COS418 Assignment 3: Raft Leader Election
Introduction
This is the first in a series of assignments in which you’ll build a
fault-tolerant key/value storage system. You’ll start in this
assignment by implementing the leader election features of Raft,
a replicated state machine protocol. In Assignment 3 you will complete
Raft’s log consensus agreement features. You will implement Raft as a
Go object with associated methods, available to be used as a module in
a larger service. Once you have completed Raft, the course assignments
will conclude with such a service: a key/value service built on top of Raft.
Raft Overview
The Raft protocol is used to manage replica servers for services
that must continue operation in the face of failure (e.g.
server crashes, broken or flaky networks). The challenge is that,
in the face of these failures, the replicas won’t always hold identical data.
The Raft protocol helps sort out what the correct data is.
Raft’s basic approach for this is to implement a replicated state
machine. Raft organizes client requests into a sequence, called
the log, and ensures that all the replicas agree on the the
contents of the log. Each replica executes the client requests
in the log in the order they appear in the log, applying those
requests to the service’s state. Since all the live replicas
see the same log contents, they all execute the same requests
in the same order, and thus continue to have identical service
state. If a server fails but later recovers, Raft takes care of
bringing its log up to date. Raft will continue to operate as
long as at least a majority of the servers are alive and can
talk to each other. If there is no such majority, Raft will
make no progress, but will pick up where it left off as soon as
a majority is alive again.
You should consult the
extended Raft paper
and the Raft lecture notes. You may also find this
illustrated Raft guide
useful to get a sense of the high-level workings of Raft. For a
wider perspective, have a look at Paxos, Chubby, Paxos Made
Live, Spanner, Zookeeper, Harp, Viewstamped Replication, and
Bolosky et al.
Software
You will continue to use the same cos418 code bundle from the previous assignments.
For this assignment, we will focus primarily on the code and tests for the Raft implementation in
src/raft and the simple RPC-like system in src/labrpc. It is worth your while to
read and digest the code in these packages.
Before you have implemented anything, your raft tests will fail, but this behavior is a sign that you
have everything properly configured and are ready to begin:
$ cd cos418 # or wherever you unpacked your tarball $ export GOPATH="$PWD" $ cd "$GOPATH/src/raft" $ go test -run Election Test: initial election ... --- FAIL: TestInitialElection (5.00s) config.go:286: expected one leader, got none Test: election after network failure ... --- FAIL: TestReElection (5.00s) config.go:286: expected one leader, got none FAIL exit status 1
You should implement Raft by adding code to
raft/raft.go (only). In that file you’ll find a bit of
skeleton code, plus some examples of how to send and receive
RPCs, and examples of how to save and restore persistent state.
Your Task: Leader Election
You should start by reading the code to determine which
functions are responsible for conducting Raft leader election, if
you haven’t already.
The natural first task is to fill in the RequestVoteArgs and
RequestVoteReply structs, and modify
Make() to create a background goroutine that
starts an election (by sending out RequestVote
RPCs) when it hasn’t heard from another peer for a
while. For election to work, you will also need to
implement the RequestVote() RPC handler so
that servers will vote for one another.
To implement heartbeats, you will need to define an
AppendEntries RPC struct (though you will not need
any real payload yet), and have the leader send
them out periodically. You will also have to write an
AppendEntries RPC handler method that resets
the election timeout so that other servers don’t step
forward as leaders when one has already been elected.
Make sure the timers in different Raft peers are not
synchronized. In particular, make sure the election
timeouts don’t always fire at the same time, or else
all peers will vote for themselves and no one will
become leader.
Your Raft implementation must support the following interface, which
the tester and (eventually) your key/value server will use.
You’ll find more details in comments in raft.go.
// create a new Raft server instance:
rf := Make(peers, me, persister, applyCh)
// start agreement on a new log entry:
rf.Start(command interface{}) (index, term, isleader)
// ask a Raft for its current term, and whether it thinks it is leader
rf.GetState() (term, isLeader)
// each time a new entry is committed to the log, each Raft peer
// should send an ApplyMsg to the service (or tester).
type ApplyMsg
A service calls Make(peers,me,…) to create a
Raft peer. The peers argument is an array of established RPC
connections, one to each Raft peer (including this one). The
me argument is the index of this peer in the peers
array. Start(command) asks Raft to start the processing
to append the command to the replicated log. Start()
should return immediately, without waiting for for this process
to complete. The service expects your implementation to send an
ApplyMsg for each new committed log entry to the
applyCh argument to Make().
Your Raft peers should exchange RPCs using the labrpc Go
package that we provide to you. It is modeled after Go’s
rpc library, but
internally uses Go channels rather than sockets.
raft.go contains some example code that sends an RPC
(sendRequestVote()) and that handles an incoming RPC
(RequestVote()).
Implementing leader election and heartbeats (empty
AppendEntries calls) should be sufficient for a
single leader to be elected and — in the absence of failures — stay the leader,
as well as redetermine leadership after failures.
Once you have this working, you should be
able to pass the two Election “go test” tests:
$ go test -run Election Test: initial election ... ... Passed Test: election after network failure ... ... Passed PASS ok raft7.008s
Resources and Advice
- Start early. Although the amount of code to implement
isn’t large, getting it to work correctly will be very
challenging. Both the algorithm and the code is tricky
and there are many corner cases to consider. When one
of the tests fails, it may take a bit of puzzling to
understand in what scenario your solution isn’t
correct, and how to fix your solution. - Read and understand the
extended Raft paper
and the Raft lecture notes before you start. Your
implementation should follow the paper’s description
closely, since that’s what the tests expect. Figure 2 may
be useful as a pseudocode reference. - Add any state you need to keep to the Raft
struct in raft.go. Figure 2 in the paper may
provide a good guideline.
Submission
Submit your code to the COS418 Assignment 3 Dropbox.
You may submit multiple times, only the one in the Dropbox at the time of grading will be recorded.
The Dropbox script will run only a small number of tests (though you should of course pass these!). It is not a substitute for doing your own testing on the full go test cases detailed above.
Before submitting, please run the full tests given above for both parts one final time. You are responsible for making sure your code works.
You will receive full credit for the leader election component if your software passes
the Election tests (as run by the go test commands above) on the CS servers.
The final portion of your credit is determined by code quality tests, using the standard tools gofmt and go vet.
You will receive full credit for this portion if all files submitted conform to the style standards set by gofmt and the report from go vet is clean for your raft package (that is, produces no errors).
If your code does not pass the gofmt test, you should reformat your code using the tool. You can also use the Go Checkstyle tool for advice to improve your code’s style, if applicable. Additionally, though not part of the graded cheks, it would also be advisable to produce code that complies with Golint where possible.
Acknowledgements
This assignment is adapted from MIT’s 6.824 course. Thanks to Frans Kaashoek, Robert Morris, and Nickolai Zeldovich for their support.
Last updated: 2016-11-27 16:37:43 -0500
