def createNewJob(self):
"""Create any jobs required for this unit"""
j = GPI.Job()
j._impl.backend = self._getParent().backend.clone()
j._impl.application = self._getParent().application.clone()
if not self.inputdata == None:
j.inputdata = self.inputdata.clone()
trf = self._getParent()
task = trf._getParent()
# copy across the outputfiles
for f in trf.outputfiles:
j.outputfiles += [f.clone()]
j.inputsandbox = trf.inputsandbox
# Sort out the splitter
if trf.splitter:
j.splitter = trf.splitter.clone()
# Postprocessors
for pp in trf.postprocessors:
j.postprocessors.append(deepcopy(pp))
return j
def createNewJob(self):
"""Create any jobs required for this unit"""
j = GPI.Job()
j.backend = self._getParent().backend.clone()
# copy form ourselves or the parent transform depending on what's
# specified
fields = [
'application', 'splitter', 'inputfiles', 'inputdata',
'inputsandbox', 'outputfiles', 'postprocessors'
]
for f in fields:
if (f == "postprocessors"
and len(getattr(self, f).process_objects) > 0):
j.postprocessors = copy.deepcopy(addProxy(self).postprocessors)
elif (f != "postprocessors" and getattr(self, f)):
setattr(j, f, copy.deepcopy(getattr(self, f)))
elif (f == "postprocessors"
and len(getattr(self._getParent(), f).process_objects) > 0):
j.postprocessors = copy.deepcopy(
addProxy(self._getParent()).postprocessors)
elif (f != "postprocessors" and getattr(self._getParent(), f)):
setattr(j, f, copy.deepcopy(getattr(self._getParent(), f)))
return j
def createNewJob(self):
"""Create any jobs required for this unit"""
j = GPI.Job()
j._impl.backend = self._getParent().backend.clone()
j._impl.application = self._getParent().application.clone()
j.inputdata = self.inputdata.clone()
trf = self._getParent()
task = trf._getParent()
# copy across the outputfiles
for f in trf.outputfiles:
j.outputfiles += [f.clone()]
j.inputsandbox = trf.inputsandbox
if type(self.eventswanted) == type(''):
subLines = self.eventswanted
else:
subLines = '\n'.join(self.eventswanted)
# Base for the naming of each subjob's CSV file
incsvfile = j._impl.application.csvfile
tmpname = os.path.basename(incsvfile)
if len(tmpname.split('.')) > 1:
patterncsv = '.'.join(tmpname.split('.')[0:-1])+"_sub%d."+ tmpname.split('.')[-1]
else:
patterncsv = tmpname+"_sub%d"
from Ganga.GPIDev.Lib.File import FileBuffer
thiscsv = patterncsv % self.subpartid
# Create the CSV file for this Unit
j._impl.getInputWorkspace().writefile(FileBuffer(thiscsv,subLines),executable=0)
j._impl.application.csvfile = j._impl.getInputWorkspace().getPath()+thiscsv
j.inputsandbox.append(j._impl.getInputWorkspace().getPath()+thiscsv)
# Base for the naming of each subjob's output file
tmpname = os.path.basename(j._impl.application.outputfile)
if len(tmpname.split('.')) > 1:
patternout = '.'.join(tmpname.split('.')[0:-1])+"_sub%d."+ tmpname.split('.')[-1]
else:
patternout = tmpname+"_sub%d"
j._impl.application.outputfile = patternout % self.subpartid
# Sort out the splitter
if trf.splitter:
j.splitter = trf.splitter.clone()
return j
def createNewJob(self, partition):
""" Returns a new job initialized with the transforms application, backend and name """
task = self._getParent(
) # this works because createNewJob is only called by a task
id = task.transforms.index(self)
j = GPI.Job()
stripProxy(j).backend = self.backend.clone()
stripProxy(j).application = self.application.clone()
stripProxy(j).application.tasks_id = "%i:%i" % (task.id, id)
stripProxy(j).application.id = self.getNewAppID(partition)
j.inputdata = self.inputdata
j.outputdata = self.outputdata
j.inputsandbox = self.inputsandbox
j.outputsandbox = self.outputsandbox
j.name = "T%i:%i C%i" % (task.id, id, partition)
return j
def createNewJob(self, partition):
""" Returns a new job initialized with the transforms application, backend and name """
j = GPI.Job()
stripProxy(j).backend = self.backend.clone()
stripProxy(j).application = self.application.clone()
stripProxy(j).application.tasks_id = "%i:%i" % (self.task_id,
self.transform_id)
stripProxy(j).application.id = self.getNewAppID(partition)
if self.splitter is not None:
stripProxy(j).splitter = LHCbTaskDummySplitter(self.splitter)
# if self.merger is not None:
# stripProxy(j).merger = self.merger
j.inputdata = self.toProcess_dataset
j.outputdata = self.outputdata
j.inputsandbox = self.inputsandbox
j.outputsandbox = self.outputsandbox
j.name = "T%i Tr%i P%i" % (self.task_id, self.transform_id, partition)
j.do_auto_resubmit = True
self.toProcess_dataset.files = []
return j
def createNewJob(self):
"""Create any jobs required for this unit"""
j = GPI.Job()
j._impl.backend = self._getParent().backend.clone()
j._impl.application = self._getParent().application.clone()
if self.inputdata:
j.inputdata = self.inputdata.clone()
trf = self._getParent()
task = trf._getParent()
if trf.outputdata:
j.outputdata = trf.outputdata.clone()
elif j.inputdata and j.inputdata._impl._name == "ATLASLocalDataset" and j.application._impl._name != "TagPrepare":
j.outputdata = GPI.ATLASOutputDataset()
elif j.application._impl._name != "TagPrepare":
j.outputdata = GPI.DQ2OutputDataset()
# check for ds name specified and length
if j.outputdata and j.outputdata._impl._name == "DQ2OutputDataset":
max_length = configDQ2['OUTPUTDATASET_NAMELENGTH'] - 11
# merge names need to be shorter
if (j.backend._impl._name == "Panda" or j.backend._impl._name == "Jedi"):
if j.backend.requirements.enableMerge:
max_length -= 12
if j.backend._impl._name == "Jedi":
# go over the outputdata and check for output names that Jedi appends to the outDS name
tmp_len_chg = 8
for o in j.outputdata.outputdata:
if (len(o)+1) > tmp_len_chg:
tmp_len_chg = len(o)+1
max_length -= tmp_len_chg
elif j.backend.individualOutDS:
max_length -= 8
if j.outputdata.datasetname != "":
dsn = [j.outputdata.datasetname, "j%i.t%i.trf%i.u%i" %
(j.id, task.id, trf.getID(), self.getID())]
if len(".".join(dsn)) > max_length:
dsn = [j.outputdata.datasetname[: - (len(".".join(dsn)) - max_length)], "j%i.t%i.trf%i.u%i" %
(j.id, task.id, trf.getID(), self.getID())]
else:
dsn = [trf.getContainerName()[:-1], self.name, "j%i.t%i.trf%i.u%i" %
(j.id, task.id, trf.getID(), self.getID())]
if len(".".join(dsn)) > max_length:
dsn2 = [trf.getContainerName(2 * max_length / 3)[:-1], "", "j%i.t%i.trf%i.u%i" % (j.id, task.id, trf.getID(), self.getID())]
dsn = [trf.getContainerName(2 * max_length / 3)[:-1], self.name[: - (len(".".join(dsn2)) - max_length)], "j%i.t%i.trf%i.u%i" %
(j.id, task.id, trf.getID(), self.getID())]
j.outputdata.datasetname = '.'.join(dsn).replace(":", "_").replace(" ", "").replace(",","_")
j.inputsandbox = self._getParent().inputsandbox
j.outputsandbox = self._getParent().outputsandbox
# check for splitter - TagPrepare and Jedi don't user splitters
if j.application._impl._name == "TagPrepare":
return j
if j.backend._impl._name == "Jedi":
if trf.files_per_job > 0:
j.backend.requirements.nFilesPerJob = trf.files_per_job
elif trf.MB_per_job > 0:
j.backend.requirements.nGBPerJob = trf.MB_per_job / 1000
return j
if not trf.splitter:
# provide a default number of files if there's nothing else given
nfiles = trf.files_per_job
if nfiles < 1:
nfiles = 5
if j.inputdata._impl._name == "ATLASLocalDataset":
j.splitter = AthenaSplitterJob()
if trf.subjobs_per_unit > 0:
j.splitter.numsubjobs = trf.subjobs_per_unit
else:
import math
j.splitter.numsubjobs = int( math.ceil( len(j.inputdata.names) / float(nfiles) ) )
else:
j.splitter = DQ2JobSplitter()
if trf.MB_per_job > 0:
j.splitter.filesize = trf.MB_per_job
elif trf.subjobs_per_unit > 0:
j.splitter.numsubjobs = trf.subjobs_per_unit
else:
j.splitter.numfiles = nfiles
else:
j.splitter = trf.splitter.clone()
# postprocessors
if len(self._getParent().postprocessors.process_objects) > 0:
import copy
j.postprocessors = copy.deepcopy( addProxy(self._getParent()).postprocessors )
return j
