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Introduction
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The ease of this method means that job execution on remote JobSchedulers can be more flexibly allocated than with process class based methods. In particular, it allows the decision about which JobScheduler a job is to be executed on to be made dynamically, for example, depending on the result of the preceeding job.
In addition, only one instance of the job and job chain need to be defined in the live folder of the 'main' JobScheduler, thereby considerably increasing flexibility and reducing maintenance.
Operation details
- The remote JobScheduler can be either a workload instance or an Agent.
- Job, job chain and order configuration data is only transferred to the remote JobScheduler as required, JobScheduler objects are not saved on the remote JobScheduler.
- The operations carried out on the remote JobScheduler are recorded in log files in the
$SCHEDULER_DATA/logsdirectory as defined in the JobScheduler - Installation Guide - Log information for the operations carried out on the remote JobScheduler is also saved in the
$SCHEDULER_DATA/logsdirectory of the 'main' JobScheduler.
A simple scheduler.remote_scheduler example
A scheduler.remote_scheduler example has been prepared and can be used to set up a simple remote scheduling demonstration.
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Note that scheduler.remote_scheduler only works when both the main and remote JobSchedulers are version 1.7 or newer.
Download the example
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TODO: Add description of job & shell script .....
Running the example
When "Order_1_Local" is started - for example, using JobScheduler's JOC interface, "Job_Chain_1" will be executed on the local host - i.e. the JobScheduler in whose file system the demo files were unpacked.
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A scheduler.remote_scheduler parameter is not set in the "Order_1_Local" order and therefore when started with this order "Job_1" will be executed by default on your local computer. The name of your local computer or host (depending on the operating system - see above) will be entered in the log file.
Application in a Production Environment
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In a production environment, particularly one where a large number or remote servers were being addressed, the scheduler.remote_scheduler parameters would be saved in an .inc file, which would be loaded as required.
Example with dynamic order generation
We have prepared a second, more complex, example showing use of scheduler.remote_scheduler with dynamically generated orders containing remote_scheduler parameters:
See
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