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License: MIT License
A Swiss Army knife for read-write quorum systems
License: MIT License
https://paste.ubuntu.com/p/nYFVm6ZYCx/
I used pyright
Hi @mwhittaker,
I see the following implementation for the uniform_strategy
method:
def uniform_strategy(self, f: int = 0) -> 'Strategy[T]':
...
xs = list(self.elements())
read_quorums = list(self._f_resilient_quorums(f, xs, self.reads))
write_quorums = list(self._f_resilient_quorums(f, xs, self.reads))
...
(line 179)
Am I right to suppose that in the f_resilient_quorums
call for the write_quorums
var, it should pass the self.writes
property of the quorum system?
Thanks
Hi @mwhittaker,
I see in the comments you mentioned the following definition for the load in the optimal strategy:
load(a) = (fr * rprob(a) / rcap(a)) + (fw * wprob(a) / wcap(a))
In the following examples, you define the constraint:
min l subject to
fr * r0 * rcap(a) + fw * (w0 + w1) * wcap(a) <= l
fr * r0 * rcap(b) + fw * (w2 + w3) * wcap(b) <= l
fr * r1 * rcap(c) + fw * (w0 + w2) * wcap(c) <= l
fr * r1 * rcap(d) + fw * (w1 + w3) * wcap(d) <= l
Am I right to assume that it is a typo in the comments, and it should be like this:
min l subject to
fr * r0 / rcap(a) + fw * (w0 + w1) / wcap(a) <= l
fr * r0 / rcap(b) + fw * (w2 + w3) / wcap(b) <= l
fr * r1 / rcap(c) + fw * (w0 + w2) / wcap(c) <= l
fr * r1 / rcap(d) + fw * (w1 + w3) / wcap(d) <= l
Or am I missing something?
Thanks
Quoracle does not work out of the box on the new Apple M1s because it depends on numpy which does not have M1 support. After trying various workaround (including running terminal through rosetta), this solution worked for me.
No action needed, I just wanted to document this workaround until numpy is updated.
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