ZK介绍
ZK = zookeeper
ZK是微服务解决方案中拥有服务注册发现最为核心的环境，是微服务的基石。作为服务注册发现模块，并不是只有ZK一种产品，目前得到行业认可的还有：Eureka、Consul。
这里我们只聊ZK，这个工具本身很小zip包就几兆，安装非常傻瓜，能够支持集群部署。
官网地址：https://zookeeper.apache.org/
背景
在集群环境下ZK的leader&follower的概念，已经节点异常ZK面临的问题以及如何解决。ZK本身是java语言开发，也开源到Github上但官方文档对内部介绍的很少，零散的博客很多，有些写的很不错。
提问：
- zookeeper选举算法中的过半票数才提供正常服务，这是什么逻辑？
ZK集群单节点状态（每个节点有且只有一个状态），ZK的定位一定需要一个leader节点处于lading状态。
- looking：寻找leader状态，当前集群没有leader，进入leader选举流程。
- following：跟随者状态，接受leading节点同步和指挥。
- leading：领导者状态。
- observing：观察者状态，表名当前服务器是observer。
ZK投票处理策略
投票信息包含 ：所选举leader的Serverid，Zxid，SelectionEpoch
- Epoch判断，自身logicEpoch与SelectionEpoch判断：大于、小于、等于。
- 优先检查ZXID。ZXID比较大的服务器优先作为Leader。
- 如果ZXID相同，那么就比较myid。myid较大的服务器作为Leader服务器。
过半选举算法
ZK中有三种选举算法，分别是LeaderElection,FastLeaderElection,AuthLeaderElection，FastLeaderElection和AuthLeaderElection是类似的选举算法，唯一区别是后者加入了认证信息， FastLeaderElection比LeaderElection更高效，后续的版本只保留FastLeaderElection。
理解：
在集群环境下多个节点启动，ZK首先需要在多个节点中选出一个节点作为leader并处于Leading状态，这样就面临一个选举问题，同时选举规则是什么样的。“过半选举算法”：投票选举中获得票数过半的节点胜出，即状态从looking变为leading，效率更高。
官网资料描述：Clustered (Multi-Server) Setup，如下图：
image
As long as a majority of the ensemble are up, the service will be available. Because Zookeeper requires a majority, it is best to use an odd number of machines. For example, with four machines ZooKeeper can only handle the failure of a single machine; if two machines fail, the remaining two machines do not constitute a majority. However, with five machines ZooKeeper can handle the failure of two machines.
以5台服务器讲解思路：
- 服务器1启动,此时只有它一台服务器启动了,它发出去的Vote没有任何响应,所以它的选举状态一直是LOOKING状态；
- 服务器2启动,它与最开始启动的服务器1进行通信,互相交换自己的选举结果,由于两者都没有历史数据,所以id值较大的服务器2胜出,但是由于没有达到超过半数以上的服务器都同意选举它(这个例子中的半数以上是3),所以服务器1,2还是继续保持LOOKING状态.
- 服务器3启动,根据前面的理论，分析有三台服务器选举了它,服务器3成为服务器1,2,3中的老大,所以它成为了这次选举的leader.
- 服务器4启动,根据前面的分析，理论上服务器4应该是服务器1,2,3,4中最大的,但是由于前面已经有半数以上的服务器选举了服务器3,所以它只能接收当小弟的命了.
- 服务器5启动,同4一样,当小弟.
假设5台中挂了2台（3、4），其中leader也挂掉：
leader和follower间有检查心跳，需要同步数据 Leader节点挂了，整个Zookeeper集群将暂停对外服务，进入新一轮Leader选举
1）服务器1、2、5发现与leader失联，状态转为looking，开始新的投票 2）服务器1、2、5分别开始投票并广播投票信息，自身Epoch自增； 3) 服务器1、2、5分别处理投票，判断出leader分别广播 4）根据投票处理逻辑会选出一台（2票过半） 5）各自服务器重新变更为leader、follower状态 6）重新提供服务
源码解析：
URL: FastLeaderElection
/**
* Starts a new round of leader election. Whenever our QuorumPeer
* changes its state to LOOKING, this method is invoked, and it
* sends notifications to all other peers.
*/
public Vote lookForLeader() throws InterruptedException {
try {
self.jmxLeaderElectionBean = new LeaderElectionBean();
MBeanRegistry.getInstance().register(self.jmxLeaderElectionBean, self.jmxLocalPeerBean);
} catch (Exception e) {
LOG.warn("Failed to register with JMX", e);
self.jmxLeaderElectionBean = null;
}
self.start_fle = Time.currentElapsedTime();
try {
Map recvset = new HashMap();
Map outofelection = new HashMap();
int notTimeout = minNotificationInterval;
synchronized (this) {
logicalclock.incrementAndGet();
updateProposal(getInitId(), getInitLastLoggedZxid(), getPeerEpoch());
}
LOG.info("New election. My id = " + self.getId() + ", proposed zxid=0x" + Long.toHexString(proposedZxid));
sendNotifications();
SyncedLearnerTracker voteSet;
/*
* Loop in which we exchange notifications until we find a leader
*/
while ((self.getPeerState() == ServerState.LOOKING) && (!stop)) {
/*
* Remove next notification from queue, times out after 2 times
* the termination time
*/
Notification n = recvqueue.poll(notTimeout, TimeUnit.MILLISECONDS);
/*
* Sends more notifications if haven't received enough.
* Otherwise processes new notification.
*/
if (n == null) {
if (manager.haveDelivered()) {
sendNotifications();
} else {
manager.connectAll();
}
/*
* Exponential backoff
*/
int tmpTimeOut = notTimeout * 2;
notTimeout = (tmpTimeOut < maxNotificationInterval ? tmpTimeOut : maxNotificationInterval);
LOG.info("Notification time out: " + notTimeout);
} else if (validVoter(n.sid) && validVoter(n.leader)) {
/*
* Only proceed if the vote comes from a replica in the current or next
* voting view for a replica in the current or next voting view.
*/
switch (n.state) {
case LOOKING:
if (getInitLastLoggedZxid() == -1) {
LOG.debug("Ignoring notification as our zxid is -1");
break;
}
if (n.zxid == -1) {
LOG.debug("Ignoring notification from member with -1 zxid {}", n.sid);
break;
}
// If notification > current, replace and send messages out
if (n.electionEpoch > logicalclock.get()) {
logicalclock.set(n.electionEpoch);
recvset.clear();
if (totalOrderPredicate(n.leader, n.zxid, n.peerEpoch, getInitId(), getInitLastLoggedZxid(), getPeerEpoch())) {
updateProposal(n.leader, n.zxid, n.peerEpoch);
} else {
updateProposal(getInitId(), getInitLastLoggedZxid(), getPeerEpoch());
}
sendNotifications();
} else if (n.electionEpoch < logicalclock.get()) {
if (LOG.isDebugEnabled()) {
LOG.debug(
"Notification election epoch is smaller than logicalclock. n.electionEpoch = 0x" + Long.toHexString(n.electionEpoch)
+ ", logicalclock=0x" + Long.toHexString(logicalclock.get()));
}
break;
} else if (totalOrderPredicate(n.leader, n.zxid, n.peerEpoch, proposedLeader, proposedZxid, proposedEpoch)) {
updateProposal(n.leader, n.zxid, n.peerEpoch);
sendNotifications();
}
if (LOG.isDebugEnabled()) {
LOG.debug("Adding vote: from=" + n.sid
+ ", proposed leader=" + n.leader
+ ", proposed zxid=0x" + Long.toHexString(n.zxid)
+ ", proposed election epoch=0x" + Long.toHexString(n.electionEpoch));
}
// don't care about the version if it's in LOOKING state
recvset.put(n.sid, new Vote(n.leader, n.zxid, n.electionEpoch, n.peerEpoch));
voteSet = getVoteTracker(recvset, new Vote(proposedLeader, proposedZxid, logicalclock.get(), proposedEpoch));
if (voteSet.hasAllQuorums()) {
// Verify if there is any change in the proposed leader
while ((n = recvqueue.poll(finalizeWait, TimeUnit.MILLISECONDS)) != null) {
if (totalOrderPredicate(n.leader, n.zxid, n.peerEpoch, proposedLeader, proposedZxid, proposedEpoch)) {
recvqueue.put(n);
break;
}
}
/*
* This predicate is true once we don't read any new
* relevant message from the reception queue
*/
if (n == null) {
setPeerState(proposedLeader, voteSet);
Vote endVote = new Vote(proposedLeader, proposedZxid, logicalclock.get(), proposedEpoch);
leaveInstance(endVote);
return endVote;
}
}
break;
case OBSERVING:
LOG.debug("Notification from observer: {}", n.sid);
break;
case FOLLOWING:
case LEADING:
/*
* Consider all notifications from the same epoch
* together.
*/
if (n.electionEpoch == logicalclock.get()) {
recvset.put(n.sid, new Vote(n.leader, n.zxid, n.electionEpoch, n.peerEpoch));
voteSet = getVoteTracker(recvset, new Vote(n.version, n.leader, n.zxid, n.electionEpoch, n.peerEpoch, n.state));
if (voteSet.hasAllQuorums() && checkLeader(outofelection, n.leader, n.electionEpoch)) {
setPeerState(n.leader, voteSet);
Vote endVote = new Vote(n.leader, n.zxid, n.electionEpoch, n.peerEpoch);
leaveInstance(endVote);
return endVote;
}
}
/*
* Before joining an established ensemble, verify that
* a majority are following the same leader.
*/
outofelection.put(n.sid, new Vote(n.version, n.leader, n.zxid, n.electionEpoch, n.peerEpoch, n.state));
voteSet = getVoteTracker(outofelection, new Vote(n.version, n.leader, n.zxid, n.electionEpoch, n.peerEpoch, n.state));
if (voteSet.hasAllQuorums() && checkLeader(outofelection, n.leader, n.electionEpoch)) {
synchronized (this) {
logicalclock.set(n.electionEpoch);
setPeerState(n.leader, voteSet);
}
Vote endVote = new Vote(n.leader, n.zxid, n.electionEpoch, n.peerEpoch);
leaveInstance(endVote);
return endVote;
}
break;
default:
LOG.warn("Notification state unrecoginized: " + n.state + " (n.state), " + n.sid + " (n.sid)");
break;
}
} else {
if (!validVoter(n.leader)) {
LOG.warn("Ignoring notification for non-cluster member sid {} from sid {}", n.leader, n.sid);
}
if (!validVoter(n.sid)) {
LOG.warn("Ignoring notification for sid {} from non-quorum member sid {}", n.leader, n.sid);
}
}
}
return null;
} finally {
try {
if (self.jmxLeaderElectionBean != null) {
MBeanRegistry.getInstance().unregister(self.jmxLeaderElectionBean);
}
} catch (Exception e) {
LOG.warn("Failed to unregister with JMX", e);
}
self.jmxLeaderElectionBean = null;
LOG.debug("Number of connection processing threads: {}", manager.getConnectionThreadCount());
}
}
/*
* We return true if one of the following three cases hold:
* 1- New epoch is higher
* 2- New epoch is the same as current epoch, but new zxid is higher
* 3- New epoch is the same as current epoch, new zxid is the same
* as current zxid, but server id is higher.
*/
return ((newEpoch > curEpoch)
|| ((newEpoch == curEpoch)
&& ((newZxid > curZxid)
|| ((newZxid == curZxid)
&& (newId > curId)))));
脑裂问题
脑裂问题出现在集群中leader死掉，follower选出了新leader而原leader又复活了的情况下，因为ZK的过半机制是允许损失一定数量的机器而扔能正常提供给服务，当leader死亡判断不一致时就会出现多个leader。
方案：
ZK的过半机制一定程度上也减少了脑裂情况的出现，起码不会出现三个leader同时。ZK中的Epoch机制（时钟）每次选举都是递增+1，当通信时需要判断epoch是否一致，小于自己的则抛弃，大于自己则重置自己，等于则选举；
// If notification > current, replace and send messages out
if (n.electionEpoch > logicalclock.get()) {
logicalclock.set(n.electionEpoch);
recvset.clear();
if (totalOrderPredicate(n.leader, n.zxid, n.peerEpoch, getInitId(), getInitLastLoggedZxid(), getPeerEpoch())) {
updateProposal(n.leader, n.zxid, n.peerEpoch);
} else {
updateProposal(getInitId(), getInitLastLoggedZxid(), getPeerEpoch());
}
sendNotifications();
} else if (n.electionEpoch < logicalclock.get()) {
if (LOG.isDebugEnabled()) {
LOG.debug(
"Notification election epoch is smaller than logicalclock. n.electionEpoch = 0x" + Long.toHexString(n.electionEpoch)
+ ", logicalclock=0x" + Long.toHexString(logicalclock.get()));
}
break;
} else if (totalOrderPredicate(n.leader, n.zxid, n.peerEpoch, proposedLeader, proposedZxid, proposedEpoch)) {
updateProposal(n.leader, n.zxid, n.peerEpoch);
sendNotifications();
}
归纳
在日常的ZK运维时需要注意以上场景在极端情况下出现问题，特别是脑裂的出现，可以采用：
过半选举策略下部署原则：
- 服务器群部署要单数，如：3、5、7、...，单数是最容易选出leader的配置量。
- ZK允许节点最大损失数，原则就是“保证过半选举正常”，多了就是浪费。
详细的算法逻辑是很复杂要考虑很多情况，其中有个Epoch的概念（自增长），分为：LogicEpoch和ElectionEpoch，每次投票都有判断每个投票周期是否一致等等。
在思考ZK策略时经常遇到这样的问题（上文中两块），梳理了一下思路以便于理解也作为后续回顾，特别感谢下面几篇博文的支持，感谢分享；
作者：Owen Jia
可以关注他的博客：Owen Blog