This is a demo implementation of the Paxos algorithm implemented in Python.
pip install paxos
- The proposer, acceptor, and learner roles of the Paxos algorithm are
implemented in with classes that subclass from a common Agent class.
- Each role/agent is run in a separate process.
- Communication between processes occurs using Queue objects, so all
processes are run on the same machine.
- Paxos Made Simple states that “we require that different proposals have
different numbers.” To achieve this, we start each proposer process’s
proposal number sequence equal to its own PID, and then increment the number
for each new proposal by the number of proposer processes in the system.
This also seems to be the method used in the “Paxos Made Live” paper by
- It is assumed that all processes in the system be considered members of the
system from the beginning, without needing to explicitly join the system by
getting a decree passed.
- Add a collapsed version of the roles so that each process plays all of the
- Once we have a collapsed version, leaders should retry a client’s request
if they determine that the instance hasn’t been decided after some timeout
amount of time. This should fix a couple issues:
- Learners are not able to determine whether or not there are more values
to learn (when it is the last value they are missing).
- Since leaders are currently remembering the original value of each
client request they propose, if a Proposer is asked to retry an
instance (e.g. from a Learner that is missing a value) then it is
possible that the value learned will be None in the situation where no
Acceptor has yet accepted a value in that instance (which means the
Proposer should specify the value, but since it is not remembering the
original values it just proposes None).
- When a learner asks a proposer to retry, the proposer shouldn’t retry if it
has already retried that proposal within a certain time period because
otherwise, by re-upping the proposal number it would be guaranteed to not
have a successful agreement in that instance it is retrying.
- With a consistent leader, only perform phase one once.
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