Data Process.


It performs a roll-up operation on a datacube, i.e. it transforms dimensions from explicit to implicit.


  • cube: name of the input datacube. The name must be in PID format.
  • schedule: scheduling algorithm. The only possible value is 0, for a static linear block distribution of resources.
  • ndim: number of explicit dimensions that will be transformed in implicit dimensions. Default value is ‘1’.
  • container: name of the container to be used to store the output cube; by default, it is the input container.
  • description: additional description to be associated with the output cube.

System parameters

  • exec_mode: operator execution mode. Possible values are async (default) for asynchronous mode, sync for synchronous mode with json-compliant output.
  • ncores: number of parallel processes to be used (min. 1).
  • nthreads: number of parallel threads per process to be used (min. 1).
  • sessionid: session identifier used server-side to manage sessions and jobs. Usually, users don’t need to use/modify it, except when it is necessary to create a new session or switch to another one.
  • objkey_filter: filter on the output of the operator written to file (default=all => no filter, none => no output, rollup => shows operator’s output PID as text).


Do a roll-up on datacube identified by the PID “URL/1/1” on 1 explicit dimension:

[OPH_TERM] >>  oph_rollup cube=URL/1/1;


Argument name Type Mandatory Values Default Min/Max-value
sessionid “string” “no”   “null”  
ncores “int” “no”   “1” “1” /
nthreads “int” “no”   “1” “1” /
exec_mode “string” “no” “async|sync” “async”  
cube “string” “yes”      
schedule “int” “no” “0” “0”  
ndim “int” “no”   “1” “1” /
container “string” “no”   “-“  
description “string” “no”   “-“  
objkey_filter “string” “no” “all|none|rollup” “all”