History of Dictionary Searches using Damerau-Levenshtein distance in T-SQL
Fuzzy-string Searches
(up to 100 most recent)
for
"losses"
| Num | Started At (CA time) | Searched Word | Change Limit | Words Checked | Words Matched | Seconds | Words Per Sec |
| 1060 | 2024-04-28 17:47:00 | losses | 1 | 48755 | 15 | 0.843 | 57835.1 |
| 1059 | 2024-04-25 10:23:11 | losses | 1 | 48755 | 15 | 2.690 | 18124.5 |
| 1058 | 2024-04-20 22:20:04 | losses | 1 | 48755 | 15 | 1.326 | 36768.5 |
| 1057 | 2024-04-16 14:58:32 | losses | 1 | 48755 | 15 | 1.660 | 29370.5 |
| 1056 | 2024-04-03 11:10:02 | losses | 2 | 82551 | 185 | 3.063 | 26951.0 |
| 1055 | 2024-04-03 08:32:25 | losses | 1 | 48755 | 15 | 1.936 | 25183.4 |
| 1054 | 2024-03-21 22:57:32 | losses | 1 | 48755 | 15 | 1.860 | 26212.4 |
| 1053 | 2024-03-04 09:09:36 | losses | 1 | 48755 | 15 | 1.876 | 25988.8 |
| 1052 | 2024-02-25 19:40:31 | losses | 1 | 48755 | 15 | 2.000 | 24377.5 |
| 1051 | 2024-02-22 09:50:20 | losses | 2 | 82551 | 185 | 2.373 | 34787.6 |
| 1050 | 2024-02-21 16:42:23 | losses | 2 | 82551 | 185 | 5.923 | 13937.4 |
| 1049 | 2024-02-20 22:51:42 | losses | 2 | 82551 | 185 | 2.346 | 35188.0 |
| 1048 | 2024-02-20 14:09:16 | losses | 1 | 48755 | 15 | 1.750 | 27860.0 |
| 1047 | 2024-01-21 13:11:00 | losses | 1 | 48755 | 15 | 0.813 | 59969.2 |
| 1046 | 2024-01-02 13:13:46 | losses | 1 | 48755 | 15 | 0.783 | 62266.9 |
| 1045 | 2023-12-22 00:31:35 | losses | 2 | 82551 | 185 | 2.173 | 37989.4 |
| 1044 | 2023-12-03 16:11:06 | losses | 2 | 82551 | 185 | 2.580 | 31996.5 |
| 1043 | 2023-11-16 01:17:27 | losses | 2 | 82551 | 185 | 2.500 | 33020.4 |
| 1042 | 2023-11-14 14:45:30 | losses | 1 | 48755 | 15 | 0.970 | 50262.9 |
| 1041 | 2023-11-13 12:53:13 | losses | 1 | 48755 | 15 | 0.750 | 65006.7 |
| 1040 | 2023-11-12 11:23:54 | losses | 1 | 48755 | 15 | 0.750 | 65006.7 |
| 1039 | 2023-11-10 09:20:57 | losses | 1 | 48755 | 15 | 0.750 | 65006.7 |
| 1038 | 2023-11-02 13:15:30 | losses | 1 | 48755 | 15 | 0.843 | 57835.1 |
| 1037 | 2023-10-26 22:16:44 | losses | 2 | 82551 | 185 | 2.530 | 32628.9 |
| 1036 | 2023-10-26 22:00:00 | losses | 1 | 48755 | 15 | 0.890 | 54780.9 |
| 1035 | 2023-10-23 16:26:43 | losses | 1 | 48755 | 15 | 0.796 | 61250.0 |
| 1034 | 2023-10-19 19:54:39 | losses | 1 | 48755 | 15 | 0.843 | 57835.1 |
| 1033 | 2023-10-17 11:55:14 | losses | 1 | 48755 | 15 | 0.763 | 63899.1 |
| 1032 | 2023-10-11 17:44:46 | losses | 1 | 48755 | 15 | 0.876 | 55656.4 |
| 1031 | 2023-10-04 03:10:40 | losses | 1 | 48755 | 15 | 0.846 | 57630.0 |
| 1030 | 2023-09-11 12:27:17 | losses | 2 | 82551 | 185 | 2.470 | 33421.5 |
| 1029 | 2023-09-10 12:00:47 | losses | 1 | 48755 | 15 | 0.736 | 66243.2 |
| 1028 | 2023-08-17 23:05:08 | losses | 1 | 48755 | 15 | 0.766 | 63648.8 |
| 1027 | 2023-07-25 18:03:24 | losses | 1 | 48755 | 15 | 0.750 | 65006.7 |
| 1026 | 2023-05-19 11:23:03 | losses | 1 | 48755 | 15 | 0.830 | 58741.0 |
| 1025 | 2023-04-21 05:56:06 | losses | 1 | 48755 | 15 | 0.750 | 65006.7 |
| 1024 | 2023-03-15 05:22:29 | losses | 1 | 48755 | 15 | 0.796 | 61250.0 |
| 1023 | 2023-01-12 14:16:46 | losses | 1 | 48755 | 15 | 0.733 | 66514.3 |
| 1022 | 2023-01-02 05:19:35 | losses | 1 | 48755 | 15 | 0.733 | 66514.3 |
| 1021 | 2022-09-25 02:40:58 | losses | 1 | 48755 | 15 | 0.733 | 66514.3 |
| 1020 | 2022-09-25 00:57:31 | losses | 1 | 48755 | 15 | 0.750 | 65006.7 |
| 1019 | 2022-08-20 13:35:02 | losses | 1 | 48755 | 15 | 0.813 | 59969.2 |
| 1018 | 2022-06-08 01:17:10 | losses | 1 | 48755 | 15 | 0.750 | 65006.7 |
| 1017 | 2022-05-19 04:12:33 | losses | 1 | 48755 | 15 | 0.906 | 53813.5 |
| 1016 | 2022-05-18 15:43:49 | losses | 1 | 48755 | 15 | 0.843 | 57835.1 |
| 1015 | 2022-05-18 00:16:08 | losses | 1 | 48755 | 15 | 0.796 | 61250.0 |
| 1014 | 2022-05-17 13:27:17 | losses | 1 | 48755 | 15 | 1.000 | 48755.0 |
| 1013 | 2022-05-16 11:26:40 | losses | 1 | 48755 | 15 | 1.046 | 46610.9 |
| 1012 | 2022-05-15 21:34:32 | losses | 1 | 48755 | 15 | 1.670 | 29194.6 |
| 1011 | 2022-05-15 02:51:39 | losses | 1 | 48755 | 15 | 0.750 | 65006.7 |
| 1010 | 2022-05-14 03:46:54 | losses | 1 | 48755 | 15 | 0.843 | 57835.1 |
| 1009 | 2022-05-13 17:51:17 | losses | 1 | 48755 | 15 | 1.093 | 44606.6 |
| 1008 | 2022-05-13 08:16:22 | losses | 1 | 48755 | 15 | 1.153 | 42285.3 |
| 1007 | 2022-05-12 22:13:48 | losses | 1 | 48755 | 15 | 1.143 | 42655.3 |
| 1006 | 2022-05-10 14:48:51 | losses | 1 | 48755 | 15 | 1.046 | 46610.9 |
| 1005 | 2022-05-07 01:26:52 | losses | 1 | 48755 | 15 | 0.733 | 66514.3 |
| 1004 | 2022-05-06 09:01:16 | losses | 1 | 48755 | 15 | 0.873 | 55847.7 |
| 1003 | 2022-05-05 16:24:46 | losses | 1 | 48755 | 15 | 0.813 | 59969.2 |
| 1002 | 2022-05-05 10:00:22 | losses | 1 | 48755 | 15 | 1.186 | 41108.8 |
| 1001 | 2022-05-04 22:14:34 | losses | 1 | 48755 | 15 | 0.750 | 65006.7 |
| 1000 | 2022-05-04 10:21:20 | losses | 1 | 48755 | 15 | 0.736 | 66243.2 |
| 999 | 2022-05-03 23:50:00 | losses | 1 | 48755 | 15 | 0.843 | 57835.1 |
| 998 | 2022-05-03 09:04:53 | losses | 1 | 48755 | 15 | 0.813 | 59969.2 |
| 997 | 2022-05-02 08:13:09 | losses | 1 | 48755 | 15 | 0.843 | 57835.1 |
| 996 | 2022-05-01 11:49:03 | losses | 1 | 48755 | 15 | 0.800 | 60943.8 |
| 995 | 2022-04-30 10:51:30 | losses | 1 | 48755 | 15 | 0.843 | 57835.1 |
| 994 | 2022-04-29 14:11:12 | losses | 1 | 48755 | 15 | 1.046 | 46610.9 |
| 993 | 2022-04-29 00:02:31 | losses | 1 | 48755 | 15 | 0.936 | 52088.7 |
| 992 | 2022-04-28 11:32:29 | losses | 1 | 48755 | 15 | 0.966 | 50471.0 |
| 991 | 2022-04-08 23:03:40 | losses | 1 | 48755 | 15 | 0.860 | 56691.9 |
| 990 | 2022-04-06 22:26:55 | losses | 1 | 48755 | 15 | 0.766 | 63648.8 |
| 989 | 2022-04-01 23:06:43 | losses | 1 | 48755 | 15 | 0.766 | 63648.8 |
| 988 | 2022-03-25 13:47:50 | losses | 1 | 48755 | 15 | 1.250 | 39004.0 |
| 987 | 2022-03-25 00:08:46 | losses | 1 | 48755 | 15 | 0.920 | 52994.6 |
| 986 | 2022-03-24 08:50:07 | losses | 1 | 48755 | 15 | 1.186 | 41108.8 |
| 985 | 2022-03-23 09:36:54 | losses | 1 | 48755 | 15 | 0.763 | 63899.1 |
| 984 | 2022-03-22 18:49:22 | losses | 1 | 48755 | 15 | 0.826 | 59025.4 |
| 983 | 2022-02-28 01:15:18 | losses | 1 | 48755 | 15 | 0.763 | 63899.1 |
| 982 | 2022-01-25 07:26:17 | losses | 1 | 48755 | 15 | 0.860 | 56691.9 |
| 981 | 2021-12-23 22:27:56 | losses | 1 | 48755 | 15 | 0.860 | 56691.9 |
| 980 | 2021-12-23 11:06:36 | losses | 1 | 48755 | 15 | 0.800 | 60943.8 |
| 979 | 2021-12-23 01:48:55 | losses | 1 | 48755 | 15 | 0.843 | 57835.1 |
| 978 | 2021-12-22 15:35:29 | losses | 1 | 48755 | 15 | 1.330 | 36657.9 |
| 977 | 2021-12-22 04:50:40 | losses | 1 | 48755 | 15 | 0.936 | 52088.7 |
| 976 | 2021-12-21 21:56:28 | losses | 1 | 48755 | 15 | 0.780 | 62506.4 |
| 975 | 2021-12-21 11:14:15 | losses | 1 | 48755 | 15 | 1.080 | 45143.5 |
| 974 | 2021-12-20 13:03:48 | losses | 1 | 48755 | 15 | 0.766 | 63648.8 |
| 973 | 2021-12-20 06:01:26 | losses | 1 | 48755 | 15 | 0.906 | 53813.5 |
| 972 | 2021-12-17 16:35:20 | losses | 1 | 48755 | 15 | 0.890 | 54780.9 |
| 971 | 2021-12-17 05:17:30 | losses | 1 | 48755 | 15 | 0.890 | 54780.9 |
| 970 | 2021-12-16 22:26:57 | losses | 1 | 48755 | 15 | 0.873 | 55847.7 |
| 969 | 2021-12-16 10:02:25 | losses | 1 | 48755 | 15 | 0.830 | 58741.0 |
| 968 | 2021-12-16 00:26:01 | losses | 1 | 48755 | 15 | 0.890 | 54780.9 |
| 967 | 2021-12-15 07:38:14 | losses | 1 | 48755 | 15 | 0.860 | 56691.9 |
| 966 | 2021-12-14 21:11:55 | losses | 1 | 48755 | 15 | 0.843 | 57835.1 |
| 965 | 2021-12-11 18:35:11 | losses | 1 | 48755 | 15 | 0.986 | 49447.3 |
| 964 | 2021-12-11 10:33:50 | losses | 1 | 48755 | 15 | 0.766 | 63648.8 |
| 963 | 2021-12-11 02:03:55 | losses | 1 | 48755 | 15 | 0.750 | 65006.7 |
| 962 | 2021-12-10 15:56:44 | losses | 1 | 48755 | 15 | 0.766 | 63648.8 |
| 961 | 2021-12-10 07:41:29 | losses | 1 | 48755 | 15 | 0.843 | 57835.1 |