History of Dictionary Searches using Damerau-Levenshtein distance in T-SQL
Fuzzy-string Searches
(up to 100 most recent)
for
"predicts"
| Num | Started At (CA time) | Searched Word | Change Limit | Words Checked | Words Matched | Seconds | Words Per Sec |
| 1021 | 2025-10-24 00:26:40 | predicts | 1 | 82945 | 2 | 1.500 | 55296.7 |
| 1020 | 2025-10-24 00:02:10 | predicts | 1 | 82945 | 2 | 1.483 | 55930.5 |
| 1019 | 2025-10-18 00:30:07 | predicts | 1 | 82945 | 2 | 3.016 | 27501.7 |
| 1018 | 2025-10-17 19:13:29 | predicts | 1 | 82945 | 2 | 1.343 | 61761.0 |
| 1017 | 2025-10-17 19:13:24 | predicts | 1 | 82945 | 2 | 1.546 | 53651.4 |
| 1016 | 2025-10-16 09:08:50 | predicts | 2 | 121059 | 20 | 6.423 | 18847.7 |
| 1015 | 2025-10-12 04:55:21 | predicts | 1 | 82945 | 2 | 1.326 | 62552.8 |
| 1014 | 2025-09-29 16:43:34 | predicts | 1 | 82945 | 2 | 1.456 | 56967.7 |
| 1013 | 2025-09-27 05:08:29 | predicts | 1 | 82945 | 2 | 1.576 | 52630.1 |
| 1012 | 2025-09-26 09:35:12 | predicts | 1 | 82945 | 2 | 1.440 | 57600.7 |
| 1011 | 2025-09-26 09:35:08 | predicts | 1 | 82945 | 2 | 1.580 | 52496.8 |
| 1010 | 2025-09-24 00:28:19 | predicts | 3 | 146162 | 196 | 6.923 | 21112.5 |
| 1009 | 2025-09-07 12:25:59 | predicts | 3 | 146162 | 196 | 8.390 | 17421.0 |
| 1008 | 2025-08-25 08:14:54 | predicts | 3 | 146162 | 196 | 48.580 | 3008.7 |
| 1007 | 2025-08-25 04:07:46 | predicts | 3 | 146162 | 196 | 47.846 | 3054.8 |
| 1006 | 2025-08-24 11:00:08 | predicts | 3 | 146162 | 196 | 17.906 | 8162.7 |
| 1005 | 2025-08-24 07:42:10 | predicts | 3 | 146162 | 196 | 34.583 | 4226.4 |
| 1004 | 2025-08-24 06:48:27 | predicts | 2 | 121059 | 20 | 9.483 | 12765.9 |
| 1003 | 2025-08-23 19:55:45 | predicts | 2 | 121059 | 20 | 3.876 | 31233.0 |
| 1002 | 2025-08-20 06:37:18 | predicts | 2 | 121059 | 20 | 11.376 | 10641.6 |
| 1001 | 2025-08-20 02:17:51 | predicts | 3 | 146162 | 196 | 10.250 | 14259.7 |
| 1000 | 2025-08-09 10:44:50 | predicts | 1 | 82945 | 2 | 7.390 | 11224.0 |
| 999 | 2025-08-05 04:41:37 | predicts | 1 | 82945 | 2 | 3.623 | 22894.0 |
| 998 | 2025-08-04 01:49:15 | predicts | 1 | 82945 | 2 | 3.296 | 25165.4 |
| 997 | 2025-07-23 19:42:50 | predicts | 1 | 82945 | 2 | 7.140 | 11616.9 |
| 996 | 2025-07-21 17:09:02 | predicts | 2 | 121059 | 20 | 3.500 | 34588.3 |
| 995 | 2025-07-21 15:27:50 | predicts | 1 | 82945 | 2 | 1.610 | 51518.6 |
| 994 | 2025-07-16 17:00:30 | predicts | 1 | 82945 | 2 | 1.376 | 60279.8 |
| 993 | 2025-07-16 02:06:48 | predicts | 3 | 146162 | 196 | 33.486 | 4364.9 |
| 992 | 2025-07-11 10:23:54 | predicts | 3 | 146162 | 196 | 65.270 | 2239.3 |
| 991 | 2025-07-09 13:26:27 | predicts | 1 | 82945 | 2 | 1.546 | 53651.4 |
| 990 | 2025-07-08 18:19:42 | predicts | 1 | 82945 | 2 | 1.500 | 55296.7 |
| 989 | 2025-07-08 07:35:50 | predicts | 2 | 121059 | 20 | 28.576 | 4236.4 |
| 988 | 2025-07-07 20:49:04 | predicts | 2 | 121059 | 20 | 18.033 | 6713.2 |
| 987 | 2025-07-07 12:02:10 | predicts | 1 | 82945 | 2 | 5.110 | 16231.9 |
| 986 | 2025-07-04 01:13:06 | predicts | 1 | 82945 | 2 | 3.923 | 21143.3 |
| 985 | 2025-07-04 00:24:51 | predicts | 2 | 121059 | 20 | 19.283 | 6278.0 |
| 984 | 2025-07-02 20:43:44 | predicts | 2 | 121059 | 20 | 17.203 | 7037.1 |
| 983 | 2025-07-02 16:33:35 | predicts | 3 | 146162 | 196 | 31.873 | 4585.8 |
| 982 | 2025-07-02 02:49:45 | predicts | 2 | 121059 | 20 | 19.186 | 6309.8 |
| 981 | 2025-06-28 05:43:25 | predicts | 1 | 82945 | 2 | 6.640 | 12491.7 |
| 980 | 2025-06-26 02:15:32 | predicts | 3 | 146162 | 196 | 56.393 | 2591.8 |
| 979 | 2025-06-26 01:10:06 | predicts | 1 | 82945 | 2 | 7.063 | 11743.6 |
| 978 | 2025-06-25 04:05:51 | predicts | 3 | 146162 | 196 | 48.580 | 3008.7 |
| 977 | 2025-06-24 03:43:08 | predicts | 3 | 146162 | 196 | 37.173 | 3931.9 |
| 976 | 2025-06-23 04:00:18 | predicts | 3 | 146162 | 196 | 8.063 | 18127.5 |
| 975 | 2025-06-15 01:16:49 | predicts | 1 | 82945 | 2 | 2.610 | 31779.7 |
| 974 | 2025-06-09 12:59:19 | predicts | 1 | 82945 | 2 | 3.500 | 23698.6 |
| 973 | 2025-06-07 20:34:05 | predicts | 2 | 121059 | 20 | 26.313 | 4600.7 |
| 972 | 2025-06-07 06:50:47 | predicts | 2 | 121059 | 20 | 14.406 | 8403.4 |
| 971 | 2025-06-05 21:10:30 | predicts | 1 | 82945 | 2 | 3.846 | 21566.6 |
| 970 | 2025-06-04 01:03:07 | predicts | 1 | 82945 | 2 | 5.546 | 14955.8 |
| 969 | 2025-06-03 09:04:00 | predicts | 3 | 146162 | 196 | 48.300 | 3026.1 |
| 968 | 2025-06-01 21:57:58 | predicts | 1 | 82945 | 2 | 7.796 | 10639.4 |
| 967 | 2025-05-30 11:40:45 | predicts | 3 | 146162 | 196 | 62.066 | 2354.9 |
| 966 | 2025-05-26 09:24:12 | predicts | 3 | 146162 | 196 | 26.403 | 5535.8 |
| 965 | 2025-05-26 02:10:14 | predicts | 3 | 146162 | 196 | 58.173 | 2512.5 |
| 964 | 2025-05-23 22:10:29 | predicts | 2 | 121059 | 20 | 26.826 | 4512.7 |
| 963 | 2025-05-23 08:52:11 | predicts | 3 | 146162 | 196 | 8.110 | 18022.4 |
| 962 | 2025-05-15 13:55:49 | predicts | 1 | 82945 | 2 | 3.313 | 25036.2 |
| 961 | 2025-05-11 11:09:01 | predicts | 1 | 82945 | 2 | 1.610 | 51518.6 |
| 960 | 2025-05-07 20:33:42 | predicts | 2 | 121059 | 20 | 20.466 | 5915.1 |
| 959 | 2025-05-07 06:57:34 | predicts | 2 | 121059 | 20 | 3.453 | 35059.1 |
| 958 | 2025-05-04 21:00:23 | predicts | 1 | 82945 | 2 | 1.626 | 51011.7 |
| 957 | 2025-05-04 11:59:27 | predicts | 1 | 82945 | 2 | 5.766 | 14385.2 |
| 956 | 2025-05-03 10:11:18 | predicts | 1 | 82945 | 2 | 1.466 | 56579.1 |
| 955 | 2025-04-29 03:48:10 | predicts | 3 | 146162 | 196 | 13.860 | 10545.6 |
| 954 | 2025-04-24 07:43:09 | predicts | 3 | 146162 | 196 | 28.003 | 5219.5 |
| 953 | 2025-04-23 02:10:50 | predicts | 3 | 146162 | 196 | 23.640 | 6182.8 |
| 952 | 2025-04-22 03:18:50 | predicts | 3 | 146162 | 196 | 24.770 | 5900.8 |
| 951 | 2025-04-21 21:42:28 | predicts | 2 | 121059 | 20 | 3.953 | 30624.6 |
| 950 | 2025-04-21 07:57:56 | predicts | 3 | 146162 | 196 | 41.376 | 3532.5 |
| 949 | 2025-04-20 04:22:58 | predicts | 1 | 82945 | 2 | 4.983 | 16645.6 |
| 948 | 2025-04-20 00:07:46 | predicts | 1 | 82945 | 2 | 5.033 | 16480.2 |
| 947 | 2025-04-03 21:01:06 | predicts | 1 | 82945 | 2 | 6.046 | 13719.0 |
| 946 | 2025-04-02 11:59:19 | predicts | 1 | 82945 | 2 | 5.220 | 15889.8 |
| 945 | 2025-04-02 00:49:26 | predicts | 2 | 121059 | 20 | 17.736 | 6825.6 |
| 944 | 2025-03-30 09:19:42 | predicts | 2 | 121059 | 20 | 4.813 | 25152.5 |
| 943 | 2025-03-24 08:30:31 | predicts | 2 | 121059 | 20 | 31.376 | 3858.3 |
| 942 | 2025-03-23 15:17:00 | predicts | 1 | 82945 | 2 | 7.060 | 11748.6 |
| 941 | 2025-03-22 04:25:57 | predicts | 3 | 146162 | 196 | 24.376 | 5996.1 |
| 940 | 2025-03-21 22:51:42 | predicts | 2 | 121059 | 20 | 4.046 | 29920.7 |
| 939 | 2025-03-20 06:20:44 | predicts | 1 | 82945 | 2 | 5.063 | 16382.6 |
| 938 | 2025-03-20 02:43:24 | predicts | 2 | 121059 | 20 | 17.686 | 6844.9 |
| 937 | 2025-03-17 08:08:16 | predicts | 1 | 82945 | 2 | 5.623 | 14751.0 |
| 936 | 2025-03-04 10:49:44 | predicts | 3 | 146162 | 196 | 44.380 | 3293.4 |
| 935 | 2025-03-03 04:05:07 | predicts | 1 | 82945 | 2 | 3.796 | 21850.6 |
| 934 | 2025-02-28 09:57:14 | predicts | 3 | 146162 | 196 | 46.566 | 3138.8 |
| 933 | 2025-02-28 07:51:26 | predicts | 3 | 146162 | 196 | 47.143 | 3100.4 |
| 932 | 2025-02-27 09:25:59 | predicts | 2 | 121059 | 20 | 19.673 | 6153.6 |
| 931 | 2025-02-27 09:24:05 | predicts | 3 | 146162 | 196 | 37.626 | 3884.6 |
| 930 | 2025-02-26 11:47:39 | predicts | 1 | 82945 | 2 | 6.890 | 12038.5 |
| 929 | 2025-02-26 11:19:50 | predicts | 3 | 146162 | 196 | 28.720 | 5089.2 |
| 928 | 2025-02-26 11:03:02 | predicts | 2 | 121059 | 20 | 3.970 | 30493.5 |
| 927 | 2025-02-26 02:00:31 | predicts | 2 | 121059 | 20 | 11.170 | 10837.9 |
| 926 | 2025-02-12 14:28:14 | predicts | 1 | 82945 | 2 | 6.283 | 13201.5 |
| 925 | 2025-02-09 13:50:38 | predicts | 1 | 82945 | 2 | 1.440 | 57600.7 |
| 924 | 2025-02-01 02:33:03 | predicts | 2 | 121059 | 20 | 14.513 | 8341.4 |
| 923 | 2025-02-01 02:32:58 | predicts | 1 | 82945 | 2 | 8.780 | 9447.0 |
| 922 | 2025-01-14 06:37:22 | predicts | 3 | 146162 | 196 | 25.690 | 5689.5 |