Zookeeper源码集群启动
使用集群模式,就是多添加几个Zookeeper节点。需要添加对应的配置文件,启动了集群模式才好去分析分布式环境下的leader的选举等源码
集群模式启动
集群模式下启动和单机启动有相似的地方,但是也有各自的特点。集群模式的配置方式和单机模式也是不一样的
新增Zookeeper配置文件
新增集群配置文件 /zoo_sample.cfg 修改每个/zoo_sample.cfg配置文件,具体修改内容如下,不同的服务使用不同的clientPort端口
/zoo_sample1.cfg
tickTime=2000
initLimit=10
syncLimit=5
dataDir=D:\\zookeeper\\data1
clientPort=2181
server.1=127.0.0.1:2888:3888
server.2=127.0.0.1:2889:3889
server.3=127.0.0.1:2890:3890
admin.serverPort=8081
/zoo_sample2.cfg
tickTime=2000
initLimit=10
syncLimit=5
dataDir=D:\\zookeeper\\data2
clientPort=2182
server.1=127.0.0.1:2888:3888
server.2=127.0.0.1:2889:3889
server.3=127.0.0.1:2890:3890
admin.serverPort=8082
/zoo_sample3.cfg
tickTime=2000
initLimit=10
syncLimit=5
dataDir=D:\\zookeeper\\data3
clientPort=2183
server.1=127.0.0.1:2888:3888
server.2=127.0.0.1:2889:3889
server.3=127.0.0.1:2890:3890
admin.serverPort=8083
为啥需要添加admin.serverPort? 查阅Zookeeper3.5的官方文档,发现这是Zookeeper3.5的新特性 这是Zookeeper AdminServer,默认使用8080端口,如果不配置启动集群时,会报端口冲突错误。
新增Zookeeper数据文件
修改数据文件/zookeeper/data*文件 在每个数据目录下创建myid文件,文件内容分别写入1、2、3
创建集群启动
zk服务端的启动入口是QuorumPeerMain类中的main方法
如果不配置的话,无法输出日志
VM options:
-Dlog4j.configuration=file:conf\log4j.properties
Program arguments:
conf\zoo_sample.cfg
创建多个集群启动,配置文件分别加载zoo_sample1.cfg,zoo_sample2.cfg,zoo_sample3.cfg 依次启动即可。
启动日志分析
启动第一个节点 ,会报错,因为其他两个节点还没启动,连接报错 Cannot open channel to 3 at election address /127.0.0.1:3890
[QuorumPeerListener:QuorumCnxManager$Listener@929] - 1 is accepting connections now, my election bind port: /127.0.0.1:3888
[QuorumPeer[myid=1](plain=[0:0:0:0:0:0:0:0]:2181)(secure=disabled):QuorumPeer@1178] - LOOKING
[QuorumPeer[myid=1](plain=[0:0:0:0:0:0:0:0]:2181)(secure=disabled):FastLeaderElection@903] - New election. My id = 1, proposed zxid=0x0
[WorkerReceiver[myid=1]:FastLeaderElection@697] - Notification: 2 (message format version), 1 (n.leader), 0x0 (n.zxid), 0x1 (n.round), LOOKING (n.state), 1 (n.sid), 0x4 (n.peerEPoch), LOOKING (my state)0 (n.config version)
[QuorumPeer[myid=1](plain=[0:0:0:0:0:0:0:0]:2181)(secure=disabled):FastLeaderElection@937] - Notification time out: 400
[QuorumPeer[myid=1](plain=[0:0:0:0:0:0:0:0]:2181)(secure=disabled):FastLeaderElection@937] - Notification time out: 800
[QuorumPeer[myid=1](plain=[0:0:0:0:0:0:0:0]:2181)(secure=disabled):FastLeaderElection@937] - Notification time out: 1600
[QuorumConnectionThread-[myid=1]-2:QuorumCnxManager@381] - Cannot open channel to 3 at election address /127.0.0.1:3890
启动第二个节点后,节点正常了, 此时经过选举将节点二选举为leader节点,节点1为follower
[main:QuorumCnxManager$Listener@878] - Election port bind maximum retries is 3
[QuorumPeerListener:QuorumCnxManager$Listener@929] - 2 is accepting connections now, my election bind port: /127.0.0.1:3889
[QuorumPeer[myid=2](plain=[0:0:0:0:0:0:0:0]:2182)(secure=disabled):QuorumPeer@1178] - LOOKING
[QuorumPeer[myid=2](plain=[0:0:0:0:0:0:0:0]:2182)(secure=disabled):FastLeaderElection@903] - New election. My id = 2, proposed zxid=0x0
[WorkerReceiver[myid=2]:FastLeaderElection@697] - Notification: 2 (message format version), 2 (n.leader), 0x0 (n.zxid), 0x1 (n.round), LOOKING (n.state), 2 (n.sid), 0x5 (n.peerEPoch), LOOKING (my state)0 (n.config version)
[WorkerReceiver[myid=2]:FastLeaderElection@697] - Notification: 2 (message format version), 1 (n.leader), 0x0 (n.zxid), 0x1 (n.round), LOOKING (n.state), 1 (n.sid), 0x5 (n.peerEPoch), LOOKING (my state)0 (n.config version)
[WorkerReceiver[myid=2]:FastLeaderElection@697] - Notification: 2 (message format version), 2 (n.leader), 0x0 (n.zxid), 0x1 (n.round), LOOKING (n.state), 1 (n.sid), 0x5 (n.peerEPoch), LOOKING (my state)0 (n.config version)
[QuorumPeer[myid=2](plain=[0:0:0:0:0:0:0:0]:2182)(secure=disabled):QuorumPeer@1266] - LEADING
节点1为follower
[WorkerReceiver[myid=1]:FastLeaderElection@697] - Notification: 2 (message format version), 2 (n.leader), 0x0 (n.zxid), 0x1 (n.round), LOOKING (n.state), 2 (n.sid), 0x5 (n.peerEPoch), LOOKING (my state)0 (n.config version)
[WorkerReceiver[myid=1]:FastLeaderElection@697] - Notification: 2 (message format version), 2 (n.leader), 0x0 (n.zxid), 0x1 (n.round), LOOKING (n.state), 1 (n.sid), 0x5 (n.peerEPoch), LOOKING (my state)0 (n.config version)
[QuorumPeer[myid=1](plain=[0:0:0:0:0:0:0:0]:2181)(secure=disabled):QuorumPeer@1254] - FOLLOWING
[QuorumPeer[myid=1](plain=[0:0:0:0:0:0:0:0]:2181)(secure=disabled):Learner@91] - TCP NoDelay set to: true
启动第三个节点后, 加入到集群,节点三的同样也是follower节点
[QuorumPeer[myid=3](plain=[0:0:0:0:0:0:0:0]:2183)(secure=disabled):ZooKeeperServer@181] - Created server with tickTime 2000 minSessionTimeout 4000 maxSessionTimeout 40000 datadir D:\zookeeper\data3\version-2 snapdir D:\zookeeper\data3\version-2
[QuorumPeer[myid=3](plain=[0:0:0:0:0:0:0:0]:2183)(secure=disabled):Follower@69] - FOLLOWING - LEADER ELECTION TOOK - 52 MS
[QuorumPeer[myid=3](plain=[0:0:0:0:0:0:0:0]:2183)(secure=disabled):Learner@395] - Getting a snapshot from leader 0x600000000
[QuorumPeer[myid=3](plain=[0:0:0:0:0:0:0:0]:2183)(secure=disabled):Learner@546] - Learner received NEWLEADER message
[QuorumPeer[myid=3](plain=[0:0:0:0:0:0:0:0]:2183)(secure=disabled):QuorumPeer@1590] - Dynamic reconfig is disabled, we don't store the last seen config.
[QuorumPeer[myid=3](plain=[0:0:0:0:0:0:0:0]:2183)(secure=disabled):FileTxnSnapLog@404] - Snapshotting: 0x600000000 to D:\zookeeper\data3\version-2\snapshot.600000000
[QuorumPeer[myid=3](plain=[0:0:0:0:0:0:0:0]:2183)(secure=disabled):Learner@529] - Learner received UPTODATE message
Zookeeper集群概念介绍
集群模式会有多台server,每台server根据不同的角色会有不同的状态,server状态的定义如下
public enum ServerState {
LOOKING, FOLLOWING, LEADING, OBSERVING;
}
LOOKING:表示服务器处于选举状态,说明集群正在进行投票选举,选出leader
FOLLOWING:表示服务器处于following状态,表示当前server的角色是follower
LEADING:表示服务器处于leading状态,当前server角色是leader
OBSERVING:表示服务器处于OBSERVING状态,当前server角色是OBSERVER
leader
投票选出的leader,可以处理读写请求。处理写请求的时候收集各个参与投票者的选票,来决出投票结果
follower
作用:
- 参与leader选举,可能被选为leader
- 接收处理读请求
- 接收写请求,转发给leader,并参与投票决定写操作是否提交
observer
为了支持zk集群可扩展性,如果直接增加follower的数量,会导致投票的性能下降。也就是防止参与投票的server太多,导致leader选举收敛速度较慢,选举所需时间过长。
observer和follower类似,但是不参与选举和投票,
- 接收处理读请求
- 接收写请求,转发给leader,但是不参与投票,接收leader的投票结果,同步数据
这样在支持集群可扩展性的同时又不会影响投票的性能
Zookeeper源码启动流程
从源码的角度分析ZooKeeper集群启动过程以及关于集群的一些知识。
启动入口
我们需要首先找到zookeeper集群启动入口,然后研究Zookeeper集群是如何启动的?Zookeeper集群启动入口是org.apache.zookeeper.server.quorum.QuorumPeerMain#main
public static void main(String[] args) {
// 初始化 QuorumPeerMain
QuorumPeerMain main = new QuorumPeerMain();
try {
// 加载配置文件并执行
main.initializeAndRun(args);
} catch (IllegalArgumentException e) {
LOG.error("Invalid arguments, exiting abnormally", e);
LOG.info(USAGE);
System.err.println(USAGE);
System.exit(2);
} catch (ConfigException e) {
LOG.error("Invalid config, exiting abnormally", e);
System.err.println("Invalid config, exiting abnormally");
System.exit(2);
} catch (DatadirException e) {
LOG.error("Unable to access datadir, exiting abnormally", e);
System.err.println("Unable to access datadir, exiting abnormally");
System.exit(3);
} catch (AdminServerException e) {
LOG.error("Unable to start AdminServer, exiting abnormally", e);
System.err.println("Unable to start AdminServer, exiting abnormally");
System.exit(4);
} catch (Exception e) {
LOG.error("Unexpected exception, exiting abnormally", e);
System.exit(1);
}
LOG.info("Exiting normally");
System.exit(0);
}
QuorumPeerMain的Main方法很简单,就是初始化QuorumPeerMain对象,然后加载配置文件并执行。
加载配置文件并执行
通过initializeAndRun方法,我们可以了解到Zookeeper初始化配置文件并执行,无论是Zookeeper单机版还是集群模式都是调用的同一个方法。那么Zookeeper是如何判断是单机还是集群的呢?
protected void initializeAndRun(String[] args)
throws ConfigException, IOException, AdminServerException
{
// 初始化配置
QuorumPeerConfig config = new QuorumPeerConfig();
// 如果参数格式是1个,解析参数
if (args.length == 1) {
config.parse(args[0]);
}
// Start and schedule the the purge task
DatadirCleanupManager purgeMgr = new DatadirCleanupManager(config
.getDataDir(), config.getDataLogDir(), config
.getSnapRetainCount(), config.getPurgeInterval());
purgeMgr.start();
if (args.length == 1 && config.isDistributed()) {
runFromConfig(config);
} else {
LOG.warn("Either no config or no quorum defined in config, running "
+ " in standalone mode");
// there is only server in the quorum -- run as standalone
ZooKeeperServerMain.main(args);
}
}
initializeAndRun
方法执行逻辑如下:
- 初始化配置配置类QuorumPeerConfig,初始化默认是单机模式
- 如果传入的参数是1个,例如
\zookeeper\conf\zoo_sample1.cfg
,说明传入的参数是配置文件。那么解析配置文件判断当前配置是单机还是集群。 - 启动清理文件的线程
- 通过判断,说明是集群启动还是单机启动。最后进行程序的启动,因为Zookeeper分为单机和集群模式,所以分为两种不同的启动方式,当zoo.cfg文件中配置了standaloneEnabled=true为单机模式,如果配置server.0,server.1……集群节点,则为集群模式.
如果是集群启动模式,执行
runFromConfig(config);
,单机执行ZooKeeperServerMain.main(args);
加载配置文件并判断单机还是集群
加载配置文件调用org.apache.zookeeper.server.quorum.QuorumPeerConfig#parse
。
public void parse(String path) throws ConfigException {
LOG.info("Reading configuration from: " + path);
try {
File configFile = (new VerifyingFileFactory.Builder(LOG)
.warnForRelativePath()
.failForNonExistingPath()
.build()).create(path);
Properties cfg = new Properties();
FileInputStream in = new FileInputStream(configFile);
try {
cfg.load(in);
configFileStr = path;
} finally {
in.close();
}
parseProperties(cfg);
} catch (IOException e) {
throw new ConfigException("Error processing " + path, e);
} catch (IllegalArgumentException e) {
throw new ConfigException("Error processing " + path, e);
}
if (dynamicConfigFileStr!=null) {
try {
Properties dynamicCfg = new Properties();
FileInputStream inConfig = new FileInputStream(dynamicConfigFileStr);
try {
dynamicCfg.load(inConfig);
if (dynamicCfg.getProperty("version") != null) {
throw new ConfigException("dynamic file shouldn't have version inside");
}
String version = getVersionFromFilename(dynamicConfigFileStr);
// If there isn't any version associated with the filename,
// the default version is 0.
if (version != null) {
dynamicCfg.setProperty("version", version);
}
} finally {
inConfig.close();
}
setupQuorumPeerConfig(dynamicCfg, false);
} catch (IOException e) {
throw new ConfigException("Error processing " + dynamicConfigFileStr, e);
} catch (IllegalArgumentException e) {
throw new ConfigException("Error processing " + dynamicConfigFileStr, e);
}
......
解析配置文件流程如下:
- 加载配置文件绝对路径,通过
load
解析为Properties,将参数解析为Key,Value方式。 2.
解析配置Properties
当dynamicConfigFileStr为空,解析配置信息
public void parseProperties(Properties zkProp)
throws IOException, ConfigException {
......
if (dynamicConfigFileStr == null) {
setupQuorumPeerConfig(zkProp, true);
if (isDistributed() && isReconfigEnabled()) {
// we don't backup static config for standalone mode.
// we also don't backup if reconfig feature is disabled.
backupOldConfig();
}
}
}
解析方法如下
void setupQuorumPeerConfig(Properties prop, boolean configBackwardCompatibilityMode)
throws IOException, ConfigException {
quorumVerifier = parseDynamicConfig(prop, electionAlg, true, configBackwardCompatibilityMode);
setupMyId();
setupClientPort();
setupPeerType();
checkValidity();
}
- 解析配置文件,获取quorumVerifier对象
- 设置MyId
- 解析ClietPort
- 解析PeerType
判断是否是分布式集群方法
public boolean isDistributed() {
return quorumVerifier!=null && (!standaloneEnabled || quorumVerifier.getVotingMembers().size() > 1);
}
解析集群如果配置server.0,server.1……集群节点,则为集群模式.将数据设置到private Map<Long, QuorumServer> allMembers = new HashMap<Long, QuorumServer>();
中,
其中Key为myid,值为Zookeeper服务器节点QuorumServer
public QuorumMaj(Properties props) throws ConfigException {
for (Entry<Object, Object> entry : props.entrySet()) {
String key = entry.getKey().toString();
String value = entry.getValue().toString();
if (key.startsWith("server.")) {
int dot = key.indexOf('.');
long sid = Long.parseLong(key.substring(dot + 1));
QuorumServer qs = new QuorumServer(sid, value);
allMembers.put(Long.valueOf(sid), qs);
if (qs.type == LearnerType.PARTICIPANT)
votingMembers.put(Long.valueOf(sid), qs);
else {
observingMembers.put(Long.valueOf(sid), qs);
}
} else if (key.equals("version")) {
version = Long.parseLong(value, 16);
}
}
half = votingMembers.size() / 2;
}
Zookeeper server节点信息
Zookeeper主程序QuorumPeerMain加载配置文件后,配置容器对象QuorumPeerConfig中持有一个QuorumVerifier对象,该对象会存储其他Zookeeper server节点信息,如果zoo.cfg中配置了server.*节点信息,会实例化一个QuorumVeriferi对象。
public interface QuorumVerifier {
long getWeight(long id);
boolean containsQuorum(Set<Long> set);
long getVersion();
void setVersion(long ver);
Map<Long, QuorumServer> getAllMembers();
Map<Long, QuorumServer> getVotingMembers();
Map<Long, QuorumServer> getObservingMembers();
boolean equals(Object o);
String toString();
}
实现类
public class QuorumMaj implements QuorumVerifier {
private Map<Long, QuorumServer> allMembers = new HashMap<Long, QuorumServer>();
private HashMap<Long, QuorumServer> votingMembers = new HashMap<Long, QuorumServer>();
private HashMap<Long, QuorumServer> observingMembers = new HashMap<Long, QuorumServer>();
private long version = 0;
//这里的half就是过半提交一个比较关键的点
private int half;
}
其中AllMembers = VotingMembers + ObservingMembers, AllMembers代表所有的Zookeeper节点。VotingMembers表示参与选举的节点。half代表参与投票的半数。
// 该构造方法遍历配置文件的server.N,将连接信息构造成一个QuorumServer对象,放到allMembers、votingMembers集合中
public QuorumMaj(Properties props) throws ConfigException {
for (Entry<Object, Object> entry : props.entrySet()) {
String key = entry.getKey().toString();
String value = entry.getValue().toString();
//QuorumServer格式: server.1=127.0.0.1:2888:3888
if (key.startsWith("server.")) {
int dot = key.indexOf('.');
long sid = Long.parseLong(key.substring(dot + 1));
QuorumServer qs = new QuorumServer(sid, value);
allMembers.put(Long.valueOf(sid), qs);
// qs.type 默认就是LearnerType.PARTICIPANT
if (qs.type == LearnerType.PARTICIPANT)
votingMembers.put(Long.valueOf(sid), qs);
else {
observingMembers.put(Long.valueOf(sid), qs);
}
} else if (key.equals("version")) {
version = Long.parseLong(value, 16);
}
}
// 过半提交 half = votingMembers.size() / 2;
half = votingMembers.size() / 2;
}
如果quorumVerifier.getVotingMembers().size() > 1 则使用集群模式启动。调用runFromConfig(QuorumPeerConfig config),同时会实例化ServerCnxnFactory 对象,初始化一个QuorumPeer对象。
初始化QuorumPeer对象
public void runFromConfig(QuorumPeerConfig config)
throws IOException, AdminServerException
{
try {
// 注册jmx
ManagedUtil.registerLog4jMBeans();
} catch (JMException e) {
LOG.warn("Unable to register log4j JMX control", e);
}
LOG.info("Starting quorum peer, myid=" + config.getServerId());
try {
ServerCnxnFactory cnxnFactory = null;
ServerCnxnFactory secureCnxnFactory = null;
// 配置客户端连接端口
if (config.getClientPortAddress() != null) {
//默认使用NIOServerCnxnFactory连接工厂,反射创建实例
cnxnFactory = ServerCnxnFactory.createFactory();
cnxnFactory.configure(config.getClientPortAddress(),
config.getMaxClientCnxns(),
false);
}
// 配置安全连接端口
if (config.getSecureClientPortAddress() != null) {
secureCnxnFactory = ServerCnxnFactory.createFactory();
secureCnxnFactory.configure(config.getSecureClientPortAddress(),
config.getMaxClientCnxns(),
true);
}
// 设置数据和快照操作
quorumPeer = getQuorumPeer();
//FileTxnSnapLog用于操作快照和事务日志的帮助类
quorumPeer.setTxnFactory(new FileTxnSnapLog(
config.getDataLogDir(),
config.getDataDir()));
quorumPeer.enableLocalSessions(config.areLocalSessionsEnabled());
quorumPeer.enableLocalSessionsUpgrading(
config.isLocalSessionsUpgradingEnabled());
//quorumPeer.setQuorumPeers(config.getAllMembers());
// 选举类型
//配置文件没设置的话,默认就是3
quorumPeer.setElectionType(config.getElectionAlg());
// server Id
quorumPeer.setMyid(config.getServerId());
quorumPeer.setTickTime(config.getTickTime());
quorumPeer.setMinSessionTimeout(config.getMinSessionTimeout());
quorumPeer.setMaxSessionTimeout(config.getMaxSessionTimeout());
quorumPeer.setInitLimit(config.getInitLimit());
quorumPeer.setSyncLimit(config.getSyncLimit());
quorumPeer.setConfigFileName(config.getConfigFilename());
// 设置zk的节点数据库
quorumPeer.setZKDatabase(new ZKDatabase(quorumPeer.getTxnFactory()));
quorumPeer.setQuorumVerifier(config.getQuorumVerifier(), false);
if (config.getLastSeenQuorumVerifier()!=null) {
quorumPeer.setLastSeenQuorumVerifier(config.getLastSeenQuorumVerifier(), false);
}
// 初始化zk数据库
quorumPeer.initConfigInZKDatabase();
quorumPeer.setCnxnFactory(cnxnFactory);
quorumPeer.setSecureCnxnFactory(secureCnxnFactory);
quorumPeer.setSslQuorum(config.isSslQuorum());
quorumPeer.setUsePortUnification(config.shouldUsePortUnification());
//设置peerType:若配置文件未指定,成员变量默认值是LearnerType.PARTICIPANT
quorumPeer.setLearnerType(config.getPeerType());
quorumPeer.setSyncEnabled(config.getSyncEnabled());
quorumPeer.setQuorumListenOnAllIPs(config.getQuorumListenOnAllIPs());
if (config.sslQuorumReloadCertFiles) {
quorumPeer.getX509Util().enableCertFileReloading();
}
// sets quorum sasl authentication configurations
quorumPeer.setQuorumSaslEnabled(config.quorumEnableSasl);
if(quorumPeer.isQuorumSaslAuthEnabled()){
quorumPeer.setQuorumServerSaslRequired(config.quorumServerRequireSasl);
quorumPeer.setQuorumLearnerSaslRequired(config.quorumLearnerRequireSasl);
quorumPeer.setQuorumServicePrincipal(config.quorumServicePrincipal);
quorumPeer.setQuorumServerLoginContext(config.quorumServerLoginContext);
quorumPeer.setQuorumLearnerLoginContext(config.quorumLearnerLoginContext);
}
quorumPeer.setQuorumCnxnThreadsSize(config.quorumCnxnThreadsSize);
// 初始化当前zk服务节点的配置
quorumPeer.initialize();
//启动
quorumPeer.start();
quorumPeer.join();
} catch (InterruptedException e) {
// warn, but generally this is ok
LOG.warn("Quorum Peer interrupted", e);
}
}
QuorumPeer为一个Zookeeper节点, QuorumPeer 为一个线程类,代表一个Zookeeper服务线程,最终会启动该线程。 runFromConfig方法中设置了一些列属性。包括选举类型、server Id、节点数据库等信息。最后通过quorumPeer.start();启动Zookeeper节点。
quorumPeer.start(); Zookeeper会首先加载本地磁盘数据,如果之前存在一些Zookeeper信息,则会加载到Zookeeper内存数据库中。通过FileTxnSnapLog中的loadDatabse();
启动Zookeeper服务器并选举
public synchronized void start() {
// 校验serverid如果不在peer列表中,抛异常
if (!getView().containsKey(myid)) {
throw new RuntimeException("My id " + myid + " not in the peer list");
}
// 加载zk数据库:载入之前持久化的一些信息
loadDataBase();
// 启动连接服务端
startServerCnxnFactory();
try {
adminServer.start();
} catch (AdminServerException e) {
LOG.warn("Problem starting AdminServer", e);
System.out.println(e);
}
// 启动之后马上进行选举,主要是创建选举必须的环境,比如:启动相关线程
startLeaderElection();
// 执行选举逻辑
super.start();
}
加载数据完之后同单机模式启动一样,会调用ServerCnxnFactory.start(),启动NIOServerCnxnFactory服务和Zookeeper服务,最后启动AdminServer服务。
与单机模式启动不同的是,集群会在启动之后马上进行选举操作,会在配置的所有Zookeeper server节点中选举出一个leader角色。startLeaderElection();
Zookeeper节点信息
serverId:服务节点Id,也就是Zookeeper dataDir中配置的myid ,server.*上指定的id。0,1,2,3,4….. ,该Id启动后不变
zxid:数据状态Id,zookeeper每次更新状态之后增加,可理解为全局有序id ,zxid越大,表示数据越新。Zxid是一个64位的数字,高32位为epoch,低32位为递增计数。
epoch:选举时钟,也可以理解为选举轮次,没进行一次选举,该值会+1;
ServerState:服务状态,Zookeeper节点角色状态,分为LOOKING、FOLLOWING、LEADING和OBSERVING,分别对应于不同的角色,当处于选举时,节点处于Looking状态。
每次投票,一个Vote会包含Zookeeper节点信息。
Zookeeper在启动之后会马上进行选举操作,不断的向其他Follower节点发送选票信息,同时也接收别的Follower发送过来的选票信息。最终每个Follower都持有共同的一个选票池,通过同样的算法选出Leader,如果当前节点选为Leader,则向其他每个Follower发送信息,如果没有则向Leader发送信息。
Zookeeper定义了Election接口;其中lookForLeader()就是选举操作。
启动peer选举策略实际启动的为fast leader 选举策略,如果peer状态为LOOKING, 创建投票(最后提交的日志id,时间戳,peerId)。
fast leader 选举策略启动时实际上启动了一个消息处理器Messenger。 消息处理器内部有一个发送消息工作线程WorkerSender,出列一个需要发送的消息,并把它放入管理器QuorumCnxManager的队列; 一个消息接收线程WorkerReceiver处理从QuorumCnxManager接收的消息。
发送消息工作线程WorkerSender,从FastLeaderElection的发送队列poll消息,并把它放入管理器QuorumCnxManager的队列,如果需要则建立消息关联的peer,并发送协议版本,服务id及选举地址, 如果连接peer的id大于 当前peer的id,则关闭连接,否则启动发送工作线程SendWorker和接收线程RecvWorker。 同时QuorumCnxManager在启动时,启动监听,监听peer的连接。发送消息线程SendWorker,从消息队列拉取消息,并通过Socket的DataOutputStream,发送给peer。
消息接收线程WorkerReceiver从QuorumCnxManager的接收队列中拉取消息,并解析出peer的状态(LOOKING, 观察,Follower,或者leader), 事务id,leaderId,leader选举时间戳,peer的时间戳等信息;如果peer不在当前投票的视图范围之内,同步当前peer的状态(构建通知消息(服务id,事务id,peer状态,时间戳等),并放到发送队列), 然后更新通知(事务id,leaderId,leader选举时间戳,peer时间戳),如果当前peer的状态为LOOKING,则添加通知消息到peer的消息接收队列,如果peer状态为LOOKING,则同步当前节点的投票信息给peer, 若果当前节点为非looker,而peer为looker,则发送当前peer相信的leader信息。
接收工作线程RecvWorker,主要是从Socket的Data输入流中读取数据,并组装成消息,放到QuorumCnxManager的消息接收队列,待消息接收线程WorkerReceiver处理。
peer状态有四种LOOKING, OBSERVING,FOLLOWING和LEADING几种状态;LOOKING为初态,Leader还没有选举成功,其他为终态。
当前QuorumPeer处于LOOKING提议投票阶段,启动一个ReadOnlyZooKeeperServer服务,并设置当前peer投票。 ReadOnlyZooKeeperServer内部的处理器链为ReadOnlyRequestProcessor->PrepRequestProcessor->FinalRequestProcessor。 ,只读处理器ReadOnlyRequestProcessor,对CRUD相关的操作,进行忽略,只处理check请求,并通过NettyServerCnxn发送ReplyHeader,头部主要的信息为内存数据库的最大事务id。
创建投票,首先更新当前的投票信息,如果peer为参与者,首先投自己一票(当前peer的serverId,最大事务id,以及时间戳),并发送通知到所有投票peer; 如果peer状态为LOOKING,且选举没有结束,则从接收消息队列拉取通知, 如果通知为空,则发送投票提议通知到所有投票peer, 否则判断下一轮投票视图是否包括当前通知的server和提议leader, 则判断peer的状态(LOOKING,OBSERVING,FOLLOWING,LEADING)。当前peer状态为LOOKING时,,如果通知的时间点,大于当前server时间点,则更新投票提议,并发送通知消息到所有投票peer。如果当前节点的Quorum Peer都进行投票回复,然后从接收队列中拉取通知投票消息,如果为空,则投票结束,更新当前投票状态为LEADING。当peer为OBSERVING,FOLLOWING状态,什么都不做;当peer状态为leading,则如果投票的时间戳和当前节点的投票时间戳一致,并且所有peer都回复,则结束投票。
leader选举
public interface Election {
public Vote lookForLeader() throws InterruptedException;
public void shutdown();
}
说明:
选举的父接口为Election,其定义了lookForLeader和shutdown两个方法,lookForLeader表示寻找Leader,shutdown则表示关闭,如关闭服务端之间的连接。
AuthFastLeaderElection,同FastLeaderElection算法基本一致,只是在消息中加入了认证信息,其在3.4.0之后的版本中已经不建议使用。
FastLeaderElection,其是标准的fast paxos算法的实现,基于TCP协议进行选举。
LeaderElection,也表示一种选举算法,其在3.4.0之后的版本中已经不建议使用。
选举入口在下面的方法中
org.apache.zookeeper.server.quorum.FastLeaderElection#lookForLeader
说明:FastLeaderElection实现了Election接口,其需要实现接口中定义的lookForLeader方法和shutdown方法,其是标准的Fast Paxos算法的实现,各服务器之间基于TCP协议进行选举。
在上面的集群模式启动流程中,最后会调用startLeaderElection()来下进行选举操作。startLeaderElection()中指定了选举算法。同时定义了为自己投一票(坚持你自己,年轻人!),一个Vote包含了投票节点、当前节点的zxid和当前的epoch。Zookeeper默认采取了FastLeaderElection选举算法。最后启动QuorumPeer线程,开始投票。
synchronized public void startLeaderElection() {
try {
// 所有节点启动的初始状态都是LOOKING,因此这里都会是创建一张投自己为Leader的票
if (getPeerState() == ServerState.LOOKING) {
currentVote = new Vote(myid, getLastLoggedZxid(), getCurrentEpoch());
}
} catch(IOException e) {
RuntimeException re = new RuntimeException(e.getMessage());
re.setStackTrace(e.getStackTrace());
throw re;
}
// if (!getView().containsKey(myid)) {
// throw new RuntimeException("My id " + myid + " not in the peer list");
//}
if (electionType == 0) {
try {
udpSocket = new DatagramSocket(myQuorumAddr.getPort());
responder = new ResponderThread();
responder.start();
} catch (SocketException e) {
throw new RuntimeException(e);
}
}
//初始化选举算法,electionType默认为3
this.electionAlg = createElectionAlgorithm(electionType);
}
FastLeaderElection类中定义三个内部类Notification、 ToSend 和 Messenger ,Messenger 中又定义了WorkerReceiver 和 WorkerSender
Notification类表示收到的选举投票信息(其他服务器发来的选举投票信息),其包含了被选举者的id、zxid、选举周期等信息。
ToSend类表示发送给其他服务器的选举投票信息,也包含了被选举者的id、zxid、选举周期等信息。
Message类为消息处理的类,用于发送和接收投票信息,包含了WorkerReceiver和WorkerSender两个线程类。
WorkerReceiver
说明:WorkerReceiver实现了Runnable接口,是选票接收器。其会不断地从QuorumCnxManager中获取其他服务器发来的选举消息,并将其转换成一个选票,然后保存到recvqueue中,在选票接收过程中,如果发现该外部选票的选举轮次小于当前服务器的,那么忽略该外部投票,同时立即发送自己的内部投票。其是将QuorumCnxManager的Message转化为FastLeaderElection的Notification。
其中,WorkerReceiver的主要逻辑在run方法中,其首先会从QuorumCnxManager中的recvQueue队列中取出其他服务器发来的选举消息,消息封装在Message数据结构中。然后判断消息中的服务器id是否包含在可以投票的服务器集合中,若不是,则会将本服务器的内部投票发送给该服务器
if(!self.getVotingView().containsKey(response.sid)){ // 当前的投票者集合不包含服务器
// 获取自己的投票
Vote current = self.getCurrentVote();
// 构造ToSend消息
ToSend notmsg = new ToSend(ToSend.mType.notification,
current.getId(),
current.getZxid(),
logicalclock,
self.getPeerState(),
response.sid,
current.getPeerEpoch());
// 放入sendqueue队列,等待发送
sendqueue.offer(notmsg);
}
若包含该服务器,则根据消息(Message)解析出投票服务器的投票信息并将其封装为Notification,然后判断当前服务器是否为LOOKING,若为LOOKING,则直接将Notification放入FastLeaderElection的recvqueue(区别于recvQueue)中。然后判断投票服务器是否为LOOKING状态,并且其选举周期小于当前服务器的逻辑时钟,则将本(当前)服务器的内部投票发送给该服务器,否则,直接忽略掉该投票。
WorkerSender
说明:WorkerSender也实现了Runnable接口,为选票发送器,其会不断地从sendqueue中获取待发送的选票,并将其传递到底层QuorumCnxManager中,其过程是将FastLeaderElection的ToSend转化为QuorumCnxManager的Message。
protected class Messenger {
// 选票发送器
WorkerSender ws;
// 选票接收器
WorkerReceiver wr;
}
说明:Messenger中维护了一个WorkerSender和WorkerReceiver,分别表示选票发送器和选票接收器。
Messenger(QuorumCnxManager manager) {
// 创建WorkerSender
this.ws = new WorkerSender(manager);
// 新创建线程
Thread t = new Thread(this.ws,
"WorkerSender[myid=" + self.getId() + "]");
// 设置为守护线程
t.setDaemon(true);
// 启动
t.start();
// 创建WorkerReceiver
this.wr = new WorkerReceiver(manager);
// 创建线程
t = new Thread(this.wr,
"WorkerReceiver[myid=" + self.getId() + "]");
// 设置为守护线程
t.setDaemon(true);
// 启动
t.start();
}
说明:会启动WorkerSender和WorkerReceiver,并设置为守护线程。
选举流程
判断投票结果的策略
上面这个是其中的一种选举算法,选举过程中,各个server收到投票后需要进行投票结果抉择,判断投票结果的策略有两种
// 按照分组权重
org.apache.zookeeper.server.quorum.flexible.QuorumHierarchical
// 简单按照是否是大多数,超过参与投票数的一半
org.apache.zookeeper.server.quorum.flexible.QuorumMaj
选票的网络传输
zookeeper中选举使用的端口和正常处理client请求的端口是不一样的,而且由于投票的数据和处理请求的数据不一样,数据传输的方法也不一样。选举使用的网络传输相关的类和数据结构如下
选举过程
- 各自初始化选票
-
- proposedLeader:一开始都是选举自己,myid
- proposedZxid:最后一次处理成功的事务的zxid
- proposedEpoch:上一次选举成功的leader的epoch,从currentEpoch 文件中读取
- proposedLeader:一开始都是选举自己,myid
- 发送自己的选票给其他参选者
- 接收其他参选者的选票
-
- 收到其他参选者的选票后会放入recvqueue,这个是阻塞队列,从里面超时获取
- 如果超时没有获取到选票vote则采用退避算法,下次使用更长的超时时间
- 校验选票的有效性,并且当前机器处于looking状态,开始判断是否接受
-
- 如果收到的选票的electionEpoch大于当前机器选票的logicalclock
-
- 进行选票pk,收到的选票和本机初始选票pk,如果收到的选票胜出则更新本地的选票为收到的选票
-
- pk的算法
-
- org.apache.zookeeper.server.quorum.FastLeaderElection#totalOrderPredicate
- 选取epoch较大的
- 如果epoch相等则取zxid较大的
- 如果zxid相等则取myid较大的
- org.apache.zookeeper.server.quorum.FastLeaderElection#totalOrderPredicate
-
- pk的算法
- 如果本机初始选票胜出则更新为当前机器的选票
- 更新完选票之后重新发出自己的选票
-
- 进行选票pk,收到的选票和本机初始选票pk,如果收到的选票胜出则更新本地的选票为收到的选票
-
- 如果收到的选票的electionEpoch大于当前机器选票的logicalclock
-
- 如果n.electionEpoch < logicalclock.get()则丢弃选票,继续准备接收其他选票
-
- 如果n.electionEpoch == logicalclock.get()并且收到的选票pk(pk算法totalOrderPredicate)之后胜出
-
- 更新本机选票并且,发送新的选票给其他参选者
- 执行到这里,说明收到的这个选票有效,将选票记录下来,recvset
- 统计选票
-
- org.apache.zookeeper.server.quorum.FastLeaderElection#getVoteTracker
- 看看已经收到的投票中,和当前机器选票一致的票数
- org.apache.zookeeper.server.quorum.FastLeaderElection#getVoteTracker
- 判断投票结果
-
- org.apache.zookeeper.server.quorum.SyncedLearnerTracker#hasAllQuorums
- 根据具体的策略判断
-
- QuorumHierarchical
- QuorumMaj,默认是这个
-
- 判断投该票的主机数目是否占参与投票主机数的大部分,也就是大于1/2
- QuorumHierarchical
- 如果本轮选举成功
-
- 如果等finalizeWait时间后还没有其他选票的时候,就认为当前选举结束
- 设置当前主机状态
- 退出本轮选举
- 如果等finalizeWait时间后还没有其他选票的时候,就认为当前选举结束
- org.apache.zookeeper.server.quorum.SyncedLearnerTracker#hasAllQuorums
-
- 如果n.electionEpoch == logicalclock.get()并且收到的选票pk(pk算法totalOrderPredicate)之后胜出
- 收到其他参选者的选票后会放入recvqueue,这个是阻塞队列,从里面超时获取
选举的整个流程为
整个选举过程可大致理解不断的接收选票,比对选票,直到选出leader,每个zookeeper节点都持有自己的选票池,按照统一的比对算法,正常情况下最终选出来的leader是一致的。
源码详解
FastLeaderElection类:
说明:其维护了服务器之间的连接(用于发送消息)、发送消息队列、接收消息队列、推选者的一些信息(zxid、id)、是否停止选举流程标识等。
public class FastLeaderElection implements Election {
//..........
/**
* Connection manager. Fast leader election uses TCP for
* communication between peers, and QuorumCnxManager manages
* such connections.
*/
QuorumCnxManager manager;
/*
Notification表示收到的选举投票信息(其他服务器发来的选举投票信息),
其包含了被选举者的id、zxid、选举周期等信息,
其buildMsg方法将选举信息封装至ByteBuffer中再进行发送
*/
static public class Notification {
//..........
}
/**
* Messages that a peer wants to send to other peers.
* These messages can be both Notifications and Acks
* of reception of notification.
*/
/*
ToSend表示发送给其他服务器的选举投票信息,也包含了被选举者的id、zxid、选举周期等信息
*/
static public class ToSend {
//..........
}
LinkedBlockingQueue<ToSend> sendqueue;
LinkedBlockingQueue<Notification> recvqueue;
/**
* Multi-threaded implementation of message handler. Messenger
* implements two sub-classes: WorkReceiver and WorkSender. The
* functionality of each is obvious from the name. Each of these
* spawns a new thread.
*/
protected class Messenger {
/**
* Receives messages from instance of QuorumCnxManager on
* method run(), and processes such messages.
*/
class WorkerReceiver extends ZooKeeperThread {
//..........
}
/**
* This worker simply dequeues a message to send and
* and queues it on the manager's queue.
*/
class WorkerSender extends ZooKeeperThread {
//..........
}
WorkerSender ws;
WorkerReceiver wr;
Thread wsThread = null;
Thread wrThread = null;
}
//..........
QuorumPeer self;
Messenger messenger;
AtomicLong logicalclock = new AtomicLong(); /* Election instance */
long proposedLeader;
long proposedZxid;
long proposedEpoch;
//..........
}
说明:构造函数中初始化了stop字段和manager字段,并且调用了starter函数
public FastLeaderElection(QuorumPeer self, QuorumCnxManager manager){
// 字段赋值
this.stop = false;
this.manager = manager;
// 初始化其他信息
starter(self, manager);
}
调用
private void starter(QuorumPeer self, QuorumCnxManager manager) {
// 赋值,对Leader和投票者的ID进行初始化操作
this.self = self;
proposedLeader = -1;
proposedZxid = -1;
// 初始化发送队列
sendqueue = new LinkedBlockingQueue<ToSend>();
// 初始化接收队列
recvqueue = new LinkedBlockingQueue<Notification>();
// 创建Messenger,会启动接收器和发送器线程
this.messenger = new Messenger(manager);
}
说明:其完成在构造函数中未完成的部分,如会初始化FastLeaderElection的sendqueue和recvqueue,并且启动接收器和发送器线程。
核心函数分析
sendNotifications函数
private void sendNotifications() {
for (QuorumServer server : self.getVotingView().values()) { // 遍历投票参与者集合
long sid = server.id;
// 构造发送消息
ToSend notmsg = new ToSend(ToSend.mType.notification,
proposedLeader,
proposedZxid,
logicalclock,
QuorumPeer.ServerState.LOOKING,
sid,
proposedEpoch);
if(LOG.isDebugEnabled()){
LOG.debug("Sending Notification: " + proposedLeader + " (n.leader), 0x" +
Long.toHexString(proposedZxid) + " (n.zxid), 0x" + Long.toHexString(logicalclock) +
" (n.round), " + sid + " (recipient), " + self.getId() +
" (myid), 0x" + Long.toHexString(proposedEpoch) + " (n.peerEpoch)");
}
// 将发送消息放置于队列
sendqueue.offer(notmsg);
}
}
说明:其会遍历所有的参与者投票集合,然后将自己的选票信息发送至上述所有的投票者集合,其并非同步发送,而是将ToSend消息放置于sendqueue中,之后由WorkerSender进行发送。
QuorumPeer线程启动后会开启对ServerState的监听,如果当前服务节点属于Looking状态,则会执行选举操作。Zookeeper服务器启动后是Looking状态,所以服务启动后会马上进行选举操作。通过调用makeLEStrategy().lookForLeader()进行投票操作,也就是FastLeaderElection.lookForLeader();
QuorumPeer.run():
public void run() {
updateThreadName();
//..........
try {
/*
* Main loop
*/
while (running) {
switch (getPeerState()) {
case LOOKING:
LOG.info("LOOKING");
if (Boolean.getBoolean("readonlymode.enabled")) {
final ReadOnlyZooKeeperServer roZk =
new ReadOnlyZooKeeperServer(logFactory, this, this.zkDb);
Thread roZkMgr = new Thread() {
public void run() {
try {
// lower-bound grace period to 2 secs
sleep(Math.max(2000, tickTime));
if (ServerState.LOOKING.equals(getPeerState())) {
roZk.startup();
}
} catch (InterruptedException e) {
LOG.info("Interrupted while attempting to start ReadOnlyZooKeeperServer, not started");
} catch (Exception e) {
LOG.error("FAILED to start ReadOnlyZooKeeperServer", e);
}
}
};
try {
roZkMgr.start();
reconfigFlagClear();
if (shuttingDownLE) {
shuttingDownLE = false;
startLeaderElection();
}
setCurrentVote(makeLEStrategy().lookForLeader());
} catch (Exception e) {
LOG.warn("Unexpected exception", e);
setPeerState(ServerState.LOOKING);
} finally {
roZkMgr.interrupt();
roZk.shutdown();
}
} else {
try {
reconfigFlagClear();
if (shuttingDownLE) {
shuttingDownLE = false;
startLeaderElection();
}
setCurrentVote(makeLEStrategy().lookForLeader());
} catch (Exception e) {
LOG.warn("Unexpected exception", e);
setPeerState(ServerState.LOOKING);
}
}
break;
case OBSERVING:
try {
LOG.info("OBSERVING");
setObserver(makeObserver(logFactory));
observer.observeLeader();
} catch (Exception e) {
LOG.warn("Unexpected exception",e );
} finally {
observer.shutdown();
setObserver(null);
updateServerState();
}
break;
case FOLLOWING:
try {
LOG.info("FOLLOWING");
setFollower(makeFollower(logFactory));
follower.followLeader();
} catch (Exception e) {
LOG.warn("Unexpected exception",e);
} finally {
follower.shutdown();
setFollower(null);
updateServerState();
}
break;
case LEADING:
LOG.info("LEADING");
try {
setLeader(makeLeader(logFactory));
leader.lead();
setLeader(null);
} catch (Exception e) {
LOG.warn("Unexpected exception",e);
} finally {
if (leader != null) {
leader.shutdown("Forcing shutdown");
setLeader(null);
}
updateServerState();
}
break;
}
start_fle = Time.currentElapsedTime();
}
} finally {
LOG.warn("QuorumPeer main thread exited");
MBeanRegistry instance = MBeanRegistry.getInstance();
instance.unregister(jmxQuorumBean);
instance.unregister(jmxLocalPeerBean);
for (RemotePeerBean remotePeerBean : jmxRemotePeerBean.values()) {
instance.unregister(remotePeerBean);
}
jmxQuorumBean = null;
jmxLocalPeerBean = null;
jmxRemotePeerBean = null;
}
}
FastLeaderElection.lookForLeader():
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;
}
if (self.start_fle == 0) {
self.start_fle = Time.currentElapsedTime();
}
try {
HashMap<Long, Vote> recvset = new HashMap<Long, Vote>();
HashMap<Long, Vote> outofelection = new HashMap<Long, Vote>();
//等待200毫秒
int notTimeout = finalizeWait;
synchronized(this){
//逻辑时钟自增+1
logicalclock.incrementAndGet();
updateProposal(getInitId(), getInitLastLoggedZxid(), getPeerEpoch());
}
LOG.info("New election. My id = " + self.getId() +
", proposed zxid=0x" + Long.toHexString(proposedZxid));
//发送投票信息
sendNotifications();
/*
* Loop in which we exchange notifications until we find a leader
*/
//判断是否为Looking状态
while ((self.getPeerState() == ServerState.LOOKING) &&
(!stop)){
/*
* Remove next notification from queue, times out after 2 times
* the termination time
*/
//获取接收其他Follow发送的投票信息
Notification n = recvqueue.poll(notTimeout,
TimeUnit.MILLISECONDS);
/*
* Sends more notifications if haven't received enough.
* Otherwise processes new notification.
*/
//未收到投票信息
if(n == null){
//判断是否和集群离线了
if(manager.haveDelivered()){
//未断开,发送投票
sendNotifications();
} else {
//断开,重连
manager.connectAll();
}
/*
* Exponential backoff
*/
int tmpTimeOut = notTimeout*2;
notTimeout = (tmpTimeOut < maxNotificationInterval?
tmpTimeOut : maxNotificationInterval);
LOG.info("Notification time out: " + notTimeout);
} //接收到了投票,则处理收到的投票信息
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.
*/
//其他节点的Server.state
switch (n.state) {
case LOOKING:
//如果其他节点也为Looking状态,说明当前正处于选举阶段,则处理投票信息。
// If notification > current, replace and send messages out
//如果当前的epoch(投票轮次)小于其他的投票信息,则说明自己的投票轮次已经过时,则更新自己的投票轮次
if (n.electionEpoch > logicalclock.get()) {
//更新投票轮次
logicalclock.set(n.electionEpoch);
//清除收到的投票
recvset.clear();
//比对投票信息
//如果本身的投票信息 低于 收到的的投票信息,则使用收到的投票信息,否则再次使用自身的投票信息进行发送投票。
if(totalOrderPredicate(n.leader, n.zxid, n.peerEpoch,
getInitId(), getInitLastLoggedZxid(), getPeerEpoch())) {
//使用收到的投票信息
updateProposal(n.leader, n.zxid, n.peerEpoch);
} else {
//使用自己的投票信息
updateProposal(getInitId(),
getInitLastLoggedZxid(),
getPeerEpoch());
}
//发送投票信息
sendNotifications();
} else if (n.electionEpoch < logicalclock.get()) {
//如果其他节点的epoch小于当前的epoch则丢弃
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)) {
//同样的epoch,正常情况,所有节点基本处于同一轮次
//如果自身投票信息 低于 收到的投票信息,则更新投票信息。并发送
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));
}
//投票信息Vote归档,收到的有效选票 票池
recvset.put(n.sid, new Vote(n.leader, n.zxid, n.electionEpoch, n.peerEpoch));
//统计投票结果 ,判断是否能结束选举
if (termPredicate(recvset,
new Vote(proposedLeader, proposedZxid,
logicalclock.get(), proposedEpoch))) {
//如果已经选出leader
// 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
*/
//如果选票结果为当前节点,则更新ServerState,否则设置为Follwer
if (n == null) {
self.setPeerState((proposedLeader == self.getId()) ?
ServerState.LEADING: learningState());
Vote endVote = new Vote(proposedLeader,
proposedZxid, 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.
*/
//如果其他节点已经确定为Leader
//如果同一个的投票轮次,则加入选票池
//判断是否能过半选举出leader ,如果是,则checkLeader
/*checkLeader:
* 【是否能选举出leader】and
* 【(如果投票leader为自身,且轮次一致) or
* (如果所选leader不是自身信息在outofelection不为空,且leader的ServerState状态已经为leader)】
*
*/
if(n.electionEpoch == logicalclock.get()){
recvset.put(n.sid, new Vote(n.leader, n.zxid, n.electionEpoch, n.peerEpoch));
if(termPredicate(recvset, new Vote(n.leader,
n.zxid, n.electionEpoch, n.peerEpoch, n.state))
&& checkLeader(outofelection, n.leader, n.electionEpoch)) {
self.setPeerState((n.leader == self.getId()) ?
ServerState.LEADING: learningState());
Vote endVote = new Vote(n.leader, n.zxid, n.peerEpoch);
leaveInstance(endVote);
return endVote;
}
}
/*
* Before joining an established ensemble, verify that
* a majority are following the same leader.
* Only peer epoch is used to check that the votes come
* from the same ensemble. This is because there is at
* least one corner case in which the ensemble can be
* created with inconsistent zxid and election epoch
* info. However, given that only one ensemble can be
* running at a single point in time and that each
* epoch is used only once, using only the epoch to
* compare the votes is sufficient.
*
* @see https://issues.apache.org/jira/browse/ZOOKEEPER-1732
*/
outofelection.put(n.sid, new Vote(n.leader,
IGNOREVALUE, IGNOREVALUE, n.peerEpoch, n.state));
//说明此时 集群中存在别的轮次选举已经有了选举结果
//比对outofelection选票池,是否能结束选举,同时检查leader信息
//如果能结束选举 接收到的选票产生的leader通过checkLeader为true,则更新当前节点信息
if (termPredicate(outofelection, new Vote(n.leader,
IGNOREVALUE, IGNOREVALUE, n.peerEpoch, n.state))
&& checkLeader(outofelection, n.leader, IGNOREVALUE)) {
synchronized(this){
logicalclock.set(n.electionEpoch);
self.setPeerState((n.leader == self.getId()) ?
ServerState.LEADING: learningState());
}
Vote endVote = new Vote(n.leader, n.zxid, 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());
}
}
说明:该函数用于开始新一轮的Leader选举,其首先会将逻辑时钟自增,然后更新本服务器的选票信息(初始化选票),之后将选票信息放入sendqueue等待发送给其他服务器
之后每台服务器会不断地从recvqueue队列中获取外部选票。如果服务器发现无法获取到任何外部投票,就立即确认自己是否和集群中其他服务器保持着有效的连接,如果没有连接,则马上建立连接,如果已经建立了连接,则再次发送自己当前的内部投票
在发送完初始化选票之后,接着开始处理外部投票。在处理外部投票时,会根据选举轮次来进行不同的处理。
· 外部投票的选举轮次大于内部投票。若服务器自身的选举轮次落后于该外部投票对应服务器的选举轮次,那么就会立即更新自己的选举轮次(logicalclock),并且清空所有已经收到的投票,然后使用初始化的投票来进行PK以确定是否变更内部投票。最终再将内部投票发送出去。
· 外部投票的选举轮次小于内部投票。若服务器接收的外选票的选举轮次落后于自身的选举轮次,那么Zookeeper就会直接忽略该外部投票,不做任何处理。
· 外部投票的选举轮次等于内部投票。此时可以开始进行选票PK,如果消息中的选票更优,则需要更新本服务器内部选票,再发送给其他服务器。
之后再对选票进行归档操作,无论是否变更了投票,都会将刚刚收到的那份外部投票放入选票集合recvset中进行归档,其中recvset用于记录当前服务器在本轮次的Leader选举中收到的所有外部投票,然后开始统计投票,统计投票是为了统计集群中是否已经有过半的服务器认可了当前的内部投票,如果确定已经有过半服务器认可了该投票,然后再进行最后一次确认,判断是否又有更优的选票产生,若无,则终止投票,然后最终的选票
若选票中的服务器状态为FOLLOWING或者LEADING时,其大致步骤会判断选举周期是否等于逻辑时钟,归档选票,是否已经完成了Leader选举,设置服务器状态,修改逻辑时钟等于选举周期,返回最终选票
lookForLeader方法中把当前选票和收到的选举进行不断的比对和更新,最终选出leader,其中比对选票的方法为totalOrderPredicate(): 其中的比对投票信息方式为:
1. 首先判断epoch(选举轮次),也就是选择epoch值更大的节点;如果收到的epoch更大,则当前阶段落后,更新自己的epoch,否则丢弃。
2. 如果同于轮次中,则选择zxid更大的节点,因为zxid越大说明数据越新。
3. 如果同一轮次,且zxid一样,则选择serverId最大的节点。
综上3点可理解为越大越棒!
totalOrderPredicate():
protected boolean totalOrderPredicate(long newId, long newZxid, long newEpoch, long curId, long curZxid, long curEpoch) {
LOG.debug("id: " + newId + ", proposed id: " + curId + ", zxid: 0x" +
Long.toHexString(newZxid) + ", proposed zxid: 0x" + Long.toHexString(curZxid));
if(self.getQuorumVerifier().getWeight(newId) == 0){
return false;
}
/*
* 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)))));
}
说明:该函数将接收的投票与自身投票进行PK,查看是否消息中包含的服务器id是否更优,其按照epoch、zxid、id的优先级进行PK。
protected boolean termPredicate(
HashMap<Long, Vote> votes,
Vote vote) {
HashSet<Long> set = new HashSet<Long>();
/*
* First make the views consistent. Sometimes peers will have
* different zxids for a server depending on timing.
*/
for (Map.Entry<Long,Vote> entry : votes.entrySet()) { // 遍历已经接收的投票集合
if (vote.equals(entry.getValue())){ // 将等于当前投票的项放入set
set.add(entry.getKey());
}
}
//统计set,查看投某个id的票数是否超过一半
return self.getQuorumVerifier().containsQuorum(set);
}
说明:该函数用于判断Leader选举是否结束,即是否有一半以上的服务器选出了相同的Leader,其过程是将收到的选票与当前选票进行对比,选票相同的放入同一个集合,之后判断选票相同的集合是否超过了半数。
protected boolean checkLeader(
HashMap<Long, Vote> votes,
long leader,
long electionEpoch){
boolean predicate = true;
/*
* If everyone else thinks I'm the leader, I must be the leader.
* The other two checks are just for the case in which I'm not the
* leader. If I'm not the leader and I haven't received a message
* from leader stating that it is leading, then predicate is false.
*/
if(leader != self.getId()){ // 自己不为leader
if(votes.get(leader) == null) predicate = false; // 还未选出leader
else if(votes.get(leader).getState() != ServerState.LEADING) predicate = false; // 选出的leader还未给出ack信号,其他服务器还不知道leader
} else if(logicalclock != electionEpoch) { // 逻辑时钟不等于选举周期
predicate = false;
}
return predicate;
}
说明:该函数检查是否已经完成了Leader的选举,此时Leader的状态应该是LEADING状态。