本文整理汇总了Python中taskbuffer.JobSpec.JobSpec.cloud方法的典型用法代码示例。如果您正苦于以下问题:Python JobSpec.cloud方法的具体用法?Python JobSpec.cloud怎么用?Python JobSpec.cloud使用的例子?那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类taskbuffer.JobSpec.JobSpec
的用法示例。
在下文中一共展示了JobSpec.cloud方法的11个代码示例,这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞,您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: defineEvgen16Job
# 需要导入模块: from taskbuffer.JobSpec import JobSpec [as 别名]
# 或者: from taskbuffer.JobSpec.JobSpec import cloud [as 别名]
def defineEvgen16Job(self, i):
"""Define an Evgen16 job based on predefined values and randomly generated names
"""
job = JobSpec()
job.computingSite = self.__site
job.cloud = self.__cloud
job.jobDefinitionID = int(time.time()) % 10000
job.jobName = "%s_%d" % (uuid.uuid1(), i)
job.AtlasRelease = 'Atlas-16.6.2'
job.homepackage = 'AtlasProduction/16.6.2.1'
job.transformation = 'Evgen_trf.py'
job.destinationDBlock = self.__datasetName
job.destinationSE = self.__destName
job.currentPriority = 10000
job.prodSourceLabel = 'test'
job.cmtConfig = 'i686-slc5-gcc43-opt'
#Output file
fileO = FileSpec()
fileO.lfn = "%s.evgen.pool.root" % job.jobName
fileO.destinationDBlock = job.destinationDBlock
fileO.destinationSE = job.destinationSE
fileO.dataset = job.destinationDBlock
fileO.destinationDBlockToken = 'ATLASDATADISK'
fileO.type = 'output'
job.addFile(fileO)
#Log file
fileL = FileSpec()
fileL.lfn = "%s.job.log.tgz" % job.jobName
fileL.destinationDBlock = job.destinationDBlock
fileL.destinationSE = job.destinationSE
fileL.dataset = job.destinationDBlock
fileL.destinationDBlockToken = 'ATLASDATADISK'
fileL.type = 'log'
job.addFile(fileL)
job.jobParameters = "2760 105048 19901 101 200 MC10.105048.PythiaB_ccmu3mu1X.py %s NONE NONE NONE MC10JobOpts-latest-test.tar.gz" % fileO.lfn
return job
示例2: range
# 需要导入模块: from taskbuffer.JobSpec import JobSpec [as 别名]
# 或者: from taskbuffer.JobSpec.JobSpec import cloud [as 别名]
jobList = []
for i in range(1):
job = JobSpec()
job.jobDefinitionID = int(time.time()) % 10000
job.jobName = "%s_%d" % (commands.getoutput('uuidgen'),i)
# job.AtlasRelease = 'Atlas-12.0.6'
# job.homepackage = 'AtlasProduction/12.0.6.5'
job.AtlasRelease = 'Atlas-12.0.7'
job.homepackage = 'AtlasProduction/12.0.7.1'
job.transformation = 'csc_evgen_trf.py'
job.destinationDBlock = datasetName
# job.destinationSE = destName
# job.cloud = 'CA'
job.cloud = cloud
job.taskID = taskid
job.currentPriority = 1000
job.prodSourceLabel = 'test'
# job.prodSourceLabel = 'cloudtest'
job.computingSite = site
file = FileSpec()
file.lfn = "%s.evgen.pool.root" % job.jobName
file.destinationDBlock = job.destinationDBlock
file.destinationSE = job.destinationSE
file.dataset = job.destinationDBlock
file.type = 'output'
job.addFile(file)
fileOL = FileSpec()
示例3: master_prepare
# 需要导入模块: from taskbuffer.JobSpec import JobSpec [as 别名]
# 或者: from taskbuffer.JobSpec.JobSpec import cloud [as 别名]
#.........这里部分代码省略.........
elif job.splitter._name not in ['DQ2JobSplitter', 'ArgSplitter', 'ArgSplitterTask']:
raise ApplicationConfigurationError('Panda splitter must be DQ2JobSplitter or ArgSplitter')
if job.backend.site == 'AUTO':
raise ApplicationConfigurationError('site is still AUTO after brokerage!')
# output dataset
if job.outputdata:
if job.outputdata._name != 'DQ2OutputDataset':
raise ApplicationConfigurationError('Panda backend supports only DQ2OutputDataset')
else:
logger.info('Adding missing DQ2OutputDataset')
job.outputdata = DQ2OutputDataset()
job.outputdata.datasetname,outlfn = dq2outputdatasetname(job.outputdata.datasetname, job.id, job.outputdata.isGroupDS, job.outputdata.groupname)
self.outDsLocation = Client.PandaSites[job.backend.site]['ddm']
try:
Client.addDataset(job.outputdata.datasetname,False,location=self.outDsLocation)
logger.info('Output dataset %s registered at %s'%(job.outputdata.datasetname,self.outDsLocation))
dq2_set_dataset_lifetime(job.outputdata.datasetname, location=self.outDsLocation)
except exceptions.SystemExit:
raise BackendError('Panda','Exception in Client.addDataset %s: %s %s'%(job.outputdata.datasetname,sys.exc_info()[0],sys.exc_info()[1]))
# handle the libds
if job.backend.libds:
self.libDataset = job.backend.libds
self.fileBO = getLibFileSpecFromLibDS(self.libDataset)
self.library = self.fileBO.lfn
elif job.backend.bexec:
self.libDataset = job.outputdata.datasetname+'.lib'
self.library = '%s.tgz' % self.libDataset
try:
Client.addDataset(self.libDataset,False,location=self.outDsLocation)
dq2_set_dataset_lifetime(self.libDataset, location=self.outDsLocation)
logger.info('Lib dataset %s registered at %s'%(self.libDataset,self.outDsLocation))
except exceptions.SystemExit:
raise BackendError('Panda','Exception in Client.addDataset %s: %s %s'%(self.libDataset,sys.exc_info()[0],sys.exc_info()[1]))
# collect extOutFiles
self.extOutFile = []
for tmpName in job.outputdata.outputdata:
if tmpName != '':
self.extOutFile.append(tmpName)
for tmpName in job.outputsandbox:
if tmpName != '':
self.extOutFile.append(tmpName)
for tmpName in job.backend.extOutFile:
if tmpName != '':
self.extOutFile.append(tmpName)
# create build job
if job.backend.bexec != '':
jspec = JobSpec()
jspec.jobDefinitionID = job.id
jspec.jobName = commands.getoutput('uuidgen 2> /dev/null')
jspec.transformation = '%s/buildGen-00-00-01' % Client.baseURLSUB
if Client.isDQ2free(job.backend.site):
jspec.destinationDBlock = '%s/%s' % (job.outputdata.datasetname,self.libDataset)
jspec.destinationSE = 'local'
else:
jspec.destinationDBlock = self.libDataset
jspec.destinationSE = job.backend.site
jspec.prodSourceLabel = configPanda['prodSourceLabelBuild']
jspec.processingType = configPanda['processingType']
jspec.assignedPriority = configPanda['assignedPriorityBuild']
jspec.computingSite = job.backend.site
jspec.cloud = job.backend.requirements.cloud
jspec.jobParameters = '-o %s' % (self.library)
if self.inputsandbox:
jspec.jobParameters += ' -i %s' % (self.inputsandbox)
else:
raise ApplicationConfigurationError('Executable on Panda with build job defined, but inputsandbox is emtpy !')
matchURL = re.search('(http.*://[^/]+)/',Client.baseURLCSRVSSL)
if matchURL:
jspec.jobParameters += ' --sourceURL %s ' % matchURL.group(1)
if job.backend.bexec != '':
jspec.jobParameters += ' --bexec "%s" ' % urllib.quote(job.backend.bexec)
jspec.jobParameters += ' -r %s ' % '.'
fout = FileSpec()
fout.lfn = self.library
fout.type = 'output'
fout.dataset = self.libDataset
fout.destinationDBlock = self.libDataset
jspec.addFile(fout)
flog = FileSpec()
flog.lfn = '%s.log.tgz' % self.libDataset
flog.type = 'log'
flog.dataset = self.libDataset
flog.destinationDBlock = self.libDataset
jspec.addFile(flog)
return jspec
else:
return None
示例4: prepare
# 需要导入模块: from taskbuffer.JobSpec import JobSpec [as 别名]
# 或者: from taskbuffer.JobSpec.JobSpec import cloud [as 别名]
def prepare(self,app,appsubconfig,appmasterconfig,jobmasterconfig):
'''prepare the subjob specific configuration'''
from pandatools import Client
from taskbuffer.JobSpec import JobSpec
from taskbuffer.FileSpec import FileSpec
job = app._getParent()
logger.debug('AthenaPandaRTHandler prepare called for %s', job.getFQID('.'))
# in case of a simple job get the dataset content, otherwise subjobs are filled by the splitter
if job.inputdata and not job._getRoot().subjobs:
if not job.inputdata.names:
contents = job.inputdata.get_contents(overlap=False, size=True)
for ds in contents.keys():
for f in contents[ds]:
job.inputdata.guids.append( f[0] )
job.inputdata.names.append( f[1][0] )
job.inputdata.sizes.append( f[1][1] )
job.inputdata.checksums.append( f[1][2] )
job.inputdata.scopes.append( f[1][3] )
site = job._getRoot().backend.site
job.backend.site = site
job.backend.actualCE = site
cloud = job._getRoot().backend.requirements.cloud
job.backend.requirements.cloud = cloud
# if no outputdata are given
if not job.outputdata:
job.outputdata = DQ2OutputDataset()
job.outputdata.datasetname = job._getRoot().outputdata.datasetname
#if not job.outputdata.datasetname:
else:
job.outputdata.datasetname = job._getRoot().outputdata.datasetname
if not job.outputdata.datasetname:
raise ApplicationConfigurationError('DQ2OutputDataset has no datasetname')
jspec = JobSpec()
jspec.jobDefinitionID = job._getRoot().id
jspec.jobName = commands.getoutput('uuidgen 2> /dev/null')
jspec.transformation = '%s/runGen-00-00-02' % Client.baseURLSUB
if job.inputdata:
jspec.prodDBlock = job.inputdata.dataset[0]
else:
jspec.prodDBlock = 'NULL'
jspec.destinationDBlock = job.outputdata.datasetname
if job.outputdata.location:
if not job._getRoot().subjobs or job.id == 0:
logger.warning('You have specified outputdata.location. Note that Panda may not support writing to a user-defined output location.')
jspec.destinationSE = job.outputdata.location
else:
jspec.destinationSE = site
jspec.prodSourceLabel = configPanda['prodSourceLabelRun']
jspec.processingType = configPanda['processingType']
jspec.assignedPriority = configPanda['assignedPriorityRun']
jspec.cloud = cloud
# memory
if job.backend.requirements.memory != -1:
jspec.minRamCount = job.backend.requirements.memory
# cputime
if job.backend.requirements.cputime != -1:
jspec.maxCpuCount = job.backend.requirements.cputime
jspec.computingSite = site
# library (source files)
if job.backend.libds:
flib = FileSpec()
flib.lfn = self.fileBO.lfn
flib.GUID = self.fileBO.GUID
flib.type = 'input'
flib.status = self.fileBO.status
flib.dataset = self.fileBO.destinationDBlock
flib.dispatchDBlock = self.fileBO.destinationDBlock
jspec.addFile(flib)
elif job.backend.bexec:
flib = FileSpec()
flib.lfn = self.library
flib.type = 'input'
flib.dataset = self.libDataset
flib.dispatchDBlock = self.libDataset
jspec.addFile(flib)
# input files FIXME: many more input types
if job.inputdata:
for guid, lfn, size, checksum, scope in zip(job.inputdata.guids,job.inputdata.names,job.inputdata.sizes, job.inputdata.checksums, job.inputdata.scopes):
finp = FileSpec()
finp.lfn = lfn
finp.GUID = guid
finp.scope = scope
# finp.fsize =
# finp.md5sum =
finp.dataset = job.inputdata.dataset[0]
#.........这里部分代码省略.........
示例5: prepare
# 需要导入模块: from taskbuffer.JobSpec import JobSpec [as 别名]
# 或者: from taskbuffer.JobSpec.JobSpec import cloud [as 别名]
def prepare(self, app, appsubconfig, appmasterconfig, jobmasterconfig):
"""Prepare the specific aspec of each subjob.
Returns: subjobconfig list of objects understood by backends."""
from pandatools import Client
from pandatools import AthenaUtils
from taskbuffer.JobSpec import JobSpec
from taskbuffer.FileSpec import FileSpec
from GangaAtlas.Lib.ATLASDataset.DQ2Dataset import dq2_set_dataset_lifetime
from GangaPanda.Lib.Panda.Panda import refreshPandaSpecs
# make sure we have the correct siteType
refreshPandaSpecs()
job = app._getParent()
masterjob = job._getRoot()
logger.debug('ProdTransPandaRTHandler prepare called for %s',
job.getFQID('.'))
job.backend.actualCE = job.backend.site
job.backend.requirements.cloud = Client.PandaSites[job.backend.site]['cloud']
# check that the site is in a submit-able status
if not job.splitter or job.splitter._name != 'DQ2JobSplitter':
allowed_sites = job.backend.list_ddm_sites()
try:
outDsLocation = Client.PandaSites[job.backend.site]['ddm']
tmpDsExist = False
if (configPanda['processingType'].startswith('gangarobot') or configPanda['processingType'].startswith('hammercloud')):
#if Client.getDatasets(job.outputdata.datasetname):
if getDatasets(job.outputdata.datasetname):
tmpDsExist = True
logger.info('Re-using output dataset %s'%job.outputdata.datasetname)
if not configPanda['specialHandling']=='ddm:rucio' and not configPanda['processingType'].startswith('gangarobot') and not configPanda['processingType'].startswith('hammercloud') and not configPanda['processingType'].startswith('rucio_test'):
Client.addDataset(job.outputdata.datasetname,False,location=outDsLocation,allowProdDisk=True,dsExist=tmpDsExist)
logger.info('Output dataset %s registered at %s'%(job.outputdata.datasetname,outDsLocation))
dq2_set_dataset_lifetime(job.outputdata.datasetname, outDsLocation)
except exceptions.SystemExit:
raise BackendError('Panda','Exception in adding dataset %s: %s %s'%(job.outputdata.datasetname,sys.exc_info()[0],sys.exc_info()[1]))
# JobSpec.
jspec = JobSpec()
jspec.currentPriority = app.priority
jspec.jobDefinitionID = masterjob.id
jspec.jobName = commands.getoutput('uuidgen 2> /dev/null')
jspec.coreCount = app.core_count
jspec.AtlasRelease = 'Atlas-%s' % app.atlas_release
jspec.homepackage = app.home_package
jspec.transformation = app.transformation
jspec.destinationDBlock = job.outputdata.datasetname
if job.outputdata.location:
jspec.destinationSE = job.outputdata.location
else:
jspec.destinationSE = job.backend.site
if job.inputdata:
jspec.prodDBlock = job.inputdata.dataset[0]
else:
jspec.prodDBlock = 'NULL'
if app.prod_source_label:
jspec.prodSourceLabel = app.prod_source_label
else:
jspec.prodSourceLabel = configPanda['prodSourceLabelRun']
jspec.processingType = configPanda['processingType']
jspec.specialHandling = configPanda['specialHandling']
jspec.computingSite = job.backend.site
jspec.cloud = job.backend.requirements.cloud
jspec.cmtConfig = app.atlas_cmtconfig
if app.dbrelease == 'LATEST':
try:
latest_dbrelease = getLatestDBReleaseCaching()
except:
from pandatools import Client
latest_dbrelease = Client.getLatestDBRelease()
m = re.search('(.*):DBRelease-(.*)\.tar\.gz', latest_dbrelease)
if m:
self.dbrelease_dataset = m.group(1)
self.dbrelease = m.group(2)
else:
raise ApplicationConfigurationError(None, "Error retrieving LATEST DBRelease. Try setting application.dbrelease manually.")
else:
self.dbrelease_dataset = app.dbrelease_dataset
self.dbrelease = app.dbrelease
jspec.jobParameters = app.job_parameters
if self.dbrelease:
if self.dbrelease == 'current':
jspec.jobParameters += ' --DBRelease=current'
else:
if jspec.transformation.endswith("_tf.py") or jspec.transformation.endswith("_tf"):
jspec.jobParameters += ' --DBRelease=DBRelease-%s.tar.gz' % (self.dbrelease,)
else:
jspec.jobParameters += ' DBRelease=DBRelease-%s.tar.gz' % (self.dbrelease,)
dbspec = FileSpec()
dbspec.lfn = 'DBRelease-%s.tar.gz' % self.dbrelease
dbspec.dataset = self.dbrelease_dataset
dbspec.prodDBlock = jspec.prodDBlock
dbspec.type = 'input'
jspec.addFile(dbspec)
#.........这里部分代码省略.........
示例6: master_prepare
# 需要导入模块: from taskbuffer.JobSpec import JobSpec [as 别名]
# 或者: from taskbuffer.JobSpec.JobSpec import cloud [as 别名]
#.........这里部分代码省略.........
## if cloudSite==eachCloud:
## cloud=cloudID
## outclouds.append(cloud)
## break
## print outclouds
## # finally, matching with user's wishes
## if len(outclouds)>0:
## if not job.backend.requirements.cloud: # no user wish, update
## job.backend.requirements.cloud=outclouds[0]
## else:
## try:
## assert job.backend.requirements.cloud in outclouds
## except:
## raise ApplicationConfigurationError(None,'Input dataset not available in target cloud %s. Please try any of the following %s' % (job.backend.requirements.cloud, str(outclouds)))
from GangaPanda.Lib.Panda.Panda import runPandaBrokerage
runPandaBrokerage(job)
if job.backend.site == 'AUTO':
raise ApplicationConfigurationError(None,'site is still AUTO after brokerage!')
# output dataset preparation and registration
try:
outDsLocation = Client.PandaSites[job.backend.site]['ddm']
except:
raise ApplicationConfigurationError(None,"Could not extract output dataset location from job.backend.site value: %s. Aborting" % job.backend.site)
if not app.dryrun:
for outtype in app.outputpaths.keys():
dset=string.replace(app.outputpaths[outtype],"/",".")
dset=dset[1:]
# dataset registration must be done only once.
print "registering output dataset %s at %s" % (dset,outDsLocation)
try:
Client.addDataset(dset,False,location=outDsLocation)
dq2_set_dataset_lifetime(dset, location=outDsLocation)
except:
raise ApplicationConfigurationError(None,"Fail to create output dataset %s. Aborting" % dset)
# extend registration to build job lib dataset:
print "registering output dataset %s at %s" % (self.libDataset,outDsLocation)
try:
Client.addDataset(self.libDataset,False,location=outDsLocation)
dq2_set_dataset_lifetime(self.libDataset, outDsLocation)
except:
raise ApplicationConfigurationError(None,"Fail to create output dataset %s. Aborting" % self.libDataset)
###
cacheVer = "-AtlasProduction_" + str(app.prod_release)
logger.debug("master job submit?")
self.outsite=job.backend.site
if app.se_name and app.se_name != "none" and not self.outsite:
self.outsite=app.se_name
# create build job
jspec = JobSpec()
jspec.jobDefinitionID = job.id
jspec.jobName = commands.getoutput('uuidgen 2> /dev/null')
jspec.AtlasRelease = 'Atlas-%s' % app.atlas_rel
jspec.homepackage = 'AnalysisTransforms'+cacheVer#+nightVer
jspec.transformation = '%s/buildJob-00-00-03' % Client.baseURLSUB # common base to Athena and AthenaMC jobs: buildJob is a pilot job which takes care of all inputs for the real jobs (in prepare()
jspec.destinationDBlock = self.libDataset
jspec.destinationSE = job.backend.site
jspec.prodSourceLabel = 'panda'
jspec.assignedPriority = 2000
jspec.computingSite = job.backend.site
jspec.cloud = job.backend.requirements.cloud
# jspec.jobParameters = self.args not known yet
jspec.jobParameters = '-o %s' % (self.library)
if app.userarea:
print app.userarea
jspec.jobParameters += ' -i %s' % (os.path.basename(app.userarea))
else:
jspec.jobParameters += ' -i %s' % (sources)
jspec.cmtConfig = AthenaUtils.getCmtConfig(athenaVer=app.atlas_rel)
matchURL = re.search('(http.*://[^/]+)/',Client.baseURLSSL)
if matchURL:
jspec.jobParameters += ' --sourceURL %s' % matchURL.group(1)
fout = FileSpec()
fout.lfn = self.library
fout.type = 'output'
fout.dataset = self.libDataset
fout.destinationDBlock = self.libDataset
jspec.addFile(fout)
flog = FileSpec()
flog.lfn = '%s.log.tgz' % self.libDataset
flog.type = 'log'
flog.dataset = self.libDataset
flog.destinationDBlock = self.libDataset
jspec.addFile(flog)
#print "MASTER JOB DETAILS:",jspec.jobParameters
return jspec
示例7: prepare
# 需要导入模块: from taskbuffer.JobSpec import JobSpec [as 别名]
# 或者: from taskbuffer.JobSpec.JobSpec import cloud [as 别名]
def prepare(self,app,appconfig,appmasterconfig,jobmasterconfig):
'''prepare the subjob specific configuration'''
# PandaTools
from pandatools import Client
from pandatools import AthenaUtils
from taskbuffer.JobSpec import JobSpec
from taskbuffer.FileSpec import FileSpec
job = app._getParent()
logger.debug('AthenaMCPandaRTHandler prepare called for %s', job.getFQID('.'))
try:
assert self.outsite
except:
logger.error("outsite not set. Aborting")
raise Exception()
job.backend.site = self.outsite
job.backend.actualCE = self.outsite
cloud = job._getRoot().backend.requirements.cloud
job.backend.requirements.cloud = cloud
# now just filling the job from AthenaMC data
jspec = JobSpec()
jspec.jobDefinitionID = job._getRoot().id
jspec.jobName = commands.getoutput('uuidgen 2> /dev/null')
jspec.AtlasRelease = 'Atlas-%s' % app.atlas_rel
if app.transform_archive:
jspec.homepackage = 'AnalysisTransforms'+app.transform_archive
elif app.prod_release:
jspec.homepackage = 'AnalysisTransforms-AtlasProduction_'+str(app.prod_release)
jspec.transformation = '%s/runAthena-00-00-11' % Client.baseURLSUB
#---->???? prodDBlock and destinationDBlock when facing several input / output datasets?
jspec.prodDBlock = 'NULL'
if job.inputdata and len(app.inputfiles)>0 and app.inputfiles[0] in app.dsetmap:
jspec.prodDBlock = app.dsetmap[app.inputfiles[0]]
# How to specify jspec.destinationDBlock when more than one type of output is available? Panda prod jobs seem to specify only the last output dataset
outdset=""
for type in ["EVNT","RDO","HITS","AOD","ESD","NTUP"]:
if type in app.outputpaths.keys():
outdset=string.replace(app.outputpaths[type],"/",".")
outdset=outdset[1:-1]
break
if not outdset:
try:
assert len(app.outputpaths.keys())>0
except:
logger.error("app.outputpaths is empty: check your output datasets")
raise
type=app.outputpaths.keys()[0]
outdset=string.replace(app.outputpaths[type],"/",".")
outdset=outdset[1:-1]
jspec.destinationDBlock = outdset
jspec.destinationSE = self.outsite
jspec.prodSourceLabel = 'user'
jspec.assignedPriority = 1000
jspec.cloud = cloud
# memory
if job.backend.requirements.memory != -1:
jspec.minRamCount = job.backend.requirements.memory
jspec.computingSite = self.outsite
jspec.cmtConfig = AthenaUtils.getCmtConfig(athenaVer=app.atlas_rel)
# library (source files)
flib = FileSpec()
flib.lfn = self.library
# flib.GUID =
flib.type = 'input'
# flib.status =
flib.dataset = self.libDataset
flib.dispatchDBlock = self.libDataset
jspec.addFile(flib)
# input files FIXME: many more input types
for lfn in app.inputfiles:
useguid=app.turls[lfn].replace("guid:","")
finp = FileSpec()
finp.lfn = lfn
finp.GUID = useguid
finp.dataset = app.dsetmap[lfn]
finp.prodDBlock = app.dsetmap[lfn]
finp.prodDBlockToken = 'local'
finp.dispatchDBlock = app.dsetmap[lfn]
finp.type = 'input'
finp.status = 'ready'
jspec.addFile(finp)
# add dbfiles if any:
for lfn in app.dbfiles:
useguid=app.dbturls[lfn].replace("guid:","")
finp = FileSpec()
finp.lfn = lfn
finp.GUID = useguid
finp.dataset = app.dsetmap[lfn]
#.........这里部分代码省略.........
示例8: createJobSpec
# 需要导入模块: from taskbuffer.JobSpec import JobSpec [as 别名]
# 或者: from taskbuffer.JobSpec.JobSpec import cloud [as 别名]
def createJobSpec(self, task, outdataset, job, jobset, jobdef, site, jobname, lfnhanger, allsites, jobid):
"""Create a spec for one job
:arg TaskWorker.DataObject.Task task: the task to work on
:arg str outdataset: the output dataset name where all the produced files will be placed
:arg WMCore.DataStructs.Job job: the abstract job
:arg int jobset: the PanDA jobset corresponding to the current task
:arg int jobdef: the PanDA jobdef where to append the current jobs --- not used
:arg str site: the borkered site where to run the jobs
:arg str jobname: the job name
:arg str lfnhanger: the random string to be added in the output file name
:arg list str allsites: all possible sites where the job can potentially run
:arg int jobid: incremental job number
:return: the sepc object."""
pandajob = JobSpec()
## always setting a job definition ID
pandajob.jobDefinitionID = jobdef if jobdef else -1
## always setting a job set ID
pandajob.jobsetID = jobset if jobset else -1
pandajob.jobName = jobname
pandajob.prodUserID = task['tm_user_dn']
pandajob.destinationDBlock = outdataset
pandajob.prodDBlock = task['tm_input_dataset']
pandajob.prodSourceLabel = 'user'
pandajob.computingSite = site
pandajob.cloud = getSite(pandajob.computingSite)
pandajob.destinationSE = 'local'
pandajob.transformation = task['tm_transformation']
## need to initialize this
pandajob.metadata = ''
def outFileSpec(of=None, log=False):
"""Local routine to create an FileSpec for the an job output/log file
:arg str of: output file base name
:return: FileSpec object for the output file."""
outfile = FileSpec()
if log:
outfile.lfn = "job.log_%d_%s.tgz" % (jobid, lfnhanger)
outfile.type = 'log'
else:
outfile.lfn = '%s_%d_%s%s' %(os.path.splitext(of)[0], jobid, lfnhanger, os.path.splitext(of)[1])
outfile.type = 'output'
outfile.destinationDBlock = pandajob.destinationDBlock
outfile.destinationSE = task['tm_asyncdest']
outfile.dataset = pandajob.destinationDBlock
return outfile
alloutfiles = []
outjobpar = {}
outfilestring = ''
for outputfile in task['tm_outfiles']:
outfilestring += '%s,' % outputfile
filespec = outFileSpec(outputfile)
alloutfiles.append(filespec)
#pandajob.addFile(filespec)
outjobpar[outputfile] = filespec.lfn
for outputfile in task['tm_tfile_outfiles']:
outfilestring += '%s,' % outputfile
filespec = outFileSpec(outputfile)
alloutfiles.append(filespec)
#pandajob.addFile(filespec)
outjobpar[outputfile] = filespec.lfn
for outputfile in task['tm_edm_outfiles']:
outfilestring += '%s,' % outputfile
filespec = outFileSpec(outputfile)
alloutfiles.append(filespec)
#pandajob.addFile(filespec)
outjobpar[outputfile] = filespec.lfn
outfilestring = outfilestring[:-1]
infiles = []
for inputfile in job['input_files']:
infiles.append( inputfile['lfn'] )
pandajob.jobParameters = '-a %s ' % task['tm_user_sandbox']
pandajob.jobParameters += '--sourceURL %s ' % task['tm_cache_url']
pandajob.jobParameters += '--jobNumber=%s ' % jobid
pandajob.jobParameters += '--cmsswVersion=%s ' % task['tm_job_sw']
pandajob.jobParameters += '--scramArch=%s ' % task['tm_job_arch']
pandajob.jobParameters += '--inputFile=\'%s\' ' % json.dumps(infiles)
self.jobParametersSetting(pandajob, job, self.jobtypeMapper[task['tm_job_type']])
pandajob.jobParameters += '-o "%s" ' % str(outjobpar)
pandajob.jobParameters += '--dbs_url=%s ' % task['tm_dbs_url']
pandajob.jobParameters += '--publish_dbs_url=%s ' % task['tm_publish_dbs_url']
pandajob.jobParameters += '--publishFiles=%s ' % ('True' if task['tm_publication'] == 'T' else 'False')
pandajob.jobParameters += '--saveLogs=%s ' % ('True' if task['tm_save_logs'] == 'T' else 'False')
pandajob.jobParameters += '--availableSites=\'%s\' ' %json.dumps(allsites)
pandajob.jobParameters += '--group=%s ' % (task['tm_user_group'] if task['tm_user_group'] else '')
pandajob.jobParameters += '--role=%s ' % (task['tm_user_role'] if task['tm_user_role'] else '')
self.logger.info(type(task['tm_user_infiles']))
self.logger.info(task['tm_user_infiles'])
if task['tm_user_infiles']:
addinfilestring = ''
#.........这里部分代码省略.........
示例9: JobSpec
# 需要导入模块: from taskbuffer.JobSpec import JobSpec [as 别名]
# 或者: from taskbuffer.JobSpec.JobSpec import cloud [as 别名]
index = 0
for lfn in files.keys():
index += 1
job = JobSpec()
job.jobDefinitionID = int(time.time()) % 10000
job.jobName = "%s_%d" % (commands.getoutput('uuidgen'),index)
job.AtlasRelease = 'Atlas-12.0.6'
job.homepackage = 'AtlasProduction/12.0.6.4'
job.transformation = 'csc_reco_trf.py'
job.destinationDBlock = datasetName
job.destinationSE = destName
job.computingSite = site
#job.prodDBlock = 'misal1_mc12.005200.T1_McAtNlo_Jimmy.digit.RDO.v12000601_tid007554'
job.prodDBlock = 'misal1_mc12.005802.JF17_pythia_jet_filter.digit.RDO.v12000601_tid008610'
job.cloud = 'US'
job.prodSourceLabel = 'test'
job.currentPriority = 10000
job.cmtConfig = 'i686-slc4-gcc34-opt'
fileI = FileSpec()
fileI.dataset = job.prodDBlock
fileI.prodDBlock = job.prodDBlock
fileI.lfn = lfn
fileI.type = 'input'
job.addFile(fileI)
fileD = FileSpec()
fileD.dataset = 'ddo.000001.Atlas.Ideal.DBRelease.v030101'
fileD.prodDBlock = 'ddo.000001.Atlas.Ideal.DBRelease.v030101'
示例10: JobSpec
# 需要导入模块: from taskbuffer.JobSpec import JobSpec [as 别名]
# 或者: from taskbuffer.JobSpec.JobSpec import cloud [as 别名]
for lfn in files.keys():
index += 1
job = JobSpec()
job.jobDefinitionID = int(time.time()) % 10000
job.jobName = "%s_%d" % (commands.getoutput('uuidgen'),index)
job.AtlasRelease = 'Atlas-13.0.40'
job.homepackage = 'AtlasProduction/13.0.40.3'
job.transformation = 'csc_simul_trf.py'
job.destinationDBlock = datasetName
job.destinationSE = destName
job.computingSite = site
job.prodDBlock = 'valid1.005001.pythia_minbias.evgen.EVNT.e306_tid019128'
job.prodSourceLabel = 'test'
job.currentPriority = 10000
job.cloud = 'IT'
fileI = FileSpec()
fileI.dataset = job.prodDBlock
fileI.prodDBlock = job.prodDBlock
fileI.lfn = lfn
fileI.type = 'input'
job.addFile(fileI)
fileD = FileSpec()
fileD.dataset = 'ddo.000001.Atlas.Ideal.DBRelease.v040701'
fileD.prodDBlock = 'ddo.000001.Atlas.Ideal.DBRelease.v030101'
fileD.lfn = 'DBRelease-4.7.1.tar.gz'
fileD.type = 'input'
job.addFile(fileD)
示例11: send_job
# 需要导入模块: from taskbuffer.JobSpec import JobSpec [as 别名]
# 或者: from taskbuffer.JobSpec.JobSpec import cloud [as 别名]
def send_job(jobid, siteid):
_logger.debug('Jobid: ' + str(jobid))
site = sites_.get(siteid)
job = jobs_.get(int(jobid))
cont = job.container
files_catalog = cont.files
fscope = getScope(job.owner.username)
datasetName = '{}:{}'.format(fscope, cont.guid)
distributive = job.distr.name
release = job.distr.release
# Prepare runScript
parameters = job.distr.command
parameters = parameters.replace("$COMMAND$", job.params)
parameters = parameters.replace("$USERNAME$", job.owner.username)
parameters = parameters.replace("$WORKINGGROUP$", job.owner.working_group)
# Prepare metadata
metadata = dict(user=job.owner.username)
# Prepare PanDA Object
pandajob = JobSpec()
pandajob.jobDefinitionID = int(time.time()) % 10000
pandajob.jobName = cont.guid
pandajob.transformation = client_config.DEFAULT_TRF
pandajob.destinationDBlock = datasetName
pandajob.destinationSE = site.se
pandajob.currentPriority = 1000
pandajob.prodSourceLabel = 'user'
pandajob.computingSite = site.ce
pandajob.cloud = 'RU'
pandajob.VO = 'atlas'
pandajob.prodDBlock = "%s:%s" % (fscope, pandajob.jobName)
pandajob.coreCount = job.corecount
pandajob.metadata = json.dumps(metadata)
#pandajob.workingGroup = job.owner.working_group
if site.encode_commands:
# It requires script wrapper on cluster side
pandajob.jobParameters = '%s %s %s "%s"' % (cont.guid, release, distributive, parameters)
else:
pandajob.jobParameters = parameters
has_input = False
for fcc in files_catalog:
if fcc.type == 'input':
f = fcc.file
guid = f.guid
fileIT = FileSpec()
fileIT.lfn = f.lfn
fileIT.dataset = pandajob.prodDBlock
fileIT.prodDBlock = pandajob.prodDBlock
fileIT.type = 'input'
fileIT.scope = fscope
fileIT.status = 'ready'
fileIT.GUID = guid
pandajob.addFile(fileIT)
has_input = True
if fcc.type == 'output':
f = fcc.file
fileOT = FileSpec()
fileOT.lfn = f.lfn
fileOT.destinationDBlock = pandajob.prodDBlock
fileOT.destinationSE = pandajob.destinationSE
fileOT.dataset = pandajob.prodDBlock
fileOT.type = 'output'
fileOT.scope = fscope
fileOT.GUID = f.guid
pandajob.addFile(fileOT)
# Save replica meta
fc.new_replica(f, site)
if not has_input:
# Add fake input
fileIT = FileSpec()
fileIT.lfn = "fake.input"
fileIT.dataset = pandajob.prodDBlock
fileIT.prodDBlock = pandajob.prodDBlock
fileIT.type = 'input'
fileIT.scope = fscope
fileIT.status = 'ready'
fileIT.GUID = "fake.guid"
pandajob.addFile(fileIT)
# Prepare lof file
fileOL = FileSpec()
fileOL.lfn = "%s.log.tgz" % pandajob.jobName
fileOL.destinationDBlock = pandajob.destinationDBlock
fileOL.destinationSE = pandajob.destinationSE
fileOL.dataset = '{}:logs'.format(fscope)
fileOL.type = 'log'
fileOL.scope = 'panda'
pandajob.addFile(fileOL)
#.........这里部分代码省略.........