Alma supports the following job types:
- Scheduled jobs – Scheduled jobs run periodically. Some of these jobs are scheduled by Alma. For other jobs you can configure the schedule using predefined job scheduling options. Note that scheduled jobs run as close as possible to their scheduled time. Some jobs can run in parallel, but part or all of a job may wait until a server has available resources.
In addition to their scheduled run times, Alma provides the ability to run some of these jobs at any time—for example, if you need to invoke the job’s process outside of its normally scheduled time.
- Workflow jobs – Workflow jobs run automatically when they are required. For example, after submitting a purchase order, the job Export Orders (PO) Job runs to send the PO to the vendor. In some cases, you can also run or rerun these jobs at any time—for example, if the original run failed.
- Manual jobs – These jobs are available to run by you as required. Some manual jobs first require you to create sets (of items, users, and so forth) for the job to process.
- Jobs are sometimes called processes in the UI.
- Some Alma jobs are dependent on other jobs due to the fact that they modify the same data. A job can also modify data that has a relationship with data updated in other jobs. To prevent these jobs from failing due to simultaneous data use, dependent jobs are scheduled to run in proximate times. An example of dependent jobs that update related entities are the MMS - Build record relations job and the Authorities - Preferred Term Correction.
Some jobs in Alma are created and configured using profiles. For more information, see Overview of Profiles.
- To run manual jobs on sets, see Running Manual Jobs on Defined Sets.
- To view scheduled jobs, see Viewing Scheduled Jobs.
In addition, this section provides links to other documentation sections that describe how to schedule and/or configure these jobs.
- To view running jobs, see Viewing Running Jobs.
In addition, this section provides links to other documentation sections that describe pages in Alma on which you can view specific types of jobs.
- To view job history and reports, see Viewing Completed Jobs.
Overview of Profiles
Alma uses profiles to configure and/or schedule certain types of jobs. You add the profile, give it a name, and configure its parameters. This creates a job that is available to run, either from a specific location within Alma or automatically as a scheduled job.
Common profiles in Alma include:
- Integration Profile – Creates a job that exports information to, or imports information from, an external system, such as a Student Information System. For more information, see Configuring Integration Profiles.
- Import Profile – Creates a job that imports bibliographic or authority records into Alma, and may also import purchase order or inventory information. For more information, see Record Import and Monitoring Import Jobs.
- Publishing Profile – Creates a job that exports bibliographic records from Alma to an external system, such as Primo or Google Scholar. For more information, see Configuring Publishing Profiles.
Batch Job Planning Guidelines
As a multi-tenant cloud based solution, Alma has a sophisticated batch job management architecture, which takes into account various factors such as the types of jobs running, the time of the day and the general load of the system, all in order to provide you with the services you require.
When using Alma’s batch job services for managing your repository, it is useful to know how long processes can be expected to run. The guidelines provided below are based on Alma’s actual production use of these services. Ex Libris expect that, on average, the times given will not be less than listed, and often even better. This depends on the system load at any given time.
|Batch Service||Records Per Hour (Peak)||Records PerHour (Off-Peak)|
Note: The different profiles of metadata import may influence the time the service takes. For example, an EOD import profile will on average take longer than a bibliographic only update.
|Global Changes – MARC Bibliographic Normalization||50k||200k|
Off-Peak hours are during the night (relative to your data center location) and usually spans 6 hours (for example, midnight to 6:00 AM).