def master_setup_bulk_subjobs(self, jobs, jdefids): from Ganga.GPIDev.Lib.Job.Job import Job master_job = self.getJobObject() for i in range(len(jdefids)): j = Job() j.copyFrom(master_job) j.splitter = None j.backend = Panda() j.backend.id = jdefids[i] j.id = i j.status = 'submitted' j.time.timenow('submitted') master_job.subjobs.append(j) return True
def master_setup_bulk_subjobs(self, jobs, jdefids): from Ganga.GPIDev.Lib.Job.Job import Job master_job=self.getJobObject() for i in range(len(jdefids)): j=Job() j.copyFrom(master_job) j.splitter = None j.backend=Panda() j.backend.id = jdefids[i] j.id = i j.status = 'submitted' j.time.timenow('submitted') master_job.subjobs.append(j) return True
def submit(N, K): jobs = [] for i in range(K): j = Job() j._auto__init__() j.backend = LCG() j.backend.middleware = 'GLITE' j.splitter = GenericSplitter() j.splitter.attribute = 'application.args' j.splitter.values = [['x']] * N j.submit() jobs.append(j) import time def finished(): for j in jobs: if not j.status in ['failed', 'completed']: return False return True while not finished(): time.sleep(1) return jobs
def createUnits(self): """Create new units if required given the inputdata""" # call parent for chaining super(CoreTransform, self).createUnits() # Use the given splitter to create the unit definitions if len(self.units) > 0: # already have units so return return if self.unit_splitter == None and len(self.inputdata) == 0: raise ApplicationConfigurationError( None, "No unit splitter or InputData provided for CoreTransform unit creation, Transform %d (%s)" % (self.getID(), self.name), ) # ----------------------------------------------------------------- # split over unit_splitter by preference if self.unit_splitter: # create a dummy job, assign everything and then call the split j = Job() j.backend = self.backend.clone() j.application = self.application.clone() if self.inputdata: j.inputdata = self.inputdata.clone() subjobs = self.unit_splitter.split(j) if len(subjobs) == 0: raise ApplicationConfigurationError( None, "Unit splitter gave no subjobs after split for CoreTransform unit creation, Transform %d (%s)" % (self.getID(), self.name), ) # only copy the appropriate elements fields = [] if len(self.fields_to_copy) > 0: fields = self.fields_to_copy elif isType(self.unit_splitter, GenericSplitter): if self.unit_splitter.attribute != "": fields = [self.unit_splitter.attribute.split(".")[0]] else: for attr in self.unit_splitter.multi_attrs.keys(): fields.append(attr.split(".")[0]) # now create the units from these jobs for sj in subjobs: unit = CoreUnit() for attr in fields: setattr(unit, attr, copy.deepcopy(getattr(sj, attr))) self.addUnitToTRF(unit) # ----------------------------------------------------------------- # otherwise split on inputdata elif len(self.inputdata) > 0: if self.files_per_unit > 0: # combine all files and split accorindgly filelist = [] for ds in self.inputdata: if isType(ds, GangaDataset): for f in ds.files: if f.containsWildcards(): # we have a wildcard so grab the subfiles for sf in f.getSubFiles(process_wildcards=True): filelist.append(sf) else: # no wildcards so just add the file filelist.append(f) else: logger.warning("Dataset '%s' doesn't support files" % getName(ds)) # create DSs and units for this list of files fid = 0 while fid < len(filelist): unit = CoreUnit() unit.name = "Unit %d" % len(self.units) unit.inputdata = GangaDataset(files=filelist[fid : fid + self.files_per_unit]) unit.inputdata.treat_as_inputfiles = self.inputdata[0].treat_as_inputfiles fid += self.files_per_unit self.addUnitToTRF(unit) else: # just produce one unit per dataset for ds in self.inputdata: # avoid splitting over chain inputs if isType(ds, TaskChainInput): continue unit = CoreUnit() unit.name = "Unit %d" % len(self.units) unit.inputdata = copy.deepcopy(ds) self.addUnitToTRF(unit)
def createUnits(self): """Create new units if required given the inputdata""" # call parent for chaining super(CoreTransform, self).createUnits() # Use the given splitter to create the unit definitions if len(self.units) > 0: # already have units so return return if self.unit_splitter == None and len(self.inputdata) == 0: raise ApplicationConfigurationError( "No unit splitter or InputData provided for CoreTransform unit creation, Transform %d (%s)" % (self.getID(), self.name)) # ----------------------------------------------------------------- # split over unit_splitter by preference if self.unit_splitter: # create a dummy job, assign everything and then call the split j = Job() j.backend = self.backend.clone() j.application = self.application.clone() if self.inputdata: j.inputdata = self.inputdata.clone() subjobs = self.unit_splitter.split(j) if len(subjobs) == 0: raise ApplicationConfigurationError( "Unit splitter gave no subjobs after split for CoreTransform unit creation, Transform %d (%s)" % (self.getID(), self.name)) # only copy the appropriate elements fields = [] if len(self.fields_to_copy) > 0: fields = self.fields_to_copy elif isType(self.unit_splitter, GenericSplitter): if self.unit_splitter.attribute != "": fields = [self.unit_splitter.attribute.split(".")[0]] else: for attr in self.unit_splitter.multi_attrs.keys(): fields.append(attr.split(".")[0]) # now create the units from these jobs for sj in subjobs: unit = CoreUnit() for attr in fields: setattr(unit, attr, copy.deepcopy(getattr(sj, attr))) self.addUnitToTRF(unit) # ----------------------------------------------------------------- # otherwise split on inputdata elif len(self.inputdata) > 0: if self.files_per_unit > 0: # combine all files and split accorindgly filelist = [] for ds in self.inputdata: if isType(ds, GangaDataset): for f in ds.files: if f.containsWildcards(): # we have a wildcard so grab the subfiles for sf in f.getSubFiles( process_wildcards=True): filelist.append(sf) else: # no wildcards so just add the file filelist.append(f) else: logger.warning("Dataset '%s' doesn't support files" % getName(ds)) # create DSs and units for this list of files fid = 0 while fid < len(filelist): unit = CoreUnit() unit.name = "Unit %d" % len(self.units) unit.inputdata = GangaDataset( files=filelist[fid:fid + self.files_per_unit]) unit.inputdata.treat_as_inputfiles = self.inputdata[ 0].treat_as_inputfiles fid += self.files_per_unit self.addUnitToTRF(unit) else: # just produce one unit per dataset for ds in self.inputdata: # avoid splitting over chain inputs if isType(ds, TaskChainInput): continue unit = CoreUnit() unit.name = "Unit %d" % len(self.units) unit.inputdata = copy.deepcopy(ds) self.addUnitToTRF(unit)