一般来说，我们是通过命令来启动kafka，但是命令的本质还是调用代码中的main方法，所以，我们重点看下启动类Kafka。源码下下来之后，我们也可以通过直接运行Kafka.scala中的main方法（需要指定启动参数，也就是server.properties的位置）来启动Kafka。因为kafka依赖zookeeper，所以我们需要提前启动zookeeper，然后在server.properties中指定zk地址后，启动。
下面我们首先看一下main()方法：
def main(args: Array[String]): Unit = {
try {
val serverProps = getPropsFromArgs(args)
val kafkaServerStartable = KafkaServerStartable.fromProps(serverProps)
// attach shutdown handler to catch control-c
Runtime.getRuntime().addShutdownHook(new Thread() {
override def run() = {
kafkaServerStartable.shutdown
}
})
kafkaServerStartable.startup
kafkaServerStartable.awaitShutdown
}
catch {
case e: Throwable =>
fatal(e)
System.exit(1)
}
System.exit(0)
}
我们慢慢来分析下，首先是getPropsFromArgs(args)，这一行很明确，就是从配置文件中读取我们配置的内容，然后赋值给serverProps。第二步，KafkaServerStartable.fromProps(serverProps)，
object KafkaServerStartable {
def fromProps(serverProps: Properties) = {
KafkaMetricsReporter.startReporters(new VerifiableProperties(serverProps))
new KafkaServerStartable(KafkaConfig.fromProps(serverProps))
}
}
这块主要是启动了一个内部的监控服务（内部状态监控）。
下面是一个在java中常见的钩子函数，在关闭时会启动一些销毁程序，保证程序安全关闭。之后就是我们启动的重头戏了：kafkaServerStartable.startup。跟进去可以很清楚的看到，里面调用的方法是KafkaServer中的startup方法，下面我们重点看下这个方法(比较长)：
def startup() {
try {
info("starting")
if(isShuttingDown.get)
throw new IllegalStateException("Kafka server is still shutting down, cannot re-start!")
if(startupComplete.get)
return
val canStartup = isStartingUp.compareAndSet(false, true)
if (canStartup) {
metrics = new Metrics(metricConfig, reporters, kafkaMetricsTime, true)
brokerState.newState(Starting)
/* start scheduler */
kafkaScheduler.startup()
/* setup zookeeper */
zkUtils = initZk()
/* start log manager */
logManager = createLogManager(zkUtils.zkClient, brokerState)
logManager.startup()
/* generate brokerId */
config.brokerId = getBrokerId
this.logIdent = "[Kafka Server " + config.brokerId + "], "
socketServer = new SocketServer(config, metrics, kafkaMetricsTime)
socketServer.startup()
/* start replica manager */
replicaManager = new ReplicaManager(config, metrics, time, kafkaMetricsTime, zkUtils, kafkaScheduler, logManager,
isShuttingDown)
replicaManager.startup()
/* start kafka controller */
kafkaController = new KafkaController(config, zkUtils, brokerState, kafkaMetricsTime, metrics, threadNamePrefix)
kafkaController.startup()
/* start group coordinator */
groupCoordinator = GroupCoordinator(config, zkUtils, replicaManager, kafkaMetricsTime)
groupCoordinator.startup()
/* Get the authorizer and initialize it if one is specified.*/
authorizer = Option(config.authorizerClassName).filter(_.nonEmpty).map { authorizerClassName =>
val authZ = CoreUtils.createObject[Authorizer](authorizerClassName)
authZ.configure(config.originals())
authZ
}
/* start processing requests */
apis = new KafkaApis(socketServer.requestChannel, replicaManager, groupCoordinator,
kafkaController, zkUtils, config.brokerId, config, metadataCache, metrics, authorizer)
requestHandlerPool = new KafkaRequestHandlerPool(config.brokerId, socketServer.requestChannel, apis, config.numIoThreads)
brokerState.newState(RunningAsBroker)
Mx4jLoader.maybeLoad()
/* start dynamic config manager */
dynamicConfigHandlers = Map[String, ConfigHandler](ConfigType.Topic -> new TopicConfigHandler(logManager, config),
ConfigType.Client -> new ClientIdConfigHandler(apis.quotaManagers))
// Apply all existing client configs to the ClientIdConfigHandler to bootstrap the overrides
// TODO: Move this logic to DynamicConfigManager
AdminUtils.fetchAllEntityConfigs(zkUtils, ConfigType.Client).foreach {
case (clientId, properties) => dynamicConfigHandlers(ConfigType.Client).processConfigChanges(clientId, properties)
}
// Create the config manager. start listening to notifications
dynamicConfigManager = new DynamicConfigManager(zkUtils, dynamicConfigHandlers)
dynamicConfigManager.startup()
/* tell everyone we are alive */
val listeners = config.advertisedListeners.map {case(protocol, endpoint) =>
if (endpoint.port == 0)
(protocol, EndPoint(endpoint.host, socketServer.boundPort(protocol), endpoint.protocolType))
else
(protocol, endpoint)
}
kafkaHealthcheck = new KafkaHealthcheck(config.brokerId, listeners, zkUtils, config.rack,
config.interBrokerProtocolVersion)
kafkaHealthcheck.startup()
// Now that the broker id is successfully registered via KafkaHealthcheck, checkpoint it
checkpointBrokerId(config.brokerId)
/* register broker metrics */
registerStats()
shutdownLatch = new CountDownLatch(1)
startupComplete.set(true)
isStartingUp.set(false)
AppInfoParser.registerAppInfo(jmxPrefix, config.brokerId.toString)
info("started")
}
}
catch {
case e: Throwable =>
fatal("Fatal error during KafkaServer startup. Prepare to shutdown", e)
isStartingUp.set(false)
shutdown()
throw e
}
}
首先判断是否目前正在关闭中或者已经启动了，这两种情况直接抛出异常。然后是一个CAS的操作isStartingUp，防止线程并发操作启动，判断是否可以启动。如果可以启动，就开始我们的启动过程。
- 构造Metrics类
- 定义broker状态为启动中starting
- 启动定时器kafkaScheduler.startup()
- 构造zkUtils：利用参数中的zk信息，启动一个zk客户端
- 启动文件管理器：读取zk中的配置信息，包含__consumer_offsets和__system.topic__。重点是启动一些定时任务，来删除符合条件的记录(cleanupLogs)，清理脏记录(flushDirtyLogs)，把所有记录写到一个文本文件中，防止在启动时重启所有的记录文件(checkpointRecoveryPointOffsets)。
/**
* Start the background threads to flush logs and do log cleanup
*/
def startup() {
/* Schedule the cleanup task to delete old logs */
if(scheduler != null) {
info("Starting log cleanup with a period of %d ms.".format(retentionCheckMs))
scheduler.schedule("kafka-log-retention",
cleanupLogs,
delay = InitialTaskDelayMs,
period = retentionCheckMs,
TimeUnit.MILLISECONDS)
info("Starting log flusher with a default period of %d ms.".format(flushCheckMs))
scheduler.schedule("kafka-log-flusher",
flushDirtyLogs,
delay = InitialTaskDelayMs,
period = flushCheckMs,
TimeUnit.MILLISECONDS)
scheduler.schedule("kafka-recovery-point-checkpoint",
checkpointRecoveryPointOffsets,
delay = InitialTaskDelayMs,
period = flushCheckpointMs,
TimeUnit.MILLISECONDS)
}
if(cleanerConfig.enableCleaner)
cleaner.startup()
}
- 下一步，获取brokerId
- 启动一个NIO socket服务
- 启动复制管理器：启动ISR超时处理线程
- 启动kafka控制器：注册session过期监听器，同时启动控制器leader选举
- 启动协调器
- 权限认证
- 开启线程，开始处理请求
- 开启配置监听，主要是监听zk节点数据变化，然后广播到所有机器
- 开启健康检查：目前只是把broker节点注册到zk上，注册成功就是活的，否则就是dead
- 注册启动数据信息
- 启动成功
- 等待关闭countDownLatch，如果shutdownLatch变为0，则关闭Kafka