History of Dictionary Searches using Damerau-Levenshtein distance in T-SQL
Fuzzy-string Searches
(up to 100 most recent)
for
"plot"
Num | Started At (CA time) | Searched Word | Change Limit | Words Checked | Words Matched | Seconds | Words Per Sec |
870 | 2025-07-20 07:14:00 | plot | 1 | 13983 | 15 | 0.250 | 55932.0 |
869 | 2025-07-17 19:31:28 | plot | 1 | 13983 | 15 | 1.296 | 10789.4 |
868 | 2025-07-11 14:42:11 | plot | 1 | 13983 | 15 | 0.923 | 15149.5 |
867 | 2025-07-07 05:33:17 | plot | 2 | 29872 | 232 | 2.093 | 14272.3 |
866 | 2025-07-06 05:10:28 | plot | 1 | 13983 | 15 | 0.470 | 29751.1 |
865 | 2025-07-06 04:20:40 | plot | 1 | 13983 | 15 | 0.940 | 14875.5 |
864 | 2025-07-04 05:23:18 | plot | 1 | 13983 | 15 | 1.356 | 10311.9 |
863 | 2025-07-04 03:06:41 | plot | 2 | 29872 | 232 | 4.813 | 6206.5 |
862 | 2025-07-03 10:21:44 | plot | 1 | 13983 | 15 | 0.236 | 59250.0 |
861 | 2025-06-30 05:35:45 | plot | 1 | 13983 | 15 | 1.656 | 8443.8 |
860 | 2025-06-28 10:58:50 | plot | 1 | 13983 | 15 | 1.280 | 10924.2 |
859 | 2025-06-23 20:08:26 | plot | 1 | 13983 | 15 | 1.953 | 7159.8 |
858 | 2025-06-20 13:24:55 | plot | 1 | 13983 | 15 | 0.250 | 55932.0 |
857 | 2025-06-19 20:49:40 | plot | 1 | 13983 | 15 | 1.843 | 7587.1 |
856 | 2025-06-18 01:49:39 | plot | 1 | 13983 | 15 | 1.346 | 10388.6 |
855 | 2025-06-14 19:16:39 | plot | 1 | 13983 | 15 | 1.060 | 13191.5 |
854 | 2025-06-11 02:00:01 | plot | 1 | 13983 | 15 | 0.250 | 55932.0 |
853 | 2025-06-06 21:56:50 | plot | 1 | 13983 | 15 | 0.500 | 27966.0 |
852 | 2025-06-06 03:46:40 | plot | 1 | 13983 | 15 | 1.850 | 7558.4 |
851 | 2025-06-03 15:00:21 | plot | 1 | 13983 | 15 | 0.516 | 27098.8 |
850 | 2025-06-02 10:14:12 | plot | 2 | 29872 | 232 | 4.453 | 6708.3 |
849 | 2025-06-02 09:00:41 | plot | 1 | 13983 | 15 | 1.060 | 13191.5 |
848 | 2025-06-02 02:20:39 | plot | 2 | 29872 | 232 | 4.406 | 6779.8 |
847 | 2025-06-01 08:20:04 | plot | 2 | 29872 | 232 | 2.220 | 13455.9 |
846 | 2025-06-01 07:53:37 | plot | 1 | 13983 | 15 | 0.673 | 20777.1 |
845 | 2025-05-31 10:07:42 | plot | 1 | 13983 | 15 | 0.936 | 14939.1 |
844 | 2025-05-31 04:57:38 | plot | 1 | 13983 | 15 | 1.500 | 9322.0 |
843 | 2025-05-30 12:33:36 | plot | 2 | 29872 | 232 | 2.250 | 13276.4 |
842 | 2025-05-29 09:59:26 | plot | 1 | 13983 | 15 | 0.656 | 21315.5 |
841 | 2025-05-28 19:22:44 | plot | 1 | 13983 | 15 | 0.266 | 52567.7 |
840 | 2025-05-26 23:40:39 | plot | 1 | 13983 | 15 | 0.280 | 49939.3 |
839 | 2025-05-20 08:39:21 | plot | 1 | 13983 | 15 | 1.283 | 10898.7 |
838 | 2025-05-16 15:35:57 | plot | 1 | 13983 | 15 | 1.296 | 10789.4 |
837 | 2025-05-07 22:08:33 | plot | 1 | 13983 | 15 | 0.783 | 17858.2 |
836 | 2025-05-06 03:13:02 | plot | 1 | 13983 | 15 | 0.923 | 15149.5 |
835 | 2025-05-02 16:32:13 | plot | 1 | 13983 | 15 | 0.950 | 14718.9 |
834 | 2025-05-02 13:12:57 | plot | 1 | 13983 | 15 | 0.690 | 20265.2 |
833 | 2025-05-02 09:39:43 | plot | 1 | 13983 | 15 | 1.000 | 13983.0 |
832 | 2025-04-29 12:35:36 | plot | 2 | 29872 | 232 | 0.890 | 33564.0 |
831 | 2025-04-28 09:51:22 | plot | 1 | 13983 | 15 | 0.330 | 42372.7 |
830 | 2025-04-27 18:04:14 | plot | 1 | 13983 | 15 | 0.250 | 55932.0 |
829 | 2025-04-27 18:01:43 | plot | 1 | 13983 | 15 | 0.250 | 55932.0 |
828 | 2025-04-20 07:42:54 | plot | 1 | 13983 | 15 | 1.406 | 9945.2 |
827 | 2025-04-14 15:13:54 | plot | 1 | 13983 | 15 | 0.640 | 21848.4 |
826 | 2025-04-06 02:44:21 | plot | 1 | 13983 | 15 | 0.686 | 20383.4 |
825 | 2025-04-02 08:45:59 | plot | 1 | 13983 | 15 | 1.576 | 8872.5 |
824 | 2025-03-29 06:09:17 | plot | 1 | 13983 | 15 | 0.656 | 21315.5 |
823 | 2025-03-20 09:48:40 | plot | 1 | 13983 | 15 | 1.140 | 12265.8 |
822 | 2025-03-17 09:07:09 | plot | 1 | 13983 | 15 | 1.970 | 7098.0 |
821 | 2025-03-14 20:42:04 | plot | 1 | 13983 | 15 | 1.406 | 9945.2 |
820 | 2025-03-09 23:57:52 | plot | 1 | 13983 | 15 | 1.343 | 10411.8 |
819 | 2025-03-06 23:40:13 | plot | 1 | 13983 | 15 | 2.140 | 6534.1 |
818 | 2025-02-26 17:39:04 | plot | 2 | 29872 | 232 | 2.030 | 14715.3 |
817 | 2025-02-26 17:24:39 | plot | 1 | 13983 | 15 | 1.153 | 12127.5 |
816 | 2025-02-25 12:04:19 | plot | 1 | 13983 | 15 | 1.140 | 12265.8 |
815 | 2025-02-25 09:10:26 | plot | 2 | 29872 | 232 | 6.453 | 4629.2 |
814 | 2025-02-25 08:51:31 | plot | 1 | 13983 | 15 | 0.233 | 60012.9 |
813 | 2025-02-24 22:24:04 | plot | 1 | 13983 | 15 | 0.810 | 17263.0 |
812 | 2025-02-23 19:18:01 | plot | 1 | 13983 | 15 | 0.983 | 14224.8 |
811 | 2025-02-05 13:31:43 | plot | 2 | 29872 | 232 | 3.860 | 7738.9 |
810 | 2025-02-04 20:35:00 | plot | 2 | 29872 | 232 | 4.143 | 7210.2 |
809 | 2025-02-04 20:28:05 | plot | 1 | 13983 | 15 | 1.076 | 12995.4 |
808 | 2025-01-27 14:57:45 | plot | 2 | 29872 | 232 | 0.843 | 35435.3 |
807 | 2025-01-27 14:57:21 | plot | 1 | 13983 | 15 | 0.216 | 64736.1 |
806 | 2025-01-26 04:30:38 | plot | 2 | 29872 | 232 | 4.093 | 7298.3 |
805 | 2025-01-26 04:11:14 | plot | 1 | 13983 | 15 | 0.220 | 63559.1 |
804 | 2025-01-24 17:14:46 | plot | 1 | 13983 | 15 | 1.126 | 12418.3 |
803 | 2025-01-22 22:50:39 | plot | 1 | 13983 | 15 | 0.953 | 14672.6 |
802 | 2025-01-05 20:38:07 | plot | 2 | 29872 | 232 | 4.563 | 6546.6 |
801 | 2025-01-05 18:44:05 | plot | 2 | 29872 | 232 | 4.143 | 7210.2 |
800 | 2025-01-05 18:37:16 | plot | 1 | 13983 | 15 | 0.563 | 24836.6 |
799 | 2024-12-28 08:33:16 | plot | 1 | 13983 | 15 | 0.530 | 26383.0 |
798 | 2024-12-27 15:42:52 | plot | 2 | 29872 | 232 | 3.986 | 7494.2 |
797 | 2024-12-27 03:09:52 | plot | 2 | 29872 | 232 | 5.643 | 5293.6 |
796 | 2024-12-27 02:43:21 | plot | 1 | 13983 | 15 | 0.860 | 16259.3 |
795 | 2024-12-25 09:37:55 | plot | 1 | 13983 | 15 | 0.780 | 17926.9 |
794 | 2024-12-06 13:15:39 | plot | 2 | 29872 | 232 | 3.940 | 7581.7 |
793 | 2024-12-06 12:38:35 | plot | 1 | 13983 | 15 | 1.983 | 7051.4 |
792 | 2024-11-28 02:02:51 | plot | 1 | 13983 | 15 | 1.313 | 10649.7 |
791 | 2024-11-27 14:33:33 | plot | 2 | 29872 | 232 | 3.076 | 9711.3 |
790 | 2024-11-27 07:04:08 | plot | 2 | 29872 | 232 | 3.533 | 8455.1 |
789 | 2024-11-27 01:50:50 | plot | 2 | 29872 | 232 | 4.970 | 6010.5 |
788 | 2024-11-27 01:45:09 | plot | 1 | 13983 | 15 | 1.080 | 12947.2 |
787 | 2024-11-25 07:37:03 | plot | 1 | 13983 | 15 | 0.936 | 14939.1 |
786 | 2024-11-06 08:21:39 | plot | 2 | 29872 | 232 | 2.203 | 13559.7 |
785 | 2024-11-06 08:21:38 | plot | 1 | 13983 | 15 | 0.266 | 52567.7 |
784 | 2024-10-28 22:18:59 | plot | 1 | 13983 | 15 | 1.326 | 10545.2 |
783 | 2024-10-28 12:26:55 | plot | 2 | 29872 | 232 | 4.283 | 6974.6 |
782 | 2024-10-27 22:09:41 | plot | 2 | 29872 | 232 | 2.206 | 13541.3 |
781 | 2024-10-27 21:22:55 | plot | 1 | 13983 | 15 | 0.250 | 55932.0 |
780 | 2024-10-26 04:00:43 | plot | 1 | 13983 | 15 | 0.640 | 21848.4 |
779 | 2024-10-24 19:31:03 | plot | 1 | 13983 | 15 | 0.953 | 14672.6 |
778 | 2024-10-09 01:28:04 | plot | 1 | 13983 | 15 | 1.640 | 8526.2 |
777 | 2024-10-08 21:48:57 | plot | 1 | 13983 | 15 | 1.890 | 7398.4 |
776 | 2024-10-07 07:16:35 | plot | 2 | 29872 | 232 | 6.220 | 4802.6 |
775 | 2024-10-07 07:11:20 | plot | 1 | 13983 | 15 | 0.530 | 26383.0 |
774 | 2024-10-06 19:24:36 | plot | 1 | 13983 | 15 | 1.486 | 9409.8 |
773 | 2024-10-06 15:25:36 | plot | 1 | 13983 | 15 | 1.000 | 13983.0 |
772 | 2024-09-28 14:09:23 | plot | 1 | 13983 | 15 | 0.203 | 68881.8 |
771 | 2024-09-28 11:13:12 | plot | 2 | 29872 | 232 | 8.750 | 3413.9 |