def master_prepare(self,app,appconfig):
'''Prepare the master job'''
from pandatools import Client
from taskbuffer.JobSpec import JobSpec
from taskbuffer.FileSpec import FileSpec
job = app._getParent()
logger.debug('ExecutablePandaRTHandler master_prepare called for %s', job.getFQID('.'))
# set chirp variables
if configPanda['chirpconfig'] or configPanda['chirpserver']:
setChirpVariables()
# Pack inputsandbox
inputsandbox = 'sources.%s.tar' % commands.getoutput('uuidgen 2> /dev/null')
inpw = job.getInputWorkspace()
# add user script to inputsandbox
if hasattr(job.application.exe, "name"):
if not job.application.exe in job.inputsandbox:
job.inputsandbox.append(job.application.exe)
for fname in [f.name for f in job.inputsandbox]:
fname.rstrip(os.sep)
path = fname[:fname.rfind(os.sep)]
f = fname[fname.rfind(os.sep)+1:]
rc, output = commands.getstatusoutput('tar rf %s -C %s %s' % (inpw.getPath(inputsandbox), path, f))
if rc:
logger.error('Packing inputsandbox failed with status %d',rc)
logger.error(output)
raise ApplicationConfigurationError('Packing inputsandbox failed.')
if len(job.inputsandbox) > 0:
rc, output = commands.getstatusoutput('gzip %s' % (inpw.getPath(inputsandbox)))
if rc:
logger.error('Packing inputsandbox failed with status %d',rc)
logger.error(output)
raise ApplicationConfigurationError('Packing inputsandbox failed.')
inputsandbox += ".gz"
else:
inputsandbox = None
# Upload Inputsandbox
if inputsandbox:
logger.debug('Uploading source tarball ...')
uploadSources(inpw.getPath(),os.path.basename(inputsandbox))
self.inputsandbox = inputsandbox
else:
self.inputsandbox = None
# input dataset
if job.inputdata:
if job.inputdata._name != 'DQ2Dataset':
raise ApplicationConfigurationError('PANDA application supports only DQ2Datasets')
# run brokerage here if not splitting
if not job.splitter:
from GangaPanda.Lib.Panda.Panda import runPandaBrokerage
runPandaBrokerage(job)
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
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)
if job.inputdata:
m = re.search('(.*)\.(.*)\.(.*)\.(.*)\.(.*)\.(.*)',
job.inputdata.dataset[0])
if not m:
logger.error("Error retrieving run number from dataset name")
#raise ApplicationConfigurationError(None, "Error retrieving run number from dataset name")
runnumber = 105200
else:
runnumber = int(m.group(2))
if jspec.transformation.endswith("_tf.py") or jspec.transformation.endswith("_tf"):
jspec.jobParameters += ' --runNumber %d' % runnumber
else:
jspec.jobParameters += ' RunNumber=%d' % runnumber
# Output files.
randomized_lfns = []
ilfn = 0
for lfn, lfntype in zip(app.output_files,app.output_type):
ofspec = FileSpec()
if app.randomize_lfns:
randomized_lfn = lfn + ('.%s.%d.%s' % (job.backend.site, int(time.time()), commands.getoutput('uuidgen 2> /dev/null')[:4] ) )
else:
randomized_lfn = lfn
ofspec.lfn = randomized_lfn
randomized_lfns.append(randomized_lfn)
ofspec.destinationDBlock = jspec.destinationDBlock
ofspec.destinationSE = jspec.destinationSE
ofspec.dataset = jspec.destinationDBlock
ofspec.type = 'output'
jspec.addFile(ofspec)
if jspec.transformation.endswith("_tf.py") or jspec.transformation.endswith("_tf"):
jspec.jobParameters += ' --output%sFile %s' % (lfntype, randomized_lfns[ilfn])
else:
jspec.jobParameters += ' output%sFile=%s' % (lfntype, randomized_lfns[ilfn])
ilfn=ilfn+1
# Input files.
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):
ifspec = FileSpec()
ifspec.lfn = lfn
ifspec.GUID = guid
ifspec.fsize = size
ifspec.md5sum = checksum
ifspec.scope = scope
ifspec.dataset = jspec.prodDBlock
ifspec.prodDBlock = jspec.prodDBlock
ifspec.type = 'input'
jspec.addFile(ifspec)
if app.input_type:
itype = app.input_type
else:
itype = m.group(5)
if jspec.transformation.endswith("_tf.py") or jspec.transformation.endswith("_tf"):
jspec.jobParameters += ' --input%sFile %s' % (itype, ','.join(job.inputdata.names))
else:
jspec.jobParameters += ' input%sFile=%s' % (itype, ','.join(job.inputdata.names))
# Log files.
lfspec = FileSpec()
lfspec.lfn = '%s.job.log.tgz' % jspec.jobName
lfspec.destinationDBlock = jspec.destinationDBlock
lfspec.destinationSE = jspec.destinationSE
lfspec.dataset = jspec.destinationDBlock
lfspec.type = 'log'
jspec.addFile(lfspec)
return jspec
def master_prepare(self,app,appmasterconfig):
# 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 master_prepare called for %s', job.getFQID('.'))
usertag = configDQ2['usertag']
#usertag='user09'
nickname = getNickname(allowMissingNickname=True)
self.libDataset = '%s.%s.ganga.%s_%d.lib._%06d' % (usertag,nickname,commands.getoutput('hostname').split('.')[0],int(time.time()),job.id)
# self.userprefix='%s.%s.ganga' % (usertag,gridProxy.identity())
sources = 'sources.%s.tar.gz' % commands.getoutput('uuidgen 2> /dev/null')
self.library = '%s.lib.tgz' % self.libDataset
# check DBRelease
# if job.backend.dbRelease != '' and job.backend.dbRelease.find(':') == -1:
# raise ApplicationConfigurationError(None,"ERROR : invalid argument for backend.dbRelease. Must be 'DatasetName:FileName'")
# unpack library
logger.debug('Creating source tarball ...')
tmpdir = '/tmp/%s' % commands.getoutput('uuidgen 2> /dev/null')
os.mkdir(tmpdir)
inputbox=[]
if os.path.exists(app.transform_archive):
# must add a condition on size.
inputbox += [ File(app.transform_archive) ]
if app.evgen_job_option:
self.evgen_job_option=app.evgen_job_option
if os.path.exists(app.evgen_job_option):
# locally modified job option file to add to the input sand box
inputbox += [ File(app.evgen_job_option) ]
self.evgen_job_option=app.evgen_job_option.split("/")[-1]
# add input sandbox files
if (job.inputsandbox):
for file in job.inputsandbox:
inputbox += [ file ]
# add option files
for extFile in job.backend.extOutFile:
try:
shutil.copy(extFile,tmpdir)
except IOError:
os.makedirs(tmpdir)
shutil.copy(extFile,tmpdir)
# fill the archive
for opt_file in inputbox:
try:
shutil.copy(opt_file.name,tmpdir)
except IOError:
os.makedirs(tmpdir)
shutil.copy(opt_file.name,tmpdir)
# now tar it up again
inpw = job.getInputWorkspace()
rc, output = commands.getstatusoutput('tar czf %s -C %s .' % (inpw.getPath(sources),tmpdir))
if rc:
logger.error('Packing sources failed with status %d',rc)
logger.error(output)
raise ApplicationConfigurationError(None,'Packing sources failed.')
shutil.rmtree(tmpdir)
# upload sources
logger.debug('Uploading source tarball ...')
try:
cwd = os.getcwd()
os.chdir(inpw.getPath())
rc, output = Client.putFile(sources)
if output != 'True':
logger.error('Uploading sources %s failed. Status = %d', sources, rc)
logger.error(output)
raise ApplicationConfigurationError(None,'Uploading archive failed')
finally:
os.chdir(cwd)
# Use Panda's brokerage
## if job.inputdata and len(app.sites)>0:
## # update cloud, use inputdata's
## from dq2.info.TiersOfATLAS import whichCloud,ToACache
## inclouds=[]
## for site in app.sites:
## cloudSite=whichCloud(app.sites[0])
## if cloudSite not in inclouds:
## inclouds.append(cloudSite)
## # now converting inclouds content into proper brokering stuff.
## outclouds=[]
## for cloudSite in inclouds:
## for cloudID, eachCloud in ToACache.dbcloud.iteritems():
## 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
def master_prepare(self, app, appconfig):
'''Prepare the master job'''
from pandatools import Client
from taskbuffer.JobSpec import JobSpec
from taskbuffer.FileSpec import FileSpec
job = app._getParent()
logger.debug('ExecutablePandaRTHandler master_prepare called for %s',
job.getFQID('.'))
# set chirp variables
if configPanda['chirpconfig'] or configPanda['chirpserver']:
setChirpVariables()
# Pack inputsandbox
inputsandbox = 'sources.%s.tar' % commands.getoutput(
'uuidgen 2> /dev/null')
inpw = job.getInputWorkspace()
# add user script to inputsandbox
if hasattr(job.application.exe, "name"):
if not job.application.exe in job.inputsandbox:
job.inputsandbox.append(job.application.exe)
for fname in [f.name for f in job.inputsandbox]:
fname.rstrip(os.sep)
path = fname[:fname.rfind(os.sep)]
f = fname[fname.rfind(os.sep) + 1:]
rc, output = commands.getstatusoutput(
'tar rf %s -C %s %s' % (inpw.getPath(inputsandbox), path, f))
if rc:
logger.error('Packing inputsandbox failed with status %d', rc)
logger.error(output)
raise ApplicationConfigurationError(
None, 'Packing inputsandbox failed.')
if len(job.inputsandbox) > 0:
rc, output = commands.getstatusoutput('gzip %s' %
(inpw.getPath(inputsandbox)))
if rc:
logger.error('Packing inputsandbox failed with status %d', rc)
logger.error(output)
raise ApplicationConfigurationError(
None, 'Packing inputsandbox failed.')
inputsandbox += ".gz"
else:
inputsandbox = None
# Upload Inputsandbox
if inputsandbox:
logger.debug('Uploading source tarball ...')
uploadSources(inpw.getPath(), os.path.basename(inputsandbox))
self.inputsandbox = inputsandbox
else:
self.inputsandbox = None
# input dataset
if job.inputdata:
if job.inputdata._name != 'DQ2Dataset':
raise ApplicationConfigurationError(
None, 'PANDA application supports only DQ2Datasets')
# run brokerage here if not splitting
if not job.splitter:
from GangaPanda.Lib.Panda.Panda import runPandaBrokerage
runPandaBrokerage(job)
elif job.splitter._name not in [
'DQ2JobSplitter', 'ArgSplitter', 'ArgSplitterTask'
]:
raise ApplicationConfigurationError(
None, 'Panda splitter must be DQ2JobSplitter or ArgSplitter')
if job.backend.site == 'AUTO':
raise ApplicationConfigurationError(
None, 'site is still AUTO after brokerage!')
# output dataset
if job.outputdata:
if job.outputdata._name != 'DQ2OutputDataset':
raise ApplicationConfigurationError(
None, '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(
None,
'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
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)
if job.inputdata:
m = re.search('(.*)\.(.*)\.(.*)\.(.*)\.(.*)\.(.*)',
job.inputdata.dataset[0])
if not m:
logger.error("Error retrieving run number from dataset name")
#raise ApplicationConfigurationError(None, "Error retrieving run number from dataset name")
runnumber = 105200
else:
runnumber = int(m.group(2))
if jspec.transformation.endswith(
"_tf.py") or jspec.transformation.endswith("_tf"):
jspec.jobParameters += ' --runNumber %d' % runnumber
else:
jspec.jobParameters += ' RunNumber=%d' % runnumber
# Output files.
randomized_lfns = []
ilfn = 0
for lfn, lfntype in zip(app.output_files, app.output_type):
ofspec = FileSpec()
if app.randomize_lfns:
randomized_lfn = lfn + (
'.%s.%d.%s' %
(job.backend.site, int(time.time()),
commands.getoutput('uuidgen 2> /dev/null')[:4]))
else:
randomized_lfn = lfn
ofspec.lfn = randomized_lfn
randomized_lfns.append(randomized_lfn)
ofspec.destinationDBlock = jspec.destinationDBlock
ofspec.destinationSE = jspec.destinationSE
ofspec.dataset = jspec.destinationDBlock
ofspec.type = 'output'
jspec.addFile(ofspec)
if jspec.transformation.endswith(
"_tf.py") or jspec.transformation.endswith("_tf"):
jspec.jobParameters += ' --output%sFile %s' % (
lfntype, randomized_lfns[ilfn])
else:
jspec.jobParameters += ' output%sFile=%s' % (
lfntype, randomized_lfns[ilfn])
ilfn = ilfn + 1
# Input files.
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):
ifspec = FileSpec()
ifspec.lfn = lfn
ifspec.GUID = guid
ifspec.fsize = size
ifspec.md5sum = checksum
ifspec.scope = scope
ifspec.dataset = jspec.prodDBlock
ifspec.prodDBlock = jspec.prodDBlock
ifspec.type = 'input'
jspec.addFile(ifspec)
if app.input_type:
itype = app.input_type
else:
itype = m.group(5)
if jspec.transformation.endswith(
"_tf.py") or jspec.transformation.endswith("_tf"):
jspec.jobParameters += ' --input%sFile %s' % (itype, ','.join(
job.inputdata.names))
else:
jspec.jobParameters += ' input%sFile=%s' % (itype, ','.join(
job.inputdata.names))
# Log files.
lfspec = FileSpec()
lfspec.lfn = '%s.job.log.tgz' % jspec.jobName
lfspec.destinationDBlock = jspec.destinationDBlock
lfspec.destinationSE = jspec.destinationSE
lfspec.dataset = jspec.destinationDBlock
lfspec.type = 'log'
jspec.addFile(lfspec)
return jspec
def master_prepare(self, app, appmasterconfig):
# 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 master_prepare called for %s',
job.getFQID('.'))
usertag = configDQ2['usertag']
#usertag='user09'
nickname = getNickname(allowMissingNickname=True)
self.libDataset = '%s.%s.ganga.%s_%d.lib._%06d' % (
usertag, nickname, commands.getoutput('hostname').split('.')[0],
int(time.time()), job.id)
# self.userprefix='%s.%s.ganga' % (usertag,gridProxy.identity())
sources = 'sources.%s.tar.gz' % commands.getoutput(
'uuidgen 2> /dev/null')
self.library = '%s.lib.tgz' % self.libDataset
# check DBRelease
# if job.backend.dbRelease != '' and job.backend.dbRelease.find(':') == -1:
# raise ApplicationConfigurationError(None,"ERROR : invalid argument for backend.dbRelease. Must be 'DatasetName:FileName'")
# unpack library
logger.debug('Creating source tarball ...')
tmpdir = '/tmp/%s' % commands.getoutput('uuidgen 2> /dev/null')
os.mkdir(tmpdir)
inputbox = []
if os.path.exists(app.transform_archive):
# must add a condition on size.
inputbox += [File(app.transform_archive)]
if app.evgen_job_option:
self.evgen_job_option = app.evgen_job_option
if os.path.exists(app.evgen_job_option):
# locally modified job option file to add to the input sand box
inputbox += [File(app.evgen_job_option)]
self.evgen_job_option = app.evgen_job_option.split("/")[-1]
# add input sandbox files
if (job.inputsandbox):
for file in job.inputsandbox:
inputbox += [file]
# add option files
for extFile in job.backend.extOutFile:
try:
shutil.copy(extFile, tmpdir)
except IOError:
os.makedirs(tmpdir)
shutil.copy(extFile, tmpdir)
# fill the archive
for opt_file in inputbox:
try:
shutil.copy(opt_file.name, tmpdir)
except IOError:
os.makedirs(tmpdir)
shutil.copy(opt_file.name, tmpdir)
# now tar it up again
inpw = job.getInputWorkspace()
rc, output = commands.getstatusoutput('tar czf %s -C %s .' %
(inpw.getPath(sources), tmpdir))
if rc:
logger.error('Packing sources failed with status %d', rc)
logger.error(output)
raise ApplicationConfigurationError(None,
'Packing sources failed.')
shutil.rmtree(tmpdir)
# upload sources
logger.debug('Uploading source tarball ...')
try:
cwd = os.getcwd()
os.chdir(inpw.getPath())
rc, output = Client.putFile(sources)
if output != 'True':
logger.error('Uploading sources %s failed. Status = %d',
sources, rc)
logger.error(output)
raise ApplicationConfigurationError(
None, 'Uploading archive failed')
finally:
os.chdir(cwd)
# Use Panda's brokerage
## if job.inputdata and len(app.sites)>0:
## # update cloud, use inputdata's
## from dq2.info.TiersOfATLAS import whichCloud,ToACache
## inclouds=[]
## for site in app.sites:
## cloudSite=whichCloud(app.sites[0])
## if cloudSite not in inclouds:
## inclouds.append(cloudSite)
## # now converting inclouds content into proper brokering stuff.
## outclouds=[]
## for cloudSite in inclouds:
## for cloudID, eachCloud in ToACache.dbcloud.iteritems():
## 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