序
本文主要研究一下powerjob的单机线程并发度(threadConcurrency)
threadConcurrency
powerjob-worker/src/main/java/tech/powerjob/worker/pojo/model/InstanceInfo.java
@Data
public class InstanceInfo implements Serializable {
/**
* 基础信息
*/
private Long jobId;
private Long instanceId;
private Long wfInstanceId;
/**
* 任务执行处理器信息
*/
// 任务执行类型，单机、广播、MR
private String executeType;
// 处理器类型（JavaBean、Jar、脚本等）
private String processorType;
// 处理器信息
private String processorInfo;
// 定时类型
private int timeExpressionType;
/**
* 超时时间
*/
// 整个任务的总体超时时间
private long instanceTimeoutMS;
/**
* 任务运行参数
*/
// 任务级别的参数，相当于类的static变量
private String jobParams;
// 实例级别的参数，相当于类的普通变量
private String instanceParams;
// 每台机器的处理线程数上限
private int threadConcurrency;
// 子任务重试次数（任务本身的重试机制由server控制）
private int taskRetryNum;
private String logConfig;
}InstanceInfo定义了threadConcurrency，即每台机器的处理线程数上限
maxDispatchNum
powerjob-worker/src/main/java/tech/powerjob/worker/core/tracker/task/heavy/HeavyTaskTracker.java
/**
* 定时扫描数据库中的task（出于内存占用量考虑，每次最多获取100个），并将需要执行的任务派发出去
*/
protected class Dispatcher implements Runnable {
// 数据库查询限制，每次最多查询几个任务
private static final int DB_QUERY_LIMIT = 100;
@Override
public void run() {
if (finished.get()) {
return;
}
Stopwatch stopwatch = Stopwatch.createStarted();
// 1. 获取可以派发任务的 ProcessorTracker
List<String> availablePtIps = ptStatusHolder.getAvailableProcessorTrackers();
// 2. 没有可用 ProcessorTracker，本次不派发
if (availablePtIps.isEmpty()) {
log.debug("[TaskTracker-{}] no available ProcessorTracker now.", instanceId);
return;
}
// 3. 避免大查询，分批派发任务
long currentDispatchNum = 0;
long maxDispatchNum = availablePtIps.size() * instanceInfo.getThreadConcurrency() * 2L;
AtomicInteger index = new AtomicInteger(0);
// 4. 循环查询数据库，获取需要派发的任务
while (maxDispatchNum > currentDispatchNum) {
int dbQueryLimit = Math.min(DB_QUERY_LIMIT, (int) maxDispatchNum);
List<TaskDO> needDispatchTasks = taskPersistenceService.getTaskByStatus(instanceId, TaskStatus.WAITING_DISPATCH, dbQueryLimit);
currentDispatchNum += needDispatchTasks.size();
needDispatchTasks.forEach(task -> {
// 获取 ProcessorTracker 地址，如果 Task 中自带了 Address，则使用该 Address
String ptAddress = task.getAddress();
if (StringUtils.isEmpty(ptAddress) || RemoteConstant.EMPTY_ADDRESS.equals(ptAddress)) {
ptAddress = availablePtIps.get(index.getAndIncrement() % availablePtIps.size());
}
dispatchTask(task, ptAddress);
});
// 数量不足 或 查询失败，则终止循环
if (needDispatchTasks.size() < dbQueryLimit) {
break;
}
}
log.debug("[TaskTracker-{}] dispatched {} tasks,using time {}.", instanceId, currentDispatchNum, stopwatch.stop());
}
}这里会计算maxDispatchNum(availablePtIps.size() * instanceInfo.getThreadConcurrency() * 2L)，之后通过availablePtIps.get(index.getAndIncrement() % availablePtIps.size())去轮询派发任务
ProcessorTracker
powerjob-worker/src/main/java/tech/powerjob/worker/core/tracker/processor/ProcessorTracker.java
calThreadPoolSize
private int calThreadPoolSize() {
ExecuteType executeType = ExecuteType.valueOf(instanceInfo.getExecuteType());
ProcessorType processorType = ProcessorType.valueOf(instanceInfo.getProcessorType());
// 脚本类自带线程池，不过为了少一点逻辑判断，还是象征性分配一个线程
if (processorType == ProcessorType.PYTHON || processorType == ProcessorType.SHELL) {
return 1;
}
if (executeType == ExecuteType.MAP_REDUCE || executeType == ExecuteType.MAP) {
return instanceInfo.getThreadConcurrency();
}
if (TimeExpressionType.FREQUENT_TYPES.contains(instanceInfo.getTimeExpressionType())) {
return instanceInfo.getThreadConcurrency();
}
return 2;
}ProcessorTracker的calThreadPoolSize方法会根据ProcessorType、ExecuteType、TimeExpressionType来确定线程池大小，比如ProcessorType.PYTHON或者ProcessorType.SHELL返回1，ExecuteType.MAP_REDUCE、ExecuteType.MAP、TimeExpressionType.FREQUENT_TYPES返回的是instanceInfo.greadConcurrency()
initThreadPool
private static final int THREAD_POOL_QUEUE_MAX_SIZE = 128;
private void initThreadPool() {
int poolSize = calThreadPoolSize();
// 待执行队列，为了防止对内存造成较大压力，内存队列不能太大
BlockingQueue<Runnable> queue = new ArrayBlockingQueue<>(THREAD_POOL_QUEUE_MAX_SIZE);
// 自定义线程池中线程名称 (PowerJob Processor Pool -> PPP)
ThreadFactory threadFactory = new ThreadFactoryBuilder().setNameFormat("PPP-%d").build();
// 拒绝策略：直接抛出异常
RejectedExecutionHandler rejectionHandler = new ThreadPoolExecutor.AbortPolicy();
threadPool = new ThreadPoolExecutor(poolSize, poolSize, 60L, TimeUnit.SECONDS, queue, threadFactory, rejectionHandler);
// 当没有任务执行时，允许销毁核心线程（即线程池最终存活线程个数可能为0）
threadPool.allowCoreThreadTimeOut(true);
}initThreadPool这里创建了ArrayBlockingQueue，大小为128，RejectedExecutionHandler为AbortPolicy，直接抛出异常RejectedExecutionExceptionsubmitTask
public void submitTask(TaskDO newTask) {
// 一旦 ProcessorTracker 出现异常，所有提交到此处的任务直接返回失败，防止形成死锁
// 死锁分析：TT创建PT，PT创建失败，无法定期汇报心跳，TT长时间未收到PT心跳，认为PT宕机（确实宕机了），无法选择可用的PT再次派发任务，死锁形成，GG斯密达 T_T
if (lethal) {
ProcessorReportTaskStatusReq report = new ProcessorReportTaskStatusReq()
.setInstanceId(instanceId)
.setSubInstanceId(newTask.getSubInstanceId())
.setTaskId(newTask.getTaskId())
.setStatus(TaskStatus.WORKER_PROCESS_FAILED.getValue())
.setResult(lethalReason)
.setReportTime(System.currentTimeMillis());
TransportUtils.ptReportTask(report, taskTrackerAddress, workerRuntime);
return;
}
boolean success = false;
// 1. 设置值并提交执行
newTask.setInstanceId(instanceInfo.getInstanceId());
newTask.setAddress(taskTrackerAddress);
HeavyProcessorRunnable heavyProcessorRunnable = new HeavyProcessorRunnable(instanceInfo, taskTrackerAddress, newTask, processorBean, omsLogger, statusReportRetryQueue, workerRuntime);
try {
threadPool.submit(heavyProcessorRunnable);
success = true;
} catch (RejectedExecutionException ignore) {
log.warn("[ProcessorTracker-{}] submit task(taskId={},taskName={}) to ThreadPool failed due to ThreadPool has too much task waiting to process, this task will dispatch to other ProcessorTracker.",
instanceId, newTask.getTaskId(), newTask.getTaskName());
} catch (Exception e) {
log.error("[ProcessorTracker-{}] submit task(taskId={},taskName={}) to ThreadPool failed.", instanceId, newTask.getTaskId(), newTask.getTaskName(), e);
}
// 2. 回复接收成功
if (success) {
ProcessorReportTaskStatusReq reportReq = new ProcessorReportTaskStatusReq();
reportReq.setInstanceId(instanceId);
reportReq.setSubInstanceId(newTask.getSubInstanceId());
reportReq.setTaskId(newTask.getTaskId());
reportReq.setStatus(TaskStatus.WORKER_RECEIVED.getValue());
reportReq.setReportTime(System.currentTimeMillis());
TransportUtils.ptReportTask(reportReq, taskTrackerAddress, workerRuntime);
log.debug("[ProcessorTracker-{}] submit task(taskId={}, taskName={}) success, current queue size: {}.",
instanceId, newTask.getTaskId(), newTask.getTaskName(), threadPool.getQueue().size());
}
}submitTask这里会根据TaskDO创建HeavyProcessorRunnable，然后提交到threadPool，若有异常则success为false，只有成功了才会创建ProcessorReportTaskStatusReq，回复接收任务成功。若有RejectedExecutionException则会打印warn日志[ProcessorTracker-{}] submit task(taskId={},taskName={}) to ThreadPool failed due to ThreadPool has too much task waiting to process, this task will dispatch to other ProcessorTracker.onReceiveProcessorReportTaskStatusReq
powerjob-worker/src/main/java/tech/powerjob/worker/actors/TaskTrackerActor.java
@Handler(path = WTT_HANDLER_REPORT_TASK_STATUS)
public AskResponse onReceiveProcessorReportTaskStatusReq(ProcessorReportTaskStatusReq req) {
int taskStatus = req.getStatus();
// 只有重量级任务才会有两级任务状态上报的机制
HeavyTaskTracker taskTracker = HeavyTaskTrackerManager.getTaskTracker(req.getInstanceId());
// 手动停止 TaskTracker 的情况下会出现这种情况
if (taskTracker == null) {
log.warn("[TaskTrackerActor] receive ProcessorReportTaskStatusReq({}) but system can't find TaskTracker.", req);
return null;
}
if (ProcessorReportTaskStatusReq.BROADCAST.equals(req.getCmd())) {
taskTracker.broadcast(taskStatus == TaskStatus.WORKER_PROCESS_SUCCESS.getValue(), req.getSubInstanceId(), req.getTaskId(), req.getResult());
}
taskTracker.updateTaskStatus(req.getSubInstanceId(), req.getTaskId(), taskStatus, req.getReportTime(), req.getResult());
// 更新工作流上下文
taskTracker.updateAppendedWfContext(req.getAppendedWfContext());
// 结束状态需要回复接受成功
if (TaskStatus.FINISHED_STATUS.contains(taskStatus)) {
return AskResponse.succeed(null);
}
return null;
}TaskTrackerActor接收到ProcessorReportTaskStatusReq，会通过updateTaskStatus更新状态，如果是FINISHED_STATUS状态则回复接收成功AskResponse.succeed(null)
TaskStatus
powerjob-worker/src/main/java/tech/powerjob/worker/common/constants/TaskStatus.java
@Getter
@AllArgsConstructor
public enum TaskStatus {
WAITING_DISPATCH(1, "等待调度器调度"),
DISPATCH_SUCCESS_WORKER_UNCHECK(2, "调度成功（但不保证worker收到）"),
WORKER_RECEIVED(3, "worker接收成功，但未开始执行"),
WORKER_PROCESSING(4, "worker正在执行"),
WORKER_PROCESS_FAILED(5, "worker执行失败"),
WORKER_PROCESS_SUCCESS(6, "worker执行成功");
public static final Set<Integer> FINISHED_STATUS = Sets.newHashSet(WORKER_PROCESS_FAILED.value, WORKER_PROCESS_SUCCESS.value);
private final int value;
private final String des;
public static TaskStatus of(int v) {
for (TaskStatus taskStatus : values()) {
if (v == taskStatus.value) {
return taskStatus;
}
}
throw new IllegalArgumentException("no TaskStatus match the value of " + v);
}
}task_info表中的status一共有等待调度WAITING_DISPATCH、调度DISPATCH_SUCCESS_WORKER_UNCHECK、worker接收成功WORKER_RECEIVED、worker处理中WORKER_PROCESSING、worker处理失败WORKER_PROCESS_FAILED、worker处理成功WORKER_PROCESS_SUCCESS这几个状态，其中处理成功和处理失败为完结状态
HeavyProcessorRunnable
powerjob-worker/src/main/java/tech/powerjob/worker/core/processor/runnable/HeavyProcessorRunnable.java
public void run() {
// 切换线程上下文类加载器（否则用的是 Worker 类加载器，不存在容器类，在序列化/反序列化时会报 ClassNotFoundException）
Thread.currentThread().setContextClassLoader(processorBean.getClassLoader());
try {
innerRun();
} catch (InterruptedException ignore) {
// ignore
} catch (Throwable e) {
reportStatus(TaskStatus.WORKER_PROCESS_FAILED, e.toString(), null, null);
log.error("[ProcessorRunnable-{}] execute failed, please contact the author(@KFCFans) to fix the bug!", task.getInstanceId(), e);
} finally {
ThreadLocalStore.clear();
}
}
public void innerRun() throws InterruptedException {
final BasicProcessor processor = processorBean.getProcessor();
String taskId = task.getTaskId();
Long instanceId = task.getInstanceId();
log.debug("[ProcessorRunnable-{}] start to run task(taskId={}&taskName={})", instanceId, taskId, task.getTaskName());
ThreadLocalStore.setTask(task);
ThreadLocalStore.setRuntimeMeta(workerRuntime);
// 0. 构造任务上下文
WorkflowContext workflowContext = constructWorkflowContext();
TaskContext taskContext = constructTaskContext();
taskContext.setWorkflowContext(workflowContext);
// 1. 上报执行信息
reportStatus(TaskStatus.WORKER_PROCESSING, null, null, null);
ProcessResult processResult;
ExecuteType executeType = ExecuteType.valueOf(instanceInfo.getExecuteType());
// 2. 根任务 & 广播执行 特殊处理
if (TaskConstant.ROOT_TASK_NAME.equals(task.getTaskName()) && executeType == ExecuteType.BROADCAST) {
// 广播执行：先选本机执行 preProcess，完成后 TaskTracker 再为所有 Worker 生成子 Task
handleBroadcastRootTask(instanceId, taskContext);
return;
}
// 3. 最终任务特殊处理（一定和 TaskTracker 处于相同的机器）
if (TaskConstant.LAST_TASK_NAME.equals(task.getTaskName())) {
handleLastTask(taskId, instanceId, taskContext, executeType);
return;
}
// 4. 正式提交运行
try {
processResult = processor.process(taskContext);
if (processResult == null) {
processResult = new ProcessResult(false, "ProcessResult can't be null");
}
} catch (Throwable e) {
log.warn("[ProcessorRunnable-{}] task(id={},name={}) process failed.", instanceId, taskContext.getTaskId(), taskContext.getTaskName(), e);
processResult = new ProcessResult(false, e.toString());
}
reportStatus(processResult.isSuccess() ? TaskStatus.WORKER_PROCESS_SUCCESS : TaskStatus.WORKER_PROCESS_FAILED, suit(processResult.getMsg()), null, workflowContext.getAppendedContextData());
}HeavyProcessorRunnable的run方法委派给了innerRun，它捕获Throwable异常然后上报为WORKER_PROCESS_FAILED状态；innerRun方法在被执行时，先上报状态为WORKER_PROCESSING，之后回调processor.process进行处理，若处理成功则上报WORKER_PROCESS_SUCCESS，否则上报WORKER_PROCESS_FAILED
小结
powerjob的InstanceInfo定义了threadConcurrency，即每台机器的处理线程数上限
- HeavyTaskTracker会计算maxDispatchNum(
availablePtIps.size() * instanceInfo.getThreadConcurrency() * 2L)，之后通过availablePtIps.get(index.getAndIncrement() % availablePtIps.size())去轮询派发任务 - ProcessorTracker的calThreadPoolSize方法会根据ProcessorType、ExecuteType、TimeExpressionType来确定线程池大小，比如ProcessorType.PYTHON或者ProcessorType.SHELL返回1，ExecuteType.MAP_REDUCE、ExecuteType.MAP、TimeExpressionType.FREQUENT_TYPES返回的是instanceInfo.greadConcurrency()；initThreadPool这里创建了ArrayBlockingQueue，大小为128，RejectedExecutionHandler为AbortPolicy，直接抛出异常
RejectedExecutionException；submitTask这里会根据TaskDO创建HeavyProcessorRunnable，然后提交到threadPool，若有异常则success为false，只有成功了才会创建ProcessorReportTaskStatusReq，回复接收任务成功 - TaskTrackerActor接收到ProcessorReportTaskStatusReq，会通过updateTaskStatus更新状态，如果是FINISHED_STATUS状态则回复接收成功AskResponse.succeed(null)
- HeavyProcessorRunnable的run方法委派给了innerRun，它捕获Throwable异常然后上报为WORKER_PROCESS_FAILED状态；innerRun方法在被执行时，先上报状态为WORKER_PROCESSING，之后回调processor.process进行处理，若处理成功则上报WORKER_PROCESS_SUCCESS，否则上报WORKER_PROCESS_FAILED
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