root> submit()to submit a job using the application, task and dataset referenced by the global variables papp, ptsk and pdst. Typically these are defined as described in the previous section. The ID assigned to the job will be recorded in the global variable jid.
The status of the job may be checked with the command
root> print(msch.job(jid))The job should quickly move from the INITIALIZED to the RUNNING state and will end up in the DONE state when it completes successfully or FAILED if there is an unrecoverable error.
You can exert additional control over how and where the processing is done by specifying non-default analysis service or job preferences.
Each primary job page also provides links to similar descriptions of the subjobs that comprise the job. You can follow these to find information such as where the subjob ran and ist status and return code after completion.
The easiest way to spcecify the analysis service is to put its URL in the file scheduler in the directory where root is run. The web interface described in the getting started section can be used to select a scheduler and find its URL. Note that the service URL is not the same as the web page address (typically the port number is incremented).
root> .x create_preferences.CThe variable max_retry specifies the maximum number of times a failed subjob may be resubmitted before the service declares the parent compound job to be failed. The default is zero.
Input datasets may be constructed from other datasets in a tree structure. Most Rome AOD datasets have subdatasets with a maximum of fifty files. The splitter parameter dataset_depth specifies the depth in this tree used for splitting (default is 1) and min_dataset specifies the minumum number of consituent datasets in a subjob (default 1). The parameter min_event specifies minumum number of events per job.