Paxos and Raft Distributed Consensus Algorithm

1. Paxos & Raft
Distributed Consensus Algorithm
Eric FU 2017-5-11

2. Leslie Lamport
• Lamport is best known for his seminal work
in distributed systems and as the initial
developer of the document preparation
system LaTeX
• Microsoft Research
• New York

3. Paxos
• Processors operate at arbitrary speed.
• Processors may experience failures.
• Processors can send messages to any other processor.
• Messages are sent asynchronously and may take
arbitrarily long to deliver.
• Messages may be lost, reordered, or duplicated.
• Messages are delivered without corruption

4. There is only one consensus protocol, and that's Paxos –
all other approaches are just broken versions of Paxos
– Mike Burrows

5. Concept
Roles
• Proposer
• Acceptor
• Learner
Quorums
• {A,B,C}, {A,C,D}, {A,B,D}, {B,C,D}
while U = {A,B,C,D}
Proposal Number: N
Agreed Value: V

6. Phase 1
a) A proposer selects a proposal number n and sends a prepare
request with number n to a majority of acceptors.
b) If an acceptor receives a prepare request with number n greater
than that of any prepare request to which it has already responded,
then it responds to the request with a promise not to accept any
more proposals numbered less than n and with the highest-
numbered proposal (if any) that it has accepted.

7. Phase 1

8. Phase 2
a) If the proposer receives a response to its prepare requests
(numbered n) from a majority of acceptors, then it sends an accept
request to each of those acceptors for a proposal numbered n with
a value v , where v is the value of the highest-numbered proposal
among the responses, or is any value if the responses reported no
proposals.
b) If an acceptor receives an accept request for a proposal numbered
n, it accepts the proposal unless it has already responded to a
prepare request having a number greater than n.

9. Phase 2

10. Demo!
https://github.com/renquinn/Paxos-Demo

11. Raft
• Raft is a consensus algorithm that is
designed to be easy to understand
• equivalent to Paxos in fault-tolerance
and performance
• Decomposed into relatively
independent subproblems
• cleanly addresses all major pieces
needed for practical systems.

12. Replicated State Machine
• Replicated state machines are
typically implemented using a
replicated log
• The consensus module on a
server receives commands from
clients and adds them to its log
• Once commands are properly
replicated, each server’s state
machine processes them in log
order

13. Subproblems
• Leader election: a new leader must be chosen when an existing
leader fails.
• Log replication: the leader must accept log entries
• Safety: if any server has applied a particular log entry to its state
machine, then no other server may apply a different command for
the same log index.

14. Leader Election

15. Log Replication

16. Demo!
http://thesecretlivesofdata.com/raft/

17. Thanks!