• 阿里seata真香，肝一下saga模式源码

    saga模式是分布式事务中使用比较多的一种模式，主要应用在多节点长流程的应用中，对一个全局事务，如果某个节点抛出了异常，则从当前这个节点依次往前补偿事务。一阶段正向服务和二阶段补偿服务都需要由业务代码来实现。今天我们就来看看它的源码实现。

    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。这个流程如下图：

    image.png

    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"        }    }}

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    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");Map startParams = 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 testStateMachineInstance inst = stateMachineEngine.startWithBusinessKey("buyGoodsOnline", null, businessKey, startParams);

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    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;    }}

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    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：

    image.png

    附:根据前面的JSON文件，我们debug跟踪到的StateMachineImpl的内容如下：

    id = nulltenantId = nullappName = "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 = nullisPersist = truetype = "STATE_LANG"content = nullgmtCreate = nullstates = {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}

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    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,                                                 Map startParams) 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;}

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    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);

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    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);    }}

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    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')

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    可以看到，这个全局事务记录在列表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;    }}

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    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);    }}

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    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：在此我向大家推荐一个架构学习交流圈。交流学习指导伪鑫：1253431195（里面有大量的面试题及答案）里面会分享一些资深架构师录制的视频录像：有Spring，MyBatis，Netty源码分析，高并发、高性能、分布式、微服务架构的原理，JVM性能优化、分布式架构等这些成为架构师必备的知识体系。还能领取免费的学习资源，目前受益良多

    image.png

    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);}

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    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);    List interceptors = 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);            }        }    }}

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    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();        Map contextVariables = (Map)context.getVariable(            DomainConstants.VAR_NAME_STATEMACHINE_CONTEXT);        ServiceTaskStateImpl state = (ServiceTaskStateImpl)instruction.getState(context);        List serviceInputParams = null;        Object isForCompensation = state.isForCompensation();        if (isForCompensation != null && (Boolean)isForCompensation) {            CompensationHolder compensationHolder = CompensationHolder.getCurrent(context, true);            StateInstance stateToBeCompensated = compensationHolder.getStatesNeedCompensation().get(state.getName());            if (stateToBeCompensated != null) {                stateToBeCompensated.setCompensationState(stateInstance);                stateInstance.setStateIdCompensatedFor(stateToBeCompensated.getId());            } else {                LOGGER.error("Compensation State[{}] has no state to compensate, maybe this is a bug.",                    state.getName());            }      //加入补偿集合            CompensationHolder.getCurrent(context, true).addForCompensationState(stateInstance.getName(),                stateInstance);        }        //省略部分代码        stateInstance.setInputParams(serviceInputParams);        if (stateMachineInstance.getStateMachine().isPersist() && state.isPersist()            && stateMachineConfig.getStateLogStore() != null) {            try {          //记录一个分支事务的状态RU到数据库        /**          *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)          */                stateMachineConfig.getStateLogStore().recordStateStarted(stateInstance, context);            }        }        //省略部分代码        stateMachineInstance.putStateInstance(stateInstance.getId(), stateInstance);//放入StateMachineInstanceImpl的stateMap用于重试或交易补偿        ((HierarchicalProcessContext)context).setVariableLocally(DomainConstants.VAR_NAME_STATE_INST, stateInstance);//记录状态后面传给TaskStateRouter判断全局事务结束    }    @Override    public void postProcess(ProcessContext context, Exception exp) throws EngineExecutionException {        StateInstruction instruction = context.getInstruction(StateInstruction.class);        ServiceTaskStateImpl state = (ServiceTaskStateImpl)instruction.getState(context);        StateMachineInstance stateMachineInstance = (StateMachineInstance)context.getVariable(            DomainConstants.VAR_NAME_STATEMACHINE_INST);        StateInstance stateInstance = (StateInstance)context.getVariable(DomainConstants.VAR_NAME_STATE_INST);        if (stateInstance == null || !stateMachineInstance.isRunning()) {            LOGGER.warn("StateMachineInstance[id:" + stateMachineInstance.getId() + "] is end. stop running");            return;        }        StateMachineConfig stateMachineConfig = (StateMachineConfig)context.getVariable(            DomainConstants.VAR_NAME_STATEMACHINE_CONFIG);        if (exp == null) {            exp = (Exception)context.getVariable(DomainConstants.VAR_NAME_CURRENT_EXCEPTION);        }        stateInstance.setException(exp);        //设置事务状态        decideExecutionStatus(context, stateInstance, state, exp);        //省略部分代码        Map contextVariables = (Map)context.getVariable(            DomainConstants.VAR_NAME_STATEMACHINE_CONTEXT);        //省略部分代码        context.removeVariable(DomainConstants.VAR_NAME_OUTPUT_PARAMS);        context.removeVariable(DomainConstants.VAR_NAME_INPUT_PARAMS);        stateInstance.setGmtEnd(new Date());        if (stateMachineInstance.getStateMachine().isPersist() && state.isPersist()            && stateMachineConfig.getStateLogStore() != null) {      //更新分支事务的状态为成功      /**        * 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'              */            stateMachineConfig.getStateLogStore().recordStateFinished(stateInstance, context);        }        //省略部分代码    }}

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    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 input = (List) context.getVariable(DomainConstants.VAR_NAME_INPUT_PARAMS);        //Set the current task execution status to RU (Running)        stateInstance.setStatus(ExecutionStatus.RU);//设置状态        if (state instanceof CompensateSubStateMachineState) {            //省略子状态机的研究        } else {            StateMachineConfig stateMachineConfig = (StateMachineConfig) context.getVariable(                    DomainConstants.VAR_NAME_STATEMACHINE_CONFIG);            //这里的state.getServiceType是springBean            ServiceInvoker serviceInvoker = stateMachineConfig.getServiceInvokerManager().getServiceInvoker(                    state.getServiceType());            if (serviceInvoker == null) {                throw new EngineExecutionException("No such ServiceInvoker[" + state.getServiceType() + "]",                        FrameworkErrorCode.ObjectNotExists);            }            if (serviceInvoker instanceof ApplicationContextAware) {                ((ApplicationContextAware) serviceInvoker).setApplicationContext(                        stateMachineConfig.getApplicationContext());            }            //这里触发了我们在JSON中定义ServiceTask中方法，比如orderSave中的saveOrder方法            result = serviceInvoker.invoke(state, input.toArray());        }        if (LOGGER.isDebugEnabled()) {            LOGGER.debug("<<<<<<<<<<<<<<<<<<<<<< State[{}], ServiceName[{}], Method[{}] Execute finish. result: {}",                    state.getName(), serviceName, methodName, result);        }    //省略部分代码    }   //省略异常处理代码}

    • 1
     

    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);}

    • 1
     

    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);    }}

    • 1
     

    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;    List interceptors = 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;}

    • 1
     

    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：
     

    image.png
     

    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;}

    • 1
     

    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：
     

    image.png
     

    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'

    • 1
     

    这篇文章我主要从一个正常的流程研究了saga模式的源代码，还有好多细节没有做分析，比如全局事务失败后的回滚或补偿逻辑，以后有机会再交流。
    
                
                    
                

                
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                    原文地址：https://blog.csdn.net/MIC_9408/article/details/126310809
                
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