def _setup_bulk_subjobs(self, dirac_ids, dirac_script):
"""
This is the old bulk submit method which is used to construct the subjobs for a parametric job
Args:
dirac_ids (list): This is a list of the Dirac ids which have been created
dirac_script (str): Name of the dirac script which contains the job jdl
"""
f = open(dirac_script, 'r')
parametric_datasets = get_parametric_datasets(f.read().split('\n'))
f.close()
if len(parametric_datasets) != len(dirac_ids):
raise BackendError(
'Dirac',
'Missmatch between number of datasets defines in dirac API script and those returned by DIRAC'
)
master_job = self.getJobObject()
master_job.subjobs = []
for i in range(len(dirac_ids)):
j = Job()
j.copyFrom(master_job)
j.splitter = None
j.backend.id = dirac_ids[i]
j.id = i
j.inputdata = self._setup_subjob_dataset(parametric_datasets[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 createSubjob(self, job, additional_skip_args=None):
""" Create a new subjob by copying the master job and setting all fields correctly.
"""
from Ganga.GPIDev.Lib.Job.Job import Job
if additional_skip_args is None:
additional_skip_args = []
j = Job()
skipping_args = [
'splitter', 'inputsandbox', 'inputfiles', 'inputdata', 'subjobs'
]
for arg in additional_skip_args:
skipping_args.append(arg)
j.copyFrom(job, skipping_args)
j.splitter = None
j.inputsandbox = []
j.inputfiles = []
j.inputdata = None
return j
def _setup_bulk_subjobs(self, dirac_ids, dirac_script):
f = open(dirac_script, 'r')
parametric_datasets = get_parametric_datasets(f.read().split('\n'))
f.close()
if len(parametric_datasets) != len(dirac_ids):
raise BackendError('Dirac', 'Missmatch between number of datasets defines in dirac API script and those returned by DIRAC')
from Ganga.GPIDev.Lib.Job.Job import Job
master_job = self.getJobObject()
master_job.subjobs = []
for i in range(len(dirac_ids)):
j = Job()
j.copyFrom(master_job)
j.splitter = None
j.backend.id = dirac_ids[i]
j.id = i
j.inputdata = self._setup_subjob_dataset(parametric_datasets[i])
j.status = 'submitted'
j.time.timenow('submitted')
master_job.subjobs.append(j)
master_job._commit()
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 master_updateMonitoringInformation(jobs):
"""Updates the statuses of the list of jobs provided by issuing crab -status."""
logger.info('Updating the monitoring information of ' +
str(len(jobs)) + ' jobs')
try:
from Ganga.GPIDev.Lib.Job.Job import Job
import sys, traceback
for j in jobs:
server = CRABServer()
logger.debug(
'Updating monitoring information for job %d (%s)' %
(j.id, j.status))
try:
dictresult, status, reason = server.status(j)
logger.info(
'CRAB3 server call answer status: %s - reason: %s' %
(status, reason))
joblist = sorted(dictresult['result'][0]['jobList'],
key=lambda x: x[1])
except KeyError:
logger.info(
'Get status for job %d didn\'t return job list, skipping job for now.'
% j.id)
continue
except:
logger.error('Get status for job %d failed, skipping.' %
j.id)
raise
if joblist:
logger.info('There are subjob statuses for job %s' % j.id)
logger.info('j: %s' % dir(j))
if not j.subjobs:
logger.warning('No subjob object for job %s' % j.id)
j.subjobs = []
for i in xrange(len(joblist)):
subjob = joblist[i]
index = int(subjob[1])
logger.info('Processing subjob %d, %s' %
(index, subjob))
sj = Job()
sj.copyFrom(j)
sj.backend.crabid = index
sj.id = i
sj.updateStatus('submitting')
sj.backend.checkReport(subjob)
sj.backend.checkStatus()
j.subjobs.append(sj)
#j.subjobs = sorted(j.subjobs, key=lambda x: x.backend.id)
#j._commit()
else:
for subjob in joblist:
index = int(subjob[1])
logger.debug(
'Found subjob %s searching with index %s' %
(j.subjobs[index - 1].backend.crabid, index))
j.subjobs[index - 1].backend.checkReport(subjob)
j.subjobs[index - 1].backend.checkStatus()
j.updateMasterJobStatus()
else:
logger.info('There are no subjobs for job %s' % (j.id))
logger.info('checking task status from report: %s' %
dictresult['result'][0]['status'])
taskstatus = dictresult['result'][0]['status']
if taskstatus in ['FAILED']:
logger.info('Job failed: %s' % dictresult)
j.updateStatus('failed')
except Exception as e:
logger.error(e)
traceback.print_exc(file=sys.stdout)
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)
def makeRegisteredJob():
"""Makes a new Job and registers it with the Registry"""
from Ganga.GPIDev.Lib.Job.Job import Job
j = Job()
j._auto__init__()
return j
