关于raft算法相关细节，可以全看之前的文章 分布式一致性算法，两阶段提交，三阶段提交，Paxos，Raft，zookeeper的选主过程,zab协议,顺序一致性,数据写入流程,节点状态,节点的角色
这里我们说下阿里开源的sofa-jraft的实现。
首先说明下，在sofa-jraft有几个比较重要的角色
- Node 代表的就是一个服务节点
- Ballot 代表的是一次投票的相关信息
- PeerId 代表的是一个复制组里面的一个参与角色
- StateMachine 当数据提交到Node之后，会执行其onApply方法
另外Node中有几个比较重要的定时器：
- electionTimer 选举定时器，如果当前leader挂了，会进行preVote
- voteTimer 投票定时器，当投票超时后，会进行preVote
- stepDownTimer leader使用，判断当前节点是否存活，且检察整个集群是否有节点下线并更新Leader节点的Timestamp
JRaft的选举投票有两个步骤preVote和vote,之所以要增加一个preVote的步骤，是为了解决系统中防止某个节点由于无法和leader同步，不断发起投票，抬升自己的Term，导致自己Term比Leader的Term还大，然后迫使Leader放弃Leader身份，开始新一轮的选举。
而preVote则强调节点必须获得半数以上的投票才能开始发起新一轮的选举。
JRaft的选举是通过定时器超时开始的，在NodeImpl中（Node的具体实现类），当我们执行NodeImpl.init的时候，会开启electionTimer:
this.electionTimer = new RepeatedTimer(name, this.options.getElectionTimeoutMs(),
TIMER_FACTORY.getElectionTimer(this.options.isSharedElectionTimer(), name)) {
protected void onTrigger() {
handleElectionTimeout();
}
protected int adjustTimeout(final int timeoutMs) {
return randomTimeout(timeoutMs);
}
};
private void handleElectionTimeout() {
boolean doUnlock = true;
this.writeLock.lock();
try {
if (this.state != State.STATE_FOLLOWER) {
return;
}
if (isCurrentLeaderValid()) {
return;
}
resetLeaderId(PeerId.emptyPeer(), new Status(RaftError.ERAFTTIMEDOUT, "Lost connection from leader %s.",
this.leaderId));
// Judge whether to launch a election.
if (!allowLaunchElection()) {
return;
}
doUnlock = false;
preVote();
} finally {
if (doUnlock) {
this.writeLock.unlock();
}
}
}
而handleElectionTimeout中主要就是进行了preVote *** 作，这里JRaft一次投票的主要几个 *** 作如下：
preVote ===> handlePreVoteRequest ===> electSelf ===>handleRequestVoteRequest
我们首先看下preVote:
private void preVote() {
.....
final LogId lastLogId = this.logManager.getLastLogId(true);
boolean doUnlock = true;
this.writeLock.lock();
try {
// pre_vote need defense ABA after unlock&writeLock
if (oldTerm != this.currTerm) {
LOG.warn("Node {} raise term {} when get lastLogId.", getNodeId(), this.currTerm);
return;
}
this.prevVoteCtx.init(this.conf.getConf(), this.conf.isStable() ? null : this.conf.getOldConf());
for (final PeerId peer : this.conf.listPeers()) {
if (peer.equals(this.serverId)) {
continue;
}
if (!this.rpcService.connect(peer.getEndpoint())) {
LOG.warn("Node {} channel init failed, address={}.", getNodeId(), peer.getEndpoint());
continue;
}
final OnPreVoteRpcDone done = new OnPreVoteRpcDone(peer, this.currTerm);
done.request = RequestVoteRequest.newBuilder() //
.setPreVote(true) // it's a pre-vote request.
.setGroupId(this.groupId) //
.setServerId(this.serverId.toString()) //
.setPeerId(peer.toString()) //
.setTerm(this.currTerm + 1) // next term
.setLastLogIndex(lastLogId.getIndex()) //
.setLastLogTerm(lastLogId.getTerm()) //
.build();
this.rpcService.preVote(peer.getEndpoint(), done.request, done);
}
this.prevVoteCtx.grant(this.serverId);
if (this.prevVoteCtx.isGranted()) {
doUnlock = false;
electSelf();
}
} finally {
if (doUnlock) {
this.writeLock.unlock();
}
}
}
可以看到preVote中会对当前出自己以外的节点发送RequestVoteRequest请求,主要设置信息如下：
RequestVoteRequest.newBuilder() //
.setPreVote(true) // it's a pre-vote request.
.setGroupId(this.groupId) //
.setServerId(this.serverId.toString()) //
.setPeerId(peer.toString()) //
.setTerm(this.currTerm + 1) // next term
.setLastLogIndex(lastLogId.getIndex()) //
.setLastLogTerm(lastLogId.getTerm()) //
.build();
可以看到，这时候并没有将自己的currTerm设置为currTerm +1，只是在请求的时候发送了一个currTerm+1的值，这和实际选举的时候有差别，实际选举的时候首选会将currTerm++
我们看下其他节点收到这个请求是怎么处理的：
public Message handlePreVoteRequest(final RequestVoteRequest request) {
boolean doUnlock = true;
this.writeLock.lock();
try {
if (!this.state.isActive()) {
LOG.warn("Node {} is not in active state, currTerm={}.", getNodeId(), this.currTerm);
return RpcFactoryHelper //
.responseFactory() //
.newResponse(RequestVoteResponse.getDefaultInstance(), RaftError.EINVAL,
"Node %s is not in active state, state %s.", getNodeId(), this.state.name());
}
final PeerId candidateId = new PeerId();
if (!candidateId.parse(request.getServerId())) {
LOG.warn("Node {} received PreVoteRequest from {} serverId bad format.", getNodeId(),
request.getServerId());
return RpcFactoryHelper //
.responseFactory() //
.newResponse(RequestVoteResponse.getDefaultInstance(), RaftError.EINVAL,
"Parse candidateId failed: %s.", request.getServerId());
}
boolean granted = false;
// noinspection ConstantConditions
do {
if (!this.conf.contains(candidateId)) {
LOG.warn("Node {} ignore PreVoteRequest from {} as it is not in conf <{}>.", getNodeId(),
request.getServerId(), this.conf);
break;
}
if (this.leaderId != null && !this.leaderId.isEmpty() && isCurrentLeaderValid()) {
LOG.info(
"Node {} ignore PreVoteRequest from {}, term={}, currTerm={}, because the leader {}'s lease is still valid.",
getNodeId(), request.getServerId(), request.getTerm(), this.currTerm, this.leaderId);
break;
}
if (request.getTerm() < this.currTerm) {
LOG.info("Node {} ignore PreVoteRequest from {}, term={}, currTerm={}.", getNodeId(),
request.getServerId(), request.getTerm(), this.currTerm);
// A follower replicator may not be started when this node become leader, so we must check it.
checkReplicator(candidateId);
break;
}
// A follower replicator may not be started when this node become leader, so we must check it.
// check replicator state
checkReplicator(candidateId);
doUnlock = false;
this.writeLock.unlock();
final LogId lastLogId = this.logManager.getLastLogId(true);
doUnlock = true;
this.writeLock.lock();
final LogId requestLastLogId = new LogId(request.getLastLogIndex(), request.getLastLogTerm());
granted = requestLastLogId.compareTo(lastLogId) >= 0;
LOG.info(
"Node {} received PreVoteRequest from {}, term={}, currTerm={}, granted={}, requestLastLogId={}, lastLogId={}.",
getNodeId(), request.getServerId(), request.getTerm(), this.currTerm, granted, requestLastLogId,
lastLogId);
} while (false);
return RequestVoteResponse.newBuilder() //
.setTerm(this.currTerm) //
.setGranted(granted) //
.build();
} finally {
if (doUnlock) {
this.writeLock.unlock();
}
}
}
这里其他节点收到PreVoteRequest的时候，会进行如下判断：
- 如果当前节点的Leader节点依然活着，直接返回本次投票granted=false
- 如果请求preVote的term比当前节点term小，直接返回本次投票granted=false
- 如果请求的Log信息（index和term比当前小），直接返回本次投票granted=false
- 如果上面都不满足，返回granted=true
这是其他节点收到PreVoteRequest的处理，我们再看发起preVote节点收到其他节点的响应是怎么处理的：
public void handlePreVoteResponse(final PeerId peerId, final long term, final RequestVoteResponse response) {
boolean doUnlock = true;
this.writeLock.lock();
try {
if (this.state != State.STATE_FOLLOWER) {
LOG.warn("Node {} received invalid PreVoteResponse from {}, state not in STATE_FOLLOWER but {}.",
getNodeId(), peerId, this.state);
return;
}
if (term != this.currTerm) {
LOG.warn("Node {} received invalid PreVoteResponse from {}, term={}, currTerm={}.", getNodeId(),
peerId, term, this.currTerm);
return;
}
if (response.getTerm() > this.currTerm) {
LOG.warn("Node {} received invalid PreVoteResponse from {}, term {}, expect={}.", getNodeId(), peerId,
response.getTerm(), this.currTerm);
stepDown(response.getTerm(), false, new Status(RaftError.EHIGHERTERMRESPONSE,
"Raft node receives higher term pre_vote_response."));
return;
}
LOG.info("Node {} received PreVoteResponse from {}, term={}, granted={}.", getNodeId(), peerId,
response.getTerm(), response.getGranted());
// check granted quorum?
if (response.getGranted()) {
this.prevVoteCtx.grant(peerId);
if (this.prevVoteCtx.isGranted()) {
doUnlock = false;
electSelf();
}
}
} finally {
if (doUnlock) {
this.writeLock.unlock();
}
}
}
这里参数中term是投票之前节点的term，peerId是当前节点发送preVote节点的PeerId信息，我们看下其判断逻辑：
- 如果当前term和投票前的term不相等，则表明发生了新一轮投票，当前响应作废直接返回
- 如果响应中term（响应节点的term）比当前节点term大，表明响应节点比当前节点的投票轮次更高，直接返回
- 如果响应允许这次投票，即response.getGranted=true,判断本轮发起的投票同意是否过半。
在NodeImpl中有两个Ballot，一个是支持preVote的prevVoteCtx，一个是支持vote,在发起preVote的时候，会对prevVoteCtx进行初始化:
public boolean init(final Configuration conf, final Configuration oldConf) {
this.peers.clear();
this.oldPeers.clear();
this.quorum = this.oldQuorum = 0;
int index = 0;
if (conf != null) {
for (final PeerId peer : conf) {
this.peers.add(new UnfoundPeerId(peer, index++, false));
}
}
this.quorum = this.peers.size() / 2 + 1;
if (oldConf == null) {
return true;
}
index = 0;
for (final PeerId peer : oldConf) {
this.oldPeers.add(new UnfoundPeerId(peer, index++, false));
}
this.oldQuorum = this.oldPeers.size() / 2 + 1;
return true;
}
可以看到这里init对Ballot的法定人数quorum 设置是当前节点/2+1个。
这里我们在来看当preVote请求被同意的情况下是怎么判断是否需要发起选举,在handlePreVoteResponse的最后，会执行this.prevVoteCtx.grant(peerId);：
public void grant(final PeerId peerId) {
grant(peerId, new PosHint());
}
public PosHint grant(final PeerId peerId, final PosHint hint) {
UnfoundPeerId peer = findPeer(peerId, this.peers, hint.pos0);
if (peer != null) {
if (!peer.found) {
peer.found = true;
this.quorum--;
}
hint.pos0 = peer.index;
} else {
hint.pos0 = -1;
}
if (this.oldPeers.isEmpty()) {
hint.pos1 = -1;
return hint;
}
peer = findPeer(peerId, this.oldPeers, hint.pos1);
if (peer != null) {
if (!peer.found) {
peer.found = true;
this.oldQuorum--;
}
hint.pos1 = peer.index;
} else {
hint.pos1 = -1;
}
return hint;
}
这里的判断逻辑很简单，响应的节点如果同意了这次投票，那么对应的投票信息Ballot法定人数quorum–，同时这里为了防止一个节点多次响应，标记每个节点只能响应一次。然后判断本次preVote投票是否过半：
public boolean isGranted() {
return this.quorum <= 0 && this.oldQuorum <= 0;
}
如果过半，开始正式选举electSelf:
private void electSelf() {
long oldTerm;
try {
LOG.info("Node {} start vote and grant vote self, term={}.", getNodeId(), this.currTerm);
if (!this.conf.contains(this.serverId)) {
LOG.warn("Node {} can't do electSelf as it is not in {}.", getNodeId(), this.conf);
return;
}
if (this.state == State.STATE_FOLLOWER) {
LOG.debug("Node {} stop election timer, term={}.", getNodeId(), this.currTerm);
this.electionTimer.stop();
}
resetLeaderId(PeerId.emptyPeer(), new Status(RaftError.ERAFTTIMEDOUT,
"A follower's leader_id is reset to NULL as it begins to request_vote."));
this.state = State.STATE_CANDIDATE;
this.currTerm++;
this.votedId = this.serverId.copy();
LOG.debug("Node {} start vote timer, term={} .", getNodeId(), this.currTerm);
this.voteTimer.start();
this.voteCtx.init(this.conf.getConf(), this.conf.isStable() ? null : this.conf.getOldConf());
oldTerm = this.currTerm;
} finally {
this.writeLock.unlock();
}
final LogId lastLogId = this.logManager.getLastLogId(true);
this.writeLock.lock();
try {
// vote need defense ABA after unlock&writeLock
if (oldTerm != this.currTerm) {
LOG.warn("Node {} raise term {} when getLastLogId.", getNodeId(), this.currTerm);
return;
}
for (final PeerId peer : this.conf.listPeers()) {
if (peer.equals(this.serverId)) {
continue;
}
if (!this.rpcService.connect(peer.getEndpoint())) {
LOG.warn("Node {} channel init failed, address={}.", getNodeId(), peer.getEndpoint());
continue;
}
final OnRequestVoteRpcDone done = new OnRequestVoteRpcDone(peer, this.currTerm, this);
done.request = RequestVoteRequest.newBuilder() //
.setPreVote(false) // It's not a pre-vote request.
.setGroupId(this.groupId) //
.setServerId(this.serverId.toString()) //
.setPeerId(peer.toString()) //
.setTerm(this.currTerm) //
.setLastLogIndex(lastLogId.getIndex()) //
.setLastLogTerm(lastLogId.getTerm()) //
.build();
this.rpcService.requestVote(peer.getEndpoint(), done.request, done);
}
this.metaStorage.setTermAndVotedFor(this.currTerm, this.serverId);
this.voteCtx.grant(this.serverId);
if (this.voteCtx.isGranted()) {
becomeLeader();
}
} finally {
this.writeLock.unlock();
}
}
正式投票会进行如下 *** 作：
- 当前currTerm++，voteTimer启动，voteCtx初始化
- 发送RequestVoteRequest请求，与preVote基本差不多，唯一区别PreVote=false
我们再看其他节点收到投票怎么处理的:
public Message handleRequestVoteRequest(final RequestVoteRequest request) {
boolean doUnlock = true;
this.writeLock.lock();
try {
if (!this.state.isActive()) {
LOG.warn("Node {} is not in active state, currTerm={}.", getNodeId(), this.currTerm);
return RpcFactoryHelper //
.responseFactory() //
.newResponse(RequestVoteResponse.getDefaultInstance(), RaftError.EINVAL,
"Node %s is not in active state, state %s.", getNodeId(), this.state.name());
}
final PeerId candidateId = new PeerId();
if (!candidateId.parse(request.getServerId())) {
LOG.warn("Node {} received RequestVoteRequest from {} serverId bad format.", getNodeId(),
request.getServerId());
return RpcFactoryHelper //
.responseFactory() //
.newResponse(RequestVoteResponse.getDefaultInstance(), RaftError.EINVAL,
"Parse candidateId failed: %s.", request.getServerId());
}
// noinspection ConstantConditions
do {
// check term
if (request.getTerm() >= this.currTerm) {
LOG.info("Node {} received RequestVoteRequest from {}, term={}, currTerm={}.", getNodeId(),
request.getServerId(), request.getTerm(), this.currTerm);
// increase current term, change state to follower
if (request.getTerm() > this.currTerm) {
stepDown(request.getTerm(), false, new Status(RaftError.EHIGHERTERMRESPONSE,
"Raft node receives higher term RequestVoteRequest."));
}
} else {
// ignore older term
LOG.info("Node {} ignore RequestVoteRequest from {}, term={}, currTerm={}.", getNodeId(),
request.getServerId(), request.getTerm(), this.currTerm);
break;
}
doUnlock = false;
this.writeLock.unlock();
final LogId lastLogId = this.logManager.getLastLogId(true);
doUnlock = true;
this.writeLock.lock();
// vote need ABA check after unlock&writeLock
if (request.getTerm() != this.currTerm) {
LOG.warn("Node {} raise term {} when get lastLogId.", getNodeId(), this.currTerm);
break;
}
final boolean logIsOk = new LogId(request.getLastLogIndex(), request.getLastLogTerm())
.compareTo(lastLogId) >= 0;
if (logIsOk && (this.votedId == null || this.votedId.isEmpty())) {
stepDown(request.getTerm(), false, new Status(RaftError.EVOTEFORCANDIDATE,
"Raft node votes for some candidate, step down to restart election_timer."));
this.votedId = candidateId.copy();
this.metaStorage.setVotedFor(candidateId);
}
} while (false);
return RequestVoteResponse.newBuilder() //
.setTerm(this.currTerm) //
.setGranted(request.getTerm() == this.currTerm && candidateId.equals(this.votedId)) //
.build();
} finally {
if (doUnlock) {
this.writeLock.unlock();
}
}
}
收到投票请求节点的处理与preVote请求的处理逻辑上差不多：
- 判断请求的term和当前term大小，比请求的term大，返回Granted=false
- 判读当前log的位置是否比请求位置小，如果小证明发起请求节点数据位置比当前节点新，如果当前节点没有投票给其他节点，那么设置当前节点term为请求节点的term，同时将当前节点的投票votedId设置为请求节点，表名当前节点将选票投给了请求节点,当前节点会执行stepDown *** 作，不会进行选举，节点变为STATE_FOLLOWER，同时开启electionTimer定时器
- 返回判断当前节点term是否等于请求term且当前节点的选票ID和请求节点是否一致，如果满足上面两个条件，表明当前节点将票投给了请求节点
接下来看请求节点收到响应节点的响应是如何处理的：
public void handleRequestVoteResponse(final PeerId peerId, final long term, final RequestVoteResponse response) {
this.writeLock.lock();
try {
if (this.state != State.STATE_CANDIDATE) {
LOG.warn("Node {} received invalid RequestVoteResponse from {}, state not in STATE_CANDIDATE but {}.",
getNodeId(), peerId, this.state);
return;
}
// check stale term
if (term != this.currTerm) {
LOG.warn("Node {} received stale RequestVoteResponse from {}, term={}, currTerm={}.", getNodeId(),
peerId, term, this.currTerm);
return;
}
// check response term
if (response.getTerm() > this.currTerm) {
LOG.warn("Node {} received invalid RequestVoteResponse from {}, term={}, expect={}.", getNodeId(),
peerId, response.getTerm(), this.currTerm);
stepDown(response.getTerm(), false, new Status(RaftError.EHIGHERTERMRESPONSE,
"Raft node receives higher term request_vote_response."));
return;
}
// check granted quorum?
if (response.getGranted()) {
this.voteCtx.grant(peerId);
if (this.voteCtx.isGranted()) {
becomeLeader();
}
}
} finally {
this.writeLock.unlock();
}
}
大致逻辑如下：
- 判断响应的reponse的term和当前节点发起投票前的term是否一致，如果不一致，直接返回
- 判断响应的reposen的term是否比当前节点发起投票前的term大，如果满足，直接返回
- 判断当前节点已经获取的选票是否过半，如果过半，将当前节点晋升为Leader节点，执行becomeLeader逻辑
becomeLeader使当前节点晋升为Leader节点，我们看看其实现：
private void becomeLeader() {
Requires.requireTrue(this.state == State.STATE_CANDIDATE, "Illegal state: " + this.state);
LOG.info("Node {} become leader of group, term={}, conf={}, oldConf={}.", getNodeId(), this.currTerm,
this.conf.getConf(), this.conf.getOldConf());
// cancel candidate vote timer
stopVoteTimer();
this.state = State.STATE_LEADER;
this.leaderId = this.serverId.copy();
this.replicatorGroup.resetTerm(this.currTerm);
// Start follower's replicators
for (final PeerId peer : this.conf.listPeers()) {
if (peer.equals(this.serverId)) {
continue;
}
LOG.debug("Node {} add a replicator, term={}, peer={}.", getNodeId(), this.currTerm, peer);
if (!this.replicatorGroup.addReplicator(peer)) {
LOG.error("Fail to add a replicator, peer={}.", peer);
}
}
// Start learner's replicators
for (final PeerId peer : this.conf.listLearners()) {
LOG.debug("Node {} add a learner replicator, term={}, peer={}.", getNodeId(), this.currTerm, peer);
if (!this.replicatorGroup.addReplicator(peer, ReplicatorType.Learner)) {
LOG.error("Fail to add a learner replicator, peer={}.", peer);
}
}
// init commit manager
this.ballotBox.resetPendingIndex(this.logManager.getLastLogIndex() + 1);
// Register _conf_ctx to reject configuration changing before the first log
// is committed.
if (this.confCtx.isBusy()) {
throw new IllegalStateException();
}
this.confCtx.flush(this.conf.getConf(), this.conf.getOldConf());
this.stepDownTimer.start();
}
主要逻辑为：
- 停止当前投票定时器
- 将所有非当前节点、角色为Follower的节点加入到复制组里面去
- 将所有角色为Learner的节点加入到复制组里面去
- 重置ballotBox（用来管理选票的）
- stepDownTimer启动
这样Leader节点就被选出来。
我们在看看如何写入数据的。
数据写入和复制客户端通过RouteTable.getInstance().selectLeader(groupId)能够获取当前分组下的Leader节点信息，拼接待写入数据的Request对象，然后通过CliClientServiceImpl..getRpcClient().invokeAsync(leader.getEndpoint(), request, new InvokeCallback() {}能够向集群Leader节点进行数据写入。
服务端则通过对应的RpcProcessor来处理写入的请求，获取到请求后取出数据部分封装成Task，然后通过Node.apply将task写入到node中去。
而Node.apply只是将Task写入到了Disruptor的RingBuffer中去，如果对这块有疑问，可以看看这篇文章高性能队列Disruptor使用入门，原理和代码实现
数据写入的时候，首先会将task转换成LogEntryAndClosure，同时会将Task.done相关信息放入到BallotBox的pendingmetaQueue和closureQueue队列中去（当数据写入完成之后会通过这两个queue取出task对应的done执行），然后将一批LogEntryAndClosure通过logManagerj将数据持久化写入。
这里Node.apply传入的是一个Task类型：
public class Task implements Serializable {
private static final long serialVersionUID = 2971309899898274575L;
private ByteBuffer data = LogEntry.EMPTY_DATA;
private Closure done;
private long expectedTerm = -1;
}
这里的data就是我们写入的数据，而Closure done则是一个回调接口，当数据被写入到集群1/2+1节点成功之后会调用Closure.run(final Status status)方法。
而NodeImpl中在写入Task是写入到了RingBuffer中，实际处理在LogEntryAndClosureHandler中：
public void onEvent(final LogEntryAndClosure event, final long sequence, final boolean endOfBatch)
throws Exception {
if (event.shutdownLatch != null) {
if (!this.tasks.isEmpty()) {
executeApplyingTasks(this.tasks);
reset();
}
final int num = GLOBAL_NUM_NODES.decrementAndGet();
event.shutdownLatch.countDown();
return;
}
this.tasks.add(event);
if (this.tasks.size() >= NodeImpl.this.raftOptions.getApplyBatch() || endOfBatch) {
executeApplyingTasks(this.tasks);
reset();
}
}
最终在executeApplyingTasks进行实际写入，这块代码有点长，就不贴代码了，大概描述下：
- 首先判断当前节点是不是Leader节点，如果不是的话，Closure.run(错误状态）返回
- task的term和当前节点term不一致，同上，返回
- 调用BallotBoxappendPendingTask，这个逻辑需要注意下：
public boolean appendPendingTask(final Configuration conf, final Configuration oldConf, final Closure done) {
// 每个写入Task都生成一个Ballot ，并放入pendingmetaQueue，后续其他
final Ballot bl = new Ballot();
if (!bl.init(conf, oldConf)) {
LOG.error("Fail to init ballot.");
return false;
}
final long stamp = this.stampedLock.writeLock();
try {
if (this.pendingIndex <= 0) {
LOG.error("Fail to appendingTask, pendingIndex={}.", this.pendingIndex);
return false;
}
this.pendingmetaQueue.add(bl);
this.closureQueue.appendPendingClosure(done);
return true;
} finally {
this.stampedLock.unlockWrite(stamp);
}
}
这里为每个写入任务都生成了一个Ballot,还记得上面选主投票的时候，用的也是这个来标记选举是否过半，这里也是一样，后续其他节点复制Leader该Task的数据的时候，会对应更新Leader中对应该Task的Ballot 投票信息，通过该Ballot 能够判断集群是否有过半节点已经完成了该Task的写入。同时也将Task写入集群过半节点成功之后的回调入口Closure 保存在closureQueue中，当其他节点写入Task成功更新对应Task的Ballot 的时候，会判断是否过半节点写入成功，如果成功则会回调对应Task的Closure的run方法。
4. 调用logManager.appendEntries将数据写入
5. 本地节点写入完成之后，回调LeaderStableClosure接口，逻辑为：
public void run(final Status status) {
if (status.isOk()) {
NodeImpl.this.ballotBox.commitAt(this.firstLogIndex, this.firstLogIndex + this.nEntries - 1,
NodeImpl.this.serverId);
} else {
this.firstLogIndex + this.nEntries - 1, status);
}
}
而ballotBox.commitAt的逻辑如下：
public boolean commitAt(final long firstLogIndex, final long lastLogIndex, final PeerId peer) {
final long stamp = this.stampedLock.writeLock();
long lastCommittedIndex = 0;
try {
if (this.pendingIndex == 0) {
return false;
}
if (lastLogIndex < this.pendingIndex) {
return true;
}
final long startAt = Math.max(this.pendingIndex, firstLogIndex);
Ballot.PosHint hint = new Ballot.PosHint();
for (long logIndex = startAt; logIndex <= lastLogIndex; logIndex++) {
final Ballot bl = this.pendingmetaQueue.get((int) (logIndex - this.pendingIndex));
hint = bl.grant(peer, hint);
if (bl.isGranted()) {
lastCommittedIndex = logIndex;
}
}
if (lastCommittedIndex == 0) {
return true;
}
this.pendingmetaQueue.removeFromFirst((int) (lastCommittedIndex - this.pendingIndex) + 1);
this.pendingIndex = lastCommittedIndex + 1;
this.lastCommittedIndex = lastCommittedIndex;
} finally {
this.stampedLock.unlockWrite(stamp);
}
this.waiter.onCommitted(lastCommittedIndex);
return true;
}
这里可以看到，就是每个节点写入成功后，调用Leader节点的.ballotBox.commitAt，更新对应写入数据的投票信息，如果bl.isGranted，即完成了过半节点的写入，那么会调用this.waiter.onCommitted逻辑，这里最终会调用到StateMachineAdapter.onApply方法。
6. 在节点成为Leader的时候，会初始化日志复制组：this.replicatorGroup.addReplicator(peer),对于集群中的每个除当前节点的节点都会启动一个Replicator进行复制同时会开启心跳超时定时器，开始的时候首先会发送一个空的EmptyEntries给到Follower，获取Follower节点的最新日志位置，获取到Follower节点的最新日志位置之后，会再次发送需要同步的日志
7. 在Replicator中对Follower的响应进行处理onAppendEntriesReturned，如果Follower写入成功，会调用Node.BallotBox().commitAt 这里和步骤5处理一样
这样就完成了数据的写入和日志的复制。
可以看到jraft中的日志复制就是Leader向Follower节点发送数据然后Follower将发送的日志写入到本地。
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