Scope
This article is about methods that can be used with the JobScheduler for executing jobs within a job chain at the same time.
See the How To Synchronize Job Execution Across Job Chains article for methods about synchronizing the execution of jobs in different Job Chains.
Methods for Parallel Execution within a Job Chain
There are a number of methods available for configuring the parallel execution of Jobs in a Job Chain.
Static configuration
For the static configuration of the parallel execution of different Jobs:
- Using the JITL split and join Jobs
FEATURE AVAILABILITY STARTING FROM RELEASE 1.11.4
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- This pattern is used for parallelization within a single Job Chain.
- The Join Job is designed for a large number of parallel Orders and is significantly faster for this purpose than the Sync Job described below. Note that the Join Job can only be used within a Job Chain.
- Note also that the Join Job waits for a specific number of Orders to be completed - it does not require specific Orders.
- See the following articles for examples and downloads using the split and join Jobs:
- Using the JITL split and sync Jobs:
- This pattern is used for parallelization across Job Chains.
The Sync Job can also be used with Versions of Job Scheduler older than 1.11.4 to synchronize Jobs within a Job Chain but note that it is only suitable for situations where performance is not an issue - i.e. situations with only a small number of parallel Orders - typically one Order for each Job Chain.
Note also that unlike the Join Job, the Sync Job waits for specific Orders to be completed.
- See the following articles for more information more information about using the split and sync Jobs:
- How To Synchronize Job Execution Across Job Chains
- How to split and sync jobs in a job chain FEATURE AVAILABILITY ENDING WITH RELEASE 1.11.4
- Using the JITL split and join Jobs
FEATURE AVAILABILITY STARTING FROM RELEASE 1.11.4
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Dynamic configuration
For the static configuration of a dynamically set number of instances of a job that are to be executed in parallel:
- Using Parallel Job Instances and JITL split and join Jobs:
See also
- For more information about configuring workflow dependencies see also:
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