Saga模式源码方法教程
本篇内容主要讲解"Saga模式源码方法教程",感兴趣的朋友不妨来看看。本文介绍的方法操作简单快捷,实用性强。下面就让小编来带大家学习"Saga模式源码方法教程"吧!
状态机定义
以一个典型的电商购物流程为例,我们定义3个服务,订单服务(OrderServer),账户服务(AccountService)和库存服务(StorageService),这里我们把订单服务当做聚合服务,也就是TM。
当外部下单时,订单服务首先会创建一个订单,然后调用账户服务扣减金额,最后调用库存服务扣减库存。这个流程入下图:
seata的saga模式是基于状态机来实现了,状态机对状态的控制需要一个JSON文件,这个JSON文件定义如下:
{ "Name": "buyGoodsOnline", "Comment": "buy a goods on line, add order, deduct account, deduct storage ", "StartState": "SaveOrder", "Version": "0.0.1", "States": { "SaveOrder": { "Type": "ServiceTask", "ServiceName": "orderSave", "ServiceMethod": "saveOrder", "CompensateState": "DeleteOrder", "Next": "ChoiceAccountState", "Input": [ "$.[businessKey]", "$.[order]" ], "Output": { "SaveOrderResult": "$.#root" }, "Status": { "#root == true": "SU", "#root == false": "FA", "$Exception{java.lang.Throwable}": "UN" } }, "ChoiceAccountState":{ "Type": "Choice", "Choices":[ { "Expression":"[SaveOrderResult] == true", "Next":"ReduceAccount" } ], "Default":"Fail" }, "ReduceAccount": { "Type": "ServiceTask", "ServiceName": "accountService", "ServiceMethod": "decrease", "CompensateState": "CompensateReduceAccount", "Next": "ChoiceStorageState", "Input": [ "$.[businessKey]", "$.[userId]", "$.[money]", { "throwException" : "$.[mockReduceAccountFail]" } ], "Output": { "ReduceAccountResult": "$.#root" }, "Status": { "#root == true": "SU", "#root == false": "FA", "$Exception{java.lang.Throwable}": "UN" }, "Catch": [ { "Exceptions": [ "java.lang.Throwable" ], "Next": "CompensationTrigger" } ] }, "ChoiceStorageState":{ "Type": "Choice", "Choices":[ { "Expression":"[ReduceAccountResult] == true", "Next":"ReduceStorage" } ], "Default":"Fail" }, "ReduceStorage": { "Type": "ServiceTask", "ServiceName": "storageService", "ServiceMethod": "decrease", "CompensateState": "CompensateReduceStorage", "Input": [ "$.[businessKey]", "$.[productId]", "$.[count]", { "throwException" : "$.[mockReduceStorageFail]" } ], "Output": { "ReduceStorageResult": "$.#root" }, "Status": { "#root == true": "SU", "#root == false": "FA", "$Exception{java.lang.Throwable}": "UN" }, "Catch": [ { "Exceptions": [ "java.lang.Throwable" ], "Next": "CompensationTrigger" } ], "Next": "Succeed" }, "DeleteOrder": { "Type": "ServiceTask", "ServiceName": "orderSave", "ServiceMethod": "deleteOrder", "Input": [ "$.[businessKey]", "$.[order]" ] }, "CompensateReduceAccount": { "Type": "ServiceTask", "ServiceName": "accountService", "ServiceMethod": "compensateDecrease", "Input": [ "$.[businessKey]", "$.[userId]", "$.[money]" ] }, "CompensateReduceStorage": { "Type": "ServiceTask", "ServiceName": "storageService", "ServiceMethod": "compensateDecrease", "Input": [ "$.[businessKey]", "$.[productId]", "$.[count]" ] }, "CompensationTrigger": { "Type": "CompensationTrigger", "Next": "Fail" }, "Succeed": { "Type":"Succeed" }, "Fail": { "Type":"Fail", "ErrorCode": "PURCHASE_FAILED", "Message": "purchase failed" } } }
状态机是运行在TM中的,也就是我们上面定义的订单服务。订单服务创建订单时需要开启一个全局事务,这时就需要启动状态机,代码如下:
StateMachineEngine stateMachineEngine = (StateMachineEngine) ApplicationContextUtils.getApplicationContext().getBean("stateMachineEngine"); MapstartParams = new HashMap<>(3); String businessKey = String.valueOf(System.currentTimeMillis()); startParams.put("businessKey", businessKey); startParams.put("order", order); startParams.put("mockReduceAccountFail", "true"); startParams.put("userId", order.getUserId()); startParams.put("money", order.getPayAmount()); startParams.put("productId", order.getProductId()); startParams.put("count", order.getCount()); //sync test StateMachineInstance inst = stateMachineEngine.startWithBusinessKey("buyGoodsOnline", null, businessKey, startParams);
可以看到,上面代码定义的buyGoodsOnline,正是JSON文件中name的属性值。
状态机初始化
那上面创建订单代码中的stateMachineEngine这个bean是在哪里定义的呢?订单服务的demo中有一个类StateMachineConfiguration来进行定义,代码如下:
public class StateMachineConfiguration { @Bean public ThreadPoolExecutorFactoryBean threadExecutor(){ ThreadPoolExecutorFactoryBean threadExecutor = new ThreadPoolExecutorFactoryBean(); threadExecutor.setThreadNamePrefix("SAGA_ASYNC_EXE_"); threadExecutor.setCorePoolSize(1); threadExecutor.setMaxPoolSize(20); return threadExecutor; } @Bean public DbStateMachineConfig dbStateMachineConfig(ThreadPoolExecutorFactoryBean threadExecutor, DataSource hikariDataSource) throws IOException { DbStateMachineConfig dbStateMachineConfig = new DbStateMachineConfig(); dbStateMachineConfig.setDataSource(hikariDataSource); dbStateMachineConfig.setThreadPoolExecutor((ThreadPoolExecutor) threadExecutor.getObject()); /** *这里配置了json文件的路径,TM在初始化的时候,会把json文件解析成StateMachineImpl类,如果数据库没有保存这个状态机,则存入数据库seata_state_machine_def表, *如果数据库有记录,则取最新的一条记录,并且注册到StateMachineRepositoryImpl, *注册的Map有2个,一个是stateMachineMapByNameAndTenant,key格式是(stateMachineName + "_" + tenantId), *一个是stateMachineMapById,key是stateMachine.getId() *具体代码见StateMachineRepositoryImpl类registryStateMachine方法 *这个注册的触发方法在DefaultStateMachineConfig的初始化方法init(),这个类是DbStateMachineConfig的父类 */ dbStateMachineConfig.setResources(new PathMatchingResourcePatternResolver().getResources("classpath*:statelang/*.json"));//json文件 dbStateMachineConfig.setEnableAsync(true); dbStateMachineConfig.setApplicationId("order-server"); dbStateMachineConfig.setTxServiceGroup("my_test_tx_group"); return dbStateMachineConfig; } @Bean public ProcessCtrlStateMachineEngine stateMachineEngine(DbStateMachineConfig dbStateMachineConfig){ ProcessCtrlStateMachineEngine stateMachineEngine = new ProcessCtrlStateMachineEngine(); stateMachineEngine.setStateMachineConfig(dbStateMachineConfig); return stateMachineEngine; } @Bean public StateMachineEngineHolder stateMachineEngineHolder(ProcessCtrlStateMachineEngine stateMachineEngine){ StateMachineEngineHolder stateMachineEngineHolder = new StateMachineEngineHolder(); stateMachineEngineHolder.setStateMachineEngine(stateMachineEngine); return stateMachineEngineHolder; } }
可以看到,我们在DbStateMachineConfig中配置了状态机的json文件,同时配置了applicationId和txServiceGroup。在DbStateMachineConfig初始化的时候,子类DefaultStateMachineConfig的init的方法会把json文件解析成状态机,并注册。
注册的过程中往seata_state_machine_def这张表里插入了1条记录,表里的content字段保存了我们的JOSON文件内容,其他字段值数据如下图:
附:根据前面的JSON文件,我们debug跟踪到的StateMachineImpl的内容如下:
id = null tenantId = null appName = "SEATA" name = "buyGoodsOnline" comment = "buy a goods on line, add order, deduct account, deduct storage " version = "0.0.1" startState = "SaveOrder" status = {StateMachine$Status@9135} "AC" recoverStrategy = null isPersist = true type = "STATE_LANG" content = null gmtCreate = null states = {LinkedHashMap@9137} size = 11 "SaveOrder" -> {ServiceTaskStateImpl@9153} "ChoiceAccountState" -> {ChoiceStateImpl@9155} "ReduceAccount" -> {ServiceTaskStateImpl@9157} "ChoiceStorageState" -> {ChoiceStateImpl@9159} "ReduceStorage" -> {ServiceTaskStateImpl@9161} "DeleteOrder" -> {ServiceTaskStateImpl@9163} "CompensateReduceAccount" -> {ServiceTaskStateImpl@9165} "CompensateReduceStorage" -> {ServiceTaskStateImpl@9167} "CompensationTrigger" -> {CompensationTriggerStateImpl@9169} "Succeed" -> {SucceedEndStateImpl@9171} "Fail" -> {FailEndStateImpl@9173}
启动状态机
在第一节创建订单的代码中,startWithBusinessKey方法进行了整个事务的启动,这个方法还有一个异步模式startWithBusinessKeyAsync,这里我们只分析同步模式,源代码如下:
public StateMachineInstance startWithBusinessKey(String stateMachineName, String tenantId, String businessKey, MapstartParams) throws EngineExecutionException { return startInternal(stateMachineName, tenantId, businessKey, startParams, false, null); } private StateMachineInstance startInternal(String stateMachineName, String tenantId, String businessKey, Map startParams, boolean async, AsyncCallback callback) throws EngineExecutionException { //省略部分源代码 //创建一个状态机实例 //默认值tenantId="000001" StateMachineInstance instance = createMachineInstance(stateMachineName, tenantId, businessKey, startParams); /** * ProcessType.STATE_LANG这个枚举只有一个元素 * OPERATION_NAME_START = "start" * callback是null * getStateMachineConfig()返回DbStateMachineConfig */ ProcessContextBuilder contextBuilder = ProcessContextBuilder.create().withProcessType(ProcessType.STATE_LANG) .withOperationName(DomainConstants.OPERATION_NAME_START).withAsyncCallback(callback).withInstruction( new StateInstruction(stateMachineName, tenantId)).withStateMachineInstance(instance) .withStateMachineConfig(getStateMachineConfig()).withStateMachineEngine(this); Map contextVariables; if (startParams != null) { contextVariables = new ConcurrentHashMap<>(startParams.size()); nullSafeCopy(startParams, contextVariables); } else { contextVariables = new ConcurrentHashMap<>(); } instance.setContext(contextVariables);//把启动参数赋值给状态机实例的context //给ProcessContextImpl的variables加参数 contextBuilder.withStateMachineContextVariables(contextVariables); contextBuilder.withIsAsyncExecution(async); //上面定义的建造者创建一个ProcessContextImpl ProcessContext processContext = contextBuilder.build(); //这个条件是true if (instance.getStateMachine().isPersist() && stateMachineConfig.getStateLogStore() != null) { //记录状态机开始状态 stateMachineConfig.getStateLogStore().recordStateMachineStarted(instance, processContext); } if (StringUtils.isEmpty(instance.getId())) { instance.setId( stateMachineConfig.getSeqGenerator().generate(DomainConstants.SEQ_ENTITY_STATE_MACHINE_INST)); } if (async) { stateMachineConfig.getAsyncProcessCtrlEventPublisher().publish(processContext); } else { //发送消息到EventBus,这里的消费者是ProcessCtrlEventConsumer,在DefaultStateMachineConfig初始化时设置 stateMachineConfig.getProcessCtrlEventPublisher().publish(processContext); } return instance; }
上面的代码中我们可以看出,启动状态记得时候主要做了2件事情,一个是记录状态机开始的状态,一个是发送消息到EventBus,下面我们详细看一下这2个过程。
开启全局事务
上面的代码分析中,有一个记录状态机开始状态的代码,如下:
stateMachineConfig.getStateLogStore().recordStateMachineStarted(instance, processContext);
这里调用了类DbAndReportTcStateLogStore的recordStateMachineStarted方法,我们来看一下,代码如下:
public void recordStateMachineStarted(StateMachineInstance machineInstance, ProcessContext context) { if (machineInstance != null) { //if parentId is not null, machineInstance is a SubStateMachine, do not start a new global transaction, //use parent transaction instead. String parentId = machineInstance.getParentId(); if (StringUtils.hasLength(parentId)) { if (StringUtils.isEmpty(machineInstance.getId())) { machineInstance.setId(parentId); } } else { //走这个分支,因为没有配置子状态机 /** * 这里的beginTransaction就是开启全局事务, * 这里是调用TC开启全局事务 */ beginTransaction(machineInstance, context); } if (StringUtils.isEmpty(machineInstance.getId()) && seqGenerator != null) { machineInstance.setId(seqGenerator.generate(DomainConstants.SEQ_ENTITY_STATE_MACHINE_INST)); } // save to db //dbType = "MySQL" machineInstance.setSerializedStartParams(paramsSerializer.serialize(machineInstance.getStartParams())); executeUpdate(stateLogStoreSqls.getRecordStateMachineStartedSql(dbType), STATE_MACHINE_INSTANCE_TO_STATEMENT_FOR_INSERT, machineInstance); } }
上面executeUpdate方法在子类AbstractStore,debug一下executeUpdate这个方法可以看到,这里执行的sql如下:
INSERT INTO seata_state_machine_inst (id, machine_id, tenant_id, parent_id, gmt_started, business_key, start_params, is_running, status, gmt_updated) VALUES ('192.168.59.146:8091:65853497147990016', '06a098cab53241ca7ed09433342e9f07', '000001', null, '2020-10-31 17:18:24.773', '1604135904773', '{"@type":"java.util.HashMap","money":50.,"productId":1L,"_business_key_":"1604135904773","businessKey":"1604135904773", "count":1,"mockReduceAccountFail":"true","userId":1L,"order":{"@type":"io.seata.sample.entity.Order","count":1,"payAmount":50, "productId":1,"userId":1}}', 1, 'RU', '2020-10-31 17:18:24.773')
可以看到,这个全局事务记录在了表seata_state_machine_inst,记录的是我们启动状态机的参数,status记录的状态是"RU"也就是RUNNING。
分支事务处理
上一节我们提到,启动状态机后,向EventBus发了一条消息,这个消息的消费者是ProcessCtrlEventConsumer,我们看一下这个类的代码:
public class ProcessCtrlEventConsumer implements EventConsumer{ private ProcessController processController; @Override public void process(ProcessContext event) throws FrameworkException { //这里的processController是ProcessControllerImpl processController.process(event); } @Override public boolean accept(Class clazz) { return ProcessContext.class.isAssignableFrom(clazz); } public void setProcessController(ProcessController processController) { this.processController = processController; } }
ProcessControllerImpl类的process方法有2个处理逻辑,process和route,代码如下:
public void process(ProcessContext context) throws FrameworkException { try { //这里的businessProcessor是CustomizeBusinessProcessor businessProcessor.process(context); businessProcessor.route(context); } catch (FrameworkException fex) { throw fex; } catch (Exception ex) { LOGGER.error("Unknown exception occurred, context = {}", context, ex); throw new FrameworkException(ex, "Unknown exception occurred", FrameworkErrorCode.UnknownAppError); } }
这里的处理逻辑有些复杂,先上一张UML类图,跟着这张图,可以捋清楚代码的调用逻辑:
我们先来看一下CustomizeBusinessProcessor中的process方法:
public void process(ProcessContext context) throws FrameworkException { /** *processType = {ProcessType@10310} "STATE_LANG" *code = "STATE_LANG" *message = "SEATA State Language" *name = "STATE_LANG" *ordinal = 0 */ ProcessType processType = matchProcessType(context); if (processType == null) { if (LOGGER.isWarnEnabled()) { LOGGER.warn("Process type not found, context= {}", context); } throw new FrameworkException(FrameworkErrorCode.ProcessTypeNotFound); } ProcessHandler processor = processHandlers.get(processType.getCode()); if (processor == null) { LOGGER.error("Cannot find process handler by type {}, context= {}", processType.getCode(), context); throw new FrameworkException(FrameworkErrorCode.ProcessHandlerNotFound); } //这里的是StateMachineProcessHandler processor.process(context); }
这里的代码不好理解,我们分四步来研究。
第一步,我们看一下StateMachineProcessHandler类中process方法,这个方法代理了ServiceTaskStateHandler的process方法,代码如下:
public void process(ProcessContext context) throws FrameworkException { /** * instruction = {StateInstruction@11057} * stateName = null * stateMachineName = "buyGoodsOnline" * tenantId = "000001" * end = false * temporaryState = null */ StateInstruction instruction = context.getInstruction(StateInstruction.class); //这里的state实现类是ServiceTaskStateImpl State state = instruction.getState(context); String stateType = state.getType(); //这里stateHandler实现类是ServiceTaskStateHandler StateHandler stateHandler = stateHandlers.get(stateType); Listinterceptors = null; if (stateHandler instanceof InterceptableStateHandler) { //list上有1个元素ServiceTaskHandlerInterceptor interceptors = ((InterceptableStateHandler)stateHandler).getInterceptors(); } List executedInterceptors = null; Exception exception = null; try { if (interceptors != null && interceptors.size() > 0) { executedInterceptors = new ArrayList<>(interceptors.size()); for (StateHandlerInterceptor interceptor : interceptors) { executedInterceptors.add(interceptor); interceptor.preProcess(context); } } stateHandler.process(context); } catch (Exception e) { exception = e; throw e; } finally { if (executedInterceptors != null && executedInterceptors.size() > 0) { for (int i = executedInterceptors.size() - 1; i >= 0; i--) { StateHandlerInterceptor interceptor = executedInterceptors.get(i); interceptor.postProcess(context, exception); } } } }
从这个方法我们看到,代理对stateHandler.process加入了前置和后置增强,增强类是ServiceTaskHandlerInterceptor,前置后置增强分别调用了interceptor的preProcess和postProcess。
第二步,我们来看一下增强逻辑。ServiceTaskHandlerInterceptor的preProcess和postProcess方法,代码如下:
public class ServiceTaskHandlerInterceptor implements StateHandlerInterceptor { //省略部分代码 @Override public void preProcess(ProcessContext context) throws EngineExecutionException { StateInstruction instruction = context.getInstruction(StateInstruction.class); StateMachineInstance stateMachineInstance = (StateMachineInstance)context.getVariable( DomainConstants.VAR_NAME_STATEMACHINE_INST); StateMachineConfig stateMachineConfig = (StateMachineConfig)context.getVariable( DomainConstants.VAR_NAME_STATEMACHINE_CONFIG); //如果超时,修改状态机状态为FA if (EngineUtils.isTimeout(stateMachineInstance.getGmtUpdated(), stateMachineConfig.getTransOperationTimeout())) { String message = "Saga Transaction [stateMachineInstanceId:" + stateMachineInstance.getId() + "] has timed out, stop execution now."; EngineUtils.failStateMachine(context, exception); throw exception; } StateInstanceImpl stateInstance = new StateInstanceImpl(); MapcontextVariables = (Map )context.getVariable( DomainConstants.VAR_NAME_STATEMACHINE_CONTEXT); ServiceTaskStateImpl state = (ServiceTaskStateImpl)instruction.getState(context); List
从这个代码我们能看到,分支事务执行前,封装了一个StateInstanceImpl赋值给了ProcessContext,分支事务执行后,对这个StateInstanceImpl进行了修改,这个StateInstanceImpl有3个作用:
传入StateMachineInstanceImpl的stateMap用于重试或交易补偿
记录了分支事务的执行情况,同时支持持久化到seata_state_inst表
传入TaskStateRouter用作判断全局事务结束
第三步,我们看一下被代理的方法stateHandler.process(context),正常执行逻辑中stateHandler的实现类是ServiceTaskStateHandler,代码如下:
public void process(ProcessContext context) throws EngineExecutionException { StateInstruction instruction = context.getInstruction(StateInstruction.class); ServiceTaskStateImpl state = (ServiceTaskStateImpl) instruction.getState(context); StateInstance stateInstance = (StateInstance) context.getVariable(DomainConstants.VAR_NAME_STATE_INST); Object result; try { /** * 这里的input是我们在JSON中定义的,比如orderSave这个ServiceTask,input如下: * 0 = "1608714480316" * 1 = {Order@11271} "Order(id=null, userId=1, productId=1, count=1, payAmount=50, status=null)" * JSON中定义如下: * "Input": [ * "$.[businessKey]", * "$.[order]" * ] */ List
可以看到,process这个方法是一个核心的业务处理,它用发射触发了JSON中定义ServiceTask的方法,并且根据状态触发了Next对象,即流程中的下一个ServiceTask。
第四步,我们再看一下CustomizeBusinessProcessor的route方法,代码如下:
public void route(ProcessContext context) throws FrameworkException { //code = "STATE_LANG" //message = "SEATA State Language" //name = "STATE_LANG" //ordinal = 0 ProcessType processType = matchProcessType(context); RouterHandler router = routerHandlers.get(processType.getCode()); //DefaultRouterHandler的route方法 router.route(context); }
我们看一下DefaultRouterHandler的route方法,代码如下:
public void route(ProcessContext context) throws FrameworkException { try { ProcessType processType = matchProcessType(context); //这里的processRouter是StateMachineProcessRouter ProcessRouter processRouter = processRouters.get(processType.getCode()); Instruction instruction = processRouter.route(context); if (instruction == null) { LOGGER.info("route instruction is null, process end"); } else { context.setInstruction(instruction); eventPublisher.publish(context); } } catch (FrameworkException e) { throw e; } catch (Exception ex) { throw new FrameworkException(ex, ex.getMessage(), FrameworkErrorCode.UnknownAppError); } }
看一下StateMachineProcessRouter的route方法,这里也是用了代理模式,代码如下:
public Instruction route(ProcessContext context) throws FrameworkException { StateInstruction stateInstruction = context.getInstruction(StateInstruction.class); State state; if (stateInstruction.getTemporaryState() != null) { state = stateInstruction.getTemporaryState(); stateInstruction.setTemporaryState(null); } else { //走这个分支 StateMachineConfig stateMachineConfig = (StateMachineConfig)context.getVariable( DomainConstants.VAR_NAME_STATEMACHINE_CONFIG); StateMachine stateMachine = stateMachineConfig.getStateMachineRepository().getStateMachine( stateInstruction.getStateMachineName(), stateInstruction.getTenantId()); state = stateMachine.getStates().get(stateInstruction.getStateName()); } String stateType = state.getType(); StateRouter router = stateRouters.get(stateType); Instruction instruction = null; Listinterceptors = null; if (router instanceof InterceptableStateRouter) { //这里只有EndStateRouter interceptors = ((InterceptableStateRouter)router).getInterceptors();//EndStateRouterInterceptor } List executedInterceptors = null; Exception exception = null; try { //前置增量实现方法是空,这里省略代码 instruction = router.route(context, state); } catch (Exception e) { exception = e; throw e; } finally { if (executedInterceptors != null && executedInterceptors.size() > 0) { for (int i = executedInterceptors.size() - 1; i >= 0; i--) { StateRouterInterceptor interceptor = executedInterceptors.get(i); interceptor.postRoute(context, state, instruction, exception);//结束状态机 } } //if 'Succeed' or 'Fail' State did not configured, we must end the state machine if (instruction == null && !stateInstruction.isEnd()) { EngineUtils.endStateMachine(context); } } return instruction; }
这里的代理只实现了一个后置增强,做的事情就是结束状态机。
下面我们来看一下StateRouter,UML类图如下:
从UML类图我们看到,除了EndStateRouter,只有一个TaskStateRouter了。而EndStateRouter并没有做什么事情,因为关闭状态机的逻辑已经由代理做了。这里我们看一下TaskStateRouter,代码如下:
public Instruction route(ProcessContext context, State state) throws EngineExecutionException { StateInstruction stateInstruction = context.getInstruction(StateInstruction.class); if (stateInstruction.isEnd()) { //如果已经结束,直接返回 //省略代码 } //The current CompensationTriggerState can mark the compensation process is started and perform compensation // route processing. State compensationTriggerState = (State)context.getVariable( DomainConstants.VAR_NAME_CURRENT_COMPEN_TRIGGER_STATE); if (compensationTriggerState != null) { //加入补偿集合进行补偿并返回 return compensateRoute(context, compensationTriggerState); } //There is an exception route, indicating that an exception is thrown, and the exception route is prioritized. String next = (String)context.getVariable(DomainConstants.VAR_NAME_CURRENT_EXCEPTION_ROUTE); if (StringUtils.hasLength(next)) { context.removeVariable(DomainConstants.VAR_NAME_CURRENT_EXCEPTION_ROUTE); } else { next = state.getNext(); } //If next is empty, the state selected by the Choice state was taken. if (!StringUtils.hasLength(next) && context.hasVariable(DomainConstants.VAR_NAME_CURRENT_CHOICE)) { next = (String)context.getVariable(DomainConstants.VAR_NAME_CURRENT_CHOICE); context.removeVariable(DomainConstants.VAR_NAME_CURRENT_CHOICE); } //从当前context中取不出下一个节点了,直接返回 if (!StringUtils.hasLength(next)) { return null; } StateMachine stateMachine = state.getStateMachine(); State nextState = stateMachine.getState(next); if (nextState == null) { throw new EngineExecutionException("Next state[" + next + "] is not exits", FrameworkErrorCode.ObjectNotExists); } //获取到下一个要流转的状态并且赋值给stateInstruction stateInstruction.setStateName(next); return stateInstruction; }
可以看到,route的作用是帮状态机确定下一个流程节点,然后放入到当前的context中的stateInstruction。
到这里,我们就分析完成了状态机的原理,ProcessControllerImpl类中。
需要注意的是,这里获取到下一个节点后,并没有直接处理,而是使用观察者模式,先发送到EventBus,等待观察者来处理,循环往复,直到EndStateRouter结束状态机。
这里观察者模式的Event是ProcessContext,里面包含了Instruction,而Instruction里面包含了State,这个State里面就决定了下一个处理的节点直到结束。UML类图如下:
总结
seata中间件中的saga模式使用比较广泛,但是代码还是比较复杂的。我从下面几个方面进行了梳理:
我们定义的json文件加载到了类StateMachineImpl中。
启动状态机,我们也就启动了全局事务,这个普通模式启动全局事务是一样的,都会向TC发送消息。
处理状态机状态和控制状态流转的入口类在ProcessControllerImpl,从process方法可以跟代码。
ProcessControllerImpl调用CustomizeBusinessProcessor的process处理当前状态,然后调用route方法获取到下一个节点并发送到EventBus。
saga模式额外引入了3张表,我们也可以根据跟全局事务和分支事务相关的2张表来跟踪代码,我之前给出的demo,如果事务成功,这2张表的写sql按照状态机执行顺序给出一个成功sql,代码如下:
INSERT INTO seata_state_machine_inst (id, machine_id, tenant_id, parent_id, gmt_started, business_key, start_params, is_running, status, gmt_updated) VALUES ('192.168.59.146:8091:65853497147990016', '06a098cab53241ca7ed09433342e9f07', '000001', null, '2020-10-31 17:18:24.773', '1604135904773', '{"@type":"java.util.HashMap","money":50.,"productId":1L,"_business_key_":"1604135904773","businessKey":"1604135904773",\"count\":1,\"mockreduceaccountfail\":\"true\","userId":1L,"order":{"@type":"io.seata.sample.entity.Order","count":1,"payAmount":50,"productId":1,"userId":1}}', 1, 'RU', '2020-10-31 17:18:24.773') INSERT INTO seata_state_inst (id, machine_inst_id, name, type, gmt_started, service_name, service_method, service_type, is_for_update, input_params, status, business_key, state_id_compensated_for, state_id_retried_for) VALUES ('4fe5f602452c84ba5e88fd2ee9c13b35', '192.168.59.146:8091:65853497147990016', 'SaveOrder', 'ServiceTask', '2020-10-31 17:18:40.84', 'orderSave', 'saveOrder', null, 1, '["1604135904773",{"@type":"io.seata.sample.entity.Order","count":1,"payAmount":50,"productId":1,"userId":1}]', 'RU', null, null, null) UPDATE seata_state_inst SET gmt_end = '2020-10-31 17:18:49.919', excep = null, status = 'SU', output_params = 'true' WHERE id = '4fe5f602452c84ba5e88fd2ee9c13b35' AND machine_inst_id = '192.168.59.146:8091:65853497147990016' INSERT INTO seata_state_inst (id, machine_inst_id, name, type, gmt_started, service_name, service_method, service_type, is_for_update, input_params, status, business_key, state_id_compensated_for, state_id_retried_for) VALUES ('8371235cb2c66c8626e148f66123d3b4', '192.168.59.146:8091:65853497147990016', 'ReduceAccount', 'ServiceTask', '2020-10-31 17:19:00.441', 'accountService', 'decrease', null, 1, '["1604135904773",1L,50.,{"@type":"java.util.LinkedHashMap","throwException":"true"}]', 'RU', null, null, null) UPDATE seata_state_inst SET gmt_end = '2020-10-31 17:19:09.593', excep = null, status = 'SU', output_params = 'true' WHERE id = '8371235cb2c66c8626e148f66123d3b4' AND machine_inst_id = '192.168.59.146:8091:65853497147990016' INSERT INTO seata_state_inst (id, machine_inst_id, name, type, gmt_started, service_name, service_method, service_type, is_for_update, input_params, status, business_key, state_id_compensated_for, state_id_retried_for) VALUES ('e70a49f1eac72f929085f4e82c2b4de2', '192.168.59.146:8091:65853497147990016', 'ReduceStorage', 'ServiceTask', '2020-10-31 17:19:18.494', 'storageService', 'decrease', null, 1, '["1604135904773",1L,1,{"@type":"java.util.LinkedHashMap"}]', 'RU', null, null, null) UPDATE seata_state_inst SET gmt_end = '2020-10-31 17:19:26.613', excep = null, status = 'SU', output_params = 'true' WHERE id = 'e70a49f1eac72f929085f4e82c2b4de2' AND machine_inst_id = '192.168.59.146:8091:65853497147990016' UPDATE seata_state_machine_inst SET gmt_end = '2020-10-31 17:19:33.581', excep = null, end_params = '{"@type":"java.util.HashMap","productId":1L,"count":1,"ReduceAccountResult":true,"mockReduceAccountFail":"true","userId":1L,"money":50.,"SaveOrderResult":true,"_business_key_":"1604135904773","businessKey":"1604135904773","ReduceStorageResult":true,"order":{"@type":"io.seata.sample.entity.Order","count":1,"id":60,"payAmount":50,"productId":1,"userId":1}}',status = 'SU', compensation_status = null, is_running = 0, gmt_updated = '2020-10-31 17:19:33.582' WHERE id = '192.168.59.146:8091:65853497147990016' and gmt_updated = '2020-10-31 17:18:24.773'
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