Using current ML 9: I’ve set up a little client-server application where the client spawns a large number of tasks on a remote cluster. Each remote task reports its status back to the client via HTTP.
However, if one of the tasks times out in the Task Server there’s no way for it to report its own failure and there doesn’t seem to be anything else other than the task server that can detect the failure and report it. Is there any built-in mechanism by which a task time limit exceeded failure can be detected in a way that would allow me to the report back to the calling client? For example, something that gets the task’s current call stack at the time of failure, which would give me the info I need to report back to the calling client. Unfortunately, the code I’m running in these tasks is pre-existing processing that I’m building this remote processing around so I can’t easily do something like provide a heartbeat signal for each running task that a separate process could poll in order to detect terminated processes, although I’m guessing that’s the most likely solution now that I think about it. I do report to the client when each task starts so I guess I could presume that if a task hasn’t finished some time after the configured max time limit that it is presumed to have failed. Thanks, Eliot -- Eliot Kimber http://contrext.com _______________________________________________ General mailing list [email protected] Manage your subscription at: http://developer.marklogic.com/mailman/listinfo/general
