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https://issues.apache.org/jira/browse/SLING-3028?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13754454#comment-13754454
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Carsten Ziegeler commented on SLING-3028:
-----------------------------------------

Ok, we have three options of where a decision to keep a job can be made:
- the job sender by setting a property
- the job consumer
- the job engine
Keeping failed jobs seems to be the most natural decision to me, so this would 
be the job engine deciding it based on the result.
I think this is a good first step.
But this leads me to the question, why do we want to keep a job - or the result 
of a job? I think the no.1 reason is trouble shooting and knowing that things 
have failed and why. So I have the feeling that this simple decision (job 
failed) is enough.
I have the tendency to keep failed jobs forever - but have an API to retry or 
remove them. A scheduled configuration might always lead to the problem that 
failed jobs are removed before someone took an action.

                
> Support for progress tracking of jobs
> -------------------------------------
>
>                 Key: SLING-3028
>                 URL: https://issues.apache.org/jira/browse/SLING-3028
>             Project: Sling
>          Issue Type: Improvement
>          Components: Extensions
>            Reporter: Victor Saar
>              Labels: jobs
>
> For long-running jobs, it would be useful to have some means to track 
> progress, which can be shown in a console for the user. This should include 
> the following:
> * ETA
> * Completeness value computed from (optional, defaults to 1.0) max and 
> current value (e.g. 42% or 23/100)
> * Log output stream for detailed progress information
> * Failure reason in case job failed
> AFAICS this requires a few changes to the existing implementation:
> * Jobs need additional support for setting properties, e.g. max and current 
> progress value
> * Jobs need to be kept at least for a while after they completed/failed to 
> give access to failure information/log stream

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