Chapter 7. Process Modelling - JBoss JBPM 3.0.4 userguide 英文版文档

A process definition represents a formal specification of a business process and is based on a directed graph. The graph is composed of nodes and transitions. Every node in the graph is of a specific type. The type of the node defines the runtime behaviour. A process definition has exactly one start state.

A token is one path of execution. A token is the runtime concept that maintains a pointer to a node in the graph.

A process instance is one execution of a process definition. When a process instance is created, a token is created for the main path of execution. This token is called the root token of the process instance and it is positioned in the start state of the process definition.

A signal instructs a token to continue graph execution. When receiving an unnamed signal, the token will leave its current node over the default leaving transition. When a transition-name is specified in the signal, the token will leave its node over the specified transition. A signal given to the process instance is delegated to the root token.

After the token has entered a node, the node is executed. Nodes themselves are responsible for the continuation of the graph execution. Continuation of graph execution is done by making the token leave the node. Each node type can implement a different behaviour for the continuation of the graph execution. A node that does not propagate execution will behave as a state.

Actions are pieces of java code that are executed upon events in the process execution. The graph is an important instrument in the communication about software requirements. But the graph is just one view (projection) of the software being produced. It hides many technical details. Actions are a mechanism to add technical details outside of the graphical representation. Once the graph is put in place, it can be decorated with actions. The main event types are entering a node, leaving a node and taking a transition.

The basis of a process definition is a graph that is made up of nodes and transitions. That information is expressed in an xml file called processdefinition.xml. Each node has a type like e.g. state, decision, fork, join,... Each node has a set of leaving transitions. A name can be given to the transitions that leave a node in order to make them distinct. For example: The following diagram shows a process graph of the jBAY auction process.

Figure 7.1. The auction process graph

Below is the process graph of the jBAY auction process represented as xml:

<process-definition>

  <start-state>
    <transition to="auction" />
  </start-state>
  
  <state name="auction">
    <transition name="auction ends" to="salefork" />
    <transition name="cancel" to="end" />
  </state>
  
  <fork name="salefork">
    <transition name="shipping" to="send item" />
    <transition name="billing" to="receive money" />
  </fork>
  
  <state name="send item">
    <transition to="receive item" />
  </state>

  <state name="receive item">
    <transition to="salejoin" />
  </state>
  
  <state name="receive money">
    <transition to="send money" />
  </state>

  <state name="send money">
    <transition to="salejoin" />
  </state>
  
  <join name="salejoin">
    <transition to="end" />
  </join>
  
  <end-state name="end" />
  
</process-definition>

A process graph is made up of nodes and transitions. For more information about the graph and its executional model, refer to Chapter 4, Graph Oriented Programming.

Each node has a specific type. The node type determines the what will happen when an execution arrives in the node at runtime. jBPM has a set of preimplemented node types that you can use. Alternatively, you can write custom code for implementing your own specific node behaviour.

Actions are pieces of java code that are executed upon events in the process execution. The graph is an important instrument in the communication about software requirements. But the graph is just one view (projection) of the software being produced. It hides many technical details. Actions are a mechanism to add technical details outside of the graphical representation. Once the graph is put in place, it can be decorated with actions. This means that java code can be associated with the graph without changing the structure of the graph. The main event types are entering a node, leaving a node and taking a transition.

Note the difference between an action that is placed in an event versus an action that is placed in a node. Actions that are put in an event are executed when the event fires. Actions on events have no way to influence the flow of control of the process. It is similar to the observer pattern. On the other hand, an action that is put on a node has the responsibility of propagating the execution.

Let's look at an example of an action on an event. Suppose we want to do a database update on a given transition. The database update is technically vital but it is not important to the business analyst.

Figure 7.2. A database update action

public class RemoveEmployeeUpdate implements ActionHandler {
  public void execute(ExecutionContext ctx) throws Exception {
    // get the fired employee from the process variables.
    String firedEmployee = (String) ctx.getContextInstance().getVariable("fired employee");
    
    // by taking the same database connection as used for the jbpm updates, we 
    // reuse the jbpm transaction for our database update.
    Connection connection = ctx.getProcessInstance().getJbpmSession().getSession().getConnection();
    Statement statement = connection.createStatement("DELETE FROM EMPLOYEE WHERE ...");
    statement.execute();
    statement.close();
  }
}

<process-definition name="yearly evaluation">

  ...
  <state name="fire employee">
    <transition to="collect badge">
      <action class="com.nomercy.hr.RemoveEmployeeUpdate" />
    </transition>
  </state>
  
  <state name="collect badge">
  ...
  
</process-definition>

<process-definition>
  <event type="node-enter">
    <script>
      System.out.println("this script is entering node "+node);
    </script>
  </event>
  ...
</process-definition>

<process-definition>
  <event type="process-end">
    <script>
      <expression>
        a = b + c;
      </expression>
      <variable name='XXX' access='write' mapped-name='a' />
      <variable name='YYY' access='read' mapped-name='b' />
      <variable name='ZZZ' access='read' mapped-name='c' />
    </script>
  </event>
  ...
</process-definition>

A Superstate is a group of nodes. Superstates can be nested recursively. Superstates can be used to bring some hierarchy in the process definition. For example, one application could be to group all the nodes of a process in phases. Actions can be associated with superstate events. A consequence is that a token can be in multiple nested nodes at a given time. This can be convenient to check wether a process execution is e.g. in the start-up phase. In the jBPM model, you are free to group any set of nodes in a superstate.

<process-definition>
  ...
  <state name="preparation">
    <transition to="phase one/invite murphy"/>
  </state>
  <super-state name="phase one">
    
  </super-state>
  ...
</process-definition>

<process-definition>
  ...
  <super-state name="phase one">
    <state name="preparation">
      <transition to="../phase two/invite murphy"/>
    </node>
  </super-state>
  <super-state name="phase two">
    
  </super-state>
  ...
</process-definition>

The exception handling mechanism of jBPM only applies to java exceptions. Graph execution on itself cannot result in problems. It is only the execution of delegation classes that can lead to exceptions.

On process-definitions, nodes and transitions, a list of exception-handlers can be specified. Each exception-handler has a list of actions. When an exception occurs in a delegation class, the process element parent hierarchy is serached for an appropriate exception-handler. When it is found, the actions of the exception-handler are executed.

Note that the exception handling mechanism of jBPM is not completely similar to the java exception handling. In java, a caught exception can have an influence on the control flow. In the case of jBPM, control flow cannot be changed by the jBPM exception handling mechanism. The exception is either caught or uncaught. Uncaught exceptions are thrown to the client (e.g. the client that called the token.signal()) or the exception is caught by a jBPM exception-handler. For caught exceptions, the graph execution continues as if no exception has occurred.

Note that in an action that handles an exception, it is possible to put the token in an arbitrary node in the graph with Token.setNode(Node node).

Process composition is supported in jBPM by means of the process-state. The process state is a state that is associated with another process definition. When graph execution arrives in the process state, a new process instance of the sub-process is created and it is associated with the path of execution that arrived in the process state. The path of execution of the super process will wait till the sub process instance has ended. When the sub process instance ends, the path of execution of the super process will leave the process state and continue graph execution in the super process.

<process-definition name="hire">
  <start-state>
    <transition to="initial interview" />
  </start-state>
  <process-state name="initial interview">
    <sub-process name="interview" />
    <variable name="a" access="read,write" mapped-name="aa" />
    <variable name="b" access="read" mapped-name="bb" />
    <transition to="..." />
  </process-state>
  ...
</process-definition>

This 'hire' process contains a process-state that spawns an 'interview' process. When execution arrives in the 'first interview', a new execution (=process instance) for the latest version of the 'interview' process is created. Then variable 'a' from the hire process is copied into variable 'aa' from the interview process. The same way, hire variable 'b' is copied into interview variable 'bb'. When the interview process finishes, only variable 'aa' from the interview process is copied back into the 'a' variable of the hire process.

In general, When a subprocess is started, all variables with read access are read from the super process and fed into the newly created sub process before the signal is given to leave the start state. When the sub process instances is finished, all the variables with write access will be copied from the sub process to the super process. The mapped-name attribute of the variable element allows you to specify the variable name that should be used in the sub process.

In jBPM, it's quite easy to write your own custom nodes. For creating custom nodes, an implementation of the ActionHandler has to be written. The implementation can execute any business logic, but also has the responsibility to propagate the graph execution. Let's look at an example that will update an ERP-system. We'll read an amout from the ERP-system, add an amount that is stored in the process variables and store the result back in the ERP-system. Based on the size of the amount, we have to leave the node via the 'small amounts' or the 'large amounts' transition.

Figure 7.3. The update erp example process snippet

public class AmountUpdate implements ActionHandler {
  public void execute(ExecutionContext ctx) throws Exception {
    // business logic
    Float erpAmount = ...get amount from erp-system...;
    Float processAmount = (Float) ctx.getContextInstance().getVariable("amount");
    float result = erpAmount.floatValue() + processAmount.floatValue();
    ...update erp-system with the result...;
    
    // graph execution propagation
    if (result > 5000) {
      ctx.leaveNode(ctx, "big amounts");
    } else {
      ctx.leaveNode(ctx, "small amounts");
    }
  }
}

It is also possible to create and join tokens in custom node implementations. For an example on how to do this, check out the Fork and Join node implementation in the jbpm source code :-).

The graph execution model of jBPM is based on interpretation of the process definition and the chain of command pattern.

Interpretation of the process definition means that the process definition data is stored in the database. At runtime the process definition information is used during process execution. Note for the concerned : we use hibernate's second level cache to avoid loading of definition information at runtime. Since the process definitions don't change (see process versioning) hibernate can cache the process definitions in memory.

The chain of command pattern means that each node in the graph is responsible for propagating the process execution. If a node does not propagate execution, it behaves as a wait state.

The idea is to start execution on process instances and that the execution continues till it enters a wait state.

A token represents a path of execution. A token has a pointer to a node in the process graph. During waitstates, the tokens can be persisted in the database. Now we are going to look at the algorithm for calculating the execution of a token. Execution starts when a signal is sent to a token. The execution is then passed over the transitions and nodes via the chain of command pattern. These are the relevant methods in a class diagram.

Figure 7.4. The graph execution related methods

When a token is in a node, signals can be sent to the token. Sending a signal is an instruction to start execution. A signal must therefore specify a leaving transition of the token's current node. The first transition is the default. In a signal to a token, the token takes its current node and calls the Node.leave(ExecutionContext,Transition) method. Think of the ExecutionContext as a Token because the main object in an ExecutionContext is a Token. The Node.leave(ExecutionContext,Transition) method will fire the node-leave event and call the Transition.take(ExecutionContext). That method will fire the transition event and call the Node.enter(ExecutionContext) on the destination node of the transition. That method will fire the node-enter event and call the Node.execute(ExecutionContext). Each type of node has its own behaviour that is implementated in the execute method. Each node is responsible for propagating graph execution by calling the Node.leave(ExecutionContext,Transition) again. In summary:

Note that the complete calculation of the next state, including the invocation of the actions is done in the thread of the client. A common misconception is that all calculations *must* be done in the thread of the client. As with any asynchronous invocation, you can use asynchronous messaging (JMS) for that. When the message is sent in the same transaction as the process instance update, all synchronization issues are taken care of. Some workflow systems use asynchronous messaging between all nodes in the graph. But in high throughput environments, this algorithm gives much more control and flexibility for tweaking performance of a business process.