如果你还没看过Flume-ng源码解析系列中的启动流程、Channel组件和Sink组件，可以点击下面链接：
Flume-ng源码解析之启动流程
Flume-ng源码解析之Channel组件
Flume-ng源码解析之Sink组件
在前面三篇文章中我们初步了解了Flume的启动流程、Channel组件和Sink组件，接下来我们一起来看看agent三大组件中Source组件。
1 Source
Source，作为agent中的消息来源组件，我们来看看它是如何将event传递给channel的和它的特性。
依然先看代码：
@InterfaceAudience.Public
@InterfaceStability.Stable
public interface Source extends LifecycleAware, NamedComponent {
public void setChannelProcessor(ChannelProcessor channelProcessor);
public ChannelProcessor getChannelProcessor();
}
我们可以看到它里面定义的两个需要实现方法是getChannelProcessor和setChannelProcessor，我们大概可以猜到，source就是通过ChannelProcessor将event传输给channel的。
这里先来了解一下Source的类型，Flume根据数据来源的特性将Source分成两类类，像Http、netcat和exec等就是属于事件驱动型（EventDrivenSource），而kafka和Jms等就是属于轮询拉取型（PollableSource）。
据我们在启动流程中了解到的，Application是先启动SourceRunner，再由SourceRunner来启动source，那么既然source有两种类型，那么Sourcerunner也分为EventDrivenSourceRunner和PollableSourceRunner，我们来看看它们的start()：
EventDrivenSourceRunner
public class EventDrivenSourceRunner extends SourceRunner {
…
@Override
public void start() {
Source source = getSource();
ChannelProcessor cp = source.getChannelProcessor();
cp.initialize();
source.start();
lifecycleState = LifecycleState.START;
}
…
}
PollableSourceRunner
public class PollableSourceRunner extends SourceRunner {
…
@Override
public void start() {
PollableSource source = (PollableSource) getSource();
ChannelProcessor cp = source.getChannelProcessor();
cp.initialize();
source.start();
runner = new PollingRunner();
runner.source = source;
runner.counterGroup = counterGroup;
runner.shouldStop = shouldStop;
runnerThread = new Thread(runner);
runnerThread.setName(getClass().getSimpleName() + "-" +
source.getClass().getSimpleName() + "-" + source.getName());
runnerThread.start();
lifecycleState = LifecycleState.START;
}
…
public static class PollingRunner implements Runnable {
private PollableSource source;
private AtomicBoolean shouldStop;
private CounterGroup counterGroup;
@Override
public void run() {
logger.debug("Polling runner starting. Source:{}", source);
while (!shouldStop.get()) {
counterGroup.incrementAndGet("runner.polls");
try {
if (source.process().equals(PollableSource.Status.BACKOFF)) {
counterGroup.incrementAndGet("runner.backoffs");
Thread.sleep(Math.min(
counterGroup.incrementAndGet("runner.backoffs.consecutive")
* source.getBackOffSleepIncrement(), source.getMaxBackOffSleepInterval()));
} else {
counterGroup.set("runner.backoffs.consecutive", 0L);
}
} catch (InterruptedException e) {
logger.info("Source runner interrupted. Exiting");
counterGroup.incrementAndGet("runner.interruptions");
} catch (EventDeliveryException e) {
logger.error("Unable to deliver event. Exception follows.", e);
counterGroup.incrementAndGet("runner.deliveryErrors");
} catch (Exception e) {
counterGroup.incrementAndGet("runner.errors");
logger.error("Unhandled exception, logging and sleeping for " +
source.getMaxBackOffSleepInterval() + "ms", e);
try {
Thread.sleep(source.getMaxBackOffSleepInterval());
} catch (InterruptedException ex) {
Thread.currentThread().interrupt();
}
}
}
logger.debug("Polling runner exiting. Metrics:{}", counterGroup);
}
}
}
无论是PollableSourceRunner还是EventDrivenSourceRunner，都是调用它里面的source的start()。这个时候我们看到ChannelProcessor的存在，那么就会有疑惑，这ChannelProcessor哪来的？我们还是得看回AbstarctConfigurationProvider，查看里面的loadSources()，我们就会发现下面这段代码：
ChannelSelectorConfiguration selectorConfig = config.getSelectorConfiguration();
ChannelSelector selector = ChannelSelectorFactory.create(sourceChannels, selectorConfig);
ChannelProcessor channelProcessor = new ChannelProcessor(selector);
Configurables.configure(channelProcessor, config);
source.setChannelProcessor(channelProcessor);
到这里我们基本已经了解了Source的启动流程，下面以AvroSource为例看看，source是在哪里调用ChannelProcessor的插入方法。
2 AvroSource
public class AvroSource extends AbstractSource implements EventDrivenSource,
Configurable, AvroSourceProtocol {
…
@Override
public Status append(AvroFlumeEvent avroEvent) {
if (logger.isDebugEnabled()) {
if (LogPrivacyUtil.allowLogRawData()) {
logger.debug("Avro source {}: Received avro event: {}", getName(), avroEvent);
} else {
logger.debug("Avro source {}: Received avro event", getName());
}
}
sourceCounter.incrementAppendReceivedCount();
sourceCounter.incrementEventReceivedCount();
Event event = EventBuilder.withBody(avroEvent.getBody().array(),
toStringMap(avroEvent.getHeaders()));
try {
getChannelProcessor().processEvent(event);
} catch (ChannelException ex) {
logger.warn("Avro source " + getName() + ": Unable to process event. " +
"Exception follows.", ex);
return Status.FAILED;
}
sourceCounter.incrementAppendAcceptedCount();
sourceCounter.incrementEventAcceptedCount();
return Status.OK;
}
@Override
public Status appendBatch(List<AvroFlumeEvent> events) {
logger.debug("Avro source {}: Received avro event batch of {} events.",
getName(), events.size());
sourceCounter.incrementAppendBatchReceivedCount();
sourceCounter.addToEventReceivedCount(events.size());
List<Event> batch = new ArrayList<Event>();
for (AvroFlumeEvent avroEvent : events) {
Event event = EventBuilder.withBody(avroEvent.getBody().array(),
toStringMap(avroEvent.getHeaders()));
batch.add(event);
}
try {
getChannelProcessor().processEventBatch(batch);
} catch (Throwable t) {
logger.error("Avro source " + getName() + ": Unable to process event " +
"batch. Exception follows.", t);
if (t instanceof Error) {
throw (Error) t;
}
return Status.FAILED;
}
sourceCounter.incrementAppendBatchAcceptedCount();
sourceCounter.addToEventAcceptedCount(events.size());
return Status.OK;
}
…
}
在append方法中我们可以看到getChannelProcessor().processEvent(event);，所以不同的Source根据它的不同触发机制和拉取机制，在特定的时候调用ChannelProcessor来执行event的插入。 ·
到此为止，我们就完成了对Flume启动流程和三大组件的研究，鉴于能力，其中有些细节没办法深入研究，希望以后有时间能够继续深入分析下去。
