History of Dictionary Searches using Damerau-Levenshtein distance in T-SQL
Fuzzy-string Searches
(up to 100 most recent)
for
"sparsity"
Num | Started At (CA time) | Searched Word | Change Limit | Words Checked | Words Matched | Seconds | Words Per Sec |
413 | 2025-09-08 07:04:21 | sparsity | 1 | 82945 | 1 | 1.343 | 61761.0 |
412 | 2025-08-21 07:41:44 | sparsity | 1 | 82945 | 1 | 3.826 | 21679.3 |
411 | 2025-08-17 05:52:32 | sparsity | 1 | 82945 | 1 | 3.376 | 24569.0 |
410 | 2025-07-27 15:45:20 | sparsity | 1 | 82945 | 1 | 4.170 | 19890.9 |
409 | 2025-07-25 02:20:13 | sparsity | 1 | 82945 | 1 | 3.453 | 24021.1 |
408 | 2025-07-24 14:24:17 | sparsity | 1 | 82945 | 1 | 4.673 | 17749.8 |
407 | 2025-07-24 03:16:59 | sparsity | 1 | 82945 | 1 | 5.906 | 14044.2 |
406 | 2025-07-14 03:06:03 | sparsity | 3 | 146162 | 79 | 47.533 | 3075.0 |
405 | 2025-07-10 22:08:28 | sparsity | 1 | 82945 | 1 | 7.283 | 11388.9 |
404 | 2025-07-10 17:15:22 | sparsity | 1 | 82945 | 1 | 7.500 | 11059.3 |
403 | 2025-07-09 21:03:47 | sparsity | 3 | 146162 | 79 | 21.423 | 6822.7 |
402 | 2025-07-08 20:11:20 | sparsity | 3 | 146162 | 79 | 9.610 | 15209.4 |
401 | 2025-07-08 04:08:11 | sparsity | 3 | 146162 | 79 | 34.610 | 4223.1 |
400 | 2025-07-06 21:28:10 | sparsity | 3 | 146162 | 79 | 50.143 | 2914.9 |
399 | 2025-07-04 12:42:30 | sparsity | 2 | 121059 | 6 | 26.233 | 4614.8 |
398 | 2025-07-04 11:48:12 | sparsity | 3 | 146162 | 79 | 22.800 | 6410.6 |
397 | 2025-06-30 06:43:02 | sparsity | 1 | 82945 | 1 | 7.096 | 11689.0 |
396 | 2025-06-26 19:09:20 | sparsity | 1 | 82945 | 1 | 5.126 | 16181.2 |
395 | 2025-06-26 14:52:27 | sparsity | 1 | 82945 | 1 | 9.860 | 8412.3 |
394 | 2025-06-25 14:11:24 | sparsity | 1 | 82945 | 1 | 7.156 | 11591.0 |
393 | 2025-06-10 03:36:53 | sparsity | 1 | 82945 | 1 | 3.546 | 23391.1 |
392 | 2025-06-09 03:43:30 | sparsity | 4 | 161609 | 766 | 17.063 | 9471.3 |
391 | 2025-06-04 09:54:48 | sparsity | 1 | 82945 | 1 | 3.923 | 21143.3 |
390 | 2025-06-02 15:59:12 | sparsity | 4 | 161609 | 766 | 68.316 | 2365.6 |
389 | 2025-06-02 08:52:26 | sparsity | 4 | 161609 | 766 | 81.050 | 1993.9 |
388 | 2025-06-02 02:09:43 | sparsity | 4 | 161609 | 766 | 45.536 | 3549.0 |
387 | 2025-06-01 22:23:12 | sparsity | 4 | 161609 | 766 | 65.156 | 2480.3 |
386 | 2025-05-31 05:28:38 | sparsity | 4 | 161609 | 766 | 70.740 | 2284.5 |
385 | 2025-05-27 13:13:09 | sparsity | 1 | 82945 | 1 | 9.236 | 8980.6 |
384 | 2025-05-26 16:20:13 | sparsity | 1 | 82945 | 1 | 12.003 | 6910.4 |
383 | 2025-05-26 05:50:34 | sparsity | 1 | 82945 | 1 | 5.750 | 14425.2 |
382 | 2025-05-18 02:03:25 | sparsity | 1 | 82945 | 1 | 9.906 | 8373.2 |
381 | 2025-05-10 19:14:12 | sparsity | 2 | 121059 | 6 | 15.173 | 7978.6 |
380 | 2025-05-10 19:12:32 | sparsity | 3 | 146162 | 79 | 22.783 | 6415.4 |
379 | 2025-05-09 05:17:28 | sparsity | 1 | 82945 | 1 | 2.580 | 32149.2 |
378 | 2025-05-03 08:47:51 | sparsity | 1 | 82945 | 1 | 5.343 | 15524.1 |
377 | 2025-05-02 00:54:25 | sparsity | 1 | 82945 | 1 | 3.810 | 21770.3 |
376 | 2025-04-26 16:04:44 | sparsity | 4 | 161609 | 766 | 67.020 | 2411.4 |
375 | 2025-04-25 22:26:55 | sparsity | 4 | 161609 | 766 | 70.596 | 2289.2 |
374 | 2025-04-25 10:35:51 | sparsity | 4 | 161609 | 766 | 13.376 | 12082.0 |
373 | 2025-04-25 01:39:14 | sparsity | 4 | 161609 | 766 | 44.126 | 3662.4 |
372 | 2025-04-24 02:10:37 | sparsity | 4 | 161609 | 766 | 82.816 | 1951.4 |
371 | 2025-04-23 23:42:41 | sparsity | 2 | 121059 | 6 | 28.593 | 4233.9 |
370 | 2025-04-23 23:28:17 | sparsity | 3 | 146162 | 79 | 29.000 | 5040.1 |
369 | 2025-04-22 13:50:17 | sparsity | 1 | 82945 | 1 | 3.296 | 25165.4 |
368 | 2025-04-16 11:18:26 | sparsity | 2 | 121059 | 6 | 14.626 | 8277.0 |
367 | 2025-04-16 06:39:40 | sparsity | 3 | 146162 | 79 | 22.703 | 6438.0 |
366 | 2025-04-15 21:50:44 | sparsity | 3 | 146162 | 79 | 37.986 | 3847.8 |
365 | 2025-04-15 05:27:26 | sparsity | 1 | 82945 | 1 | 7.393 | 11219.4 |
364 | 2025-03-31 01:39:57 | sparsity | 1 | 82945 | 1 | 6.813 | 12174.5 |
363 | 2025-03-23 10:21:47 | sparsity | 1 | 82945 | 1 | 6.893 | 12033.2 |
362 | 2025-03-22 15:39:01 | sparsity | 1 | 82945 | 1 | 6.766 | 12259.1 |
361 | 2025-03-12 16:50:07 | sparsity | 1 | 82945 | 1 | 4.486 | 18489.7 |
360 | 2025-02-25 22:59:02 | sparsity | 1 | 82945 | 1 | 6.500 | 12760.8 |
359 | 2025-02-23 12:54:01 | sparsity | 1 | 82945 | 1 | 10.936 | 7584.6 |
358 | 2025-02-20 02:56:14 | sparsity | 1 | 82945 | 1 | 10.970 | 7561.1 |
357 | 2025-02-05 03:10:35 | sparsity | 1 | 82945 | 1 | 2.516 | 32967.0 |
356 | 2025-01-27 22:36:40 | sparsity | 1 | 82945 | 1 | 6.296 | 13174.2 |
355 | 2025-01-27 10:50:05 | sparsity | 3 | 146162 | 79 | 31.860 | 4587.6 |
354 | 2025-01-27 08:59:34 | sparsity | 3 | 146162 | 79 | 41.673 | 3507.4 |
353 | 2025-01-27 01:30:59 | sparsity | 3 | 146162 | 79 | 11.780 | 12407.6 |
352 | 2025-01-27 01:31:01 | sparsity | 3 | 146162 | 79 | 7.906 | 18487.5 |
351 | 2025-01-27 01:31:00 | sparsity | 2 | 121059 | 6 | 7.810 | 15500.5 |
350 | 2025-01-23 12:05:13 | sparsity | 1 | 82945 | 1 | 4.106 | 20200.9 |
349 | 2025-01-18 10:38:10 | sparsity | 1 | 82945 | 1 | 6.953 | 11929.4 |
348 | 2025-01-05 21:48:41 | sparsity | 1 | 82945 | 1 | 6.656 | 12461.7 |
347 | 2024-12-27 08:24:19 | sparsity | 1 | 82945 | 1 | 3.640 | 22787.1 |
346 | 2024-12-19 08:43:45 | sparsity | 3 | 146162 | 79 | 53.126 | 2751.2 |
345 | 2024-12-19 08:43:20 | sparsity | 2 | 121059 | 6 | 12.736 | 9505.3 |
344 | 2024-12-19 08:43:10 | sparsity | 1 | 82945 | 1 | 5.110 | 16231.9 |
343 | 2024-12-08 18:04:08 | sparsity | 3 | 146162 | 79 | 33.740 | 4332.0 |
342 | 2024-12-06 23:39:50 | sparsity | 3 | 146162 | 79 | 31.766 | 4601.2 |
341 | 2024-12-06 15:14:02 | sparsity | 3 | 146162 | 79 | 40.270 | 3629.6 |
340 | 2024-12-06 15:14:03 | sparsity | 3 | 146162 | 79 | 31.563 | 4630.8 |
339 | 2024-12-06 15:14:04 | sparsity | 2 | 121059 | 6 | 15.736 | 7693.1 |
338 | 2024-12-06 07:57:48 | sparsity | 1 | 82945 | 1 | 6.283 | 13201.5 |
337 | 2024-11-16 13:35:29 | sparsity | 2 | 121059 | 6 | 9.253 | 13083.2 |
336 | 2024-11-16 13:21:50 | sparsity | 1 | 82945 | 1 | 1.483 | 55930.5 |
335 | 2024-11-12 11:56:55 | sparsity | 3 | 146162 | 79 | 42.940 | 3403.9 |
334 | 2024-11-12 05:12:55 | sparsity | 1 | 82945 | 1 | 1.406 | 58993.6 |
333 | 2024-11-07 20:40:44 | sparsity | 3 | 146162 | 79 | 40.503 | 3608.7 |
332 | 2024-11-07 18:57:47 | sparsity | 3 | 146162 | 79 | 47.740 | 3061.6 |
331 | 2024-11-06 19:36:14 | sparsity | 3 | 146162 | 79 | 31.243 | 4678.2 |
330 | 2024-11-06 04:25:37 | sparsity | 3 | 146162 | 79 | 39.736 | 3678.3 |
329 | 2024-11-06 04:25:33 | sparsity | 1 | 82945 | 1 | 3.826 | 21679.3 |
328 | 2024-10-15 03:02:49 | sparsity | 3 | 146162 | 79 | 41.486 | 3523.2 |
327 | 2024-10-15 03:02:49 | sparsity | 2 | 121059 | 6 | 17.706 | 6837.2 |
326 | 2024-10-14 17:58:32 | sparsity | 3 | 146162 | 79 | 37.376 | 3910.6 |
325 | 2024-10-14 17:58:27 | sparsity | 2 | 121059 | 6 | 18.470 | 6554.4 |
324 | 2024-10-14 17:58:22 | sparsity | 1 | 82945 | 1 | 2.593 | 31988.0 |
323 | 2024-10-14 01:36:33 | sparsity | 1 | 82945 | 1 | 7.170 | 11568.3 |
322 | 2024-10-08 15:50:29 | sparsity | 3 | 146162 | 79 | 43.470 | 3362.4 |
321 | 2024-10-08 07:12:04 | sparsity | 3 | 146162 | 79 | 42.236 | 3460.6 |
320 | 2024-10-07 09:38:26 | sparsity | 3 | 146162 | 79 | 68.613 | 2130.2 |
319 | 2024-10-07 09:35:51 | sparsity | 1 | 82945 | 1 | 10.923 | 7593.6 |
318 | 2024-10-03 20:26:10 | sparsity | 3 | 146162 | 79 | 48.686 | 3002.1 |
317 | 2024-09-28 08:47:07 | sparsity | 1 | 82945 | 1 | 7.720 | 10744.2 |
316 | 2024-09-11 20:08:43 | sparsity | 2 | 121059 | 6 | 16.110 | 7514.5 |
315 | 2024-09-09 15:16:11 | sparsity | 1 | 82945 | 1 | 12.360 | 6710.8 |
314 | 2024-09-08 22:22:31 | sparsity | 2 | 121059 | 6 | 25.753 | 4700.8 |