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')
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)
return True
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 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 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()
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 _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
