elastic-job-lite源码解析
前段时间写过一遍文章<一文揭秘定时任务调度框架quartz>,有读者建议我再讲讲elastic-job这个任务调度框架，年末没有那么忙，就来学习一下elastic-job。
首先一点，elastic-job基于quartz，理解quartz的运行机制有助于对elastic-job的快速理解。
首先看一下elastic-job-lite的架构
我们知道quartz有三个重要的概念：Job,Trigger,Scheduler。那么elastic-job里面三个概念是什么体现的呢？
1.Job
LiteJob继承自quartz的job接口
import org.quartz.Job; import org.quartz.JobExecutionContext; import org.quartz.JobExecutionException; /** * Lite调度作业. * * @author zhangliang */ public final class LiteJob implements Job { @Setter private ElasticJob elasticJob; @Setter private JobFacade jobFacade; @Override public void execute(final JobExecutionContext context) throws JobExecutionException { JobExecutorFactory.getJobExecutor(elasticJob, jobFacade).execute(); } }
其中，
1.1 ElasticJob实现了不同的Job类型
1.2.JobFacade是作业内部服务门面服务
注意：elasticJob的特性在里面可以看到如：
任务分片：
将整体任务拆解为多个子任务
可通过服务器的增减弹性伸缩任务处理能力
分布式协调，任务服务器上下线的全自动发现与处理
容错性：
支持定时自我故障检测与自动修复
分布式任务分片唯一性保证
支持失效转移和错过任务重触发
任务跟踪
任务调度
public interface JobFacade { /** * 读取作业配置. * * @param fromCache 是否从缓存中读取 * @return 作业配置 */ JobRootConfiguration loadJobRootConfiguration(boolean fromCache); /** * 检查作业执行环境. * * @throws JobExecutionEnvironmentException 作业执行环境异常 */ void checkJobExecutionEnvironment() throws JobExecutionEnvironmentException; /** * 如果需要失效转移, 则执行作业失效转移. */ void failoverIfNecessary(); /** * 注册作业启动信息. * * @param shardingContexts 分片上下文 */ void registerJobBegin(ShardingContexts shardingContexts); /** * 注册作业完成信息. * * @param shardingContexts 分片上下文 */ void registerJobCompleted(ShardingContexts shardingContexts); /** * 获取当前作业服务器的分片上下文. * * @return 分片上下文 */ ShardingContexts getShardingContexts(); /** * 设置任务被错过执行的标记. * * @param shardingItems 需要设置错过执行的任务分片项 * @return 是否满足misfire条件 */ boolean misfireIfRunning(Collection<Integer> shardingItems); /** * 清除任务被错过执行的标记. * * @param shardingItems 需要清除错过执行的任务分片项 */ void clearMisfire(Collection<Integer> shardingItems); /** * 判断作业是否需要执行错过的任务. * * @param shardingItems 任务分片项集合 * @return 作业是否需要执行错过的任务 */ boolean isExecuteMisfired(Collection<Integer> shardingItems); /** * 判断作业是否符合继续运行的条件. * * <p>如果作业停止或需要重分片或非流式处理则作业将不会继续运行.</p> * * @return 作业是否符合继续运行的条件 */ boolean isEligibleForJobRunning(); /**判断是否需要重分片. * * @return 是否需要重分片 */ boolean isNeedSharding(); /** * 作业执行前的执行的方法. * * @param shardingContexts 分片上下文 */ void beforeJobExecuted(ShardingContexts shardingContexts); /** * 作业执行后的执行的方法. * * @param shardingContexts 分片上下文 */ void afterJobExecuted(ShardingContexts shardingContexts); /** * 发布执行事件. * * @param jobExecutionEvent 作业执行事件 */ void postJobExecutionEvent(JobExecutionEvent jobExecutionEvent); /** * 发布作业状态追踪事件. * * @param taskId 作业Id * @param state 作业执行状态 * @param message 作业执行消息 */ void postJobStatusTraceEvent(String taskId, State state, String message); }
2.JobDetail
通用的Job属性，定义在job.xsd
<xsd:complexType name="base"> <xsd:complexContent> <xsd:extension base="beans:identifiedType"> <xsd:all> <xsd:element ref="listener" minOccurs="0" maxOccurs="1" /> <xsd:element ref="distributed-listener" minOccurs="0" maxOccurs="1" /> </xsd:all> <xsd:attribute name="class" type="xsd:string" /> <xsd:attribute name="job-ref" type="xsd:string" /> <xsd:attribute name="registry-center-ref" type="xsd:string" use="required" /> <xsd:attribute name="cron" type="xsd:string" use="required" /> <xsd:attribute name="sharding-total-count" type="xsd:string" use="required" /> <xsd:attribute name="sharding-item-parameters" type="xsd:string" /> <xsd:attribute name="job-parameter" type="xsd:string" /> <xsd:attribute name="monitor-execution" type="xsd:string" default="true"/> <xsd:attribute name="monitor-port" type="xsd:string" default="-1"/> <xsd:attribute name="max-time-diff-seconds" type="xsd:string" default="-1"/> <xsd:attribute name="failover" type="xsd:string" default="false"/> <xsd:attribute name="reconcile-interval-minutes" type="xsd:int" default="10"/> <xsd:attribute name="misfire" type="xsd:string" default="true"/> <xsd:attribute name="job-sharding-strategy-class" type="xsd:string" /> <xsd:attribute name="description" type="xsd:string" /> <xsd:attribute name="disabled" type="xsd:string" default="false"/> <xsd:attribute name="overwrite" type="xsd:string" default="false"/> <xsd:attribute name="executor-service-handler" type="xsd:string" default="io.elasticjob.lite.executor.handler.impl.DefaultExecutorServiceHandler"/> <xsd:attribute name="job-exception-handler" type="xsd:string" default="io.elasticjob.lite.executor.handler.impl.DefaultJobExceptionHandler"/> <xsd:attribute name="event-trace-rdb-data-source" type="xsd:string" /> </xsd:extension> </xsd:complexContent> </xsd:complexType>
其中Simple类型的任务完全继承通用属性，dataflow类型的任务增加了streaming-process属性，script增加了script-command-line属性
使用的解析器定义在spring.handlers
http\://www.dangdang.com/schema/ddframe/reg=io.elasticjob.lite.spring.reg.handler.RegNamespaceHandler
http\://www.dangdang.com/schema/ddframe/job=io.elasticjob.lite.spring.job.handler.JobNamespaceHandler
JobNamespaceHandler
/** * 分布式作业的命名空间处理器. * * @author caohao */ public final class JobNamespaceHandler extends NamespaceHandlerSupport { @Override public void init() { registerBeanDefinitionParser("simple", new SimpleJobBeanDefinitionParser()); registerBeanDefinitionParser("dataflow", new DataflowJobBeanDefinitionParser()); registerBeanDefinitionParser("script", new ScriptJobBeanDefinitionParser()); } }
在弹性化分布式作业执行器AbstractElasticJobExecutor.java初始化时获取配置属性，并使用对应的Handler进行处理。
protected AbstractElasticJobExecutor(final JobFacade jobFacade) { this.jobFacade = jobFacade; jobRootConfig = jobFacade.loadJobRootConfiguration(true); jobName = jobRootConfig.getTypeConfig().getCoreConfig().getJobName(); executorService = ExecutorServiceHandlerRegistry.getExecutorServiceHandler(jobName, (ExecutorServiceHandler) getHandler(JobProperties.JobPropertiesEnum.EXECUTOR_SERVICE_HANDLER)); jobExceptionHandler = (JobExceptionHandler) getHandler(JobProperties.JobPropertiesEnum.JOB_EXCEPTION_HANDLER); itemErrorMessages = new ConcurrentHashMap<>(jobRootConfig.getTypeConfig().getCoreConfig().getShardingTotalCount(), 1); }
3 执行作业
弹性化分布式作业执行器AbstractElasticJobExecutor.java
/**
* 执行作业.
*/
public final void execute() {
try {
jobFacade.checkJobExecutionEnvironment(); //1
} catch (final JobExecutionEnvironmentException cause) {
jobExceptionHandler.handleException(jobName, cause);
}
ShardingContexts shardingContexts = jobFacade.getShardingContexts(); //2
if (shardingContexts.isAllowSendJobEvent()) {
jobFacade.postJobStatusTraceEvent(shardingContexts.getTaskId(), State.TASK_STAGING, String.format("Job '%s' execute begin.", jobName)); //3
}
if (jobFacade.misfireIfRunning(shardingContexts.getShardingItemParameters().keySet())) {
if (shardingContexts.isAllowSendJobEvent()) {
jobFacade.postJobStatusTraceEvent(shardingContexts.getTaskId(), State.TASK_FINISHED, String.format(
"Previous job '%s' - shardingItems '%s' is still running, misfired job will start after previous job completed.", jobName,
shardingContexts.getShardingItemParameters().keySet()));
}
return;
}
try {
jobFacade.beforeJobExecuted(shardingContexts); //4
//CHECKSTYLE:OFF
} catch (final Throwable cause) {
//CHECKSTYLE:ON
jobExceptionHandler.handleException(jobName, cause);
}
execute(shardingContexts, JobExecutionEvent.ExecutionSource.NORMAL_TRIGGER); //5
while (jobFacade.isExecuteMisfired(shardingContexts.getShardingItemParameters().keySet())) {
jobFacade.clearMisfire(shardingContexts.getShardingItemParameters().keySet());
execute(shardingContexts, JobExecutionEvent.ExecutionSource.MISFIRE);
}
jobFacade.failoverIfNecessary(); //6
try {
jobFacade.afterJobExecuted(shardingContexts); //7
//CHECKSTYLE:OFF
} catch (final Throwable cause) {
//CHECKSTYLE:ON
jobExceptionHandler.handleException(jobName, cause);
}
}
3.1 环境监测
检查本机与注册中心的时间误差秒数是否在允许范围
/** * 检查本机与注册中心的时间误差秒数是否在允许范围. * * @throws JobExecutionEnvironmentException 本机与注册中心的时间误差秒数不在允许范围所抛出的异常 */ public void checkMaxTimeDiffSecondsTolerable() throws JobExecutionEnvironmentException { int maxTimeDiffSeconds = load(true).getMaxTimeDiffSeconds(); if (-1 == maxTimeDiffSeconds) { return; } long timeDiff = Math.abs(timeService.getCurrentMillis() - jobNodeStorage.getRegistryCenterTime()); if (timeDiff > maxTimeDiffSeconds * 1000L) { throw new JobExecutionEnvironmentException( "Time different between job server and register center exceed '%s' seconds, max time different is '%s' seconds.", timeDiff / 1000, maxTimeDiffSeconds); } }
3.2 根据分片规则进行分片
如果需要分片且当前节点为主节点, 则作业分片.
如果当前无可用节点则不分片.
/** * 如果需要分片且当前节点为主节点, 则作业分片. * * <p> * 如果当前无可用节点则不分片. * </p> */ public void shardingIfNecessary() { List<JobInstance> availableJobInstances = instanceService.getAvailableJobInstances(); if (!isNeedSharding() || availableJobInstances.isEmpty()) { return; } if (!leaderService.isLeaderUntilBlock()) { blockUntilShardingCompleted(); return; } waitingOtherShardingItemCompleted(); LiteJobConfiguration liteJobConfig = configService.load(false); int shardingTotalCount = liteJobConfig.getTypeConfig().getCoreConfig().getShardingTotalCount(); log.debug("Job '{}' sharding begin.", jobName); jobNodeStorage.fillEphemeralJobNode(ShardingNode.PROCESSING, ""); resetShardingInfo(shardingTotalCount); JobShardingStrategy jobShardingStrategy = JobShardingStrategyFactory.getStrategy(liteJobConfig.getJobShardingStrategyClass()); jobNodeStorage.executeInTransaction(new PersistShardingInfoTransactionExecutionCallback(jobShardingStrategy.sharding(availableJobInstances, jobName, shardingTotalCount))); log.debug("Job '{}' sharding complete.", jobName); }
3.3 使用EventBus通知
com.google.common.eventbus.EventBus
/** * Posts an event to all registered subscribers. This method will return * successfully after the event has been posted to all subscribers, and * regardless of any exceptions thrown by subscribers. * * <p>If no subscribers have been subscribed for {@code event}'s class, and * {@code event} is not already a {@link DeadEvent}, it will be wrapped in a * DeadEvent and reposted. * * @param event event to post. */ public void post(Object event) { Set<Class<?>> dispatchTypes = flattenHierarchy(event.getClass()); boolean dispatched = false; for (Class<?> eventType : dispatchTypes) { subscribersByTypeLock.readLock().lock(); try { Set<EventSubscriber> wrappers = subscribersByType.get(eventType); if (!wrappers.isEmpty()) { dispatched = true; for (EventSubscriber wrapper : wrappers) { enqueueEvent(event, wrapper); } } } finally { subscribersByTypeLock.readLock().unlock(); } } if (!dispatched && !(event instanceof DeadEvent)) { post(new DeadEvent(this, event)); } dispatchQueuedEvents(); }
3.4 job预执行，监听ElasticJobListener
@Override public void beforeJobExecuted(final ShardingContexts shardingContexts) { for (ElasticJobListener each : elasticJobListeners) { each.beforeJobExecuted(shardingContexts); } }
3.5 job执行
private void execute(final ShardingContexts shardingContexts, final JobExecutionEvent.ExecutionSource executionSource) { if (shardingContexts.getShardingItemParameters().isEmpty()) { if (shardingContexts.isAllowSendJobEvent()) { jobFacade.postJobStatusTraceEvent(shardingContexts.getTaskId(), State.TASK_FINISHED, String.format("Sharding item for job '%s' is empty.", jobName)); } return; } jobFacade.registerJobBegin(shardingContexts);//1 String taskId = shardingContexts.getTaskId(); if (shardingContexts.isAllowSendJobEvent()) { jobFacade.postJobStatusTraceEvent(taskId, State.TASK_RUNNING, ""); } try { process(shardingContexts, executionSource);//2 } finally { // TODO 考虑增加作业失败的状态，并且考虑如何处理作业失败的整体回路 jobFacade.registerJobCompleted(shardingContexts); if (itemErrorMessages.isEmpty()) { if (shardingContexts.isAllowSendJobEvent()) { jobFacade.postJobStatusTraceEvent(taskId, State.TASK_FINISHED, ""); } } else { if (shardingContexts.isAllowSendJobEvent()) { jobFacade.postJobStatusTraceEvent(taskId, State.TASK_ERROR, itemErrorMessages.toString()); } } } }
>>1.将job注册到注册中心
>>2.将各个任务分片放到线程池中执行
3.6 实现转移
如果需要失效转移, 则执行作业失效转移.
/** * 在主节点执行操作. * * @param latchNode 分布式锁使用的作业节点名称 * @param callback 执行操作的回调 */ public void executeInLeader(final String latchNode, final LeaderExecutionCallback callback) { try (LeaderLatch latch = new LeaderLatch(getClient(), jobNodePath.getFullPath(latchNode))) { latch.start(); latch.await(); callback.execute(); //CHECKSTYLE:OFF } catch (final Exception ex) { //CHECKSTYLE:ON handleException(ex); } }
3.7 作业执行后处理
作业执行后的执行的方法
@Override public void afterJobExecuted(final ShardingContexts shardingContexts) { for (ElasticJobListener each : elasticJobListeners) { each.afterJobExecuted(shardingContexts); } }
4.Trigger
elasticJob默认使用Cron Trigger，在job属性里定义
<xsd:attribute name="cron" type="xsd:string" use="required" />
5.作业调度器JobScheduler
/** * 初始化作业. */ public void init() { LiteJobConfiguration liteJobConfigFromRegCenter = schedulerFacade.updateJobConfiguration(liteJobConfig); //1 JobRegistry.getInstance().setCurrentShardingTotalCount(liteJobConfigFromRegCenter.getJobName(), liteJobConfigFromRegCenter.getTypeConfig().getCoreConfig().getShardingTotalCount()); JobScheduleController jobScheduleController = new JobScheduleController( createScheduler(), createJobDetail(liteJobConfigFromRegCenter.getTypeConfig().getJobClass()), liteJobConfigFromRegCenter.getJobName()); //2 JobRegistry.getInstance().registerJob(liteJobConfigFromRegCenter.getJobName(), jobScheduleController, regCenter); //3 schedulerFacade.registerStartUpInfo(!liteJobConfigFromRegCenter.isDisabled()); jobScheduleController.scheduleJob(liteJobConfigFromRegCenter.getTypeConfig().getCoreConfig().getCron()); //4 } private JobDetail createJobDetail(final String jobClass) { JobDetail result = JobBuilder.newJob(LiteJob.class).withIdentity(liteJobConfig.getJobName()).build(); result.getJobDataMap().put(JOB_FACADE_DATA_MAP_KEY, jobFacade); Optional<ElasticJob> elasticJobInstance = createElasticJobInstance(); if (elasticJobInstance.isPresent()) { result.getJobDataMap().put(ELASTIC_JOB_DATA_MAP_KEY, elasticJobInstance.get()); } else if (!jobClass.equals(ScriptJob.class.getCanonicalName())) { try { result.getJobDataMap().put(ELASTIC_JOB_DATA_MAP_KEY, Class.forName(jobClass).newInstance()); } catch (final ReflectiveOperationException ex) { throw new JobConfigurationException("Elastic-Job: Job class '%s' can not initialize.", jobClass); } } return result; } protected Optional<ElasticJob> createElasticJobInstance() { return Optional.absent(); } private Scheduler createScheduler() { Scheduler result; try { StdSchedulerFactory factory = new StdSchedulerFactory(); factory.initialize(getBaseQuartzProperties()); result = factory.getScheduler(); result.getListenerManager().addTriggerListener(schedulerFacade.newJobTriggerListener()); } catch (final SchedulerException ex) { throw new JobSystemException(ex); } return result; } private Properties getBaseQuartzProperties() { Properties result = new Properties(); result.put("org.quartz.threadPool.class", org.quartz.simpl.SimpleThreadPool.class.getName()); result.put("org.quartz.threadPool.threadCount", "1"); result.put("org.quartz.scheduler.instanceName", liteJobConfig.getJobName()); result.put("org.quartz.jobStore.misfireThreshold", "1"); result.put("org.quartz.plugin.shutdownhook.class", JobShutdownHookPlugin.class.getName()); result.put("org.quartz.plugin.shutdownhook.cleanShutdown", Boolean.TRUE.toString()); return result; }
5.1 更新作业配置.
/** * 更新作业配置. * * @param liteJobConfig 作业配置 * @return 更新后的作业配置 */ public LiteJobConfiguration updateJobConfiguration(final LiteJobConfiguration liteJobConfig) { configService.persist(liteJobConfig); return configService.load(false); }
5.2 初始化一系列操作
5.2.1 创建quartz scheduler
private Scheduler createScheduler() { Scheduler result; try { StdSchedulerFactory factory = new StdSchedulerFactory(); factory.initialize(getBaseQuartzProperties()); result = factory.getScheduler(); result.getListenerManager().addTriggerListener(schedulerFacade.newJobTriggerListener()); } catch (final SchedulerException ex) { throw new JobSystemException(ex); } return result; }
5.2.2 创建JobDetail
private JobDetail createJobDetail(final String jobClass) { JobDetail result = JobBuilder.newJob(LiteJob.class).withIdentity(liteJobConfig.getJobName()).build(); result.getJobDataMap().put(JOB_FACADE_DATA_MAP_KEY, jobFacade); Optional<ElasticJob> elasticJobInstance = createElasticJobInstance(); if (elasticJobInstance.isPresent()) { result.getJobDataMap().put(ELASTIC_JOB_DATA_MAP_KEY, elasticJobInstance.get()); } else if (!jobClass.equals(ScriptJob.class.getCanonicalName())) { try { result.getJobDataMap().put(ELASTIC_JOB_DATA_MAP_KEY, Class.forName(jobClass).newInstance()); } catch (final ReflectiveOperationException ex) { throw new JobConfigurationException("Elastic-Job: Job class '%s' can not initialize.", jobClass); } } return result; }
5.2.3 添加作业调度控制器.
/** * 添加作业调度控制器. * * @param jobName 作业名称 * @param jobScheduleController 作业调度控制器 * @param regCenter 注册中心 */ public void registerJob(final String jobName, final JobScheduleController jobScheduleController, final CoordinatorRegistryCenter regCenter) { schedulerMap.put(jobName, jobScheduleController); regCenterMap.put(jobName, regCenter); regCenter.addCacheData("/" + jobName); }
5.2.4 调度作业.
/** * 调度作业. * * @param cron CRON表达式 */ public void scheduleJob(final String cron) { try { if (!scheduler.checkExists(jobDetail.getKey())) { scheduler.scheduleJob(jobDetail, createTrigger(cron)); } scheduler.start(); } catch (final SchedulerException ex) { throw new JobSystemException(ex); } }
6.总结
>>elastic-job使用了quartz的调度机制，内部原理一致，增加了性能和可用性。
>>elastic-job使用注册中心(zookeeper)替换了quartz的jdbc数据存储方式，性能有较大提升。
>> elastic-job增加了job的追踪(使用Listener)，便于monitor
>>elastic-job使用了分片机制，可以将job分成多个任务项，放到不同的地方执行
>>elastic-job仅支持cronTrigger，quartz支持更多的trigger实现
版权声明：本文为davidwang456原创文章，遵循 CC 4.0 BY-SA 版权协议，转载请附上原文出处链接和本声明。