【xxl-job】源码分析 - 执行处理
【引言】
上篇博客分析的xxl-job的调度中心任务触发源码，本篇博客分析的内容是执行器在接收到任务后，如何处理的。
【实现】
在xxl-job系列博客的第一篇demo实例中，结合spring boot框架集成的，其中在xxl-job配置类中，有如下一段代码：
@Bean(initMethod = "start", destroyMethod = "destroy")
public XxlJobExecutor xxlJobExecutor() {
logger.info(">>>>>>>>>>> xxl-job config init.");
XxlJobExecutor xxlJobExecutor = new XxlJobExecutor();
xxlJobExecutor.setAdminAddresses(adminAddresses);
xxlJobExecutor.setAppName(appName);
xxlJobExecutor.setIp(ip);
xxlJobExecutor.setPort(port);
xxlJobExecutor.setAccessToken(accessToken);
xxlJobExecutor.setLogPath(logPath);
xxlJobExecutor.setLogRetentionDays(logRetentionDays);
return xxlJobExecutor;
}
执行器在接收到任务后，会执行start()，代码如下：
public void start() throws Exception {
// init admin-client
// 初始化调度中心的地址列表， 通过NetComClientProxy创建好adminBiz实例
initAdminBizList(adminAddresses, accessToken);
// init executor-jobHandlerRepository
// 初始化所有带有@JobHandler的handle， 根据name , 放入一个ConcurrentHashMap 中
initJobHandlerRepository(applicationContext);
// init logpath
// 初始化本地日志路径
XxlJobFileAppender.initLogPath(logPath);
// init executor-server
// 初始化本地jetty服务器
initExecutorServer(port, ip, appName, accessToken);
// init JobLogFileCleanThread
// 启动一个线程，用来清理本地日志， 默认保留最近一天的日志
JobLogFileCleanThread.getInstance().start(logRetentionDays);
}
以上五个方法，重点在第四个，源码如下：
private void initExecutorServer(int port, String ip, String appName, String accessToken) throws Exception {
// valid param
// 如果port为空，则默认9999为他的jetty服务器端口
port = port>0?port: NetUtil.findAvailablePort(9999);
// start server
// 创建一个ExecutorService 实例，放入Map中，后面会通过class获取到他的实例执行run方法
NetComServerFactory.putService(ExecutorBiz.class, new ExecutorBizImpl()); // rpc-service, base on jetty
NetComServerFactory.setAccessToken(accessToken);
// 启动jetty 服务器
serverFactory.start(port, ip, appName); // jetty + registry
}
jetty启动方法源码如下：
public void start(final int port, final String ip, final String appName) throws Exception {
thread = new Thread(new Runnable() {
@Override
public void run() {
// The Server
server = new Server(new ExecutorThreadPool(32, 256, 60L * 1000)); // 非阻塞
// HTTP connector
ServerConnector connector = new ServerConnector(server);
if (ip!=null && ip.trim().length()>0) {
//connector.setHost(ip); // The network interface this connector binds to as an IP address or a hostname. If null or 0.0.0.0, then bind to all interfaces.
}
connector.setPort(port);
server.setConnectors(new Connector[]{connector});
// Set a handler
HandlerCollection handlerc =new HandlerCollection();
handlerc.setHandlers(new Handler[]{new JettyServerHandler()});
server.setHandler(handlerc);
try {
// Start server
server.start();
logger.info(">>>>>>>>>>> xxl-job jetty server start success at port:{}.", port);
// Start Registry-Server
// 启动一个执行器注册的线程， 该线程第一次执行的时候，将该执行器的信息注册到数据库， xxl_job_qrtz_trigger_registry 这张表中 ，
// 此后，每过30秒， 执行器就会去数据库更新数据，表示自己还在存活中
// 调度中心那边会有一个线程定期的去数据库扫描，会自动的将30秒之内未更新信息的机器剔除， 同时将新加入的服务载入到集群列表中
ExecutorRegistryThread.getInstance().start(port, ip, appName);
// Start Callback-Server
// 启动一个日志监控的线程，里面设置了一个队列，每次有任务结束后，都会把任务的日志ID和处理结果放入队列，
// 线程从队列里面拿到日志ID和处理结果，通过调用adminBiz的callback方法来回调给调度中心执行结果
TriggerCallbackThread.getInstance().start();
server.join(); // block until thread stopped
logger.info(">>>>>>>>>>> xxl-rpc server join success, netcon={}, port={}", JettyServer.class.getName(), port);
} catch (Exception e) {
logger.error(e.getMessage(), e);
} finally {
//destroy();
}
}
});
thread.setDaemon(true); // daemon, service jvm, user thread leave >>> daemon leave >>> jvm leave
thread.start();
}
JettyServerHandler 接收请求后的核心处理方法主要是NetComServerFactory中的invokeService()，源码如下：
public static RpcResponse invokeService(RpcRequest request, Object serviceBean) {
// request参数就是上篇博客中最后写到的通过调度中心发送的http请求参数
if (serviceBean==null) {
// 这个serviceBean 就是在执行器启动的时候，initExecutorServer （） 这个方法中，将一个ExecutorBiz的实例放进去了，此处通过classname来获取这个实例
serviceBean = serviceMap.get(request.getClassName());
}
if (serviceBean == null) {
// TODO
}
RpcResponse response = new RpcResponse();
if (System.currentTimeMillis() - request.getCreateMillisTime() > 180000) {
response.setResult(new ReturnT(ReturnT.FAIL_CODE, "The timestamp difference between admin and executor exceeds the limit."));
return response;
}
if (accessToken!=null && accessToken.trim().length()>0 && !accessToken.trim().equals(request.getAccessToken())) {
response.setResult(new ReturnT(ReturnT.FAIL_CODE, "The access token[" + request.getAccessToken() + "] is wrong."));
return response;
}
try {
Class serviceClass = serviceBean.getClass();
String methodName = request.getMethodName();
Class[] parameterTypes = request.getParameterTypes();
Object[] parameters = request.getParameters();
FastClass serviceFastClass = FastClass.create(serviceClass);
FastMethod serviceFastMethod = serviceFastClass.getMethod(methodName, parameterTypes);
Object result = serviceFastMethod.invoke(serviceBean, parameters);
response.setResult(result);
} catch (Throwable t) {
t.printStackTrace();
response.setError(t.getMessage());
}
return response;
}
通过调度任务和以上分析，可以得出下面执行的方法是ExecutorBizImpl中的run方法：
@Override
public ReturnT run(TriggerParam triggerParam) {
// load old：jobHandler + jobThread
JobThread jobThread = XxlJobExecutor.loadJobThread(triggerParam.getJobId());
IJobHandler jobHandler = jobThread!=null?jobThread.getHandler():null;
String removeOldReason = null;
// valid：jobHandler + jobThread
GlueTypeEnum glueTypeEnum = GlueTypeEnum.match(triggerParam.getGlueType());
//匹配任务类型， BEAN模式
if (GlueTypeEnum.BEAN == glueTypeEnum) {
// new jobhandler
// 通过参数中的handlerName从本地内存中获取handler实例 （在执行器启动的时候，是把所有带有@JobHandler的实例通过name放入到一个map中的 ）
IJobHandler newJobHandler = XxlJobExecutor.loadJobHandler(triggerParam.getExecutorHandler());
// valid old jobThread
if (jobThread!=null && jobHandler != newJobHandler) {
// change handler, need kill old thread
removeOldReason = "change jobhandler or glue type, and terminate the old job thread.";
jobThread = null;
jobHandler = null;
}
// valid handler
if (jobHandler == null) {
jobHandler = newJobHandler;
if (jobHandler == null) {
return new ReturnT(ReturnT.FAIL_CODE, "job handler [" + triggerParam.getExecutorHandler() + "] not found.");
}
}
// GLUE模式
} else if (GlueTypeEnum.GLUE_GROOVY == glueTypeEnum) {
...
} else if (glueTypeEnum!=null && glueTypeEnum.isScript()) {
// 其他脚本执行模式
...
} else {
return new ReturnT(ReturnT.FAIL_CODE, "glueType[" + triggerParam.getGlueType() + "] is not valid.");
}
// executor block strategy
if (jobThread != null) {
ExecutorBlockStrategyEnum blockStrategy = ExecutorBlockStrategyEnum.match(triggerParam.getExecutorBlockStrategy(), null);
if (ExecutorBlockStrategyEnum.DISCARD_LATER == blockStrategy) {
// discard when running
if (jobThread.isRunningOrHasQueue()) {
return new ReturnT(ReturnT.FAIL_CODE, "block strategy effect："+ExecutorBlockStrategyEnum.DISCARD_LATER.getTitle());
}
} else if (ExecutorBlockStrategyEnum.COVER_EARLY == blockStrategy) {
// kill running jobThread
if (jobThread.isRunningOrHasQueue()) {
removeOldReason = "block strategy effect：" + ExecutorBlockStrategyEnum.COVER_EARLY.getTitle();
jobThread = null;
}
} else {
// just queue trigger
}
}
// replace thread (new or exists invalid)
// 如果jobThread为空，那么这个时候，就要注册一个线程到本地线程库里面去。 同时启动这个线程。
if (jobThread == null) {
jobThread = XxlJobExecutor.registJobThread(triggerParam.getJobId(), jobHandler, removeOldReason);
}
// push data to queue
// 将本次任务的参数 ，放入到队列里面去，供线程调度。
ReturnT pushResult = jobThread.pushTriggerQueue(triggerParam);
return pushResult;
}
以上过程主要是通过jobid，从本地线程库去获取该任务对应的线程，同时，如果任务的JobHandler有更新的话，那么会自动使用最新的jobHandler，其次根据任务的阻塞策略，执行不同的操作。最终，如果是第一次执行任务的时候，系统会分配给任务一个线程，同时启动该线程。最后，看下任务的执行方法，JobThread.run()，源码如下：
@Override
public void run() {
// init
try {
// 执行IJobHandler 中的init方法，以后如果有一些，在执行handler之前的初始化的工作，可以覆写这个方法
handler.init();
} catch (Throwable e) {
logger.error(e.getMessage(), e);
}
// execute
while(!toStop){
running = false;
idleTimes++;
TriggerParam triggerParam = null;
ReturnT executeResult = null;
try {
// to check toStop signal, we need cycle, so wo cannot use queue.take(), instand of poll(timeout)
triggerParam = triggerQueue.poll(3L, TimeUnit.SECONDS);
if (triggerParam!=null) {
running = true;
idleTimes = 0;
triggerLogIdSet.remove(triggerParam.getLogId());
// log filename, like "logPath/yyyy-MM-dd/9999.log"
String logFileName = XxlJobFileAppender.makeLogFileName(new Date(triggerParam.getLogDateTim()), triggerParam.getLogId());
XxlJobFileAppender.contextHolder.set(logFileName);
// 写入分片信息， 将当前机器的分片标记和分片总数写入到ShardingUtil中
ShardingUtil.setShardingVo(new ShardingUtil.ShardingVO(triggerParam.getBroadcastIndex(), triggerParam.getBroadcastTotal()));
// execute
XxlJobLogger.log("
----------- xxl-job job execute start -----------
----------- Param:" + triggerParam.getExecutorParams());
if (triggerParam.getExecutorTimeout() > 0) {
// limit timeout
Thread futureThread = null;
try {
final TriggerParam triggerParamTmp = triggerParam;
FutureTask> futureTask = new FutureTask>(new Callable>() {
@Override
public ReturnT call() throws Exception {
// 执行
return handler.execute(triggerParamTmp.getExecutorParams());
}
});
futureThread = new Thread(futureTask);
futureThread.start();
executeResult = futureTask.get(triggerParam.getExecutorTimeout(), TimeUnit.SECONDS);
} catch (TimeoutException e) {
XxlJobLogger.log("
----------- xxl-job job execute timeout");
XxlJobLogger.log(e);
executeResult = new ReturnT(IJobHandler.FAIL_TIMEOUT.getCode(), "job execute timeout ");
} finally {
futureThread.interrupt();
}
} else {
// just execute
executeResult = handler.execute(triggerParam.getExecutorParams());
}
if (executeResult == null) {
executeResult = IJobHandler.FAIL;
}
XxlJobLogger.log("
----------- xxl-job job execute end(finish) -----------
----------- ReturnT:" + executeResult);
} else {
if (idleTimes > 30) {
XxlJobExecutor.removeJobThread(jobId, "excutor idel times over limit.");
}
}
} catch (Throwable e) {
if (toStop) {
XxlJobLogger.log("
----------- JobThread toStop, stopReason:" + stopReason);
}
StringWriter stringWriter = new StringWriter();
e.printStackTrace(new PrintWriter(stringWriter));
String errorMsg = stringWriter.toString();
executeResult = new ReturnT(ReturnT.FAIL_CODE, errorMsg);
XxlJobLogger.log("
----------- JobThread Exception:" + errorMsg + "
----------- xxl-job job execute end(error) -----------");
} finally {
if(triggerParam != null) {
// callback handler info
if (!toStop) {
// commonm
TriggerCallbackThread.pushCallBack(new HandleCallbackParam(triggerParam.getLogId(), triggerParam.getLogDateTim(), executeResult));
} else {
// is killed
ReturnT stopResult = new ReturnT(ReturnT.FAIL_CODE, stopReason + " [job running，killed]");
TriggerCallbackThread.pushCallBack(new HandleCallbackParam(triggerParam.getLogId(), triggerParam.getLogDateTim(), stopResult));
}
}
}
}
// callback trigger request in queue
while(triggerQueue !=null && triggerQueue.size()>0){
TriggerParam triggerParam = triggerQueue.poll();
if (triggerParam!=null) {
// is killed
ReturnT stopResult = new ReturnT(ReturnT.FAIL_CODE, stopReason + " [job not executed, in the job queue, killed.]");
// handler执行完成之后，将结果写入到日志里面去， 就是在执行器启动的时候，会建立一个线程，用来实时处理日志，此处是将结果和logID放入到队列里面去，
// 日志线程异步的去处理
TriggerCallbackThread.pushCallBack(new HandleCallbackParam(triggerParam.getLogId(), triggerParam.getLogDateTim(), stopResult));
}
}
// destroy
try {
handler.destroy();
} catch (Throwable e) {
logger.error(e.getMessage(), e);
}
logger.info(">>>>>>>>>>> xxl-job JobThread stoped, hashCode:{}", Thread.currentThread());
}
【总结】
通过以上分析过程，只能说大致了解了执行器处理的过程，结合之前的几篇博客，只能说是对xxl-job有了大概的了解，学习过程中，除了官网资料，还查了不少其他博客文章做参考，便于自己理解。
从最开始的demo实例到源码分析，这一系列博客下来，还是学习到很多。源码分析过程中并不是源码都能看懂，但在看代码过程中还是看到了不少熟悉的代码，类似线程，队列，其他工具类的使用，这也是一个积累，以后将其用在项目实践中也是很好的。