History of Dictionary Searches using Damerau-Levenshtein distance in T-SQL
Fuzzy-string Searches
(up to 100 most recent)
for
"biasnesses"
Num | Started At (CA time) | Searched Word | Change Limit | Words Checked | Words Matched | Seconds | Words Per Sec |
385 | 2025-06-10 18:00:58 | biasnesses | 2 | 108824 | 7 | 23.406 | 4649.4 |
384 | 2025-06-10 17:56:04 | biasnesses | 3 | 140603 | 120 | 28.906 | 4864.1 |
383 | 2025-06-09 10:37:29 | biasnesses | 1 | 67641 | 1 | 1.000 | 67641.0 |
382 | 2025-06-08 17:35:40 | biasnesses | 3 | 140603 | 120 | 36.670 | 3834.3 |
381 | 2025-06-08 02:29:59 | biasnesses | 2 | 108824 | 7 | 21.813 | 4989.0 |
380 | 2025-06-07 14:54:22 | biasnesses | 1 | 67641 | 1 | 1.170 | 57812.8 |
379 | 2025-06-04 13:14:48 | biasnesses | 1 | 67641 | 1 | 5.203 | 13000.4 |
378 | 2025-05-29 13:49:48 | biasnesses | 1 | 67641 | 1 | 3.250 | 20812.6 |
377 | 2025-05-26 19:36:24 | biasnesses | 1 | 67641 | 1 | 6.063 | 11156.4 |
376 | 2025-05-22 05:10:17 | biasnesses | 1 | 67641 | 1 | 2.890 | 23405.2 |
375 | 2025-05-08 10:27:54 | biasnesses | 1 | 67641 | 1 | 3.826 | 17679.3 |
374 | 2025-05-04 15:10:33 | biasnesses | 1 | 67641 | 1 | 4.843 | 13966.8 |
373 | 2025-05-02 14:22:43 | biasnesses | 1 | 67641 | 1 | 5.580 | 12122.0 |
372 | 2025-05-02 13:29:03 | biasnesses | 1 | 67641 | 1 | 4.313 | 15683.1 |
371 | 2025-04-26 14:08:24 | biasnesses | 1 | 67641 | 1 | 4.373 | 15467.9 |
370 | 2025-04-18 03:51:25 | biasnesses | 1 | 67641 | 1 | 5.423 | 12473.0 |
369 | 2025-04-04 10:28:48 | biasnesses | 1 | 67641 | 1 | 8.000 | 8455.1 |
368 | 2025-04-02 15:13:41 | biasnesses | 1 | 67641 | 1 | 3.686 | 18350.8 |
367 | 2025-04-02 12:33:48 | biasnesses | 1 | 67641 | 1 | 7.140 | 9473.5 |
366 | 2025-03-27 06:21:20 | biasnesses | 2 | 108824 | 7 | 15.330 | 7098.8 |
365 | 2025-03-24 15:54:23 | biasnesses | 1 | 67641 | 1 | 5.236 | 12918.4 |
364 | 2025-03-23 16:51:12 | biasnesses | 1 | 67641 | 1 | 5.500 | 12298.4 |
363 | 2025-03-23 14:26:09 | biasnesses | 2 | 108824 | 7 | 11.313 | 9619.4 |
362 | 2025-03-18 04:03:08 | biasnesses | 2 | 108824 | 7 | 10.986 | 9905.7 |
361 | 2025-03-18 03:56:47 | biasnesses | 1 | 67641 | 1 | 5.343 | 12659.7 |
360 | 2025-03-18 02:48:14 | biasnesses | 3 | 140603 | 120 | 30.533 | 4605.0 |
359 | 2025-03-14 05:17:42 | biasnesses | 3 | 140603 | 120 | 27.486 | 5115.4 |
358 | 2025-03-13 19:10:08 | biasnesses | 3 | 140603 | 120 | 28.753 | 4890.0 |
357 | 2025-03-11 06:42:08 | biasnesses | 3 | 140603 | 120 | 31.846 | 4415.1 |
356 | 2025-03-02 09:15:47 | biasnesses | 2 | 108824 | 7 | 7.703 | 14127.5 |
355 | 2025-03-02 09:15:33 | biasnesses | 1 | 67641 | 1 | 4.250 | 15915.5 |
354 | 2025-03-02 08:51:27 | biasnesses | 3 | 140603 | 120 | 44.516 | 3158.5 |
353 | 2025-03-01 11:49:18 | biasnesses | 3 | 140603 | 120 | 31.940 | 4402.1 |
352 | 2025-02-27 05:53:56 | biasnesses | 2 | 108824 | 7 | 8.123 | 13397.0 |
351 | 2025-02-20 19:49:12 | biasnesses | 1 | 67641 | 1 | 8.673 | 7799.0 |
350 | 2025-01-22 16:39:07 | biasnesses | 1 | 67641 | 1 | 4.296 | 15745.1 |
349 | 2025-01-22 14:13:05 | biasnesses | 3 | 140603 | 120 | 28.910 | 4863.5 |
348 | 2025-01-21 13:33:26 | biasnesses | 3 | 140603 | 120 | 33.470 | 4200.9 |
347 | 2025-01-20 22:37:44 | biasnesses | 3 | 140603 | 120 | 31.020 | 4532.7 |
346 | 2025-01-20 07:29:11 | biasnesses | 3 | 140603 | 120 | 35.953 | 3910.7 |
345 | 2025-01-20 07:29:18 | biasnesses | 2 | 108824 | 7 | 14.030 | 7756.5 |
344 | 2025-01-20 07:26:53 | biasnesses | 1 | 67641 | 1 | 6.080 | 11125.2 |
343 | 2025-01-14 08:33:23 | biasnesses | 2 | 108824 | 7 | 15.566 | 6991.1 |
342 | 2025-01-14 08:07:56 | biasnesses | 1 | 67641 | 1 | 1.173 | 57665.0 |
341 | 2025-01-10 12:30:41 | biasnesses | 1 | 67641 | 1 | 1.203 | 56226.9 |
340 | 2025-01-03 17:01:26 | biasnesses | 2 | 108824 | 7 | 11.143 | 9766.1 |
339 | 2024-12-20 22:31:18 | biasnesses | 3 | 140603 | 120 | 31.610 | 4448.1 |
338 | 2024-12-20 19:50:39 | biasnesses | 3 | 140603 | 120 | 30.580 | 4597.9 |
337 | 2024-12-20 16:01:35 | biasnesses | 3 | 140603 | 120 | 32.406 | 4338.8 |
336 | 2024-12-20 15:58:42 | biasnesses | 1 | 67641 | 1 | 2.813 | 24045.9 |
335 | 2024-12-19 03:00:58 | biasnesses | 1 | 67641 | 1 | 4.673 | 14474.9 |
334 | 2024-11-21 10:14:59 | biasnesses | 2 | 108824 | 7 | 15.000 | 7254.9 |
333 | 2024-11-16 01:52:29 | biasnesses | 2 | 108824 | 7 | 21.750 | 5003.4 |
332 | 2024-11-16 01:11:36 | biasnesses | 1 | 67641 | 1 | 1.080 | 62630.6 |
331 | 2024-11-11 16:11:45 | biasnesses | 1 | 67641 | 1 | 5.423 | 12473.0 |
330 | 2024-11-10 04:45:31 | biasnesses | 1 | 67641 | 1 | 3.343 | 20233.6 |
329 | 2024-11-07 08:30:53 | biasnesses | 1 | 67641 | 1 | 5.156 | 13118.9 |
328 | 2024-10-21 16:12:21 | biasnesses | 3 | 140603 | 120 | 31.860 | 4413.2 |
327 | 2024-10-21 03:53:45 | biasnesses | 3 | 140603 | 120 | 33.923 | 4144.8 |
326 | 2024-10-20 22:30:33 | biasnesses | 3 | 140603 | 120 | 41.423 | 3394.3 |
325 | 2024-10-20 22:30:34 | biasnesses | 2 | 108824 | 7 | 20.906 | 5205.4 |
324 | 2024-10-15 14:30:20 | biasnesses | 2 | 108824 | 7 | 15.470 | 7034.5 |
323 | 2024-10-15 14:26:14 | biasnesses | 1 | 67641 | 1 | 5.296 | 12772.1 |
322 | 2024-10-08 15:12:37 | biasnesses | 1 | 67641 | 1 | 1.016 | 66575.8 |
321 | 2024-09-06 13:22:38 | biasnesses | 2 | 108824 | 7 | 32.920 | 3305.7 |
320 | 2024-09-02 20:52:38 | biasnesses | 2 | 108824 | 7 | 35.033 | 3106.3 |
319 | 2024-09-02 20:52:10 | biasnesses | 1 | 67641 | 1 | 7.733 | 8747.1 |
318 | 2024-09-02 20:39:51 | biasnesses | 3 | 140603 | 120 | 39.423 | 3566.5 |
317 | 2024-09-01 19:11:13 | biasnesses | 1 | 67641 | 1 | 8.283 | 8166.2 |
316 | 2024-08-26 11:51:26 | biasnesses | 3 | 140603 | 120 | 52.130 | 2697.2 |
315 | 2024-08-25 00:51:55 | biasnesses | 3 | 140603 | 120 | 47.910 | 2934.7 |
314 | 2024-08-23 02:07:20 | biasnesses | 3 | 140603 | 120 | 35.830 | 3924.2 |
313 | 2024-08-22 21:53:39 | biasnesses | 3 | 140603 | 120 | 6.280 | 22389.0 |
312 | 2024-08-22 21:53:40 | biasnesses | 2 | 108824 | 7 | 3.063 | 35528.6 |
311 | 2024-08-22 21:53:33 | biasnesses | 1 | 67641 | 1 | 1.110 | 60937.8 |
310 | 2024-08-14 20:20:51 | biasnesses | 1 | 67641 | 1 | 10.470 | 6460.5 |
309 | 2024-07-30 12:50:43 | biasnesses | 1 | 67641 | 1 | 1.156 | 58513.0 |
308 | 2024-07-28 02:53:49 | biasnesses | 1 | 67641 | 1 | 4.080 | 16578.7 |
307 | 2024-07-25 05:54:47 | biasnesses | 1 | 67641 | 1 | 6.016 | 11243.5 |
306 | 2024-07-25 02:39:46 | biasnesses | 1 | 67641 | 1 | 2.000 | 33820.5 |
305 | 2024-07-21 21:07:07 | biasnesses | 1 | 67641 | 1 | 2.236 | 30250.9 |
304 | 2024-07-21 09:53:19 | biasnesses | 1 | 67641 | 1 | 2.153 | 31417.1 |
303 | 2024-07-09 11:23:22 | biasnesses | 3 | 140603 | 120 | 41.470 | 3390.5 |
302 | 2024-07-08 22:22:10 | biasnesses | 3 | 140603 | 120 | 32.156 | 4372.5 |
301 | 2024-07-08 22:22:09 | biasnesses | 2 | 108824 | 7 | 16.393 | 6638.4 |
300 | 2024-07-08 22:15:04 | biasnesses | 1 | 67641 | 1 | 2.280 | 29667.1 |
299 | 2024-07-07 07:30:53 | biasnesses | 1 | 67641 | 1 | 5.626 | 12022.9 |
298 | 2024-07-07 07:16:16 | biasnesses | 1 | 67641 | 1 | 3.783 | 17880.3 |
297 | 2024-07-02 07:50:22 | biasnesses | 1 | 67641 | 1 | 2.736 | 24722.6 |
296 | 2024-06-23 16:38:51 | biasnesses | 1 | 67641 | 1 | 3.186 | 21230.7 |
295 | 2024-06-18 16:03:10 | biasnesses | 3 | 140603 | 120 | 27.813 | 5055.3 |
294 | 2024-06-15 14:57:58 | biasnesses | 3 | 140603 | 120 | 12.500 | 11248.2 |
293 | 2024-06-15 14:57:58 | biasnesses | 2 | 108824 | 7 | 11.580 | 9397.6 |
292 | 2024-06-15 14:52:00 | biasnesses | 1 | 67641 | 1 | 2.046 | 33060.1 |
291 | 2024-06-03 22:57:09 | biasnesses | 1 | 67641 | 1 | 3.846 | 17587.4 |
290 | 2024-05-24 00:03:31 | biasnesses | 2 | 108824 | 7 | 9.686 | 11235.2 |
289 | 2024-05-24 00:03:15 | biasnesses | 1 | 67641 | 1 | 3.953 | 17111.3 |
288 | 2024-05-23 12:34:57 | biasnesses | 3 | 140603 | 120 | 17.516 | 8027.1 |
287 | 2024-05-23 02:01:05 | biasnesses | 3 | 140603 | 120 | 17.283 | 8135.3 |
286 | 2024-05-23 02:01:06 | biasnesses | 2 | 108824 | 7 | 6.200 | 17552.3 |