plots | 1 | 28756 | 15 | 0.470 | 61183.0 |
| 1006 | 2025-08-27 12:25:17 | plots | 1 | 28756 | 15 | 0.500 | 57512.0 |
| 1005 | 2025-08-26 22:04:36 | plots | 2 | 53800 | 230 | 1.733 | 31044.4 |
| 1004 | 2025-08-26 08:26:39 | plots | 2 | 53800 | 230 | 3.373 | 15950.2 |
| 1003 | 2025-08-24 22:10:53 | plots | 1 | 28756 | 15 | 3.313 | 8679.7 |
| 1002 | 2025-08-22 22:16:43 | plots | 1 | 28756 | 15 | 3.546 | 8109.4 |
| 1001 | 2025-08-19 12:24:35 | plots | 1 | 28756 | 15 | 1.610 | 17860.9 |
| 1000 | 2025-08-17 20:55:58 | plots | 2 | 53800 | 230 | 7.546 | 7129.6 |
| 999 | 2025-08-15 23:59:26 | plots | 1 | 28756 | 15 | 1.000 | 28756.0 |
| 998 | 2025-08-01 02:33:51 | plots | 1 | 28756 | 15 | 3.313 | 8679.7 |
| 997 | 2025-08-01 02:33:27 | plots | 2 | 53800 | 230 | 4.626 | 11629.9 |
| 996 | 2025-07-31 11:49:09 | plots | 1 | 28756 | 15 | 0.826 | 34813.6 |
| 995 | 2025-07-31 08:10:42 | plots | 1 | 28756 | 15 | 3.343 | 8601.9 |
| 994 | 2025-07-28 00:22:23 | plots | 2 | 53800 | 230 | 4.313 | 12473.9 |
| 993 | 2025-07-27 13:29:29 | plots | 1 | 28756 | 15 | 2.000 | 14378.0 |
| 992 | 2025-07-27 07:05:07 | plots | 2 | 53800 | 230 | 8.953 | 6009.2 |
| 991 | 2025-07-25 22:59:39 | plots | 2 | 53800 | 230 | 1.763 | 30516.2 |
| 990 | 2025-07-25 22:39:22 | plots | 1 | 28756 | 15 | 0.516 | 55728.7 |
| 989 | 2025-07-23 10:46:44 | plots | 2 | 53800 | 230 | 8.203 | 6558.6 |
| 988 | 2025-07-22 20:51:52 | plots | 2 | 53800 | 230 | 7.846 | 6857.0 |
| 987 | 2025-07-22 11:13:23 | plots | 1 | 28756 | 15 | 2.330 | 12341.6 |
| 986 | 2025-07-20 00:03:26 | plots | 2 | 53800 | 230 | 7.796 | 6901.0 |
| 985 | 2025-07-19 20:26:17 | plots | 1 | 28756 | 15 | 1.483 | 19390.4 |
| 984 | 2025-07-19 20:26:15 | plots | 1 | 28756 | 15 | 1.143 | 25158.4 |
| 983 | 2025-07-19 04:05:38 | plots | 1 | 28756 | 15 | 0.486 | 59168.7 |
| 982 | 2025-07-17 16:12:47 | plots | 1 | 28756 | 15 | 0.970 | 29645.4 |
| 981 | 2025-07-12 09:56:54 | plots | 2 | 53800 | 230 | 2.093 | 25704.7 |
| 980 | 2025-07-12 07:34:15 | plots | 1 | 28756 | 15 | 0.513 | 56054.6 |
| 979 | 2025-07-11 00:14:52 | plots | 1 | 28756 | 15 | 0.983 | 29253.3 |
| 978 | 2025-07-10 20:58:53 | plots | 2 | 53800 | 230 | 8.766 | 6137.3 |
| 977 | 2025-07-07 14:04:11 | plots | 2 | 53800 | 230 | 3.766 | 14285.7 |
| 976 | 2025-07-03 21:26:13 | plots | 1 | 28756 | 15 | 0.783 | 36725.4 |
| 975 | 2025-07-02 17:47:13 | plots | 1 | 28756 | 15 | 2.703 | 10638.5 |
| 974 | 2025-07-01 13:21:13 | plots | 2 | 53800 | 230 | 1.373 | 39184.3 |
| 973 | 2025-06-28 22:53:35 | plots | 2 | 53800 | 230 | 9.376 | 5738.1 |
| 972 | 2025-06-27 21:52:14 | plots | 1 | 28756 | 15 | 0.530 | 54256.6 |
| 971 | 2025-06-25 20:56:45 | plots | 1 | 28756 | 15 | 0.483 | 59536.2 |
| 970 | 2025-06-21 16:07:29 | plots | 1 | 28756 | 15 | 0.440 | 65354.5 |
| 969 | 2025-06-20 02:53:51 | plots | 1 | 28756 | 15 | 1.856 | 15493.5 |
| 968 | 2025-06-15 01:53:42 | plots | 1 | 28756 | 15 | 0.513 | 56054.6 |
| 967 | 2025-06-14 23:34:11 | plots | 2 | 53800 | 230 | 1.843 | 29191.5 |
| 966 | 2025-06-13 15:03:10 | plots | 1 | 28756 | 15 | 0.453 | 63479.0 |
| 965 | 2025-06-13 11:30:44 | plots | 1 | 28756 | 15 | 0.513 | 56054.6 |
| 964 | 2025-06-12 17:37:47 | plots | 1 | 28756 | 15 | 1.016 | 28303.1 |
| 963 | 2025-06-11 23:29:59 | plots | 1 | 28756 | 15 | 1.000 | 28756.0 |
| 962 | 2025-06-06 22:45:52 | plots | 1 | 28756 | 15 | 1.046 | 27491.4 |
| 961 | 2025-06-05 09:35:04 | plots | 1 | 28756 | 15 | 0.513 | 56054.6 |
| 960 | 2025-06-04 12:40:00 | plots | 2 | 53800 | 230 | 3.766 | 14285.7 |
| 959 | 2025-06-04 11:50:33 | plots | 2 | 53800 | 230 | 8.690 | 6191.0 |
| 958 | 2025-06-02 17:03:53 | plots | 2 | 53800 | 230 | 6.466 | 8320.4 |
| 957 | 2025-06-01 23:07:56 | plots | 1 | 28756 | 15 | 1.406 | 20452.3 |
| 956 | 2025-05-31 11:35:51 | plots | 1 | 28756 | 15 | 2.546 | 11294.6 |
| 955 | 2025-05-29 12:08:16 | plots | 1 | 28756 | 15 | 2.453 | 11722.8 |
| 954 | 2025-05-29 00:35:56 | plots | 2 | 53800 | 230 | 8.143 | 6606.9 |
| 953 | 2025-05-28 22:12:19 | plots | 2 | 53800 | 230 | 8.576 | 6273.3 |
| 952 | 2025-05-28 18:14:17 | plots | 2 | 53800 | 230 | 1.623 | 33148.5 |
| 951 | 2025-05-28 11:27:14 | plots | 2 | 53800 | 230 | 1.580 | 34050.6 |
| 950 | 2025-05-28 02:19:22 | plots | 1 | 28756 | 15 | 0.530 | 54256.6 |
| 949 | 2025-05-27 21:05:09 | plots | 1 | 28756 | 15 | 0.533 | 53951.2 |
| 948 | 2025-05-26 21:33:46 | plots | 2 | 53800 | 230 | 7.750 | 6941.9 |
| 947 | 2025-05-19 01:55:28 | plots | 2 | 53800 | 230 | 7.373 | 7296.9 |