History of Dictionary Searches using Damerau-Levenshtein distance in T-SQL
Fuzzy-string Searches
(up to 100 most recent)
for
"readiness"
Num | Started At (CA time) | Searched Word | Change Limit | Words Checked | Words Matched | Seconds | Words Per Sec |
393 | 2025-04-27 08:26:17 | readiness | 1 | 81242 | 4 | 1.483 | 54782.2 |
392 | 2025-04-26 09:10:20 | readiness | 3 | 148641 | 248 | 45.096 | 3296.1 |
391 | 2025-04-26 05:40:37 | readiness | 2 | 121436 | 42 | 28.656 | 4237.7 |
390 | 2025-04-25 15:25:08 | readiness | 1 | 81242 | 4 | 1.530 | 53099.3 |
389 | 2025-04-18 15:39:30 | readiness | 2 | 121436 | 42 | 8.000 | 15179.5 |
388 | 2025-04-17 23:10:15 | readiness | 3 | 148641 | 248 | 37.596 | 3953.6 |
387 | 2025-04-16 15:51:06 | readiness | 2 | 121436 | 42 | 8.750 | 13878.4 |
386 | 2025-04-15 12:36:43 | readiness | 3 | 148641 | 248 | 41.470 | 3584.3 |
385 | 2025-04-14 03:20:17 | readiness | 3 | 148641 | 248 | 47.190 | 3149.8 |
384 | 2025-04-12 14:14:49 | readiness | 2 | 121436 | 42 | 17.313 | 7014.2 |
383 | 2025-04-12 01:34:14 | readiness | 3 | 148641 | 248 | 36.593 | 4062.0 |
382 | 2025-04-10 20:54:59 | readiness | 1 | 81242 | 4 | 4.750 | 17103.6 |
381 | 2025-04-06 15:30:46 | readiness | 1 | 81242 | 4 | 5.143 | 15796.6 |
380 | 2025-04-04 16:05:28 | readiness | 1 | 81242 | 4 | 6.643 | 12229.7 |
379 | 2025-03-25 07:09:03 | readiness | 2 | 121436 | 42 | 18.563 | 6541.8 |
378 | 2025-03-23 03:54:20 | readiness | 2 | 121436 | 42 | 16.096 | 7544.5 |
377 | 2025-03-21 04:31:27 | readiness | 3 | 148641 | 248 | 62.766 | 2368.2 |
376 | 2025-03-15 04:00:27 | readiness | 1 | 81242 | 4 | 3.936 | 20640.8 |
375 | 2025-03-13 04:57:51 | readiness | 2 | 121436 | 42 | 16.860 | 7202.6 |
374 | 2025-03-11 13:05:23 | readiness | 2 | 121436 | 42 | 9.750 | 12455.0 |
373 | 2025-03-11 12:00:12 | readiness | 1 | 81242 | 4 | 5.263 | 15436.4 |
372 | 2025-03-10 12:47:50 | readiness | 3 | 148641 | 248 | 45.550 | 3263.2 |
371 | 2025-03-08 01:13:28 | readiness | 3 | 148641 | 248 | 49.500 | 3002.8 |
370 | 2025-03-07 02:04:48 | readiness | 1 | 81242 | 4 | 3.466 | 23439.7 |
369 | 2025-03-03 04:39:52 | readiness | 3 | 148641 | 248 | 33.396 | 4450.9 |
368 | 2025-03-02 19:05:54 | readiness | 3 | 148641 | 248 | 35.156 | 4228.0 |
367 | 2025-02-28 15:01:33 | readiness | 3 | 148641 | 248 | 39.283 | 3783.9 |
366 | 2025-02-25 17:30:45 | readiness | 1 | 81242 | 4 | 1.266 | 64172.2 |
365 | 2025-02-21 08:06:57 | readiness | 3 | 148641 | 248 | 37.330 | 3981.8 |
364 | 2025-02-19 09:15:58 | readiness | 3 | 148641 | 248 | 57.453 | 2587.2 |
363 | 2025-02-19 09:16:17 | readiness | 2 | 121436 | 42 | 22.753 | 5337.1 |
362 | 2025-02-19 09:14:21 | readiness | 1 | 81242 | 4 | 2.360 | 34424.6 |
361 | 2025-02-09 03:04:28 | readiness | 1 | 81242 | 4 | 1.640 | 49537.8 |
360 | 2025-02-05 03:28:32 | readiness | 1 | 81242 | 4 | 6.080 | 13362.2 |
359 | 2025-02-05 03:16:38 | readiness | 3 | 148641 | 248 | 34.766 | 4275.5 |
358 | 2025-01-31 05:36:16 | readiness | 3 | 148641 | 248 | 34.643 | 4290.7 |
357 | 2025-01-31 05:35:24 | readiness | 2 | 121436 | 42 | 11.203 | 10839.6 |
356 | 2025-01-31 05:35:19 | readiness | 1 | 81242 | 4 | 2.346 | 34630.0 |
355 | 2025-01-20 21:18:51 | readiness | 1 | 81242 | 4 | 3.436 | 23644.4 |
354 | 2025-01-20 21:15:52 | readiness | 3 | 148641 | 248 | 30.000 | 4954.7 |
353 | 2025-01-20 21:15:51 | readiness | 2 | 121436 | 42 | 28.550 | 4253.5 |
352 | 2025-01-20 04:33:47 | readiness | 3 | 148641 | 248 | 47.363 | 3138.3 |
351 | 2025-01-20 04:33:58 | readiness | 2 | 121436 | 42 | 16.720 | 7262.9 |
350 | 2025-01-20 04:32:33 | readiness | 1 | 81242 | 4 | 6.266 | 12965.5 |
349 | 2025-01-02 01:20:17 | readiness | 1 | 81242 | 4 | 3.690 | 22016.8 |
348 | 2025-01-01 22:24:23 | readiness | 3 | 148641 | 248 | 28.626 | 5192.5 |
347 | 2025-01-01 22:24:15 | readiness | 2 | 121436 | 42 | 8.186 | 14834.6 |
346 | 2024-12-30 04:58:32 | readiness | 3 | 148641 | 248 | 39.143 | 3797.4 |
345 | 2024-12-30 04:58:23 | readiness | 2 | 121436 | 42 | 27.050 | 4489.3 |
344 | 2024-12-30 04:04:46 | readiness | 1 | 81242 | 4 | 3.516 | 23106.4 |
343 | 2024-12-16 09:22:52 | readiness | 1 | 81242 | 4 | 6.483 | 12531.5 |
342 | 2024-12-11 09:08:41 | readiness | 3 | 148641 | 248 | 43.016 | 3455.5 |
341 | 2024-12-11 09:08:36 | readiness | 2 | 121436 | 42 | 19.126 | 6349.3 |
340 | 2024-12-11 04:25:49 | readiness | 3 | 148641 | 248 | 40.313 | 3687.2 |
339 | 2024-12-11 04:25:52 | readiness | 2 | 121436 | 42 | 19.030 | 6381.3 |
338 | 2024-12-11 04:25:12 | readiness | 1 | 81242 | 4 | 3.750 | 21664.5 |
337 | 2024-12-02 14:50:45 | readiness | 1 | 81242 | 4 | 10.640 | 7635.5 |
336 | 2024-11-28 12:34:00 | readiness | 1 | 81242 | 4 | 5.330 | 15242.4 |
335 | 2024-11-18 16:28:38 | readiness | 2 | 121436 | 42 | 24.173 | 5023.6 |
334 | 2024-11-16 04:55:22 | readiness | 2 | 121436 | 42 | 23.050 | 5268.4 |
333 | 2024-11-08 22:29:21 | readiness | 1 | 81242 | 4 | 7.420 | 10949.1 |
332 | 2024-11-08 04:25:47 | readiness | 1 | 81242 | 4 | 1.280 | 63470.3 |
331 | 2024-10-30 10:17:01 | readiness | 1 | 81242 | 4 | 7.140 | 11378.4 |
330 | 2024-10-29 10:37:52 | readiness | 2 | 121436 | 42 | 18.736 | 6481.4 |
329 | 2024-10-27 19:33:03 | readiness | 3 | 148641 | 248 | 36.673 | 4053.1 |
328 | 2024-10-26 16:27:17 | readiness | 1 | 81242 | 4 | 9.046 | 8981.0 |
327 | 2024-10-26 11:33:29 | readiness | 3 | 148641 | 248 | 33.173 | 4480.8 |
326 | 2024-10-25 00:44:49 | readiness | 3 | 148641 | 248 | 37.533 | 3960.3 |
325 | 2024-10-23 19:08:34 | readiness | 1 | 81242 | 4 | 5.906 | 13755.8 |
324 | 2024-10-23 18:35:58 | readiness | 1 | 81242 | 4 | 6.280 | 12936.6 |
323 | 2024-10-23 18:32:07 | readiness | 3 | 148641 | 248 | 23.346 | 6366.9 |
322 | 2024-10-23 18:30:12 | readiness | 1 | 81242 | 4 | 7.310 | 11113.8 |
321 | 2024-10-08 15:15:43 | readiness | 1 | 81242 | 4 | 1.516 | 53589.7 |
320 | 2024-10-05 04:07:54 | readiness | 3 | 148641 | 248 | 79.063 | 1880.0 |
319 | 2024-09-25 23:54:19 | readiness | 3 | 148641 | 248 | 58.846 | 2525.9 |
318 | 2024-09-25 00:27:33 | readiness | 3 | 148641 | 248 | 44.390 | 3348.5 |
317 | 2024-09-25 00:26:52 | readiness | 2 | 121436 | 42 | 14.250 | 8521.8 |
316 | 2024-09-24 06:46:56 | readiness | 3 | 148641 | 248 | 44.940 | 3307.5 |
315 | 2024-09-24 06:47:01 | readiness | 2 | 121436 | 42 | 31.330 | 3876.0 |
314 | 2024-09-24 06:44:53 | readiness | 1 | 81242 | 4 | 4.530 | 17934.2 |
313 | 2024-09-13 03:32:52 | readiness | 1 | 81242 | 4 | 11.016 | 7374.9 |
312 | 2024-09-06 03:40:33 | readiness | 1 | 81242 | 4 | 11.093 | 7323.7 |
311 | 2024-09-04 10:59:46 | readiness | 1 | 81242 | 4 | 11.363 | 7149.7 |
310 | 2024-08-16 08:14:41 | readiness | 3 | 148641 | 248 | 77.236 | 1924.5 |
309 | 2024-08-15 11:48:56 | readiness | 3 | 148641 | 248 | 69.753 | 2131.0 |
308 | 2024-08-12 14:04:20 | readiness | 3 | 148641 | 248 | 32.753 | 4538.2 |
307 | 2024-08-09 07:38:22 | readiness | 3 | 148641 | 248 | 31.533 | 4713.8 |
306 | 2024-08-03 03:11:34 | readiness | 3 | 148641 | 248 | 28.893 | 5144.5 |
305 | 2024-08-03 03:11:31 | readiness | 2 | 121436 | 42 | 23.063 | 5265.4 |
304 | 2024-08-02 00:37:15 | readiness | 3 | 148641 | 248 | 27.423 | 5420.3 |
303 | 2024-08-02 00:37:18 | readiness | 2 | 121436 | 42 | 14.110 | 8606.4 |
302 | 2024-08-02 00:36:59 | readiness | 1 | 81242 | 4 | 6.906 | 11764.0 |
301 | 2024-07-28 04:19:38 | readiness | 1 | 81242 | 4 | 7.500 | 10832.3 |
300 | 2024-07-23 02:10:11 | readiness | 2 | 121436 | 42 | 11.186 | 10856.1 |
299 | 2024-07-22 02:05:58 | readiness | 2 | 121436 | 42 | 7.453 | 16293.6 |
298 | 2024-07-22 00:58:19 | readiness | 1 | 81242 | 4 | 7.373 | 11018.9 |
297 | 2024-07-17 21:33:52 | readiness | 1 | 81242 | 4 | 5.220 | 15563.6 |
296 | 2024-07-16 12:45:37 | readiness | 3 | 148641 | 248 | 28.303 | 5251.8 |
295 | 2024-07-14 02:16:04 | readiness | 3 | 148641 | 248 | 25.903 | 5738.4 |
294 | 2024-07-14 02:15:11 | readiness | 3 | 148641 | 248 | 24.030 | 6185.6 |