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current implementation has a high rate of empty ids generated (~2%)
we should change it to have similar collision rate (~0.4%), but more evenly spread throughout id values
The text was updated successfully, but these errors were encountered:
dumping some stats here to compare the two id methods using 1M iterations to simulate ~24 hours of events for a large site
[A]: Array.from({ length: 75 }, (_, i) => String.fromCharCode(48 + i)).filter((a) => /\d|[A-Z]/i.test(a)).filter(() => Math.random() * 75 > 70).join('') 11825.2205ms duration, 0.0118ms average unique results: 604597 average frequency: 1.6540 collision rate: 0.3954% top 10: => 13730 (2.27%) 8 => 1065 (0.18%) V => 1051 (0.17%) 1 => 1044 (0.17%) h => 1038 (0.17%) K => 1038 (0.17%) S => 1033 (0.17%) i => 1032 (0.17%) T => 1029 (0.17%) G => 1023 (0.17%) bottom 10: 2ACMNUqtx => 1 (0.00%) 01GJQU => 1 (0.00%) 6CTVYcir => 1 (0.00%) BEFKQj => 1 (0.00%) 016JXg => 1 (0.00%) anuw => 1 (0.00%) 45NRcm => 1 (0.00%) 8HSrs => 1 (0.00%) 79ahv => 1 (0.00%) MYek => 1 (0.00%)
[B]: Math.random().toString(36).slice(-4) 556.9435ms duration, 0.0006ms average unique results: 728323 average frequency: 1.3730 collision rate: 0.2717% top 10: 72fh => 8 (0.00%) 84mb => 8 (0.00%) kr1l => 7 (0.00%) b8ta => 7 (0.00%) 8vdc => 7 (0.00%) 4hll => 7 (0.00%) eszi => 7 (0.00%) s629 => 7 (0.00%) oj8n => 7 (0.00%) hjyb => 7 (0.00%) bottom 10: nb13 => 1 (0.00%) smwi => 1 (0.00%) 4q0f => 1 (0.00%) prvx => 1 (0.00%) 8bis => 1 (0.00%) 47qb => 1 (0.00%) q4nw => 1 (0.00%) ilhg => 1 (0.00%) m57f => 1 (0.00%) t8mv => 1 (0.00%)
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maxakuru
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current implementation has a high rate of empty ids generated (~2%)
we should change it to have similar collision rate (~0.4%), but more evenly spread throughout id values
The text was updated successfully, but these errors were encountered: