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  • The job chain provided by the sample is not specifiic for this solution, the same applies to the query job..
  • The prepare job is used to dynamically calculate the number of parallel instances of the query job. This job creates an order parameter parallel_executions=5 for use with the subsequent generate job.
  • The generate job implements the solution by creating the number of orders specified by the parallel_executions parameter. 
    • Each order is added the following parameters
      • number_of_orders: a copy of the parallel_executions parameter.
      • order_sequence: the sequence number of the order created. The sequence starts from 1 up to the value of the parallel_executions parameter.
      • synchronize_required_orders: the number of orders that the synchronize job waits for. This includes the value of the parallel_executions parameter incremented by 1 for the main order. The prefix synchronize of the parameter name reflects the state that the synchronize job node is assigned in the job chain.
    • The orders are assigned the state that is associated with the next job node, the query job, i.e. the orders will be executed starting with that state.
    • The orders are assigned the end state that is associated with the synchronize job.
  • The query job is configured for a maximum number of 3 parallel tasks via the attribute <job tasks="3">. It could be configured for any number of parallel tasks. For the sake of this sample the limitation shows the behavior of the job to wait for processes to become free that could be assigned to subsequent orders for the same job.
  • The job synchronize is used to synchronize splitted orders and is provided by the Sync JITL Job with the Java class com.sos.jitl.sync.JobSchedulerSynchronizeJobChainsJSAdapterClass.
    • This job is used without parameters.
  • Hint: to re-use the generate job you can
    • store the job to some central folder and reference the job in individual job chains.
    • move the JavaScript code of the job to come central location and use a corresponding <include> element for individual job scripts.

 

Code Block
languagejs
titleJob generate
collapsetrue
<?xml version="1.0" encoding="ISO-8859-1"?>

<job  order="yes" stop_on_error="no" title="Generate orders for parallel processing" name="generate">
    <params >
        <param  name="sync_state_name" value="synchronize"/>
    </params>
    <script  language="java:javascript">
        <![CDATA[
function spooler_process(){
  
  var currentJobChain = spooler_task.order.job_chain;
  var currentJobChainName = spooler_task.order.job_chain.name;
  params = spooler.create_variable_set();
  params.merge( spooler_task.params );
  params.merge( spooler_task.order.params );
  var numOfOrders = params.value("parallel_executions");
  spooler_log.info(" creating " + numOfOrders + " orders");
  
  var syncParameterName = currentJobChainName + "_required_orders";
  var numOfRequiredOrders = parseInt( numOfOrders )+1;
  params.set_var( syncParameterName, numOfRequiredOrders );
   
  for (var i = 1; i <= numOfOrders; i++) { 
    var subOrder = spooler.create_order()
    var subParams = spooler.create_variable_set();
    subParams.set_var( "number_of_orders", numOfOrders );
    subParams.set_var( "order_sequence", i );
    subParams.set_var( syncParameterName, numOfRequiredOrders );
    subOrder.params = subParams;
    subOrder.state = spooler_task.order.job_chain_node.next_state;
    subOrder.end_state = params.value( "sync_state_name" );
    currentJobChain.add_order( subOrder );
    spooler_log.info( "order has been added: " + i );
  }
  spooler_task.order.params.set_var( syncParameterName, numOfRequiredOrders );
  spooler_task.order.state = params.value( "sync_state_name" );
  return true;
}
        ]]>
    </script>
    <run_time />
</job>  

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