jBPM Developers Guide

In the example that follows, there is a need to collect reports from different departments. The same task is to be performed by different groups. This situation is easily modeled with foreach. Process variable departments provides the group names, whereas quota indicates how many tasks must be completed before execution leaves the join activity.

<process name="ForEach" xmlns="http://jbpm.org/4.4/jpdl">

   <start g="28,61,48,48" name="start1">
      <transition to="foreach1"/>
   </start>

   <foreach var="department" in="#{departments}" g="111,60,48,48" name="foreach1">
      <transition to="Collect reports"/>
   </foreach>

   <task candidate-groups="#{department}" g="201,58,92,52" name="Collect reports">
      <transition to="join1"/>
   </task>

   <join g="343,59,48,48" multiplicity="#{quorum}" name="join1">
      <transition to="end1"/>
   </join>

   <end g="433,60,48,48" name="end1"/>

</process>

Here is how to initialize the iterative process variables.

Map<String, Object> variables = new HashMap<String, Object>();
variables.put("departments", new String[] { "sales-dept", "hr-dept", "finance-dept" });
variables.put("quorum", 3);
ProcessInstance processInstance = executionService.startProcessInstanceByKey("ForEach", variables);

<process name="EJB">

  <start>
    <transition to="calculate" />
  </start>

  <java name="calculate" 
        ejb-jndi-name="CalculatorBean/local"
        method="add"
        var="answer">
        
    <arg><int value="25"/></arg>
    <arg><int value="38"/></arg>
    
    <transition to="wait" />
  </java>
  
  <state name="wait" />

</process>

As you can expect, the execution of this node will invoke the add method of the ejb that is known under the jndi name CalculatorBean/local. The result will be stored in the variable answer. This is illustrated in the following test snippet.

public void testEjbInvocation() throws Exception {
  String executionId = executionService
      .startProcessInstanceByKey("EJB")
      .getProcessInstance()
      .getId();
  assertEquals(63, executionService.getVariable(executionId, "answer"));
}

Every form of from can be combined with any form of to. The listing below simply assigns a variable to another.

<assign name='copy' from-var='person' to-var='clone'>
  <transition to='wait' />
</assign>

The next example shows an expression value being assigned to a variable.

<assign name='resolve' from-expr='#{person.name}' to-var='name'>
  <transition to='wait' />
</assign>

Our last example presents a value constructed by a descriptor being assigned to the expression location.

<assign name='resolve' to-expr='#{person.address.street}'>
  <from><string value='gasthuisstraat' /></from>
  <transition to='wait' />
</assign>

<process name="RulesDecision">

  <start>
    <transition to="isImportant" />
  </start>

  <rules-decision name="isImportant">
    <transition name="dunno" to="analyseManually" />
    <transition name="important" to="processWithPriority" />
    <transition name="irrelevant" to="processWhenResourcesAvailable" />
  </rules-decision>

  <state name="analyseManually" />
  <state name="processWithPriority" />
  <state name="processWhenResourcesAvailable" />

</process>

The following isImportant.drl is included in the business archive deployment.

global java.lang.Integer amount;
global java.lang.String product;
global org.jbpm.jpdl.internal.rules.Outcome outcome;

rule "LessThen3IsIrrelevant"
  when
    eval(amount < 3)
  then 
    outcome.set("irrelevant");
end

rule "MoreThen24IsImportant"
  when
    eval(amount > 24)
  then 
    outcome.set("important");
end

rule "TwelveTempranillosIsImportant"
  when
    eval(product == "Tempranillo")
    eval(amount > 12)
  then 
    outcome.set("important");
end

First you see that amount and product are defined as globals. Those will resolve by the rules-decision to the process variables with those respective names.

outcome is a special global variable that is used to indicate the transition to take in the consequence. Also, if no outcome is specified by the rules, the default transition will be taken.

So let's start a new process instance and set 2 variables product and amount with respective values shoe and 32:

Map<String, Object> variables = new HashMap<String, Object>();
variables.put("amount", 32);
variables.put("product", "shoe");

ProcessInstance processInstance = 
    executionService.startProcessInstanceByKey("RulesDecision", variables);

After starting the process instance method returns, the process instance will have arrived in the activity processWithPriority

In similar style, a new RulesDecision process instance with 2 missiles will go to activity processWhenResourcesAvailable

A RulesDecision process instance with 15 shoes will go to activity analyseManually

And a RulesDecision process instance with 13 Tempranillos will go to activity analyseManually

If a rules activity has one outgoing transition, then that one is taken automatically. But multiple outgoing transitions can be specified with conditions on them, just like with the decision activity when using the conditions.

For example:

<process name="Rules">

  <start>
    <transition to="evaluateStatus"/>
  </start>

  <rules name="evaluateStatus">
    <fact var="room" />
    <transition to="checkForFires"/>
  </rules>

  <decision name="checkForFires">
    <transition to="getFireExtinguisher">
      <condition expr="#{room.onFire}" />
    </transition>
    <transition to="goToPub"/>
  </decision>

  <state name="getFireExtinguisher"/>
  <state name="goToPub"/>

</process>

The process first checks with rules if the room is on fire. The Room class looks like this:

public class Room implements Serializable {

  int temperature = 21; 
  boolean smoke = false;
  boolean isOnFire = false;
  
  public Room(int temperature, boolean smoke) {
    this.temperature = temperature;
    this.smoke = smoke;
  }
  
  ...getters and setters...
}

Following rules are deployed in the same business archive:

rule "CheckRoomOnFire"
  when
    room : org.jbpm.examples.rules.Room( temperature > 30, smoke == true )
  then 
    room.setOnFire( true );
end

So when a new Rules process instance is started like this:

Map<String, Object> variables = new HashMap<String, Object>();
variables.put("room", new Room(350, true));

ProcessInstance processInstance = 
    executionService.startProcessInstanceByKey("Rules", variables);

Then the process will end up in the activity getFireExtinguisher

And when the process is started with a Room(21, false), it will end up in the activity goToPub

There are 3 types of JMS messages that you can send to to the destination: text, object and map. The connection-factory and destination attributes are mandatory and respectively contain the names of the connection factory and destination (queue or topic) that will be used to lookup the corresponding objects in JNDI. The lookup is done like this:

InitialContext initialContext = new InitialContext();
Destination destination = (Destination) initialContext.lookup(destinationName);
Object connectionFactory = initialContext.lookup(connectionFactoryName);

The jms activity will use the JMS queue apis if the destination is an instanceof Queue. Analogue for topics.

The jms activity will use the XA JMS apis if the connectionFactory is an instanceof XAConnectionFactory. Analogue for plain ConnectionFactory's.

So if you're running inside an appserver, then the new InitialContext() will see the queue's and topics configured in the appserver.

When your're using the JMS mocking in standalone test mode, then the queues and topics that you created with JbpmTestCase.jmsCreateQueue and JbpmTestCase.jmsCreateTopic will be available.

Exactly one of the elements text, object or map is mandatory. The presence of this element will determine the kind of message that will be sent to the queue obtained in the lookup mentioned above. This message will be a TextMessage, ObjectMessage or MapMessage respectively.

In the following subsections the different types of supported messages will be explained. The used process is in the three cases similar. The graphical representation of the process is shown below.

<history-sessions>
      <object class="org.jbpm.pvm.internal.history.HistorySessionImpl" />
</history-sessions>  	
  	

The services interfaces should be used from application code that wants to interact with the Process Virtual Machine which runs in transactional persistent mode, backed by a database. This is the most typical way how users interact with the PVM as a workflow engine.

To execute processes without persistence, the client API can be used to work with process and execution objects directly. The client API expose the methods of the core model objects.

The activity API is used to implement the runtime behaviour of activities. So a activity type is in fact a component with at the core an implementation of the ActivityBehaviour interface. ActivityBehaviour implementations can control the flow of execution.

The event listener API serves to write pieces of Java code that should be executed upon process events. It's very similar to the activity API with that exception that event listeners are not able to control the flow of execution.

The retry interceptor is the first in the chain and that one that will be exposed as the CommandService.class from the environment. So the retry interceptor will be given to the respective services repository-service, execution-service and management-service.

The retry-interceptor will catch hibernate StaleObjectExceptions (indicating optimistic locking failures) and retry to execute the command.

The environment-interceptor will put an environment block around the execution of the command.

The standard-transaction-interceptor will initialize a StandardTransaction. The hibernate session/transaction will be enlisted as a resource with this standard transaction.

Different configurations of this interceptor stack will also enable to

TODO add ProcessBuilder example code

Now we can execute this process as follows:

Execution execution = processDefinition.startExecution();

The invocation of startExecution will print hello world to the console:

hello
world

One thing already worth noticing is that activities can be configured with properties. In the Display example, you can see that the message property is configured differently in the two usages. With configuration properties it becomes possible to write reusable activities. They can then be configured differently each time they are used in a process. That is an essential part of how process languages can be build on top of the Process Virtual Machine.

The other part that needs explanation is that this activity implementation does not contain any instructions for the propagation of the execution. When a new process instance is started, the execution is positioned in the initial activity and that activity is executed. The method Display.execute makes use of what is called implicit propagation of execution. Concretely this means that the activity itself does not invoke any of the methods on the execution to propagate it. In that case implicit propagation kicks in. Implicit propagation will take the first transition if there is one. If not, it will end the execution. This explains why both activities a and b are executed and that the execution stops after activity b is executed.

ClientProcessDefinition processDefinition = ProcessFactory.build()
    .activity("a").initial().behaviour(new WaitState())
      .transition().to("b")
    .activity("b").behaviour(new WaitState())
.done();

Let's start a new process instance for this process definition:

ClientExecution execution = processDefinition.startProcessInstance();

Starting this process will execute the WaitState activity in activity a. WaitState.execute will invoke ActivityExecution.waitForSignal. So when the processDefinition.startProcessInstance() returns, the execution will still be positioned in activity a.

assertEquals("a", execution.getActivityName());

Then we provide the external trigger by calling the signal method.

execution.signal();

The execution.signal() will delegate to the activity of the current activity. So in this case that is the WaitState activity in activity a. The WaitState.signal will invoke the ActivityExecution.take(String transitionName). Since we didn't supply a signalName, the first transition with name null will be taken. The only transition we specified out of activity a didn't get a name so that one will be taken. And that transition points to activity b. When the execution arrives in activity b, the WaitState in activity b is executed. Similar as we saw above, the execution will wait in activity b and this time the signal method will return, leaving the execution positioned in activity b.

assertEquals("b", execution.getActivityName());

Now, the execution is at an interesting point. There are two transitions out of the state evaluate. One transition is called approve and one transition is called reject. As we explained above, the WaitState implementation will take the transition that corresponds to the signal that is given. Let's feed in the 'approve' signal like this:

execution.signal("approve");

The approve signal will cause the execution to take the approve transition and it will arrive in the activity wire money.

In activity wire money, the message will be printed to the console. Since, the Display activity didn't invoke the execution.waitForSignal(), nor any of the other execution propagation methods, the implicit proceed behaviour will just make the execution continue over the outgoing transition to activity archive, which is again a WaitState.

So only when the archive wait state is reached, the signal("approve") returns.

Another signal like this:

execution.signal("approve");

will bring the execution eventually in the end state.

ClientProcessDefinition processDefinition = ProcessFactory.build()
  .activity("a").initial().behaviour(new AutomaticActivity())
    .event("end")
      .listener(new PrintLn("leaving a"))
      .listener(new PrintLn("second message while leaving a"))
    .transition().to("b")
      .listener(new PrintLn("taking transition"))
  .activity("b").behaviour(new WaitState())
    .event("start")
      .listener(new PrintLn("entering b"))
.done();

The first event shows how to register multiple listeners to the same event. They will be notified in the order as they are specified.

Then, on the transition, there is only one type of event. So in that case, the event type must not be specified and the listeners can be added directly on the transition.

A listeners will be called each time an execution fires the event to which the listener is subscribed. The execution will be provided in the activity interface as a parameter and can be used by listeners except for the methods that control the propagation of execution.

TODO update code snippet

Next we'll start an execution.

ClientExecution execution = processDefinition.startProcessInstance();

After starting a new execution, the execution will be in activity a as that is the initial activity. No activities have been left so no message is logged. Next a signal will be given to the execution, causing it to take the transition from a to b.

execution.signal();

When the signal method returns, the execution will have taken the transition and the end event will be fired on activity a. That event will be propagated to the composite activity and to the process definition. Since our DisplaySource event listener is placed on the composite activity, it will receive the event and print the following message on the console:

leaving activity(a)

Another

execution.signal();

will take the transition from b to c. That will fire two activity-leave events. One on activity b and one on activity composite. So the following lines will be appended to the console output:

leaving activity(b)
leaving activity(composite)

Event propagation is build on the hierarchical composition structure of the process definition. The top level element is always the process definition. The process definition contains a list of activities. Each activity can be a leaf activity or it can be a composite activity, which means that it contains a list of nested activities. Nested activities can be used for e.g. super states or composite activities in nested process languages like BPEL.

So the even model also works similarly for composite activities as it did for the process definition above. Suppose that 'Phase one' models a super state as in state machines. Then event propagation allows to subscribe to all events within that super state. The idea is that the hierarchical composition corresponds to diagram representation. If an element 'e' is drawn inside another element 'p', then p is the parent of e. A process definition has a set of top level activities. Every activity can have a set of nested activities. The parent of a transition is considered as the first common parent for it's source and destination.

If an event listener is not interested in propagated events, propagation can be disabled with propagationDisabled() while building the process with the ProcessFactory. The next process is the same process as above except that propagated events will be disabled on the event listener. The graph diagram remains the same.

Building the process with the process factory:

TODO update code snippet

So when the first signal is given for this process, again the end event will be fired on activity a, but now the event listener on the composite activity will not be executed cause propagated events have been disabled. Disabling propagation is a property on the individual event listener and doesn't influence the other listeners. The event will always be fired and propagated over the whole parent hierarchy.

ClientExecution execution = processDefinition.startProcessInstance();

The first signal will take the process from a to b. No messages will be printed to the console.

execution.signal();

Next, the second signal will take the transition from b to c.

execution.signal()

Again two end events are fired just like above on activities b and composite respectively. The first event is the end event on activity b. That will be propagated to the composite activity. So the event listener will not be executed for this event cause it has propagation disabled. But the event listener will be executed for the end event on the composite activity. That is not propagated, but fired directly on the composite activity. So the event listener will now be executed only once for the composite activity as shown in the following console output:

leaving activity(composite)

In most situations, the computational work that needs to be done as part of the process after an external trigger (the red pieces) is pretty minimal. Typically transactions combining the process execution and processing the request from the UI takes typically less then a second. Whereas the wait state in business processes typically can span for hours, days or even years. The clue is to clearly distinct when a wait state starts so that only the computational work done before the start of that wait state should be included in the transaction.

Think of it this way: "When an approval arrives, what are all the automated processing that needs to be done before the process system needs to wait for another external trigger?" Unless pdf's need to be generated or mass emails need to be send, the amount of time that this takes is usually neglectable. That is why in the default persistent execution mode, the process work is executed in the thread of the client.

This reasoning even holds in case of concurrent paths of execution. When a single path of execution splits into concurrent paths of execution, the process overhead of calculating that is neglectable. So that is why it makes sense for a fork or split activity implementation that targets persistent execution mode to spawn the concurrent paths sequentially in the same thread. Basically it's all just computational work as part of the same transaction. This can only be done because the fork/split knows that each concurrent path of execution will return whenever a wait state is encountered.

Since this is a difficult concept to grasp, I'll explain it again with other words. Look at it from the overhead that is produced by the process execution itself in persistent execution mode. If in a transaction, an execution is given an external trigger and that causes the execution to split into multiple concurrent paths of execution. Then the process overhead of calculating this is neglectable. Also the overhead of the generated SQL is neglectable. And since all the work done in the concurrent branches must be done inside that single transaction, there is typically no point in having fork/split implementations spawn the concurrent paths of execution in multiple threads.

To make executable processes, developers need to know exactly what the automatic activities are, what the wait states are and which threads will be allocated to the process execution. For business analysts that draw the analysis process, things are a bit simpler. For the activities they draw, they usually know whether it's a human or a system that is responsible. But they typically don't not how this translates to threads and transactions.

So for the developer, the first job is to analyse what needs to be executed within the thread of control of the process and what is outside. Looking for the external triggers can be a good start to find the wait states in a process, just like verbs and nouns can be the rule of thumb in building UML class diagrams.

To establish multiple concurrent paths of execution, activity implementations like a fork or split can create child executions with method ActivityExecution.createExecution. Activity implementations like join or merge can stop these concurrent paths of execution by calling method stop on the concurrent execution.

Only leaf executions can be active. Non-leave executions should be inactive. This tree structure of executions doesn't enforce a particular type of concurrency or join behaviour. It's up to the forks or and-splits and to the joins or and-merges to use the execution tree structure in any way they want to define the wanted concurrency behaviour. Here you see an example of concurrent executions.

There is a billing and a shipping path of execution. In this case, the flat bar activities represent activities that fork and join. The execution shows a three executions. The main path of execution is inactive (represented as gray) and the billing and shipping paths of execution are active and point to the activity bill and ship respectively.

It's up to the activity behaviour implementations how they want to use this execution structure. Suppose that multiple tasks have to be completed before the execution is to proceed. The activity behaviour can spawn a series of child executions for this. Or alternatively, the task component could support task groups that are associated to one single execution. In that case, the task component becomes responsible for synchronizing the tasks, thereby moving this responsibility outside the scope of the execution tree structure.

If an execution is locked, methods that change the execution will throw a PvmException and the message will reference the actual locking state. Firing events, updating variables, updating priority and adding comments are not considered to change an execution. Also creation and removal of child executions are unchecked, which means that those methods can be invoked by external API clients and activity behaviour methods, even while the execution is in a locked state.

Make sure that comparisons between getState() and the STATE_* constants are done with .equals and not with '==' because if executions are loaded from persistent storage, a new string is created instead of the constants.

An execution implementation will be locked:

Furthermore, locking can be used by Activity implementations to make executions read only during wait states hen responsibility for the execution is transferred to an external entity such as:

In these situations the strategy is that the external entity should get full control over the execution because it wants to control what is allowed and what not. To get that control, they lock the execution so that all interactions have to go through the external entity.

One of the main reasons to create external entities is that they can live on after the execution has already proceeded. For example, in case of a service invocation, a timer could cause the execution to take the timeout transition. When the response arrives after the timeout, the service invocation entity should make sure it doesn't signal the execution. So the service invocation can be seen as a activity instance (aka activity instance) and is unique for every execution of the activity.

External entities themselves are responsible for managing the execution lock. If the timers and client applications are consequent in addressing the external entities instead of the execution directly, then locking is in theory unnecessary. It's up to the activity behaviour implementations whether they want to take the overhead of locking and unlocking.

When using timers or asynchronous continuations in a business process, the jBPM engine will store a 'job' into the database (a job contains mainly a duedate and continuation logic). Do note that this mechanism is pluggable, which means that in the future other destinations could be used (JMS, JCR, etc).

Now the JobExecutor comes in to play, which is in fact a manager for several subcomponents: