def test():
'''test submission'''
from pandaharvester.harvestercore.job_spec import JobSpec
from pandaharvester.harvestercore.plugin_factory import PluginFactory
import json
queuename = 'ARC-TEST'
queueconfmapper = QueueConfigMapper()
queueconf = queueconfmapper.get_queue(queuename)
pluginfactory = PluginFactory()
pandajob = '{"jobsetID": 11881, "logGUID": "88ee8a52-5c70-490c-a585-5eb6f48e4152", "cmtConfig": "x86_64-slc6-gcc49-opt", "prodDBlocks": "mc16_13TeV:mc16_13TeV.364168.Sherpa_221_NNPDF30NNLO_Wmunu_MAXHTPTV500_1000.merge.EVNT.e5340_e5984_tid11329621_00", "dispatchDBlockTokenForOut": "NULL,NULL", "destinationDBlockToken": "dst:CERN-PROD_DATADISK,dst:NDGF-T1_DATADISK", "destinationSE": "CERN-PROD_PRESERVATION", "realDatasets": "mc16_13TeV.364168.Sherpa_221_NNPDF30NNLO_Wmunu_MAXHTPTV500_1000.simul.HITS.e5340_e5984_s3126_tid11364822_00,mc16_13TeV.364168.Sherpa_221_NNPDF30NNLO_Wmunu_MAXHTPTV500_1000.simul.log.e5340_e5984_s3126_tid11364822_00", "prodUserID": "gingrich", "GUID": "A407D965-B139-A543-8851-A8E134A678D7", "realDatasetsIn": "mc16_13TeV:mc16_13TeV.364168.Sherpa_221_NNPDF30NNLO_Wmunu_MAXHTPTV500_1000.merge.EVNT.e5340_e5984_tid11329621_00", "nSent": 2, "cloud": "WORLD", "StatusCode": 0, "homepackage": "AtlasOffline/21.0.15", "inFiles": "EVNT.11329621._001079.pool.root.1", "processingType": "simul", "currentPriority": 900, "fsize": "129263662", "fileDestinationSE": "CERN-PROD_PRESERVATION,BOINC_MCORE", "scopeOut": "mc16_13TeV", "minRamCount": 1573, "jobDefinitionID": 0, "maxWalltime": 40638, "scopeLog": "mc16_13TeV", "transformation": "Sim_tf.py", "maxDiskCount": 485, "coreCount": 1, "prodDBlockToken": "NULL", "transferType": "NULL", "destinationDblock": "mc16_13TeV.364168.Sherpa_221_NNPDF30NNLO_Wmunu_MAXHTPTV500_1000.simul.HITS.e5340_e5984_s3126_tid11364822_00_sub0418634273,mc16_13TeV.364168.Sherpa_221_NNPDF30NNLO_Wmunu_MAXHTPTV500_1000.simul.log.e5340_e5984_s3126_tid11364822_00_sub0418634276", "dispatchDBlockToken": "NULL", "jobPars": "--inputEVNTFile=EVNT.11329621._001079.pool.root.1 --maxEvents=50 --postInclude \\"default:RecJobTransforms/UseFrontier.py\\" --preExec \\"EVNTtoHITS:simFlags.SimBarcodeOffset.set_Value_and_Lock(200000)\\" \\"EVNTtoHITS:simFlags.TRTRangeCut=30.0;simFlags.TightMuonStepping=True\\" --preInclude \\"EVNTtoHITS:SimulationJobOptions/preInclude.BeamPipeKill.py,SimulationJobOptions/preInclude.FrozenShowersFCalOnly.py\\" --skipEvents=4550 --firstEvent=5334551 --outputHITSFile=HITS.11364822._128373.pool.root.1 --physicsList=FTFP_BERT_ATL_VALIDATION --randomSeed=106692 --DBRelease=\\"all:current\\" --conditionsTag \\"default:OFLCOND-MC16-SDR-14\\" --geometryVersion=\\"default:ATLAS-R2-2016-01-00-01_VALIDATION\\" --runNumber=364168 --AMITag=s3126 --DataRunNumber=284500 --simulator=FullG4 --truthStrategy=MC15aPlus", "attemptNr": 2, "swRelease": "Atlas-21.0.15", "nucleus": "CERN-PROD", "maxCpuCount": 40638, "outFiles": "HITS.11364822._128373.pool.root.11,log.11364822._128373.job.log.tgz.11", "ddmEndPointOut": "CERN-PROD_DATADISK,NDGF-T1_DATADISK", "scopeIn": "mc16_13TeV", "PandaID": 3487584273, "sourceSite": "NULL", "dispatchDblock": "panda.11364822.07.05.GEN.0c9b1d3b-feec-411a-89e4-1cbf7347d70c_dis003487584270", "prodSourceLabel": "managed", "checksum": "ad:cd0bf10b", "jobName": "mc16_13TeV.364168.Sherpa_221_NNPDF30NNLO_Wmunu_MAXHTPTV500_1000.simul.e5340_e5984_s3126.3433643361", "ddmEndPointIn": "NDGF-T1_DATADISK", "taskID": 11364822, "logFile": "log.11364822._128373.job.log.tgz.1"}'
pandajob = json.loads(pandajob)
jspec = JobSpec()
jspec.convert_job_json(pandajob)
jspec.computingSite = queuename
jspeclist = [jspec]
maker = pluginfactory.get_plugin(queueconf.workerMaker)
wspec = maker.make_worker(jspeclist, queueconf)
wspec.hasJob = 1
wspec.set_jobspec_list(jspeclist)
sub = ARCSubmitter()
print sub.submit_workers([wspec])
print wspec.batchID
def test():
'''test submission'''
from pandaharvester.harvestercore.job_spec import JobSpec
from pandaharvester.harvestercore.plugin_factory import PluginFactory
import json
queuename = 'ARC-TEST'
queueconfmapper = QueueConfigMapper()
queueconf = queueconfmapper.get_queue(queuename)
pluginfactory = PluginFactory()
pandajob = '{"jobsetID": 11881, "logGUID": "88ee8a52-5c70-490c-a585-5eb6f48e4152", "cmtConfig": "x86_64-slc6-gcc49-opt", "prodDBlocks": "mc16_13TeV:mc16_13TeV.364168.Sherpa_221_NNPDF30NNLO_Wmunu_MAXHTPTV500_1000.merge.EVNT.e5340_e5984_tid11329621_00", "dispatchDBlockTokenForOut": "NULL,NULL", "destinationDBlockToken": "dst:CERN-PROD_DATADISK,dst:NDGF-T1_DATADISK", "destinationSE": "CERN-PROD_PRESERVATION", "realDatasets": "mc16_13TeV.364168.Sherpa_221_NNPDF30NNLO_Wmunu_MAXHTPTV500_1000.simul.HITS.e5340_e5984_s3126_tid11364822_00,mc16_13TeV.364168.Sherpa_221_NNPDF30NNLO_Wmunu_MAXHTPTV500_1000.simul.log.e5340_e5984_s3126_tid11364822_00", "prodUserID": "gingrich", "GUID": "A407D965-B139-A543-8851-A8E134A678D7", "realDatasetsIn": "mc16_13TeV:mc16_13TeV.364168.Sherpa_221_NNPDF30NNLO_Wmunu_MAXHTPTV500_1000.merge.EVNT.e5340_e5984_tid11329621_00", "nSent": 2, "cloud": "WORLD", "StatusCode": 0, "homepackage": "AtlasOffline/21.0.15", "inFiles": "EVNT.11329621._001079.pool.root.1", "processingType": "simul", "currentPriority": 900, "fsize": "129263662", "fileDestinationSE": "CERN-PROD_PRESERVATION,BOINC_MCORE", "scopeOut": "mc16_13TeV", "minRamCount": 1573, "jobDefinitionID": 0, "maxWalltime": 40638, "scopeLog": "mc16_13TeV", "transformation": "Sim_tf.py", "maxDiskCount": 485, "coreCount": 1, "prodDBlockToken": "NULL", "transferType": "NULL", "destinationDblock": "mc16_13TeV.364168.Sherpa_221_NNPDF30NNLO_Wmunu_MAXHTPTV500_1000.simul.HITS.e5340_e5984_s3126_tid11364822_00_sub0418634273,mc16_13TeV.364168.Sherpa_221_NNPDF30NNLO_Wmunu_MAXHTPTV500_1000.simul.log.e5340_e5984_s3126_tid11364822_00_sub0418634276", "dispatchDBlockToken": "NULL", "jobPars": "--inputEVNTFile=EVNT.11329621._001079.pool.root.1 --maxEvents=50 --postInclude \\"default:RecJobTransforms/UseFrontier.py\\" --preExec \\"EVNTtoHITS:simFlags.SimBarcodeOffset.set_Value_and_Lock(200000)\\" \\"EVNTtoHITS:simFlags.TRTRangeCut=30.0;simFlags.TightMuonStepping=True\\" --preInclude \\"EVNTtoHITS:SimulationJobOptions/preInclude.BeamPipeKill.py,SimulationJobOptions/preInclude.FrozenShowersFCalOnly.py\\" --skipEvents=4550 --firstEvent=5334551 --outputHITSFile=HITS.11364822._128373.pool.root.1 --physicsList=FTFP_BERT_ATL_VALIDATION --randomSeed=106692 --DBRelease=\\"all:current\\" --conditionsTag \\"default:OFLCOND-MC16-SDR-14\\" --geometryVersion=\\"default:ATLAS-R2-2016-01-00-01_VALIDATION\\" --runNumber=364168 --AMITag=s3126 --DataRunNumber=284500 --simulator=FullG4 --truthStrategy=MC15aPlus", "attemptNr": 2, "swRelease": "Atlas-21.0.15", "nucleus": "CERN-PROD", "maxCpuCount": 40638, "outFiles": "HITS.11364822._128373.pool.root.11,log.11364822._128373.job.log.tgz.11", "ddmEndPointOut": "CERN-PROD_DATADISK,NDGF-T1_DATADISK", "scopeIn": "mc16_13TeV", "PandaID": 3487584273, "sourceSite": "NULL", "dispatchDblock": "panda.11364822.07.05.GEN.0c9b1d3b-feec-411a-89e4-1cbf7347d70c_dis003487584270", "prodSourceLabel": "managed", "checksum": "ad:cd0bf10b", "jobName": "mc16_13TeV.364168.Sherpa_221_NNPDF30NNLO_Wmunu_MAXHTPTV500_1000.simul.e5340_e5984_s3126.3433643361", "ddmEndPointIn": "NDGF-T1_DATADISK", "taskID": 11364822, "logFile": "log.11364822._128373.job.log.tgz.1"}'
pandajob = json.loads(pandajob)
jspec = JobSpec()
jspec.convert_job_json(pandajob)
jspec.computingSite = queuename
jspeclist = [jspec]
maker = pluginfactory.get_plugin(queueconf.workerMaker)
wspec = maker.make_worker(jspeclist, queueconf)
wspec.hasJob = 1
wspec.set_jobspec_list(jspeclist)
sub = ARCSubmitter()
print sub.submit_workers([wspec])
print wspec.batchID
def run(self):
while True:
mainLog = self.make_logger(_logger, 'id={0}'.format(self.get_pid()), method_name='run')
mainLog.debug('getting number of jobs to be fetched')
# get number of jobs to be fetched
nJobsPerQueue = self.dbProxy.get_num_jobs_to_fetch(harvester_config.jobfetcher.nQueues,
harvester_config.jobfetcher.lookupTime)
mainLog.debug('got {0} queues'.format(len(nJobsPerQueue)))
# loop over all queues
for queueName, nJobs in iteritems(nJobsPerQueue):
# check queue
if not self.queueConfigMapper.has_queue(queueName):
continue
tmpLog = self.make_logger(_logger, 'queueName={0}'.format(queueName),
method_name='run')
# get queue
queueConfig = self.queueConfigMapper.get_queue(queueName)
# upper limit
if nJobs > harvester_config.jobfetcher.maxJobs:
nJobs = harvester_config.jobfetcher.maxJobs
# get jobs
tmpLog.debug('getting {0} jobs'.format(nJobs))
sw = core_utils.get_stopwatch()
siteName = queueConfig.siteName
jobs, errStr = self.communicator.get_jobs(siteName, self.nodeName,
queueConfig.get_source_label(),
self.nodeName, nJobs,
queueConfig.getJobCriteria)
tmpLog.info('got {0} jobs with {1} {2}'.format(len(jobs), errStr, sw.get_elapsed_time()))
# convert to JobSpec
if len(jobs) > 0:
jobSpecs = []
fileStatMap = dict()
sw_startconvert = core_utils.get_stopwatch()
for job in jobs:
timeNow = datetime.datetime.utcnow()
jobSpec = JobSpec()
jobSpec.convert_job_json(job)
jobSpec.computingSite = queueName
jobSpec.status = 'starting'
jobSpec.subStatus = 'fetched'
jobSpec.creationTime = timeNow
jobSpec.stateChangeTime = timeNow
jobSpec.configID = queueConfig.configID
jobSpec.set_one_attribute('schedulerID',
'harvester-{0}'.format(harvester_config.master.harvester_id))
if queueConfig.zipPerMB is not None and jobSpec.zipPerMB is None:
jobSpec.zipPerMB = queueConfig.zipPerMB
for tmpLFN, fileAttrs in iteritems(jobSpec.get_input_file_attributes()):
# check file status
if tmpLFN not in fileStatMap:
fileStatMap[tmpLFN] = self.dbProxy.get_file_status(tmpLFN, 'input',
queueConfig.ddmEndpointIn,
'starting')
# make file spec
fileSpec = FileSpec()
fileSpec.PandaID = jobSpec.PandaID
fileSpec.taskID = jobSpec.taskID
fileSpec.lfn = tmpLFN
fileSpec.endpoint = queueConfig.ddmEndpointIn
fileSpec.scope = fileAttrs['scope']
# set preparing to skip stage-in if the file is (being) taken care of by another job
if 'ready' in fileStatMap[tmpLFN] or 'preparing' in fileStatMap[tmpLFN] \
or 'to_prepare' in fileStatMap[tmpLFN]:
fileSpec.status = 'preparing'
else:
fileSpec.status = 'to_prepare'
if fileSpec.status not in fileStatMap[tmpLFN]:
fileStatMap[tmpLFN][fileSpec.status] = 0
fileStatMap[tmpLFN][fileSpec.status] += 1
fileSpec.fileType = 'input'
jobSpec.add_in_file(fileSpec)
jobSpec.trigger_propagation()
jobSpecs.append(jobSpec)
# insert to DB
tmpLog.debug("Converting of {0} jobs {1}".format(len(jobs),sw_startconvert.get_elapsed_time()))
sw_insertdb =core_utils.get_stopwatch()
self.dbProxy.insert_jobs(jobSpecs)
tmpLog.debug('Insert of {0} jobs {1}'.format(len(jobSpecs), sw_insertdb.get_elapsed_time()))
mainLog.debug('done')
# check if being terminated
if self.terminated(harvester_config.jobfetcher.sleepTime):
mainLog.debug('terminated')
return
import sys
queueName = sys.argv[1]
from pandaharvester.harvestercore.queue_config_mapper import QueueConfigMapper
queueConfigMapper = QueueConfigMapper()
queueConfig = queueConfigMapper.get_queue(queueName)
from pandaharvester.harvestercore.job_spec import JobSpec
jobSpec = JobSpec()
jobSpec.computingSite = sys.argv[1]
jobSpec.jobParams = {'inFiles': 'EVNT.06820166._000001.pool.root.1',
'scopeIn': 'mc15_13TeV',
'fsize': '196196765',
'GUID': 'B7F387CD-1F97-1C47-88BD-D8785442C49D',
'checksum': 'ad:326e445d',
'ddmEndPointIn': 'MWT2_DATADISK',
'realDatasetsIn': 'mc15_13TeV:mc15_13TeV.301042.PowhegPythia8EvtGen_AZNLOCTEQ6L1_DYtautau_250M400.evgen.EVNT.e3649_tid06820166_00',
}
from pandaharvester.harvestercore.plugin_factory import PluginFactory
pluginFactory = PluginFactory()
# get plugin
preparatorCore = pluginFactory.get_plugin(queueConfig.preparator)
print ("plugin={0}".format(preparatorCore.__class__.__name__))
queueName = sys.argv[1]
queueConfigMapper = QueueConfigMapper()
queueConfig = queueConfigMapper.get_queue(queueName)
jobSpec = JobSpec()
jobSpec.jobParams = {'inFiles': 'DAOD_STDM4.09596175._000008.pool.root.1',
'scopeIn': 'mc15_13TeV',
'fsize': '658906675',
'GUID': '7e3776f9bb0af341b03e59d3de895a13',
'checksum': 'ad:3734bdd9',
'ddmEndPointIn': 'BNL-OSG2_DATADISK',
'realDatasetsIn': 'mc15_13TeV.363638.MGPy8EG_N30NLO_Wmunu_Ht500_700_BFilter.merge.DAOD_STDM4.e4944_s2726_r7772_r7676_p2842_tid09596175_00',
}
jobSpec.computingSite = queueName
from pandaharvester.harvestercore.plugin_factory import PluginFactory
pluginFactory = PluginFactory()
# get plugin
preparatorCore = pluginFactory.get_plugin(queueConfig.preparator)
print ("plugin={0}".format(preparatorCore.__class__.__name__))
print ("testing stagein:")
print ("BasePath from preparator configuration: %s " % preparatorCore.basePath)
preparatorCore.basePath = preparatorCore.basePath + "/testdata/"
print ("basePath redifuned for test data: %s " % preparatorCore.basePath)
tmpStat, tmpOut = preparatorCore.trigger_preparation(jobSpec)
# now unlock db
unlocked = stagerCore.dbInterface.release_object_lock('dummy_id_for_out_0')
if unlocked :
tmpLog.debug('unlocked db')
else:
tmpLog.debug(' Could not unlock db')
# loop over the job id's creating various JobSpecs
jobSpec_list = []
for job_id in range(begin_job_id,end_job_id+1):
jobSpec = JobSpec()
jobSpec.jobParams = {
'scopeLog': 'panda',
'logFile': 'log',
}
jobSpec.computingSite = queueName
jobSpec.PandaID = job_id
jobSpec.modificationTime = datetime.datetime.now()
realDataset = 'panda.sgotest.' + uuid.uuid4().hex
ddmEndPointOut = 'BNL-OSG2_DATADISK'
outFiles_scope_str = ''
outFiles_str = ''
realDatasets_str = ''
ddmEndPointOut_str = ''
# create up 5 files for output
for index in range(random.randint(1, 5)):
fileSpec = FileSpec()
assFileSpec = FileSpec()
fileSpec.fileType = 'es_output'
assFileSpec.lfn = 'panda.sgotest.' + uuid.uuid4().hex
fileSpec.lfn = assFileSpec.lfn + '.gz'
def run(self):
while True:
mainLog = self.make_logger(_logger,
'id={0}'.format(self.get_pid()),
method_name='run')
mainLog.debug('getting number of jobs to be fetched')
# get number of jobs to be fetched
nJobsPerQueue = self.dbProxy.get_num_jobs_to_fetch(
harvester_config.jobfetcher.nQueues,
harvester_config.jobfetcher.lookupTime)
mainLog.debug('got {0} queues'.format(len(nJobsPerQueue)))
# loop over all queues
for queueName, nJobs in iteritems(nJobsPerQueue):
# check queue
if not self.queueConfigMapper.has_queue(queueName):
continue
tmpLog = self.make_logger(_logger,
'queueName={0}'.format(queueName),
method_name='run')
# get queue
queueConfig = self.queueConfigMapper.get_queue(queueName)
# upper limit
if nJobs > harvester_config.jobfetcher.maxJobs:
nJobs = harvester_config.jobfetcher.maxJobs
# get jobs
default_prodSourceLabel = queueConfig.get_source_label()
pdpm = getattr(queueConfig,
'prodSourceLabelRandomWeightsPermille', {})
choice_list = core_utils.make_choice_list(
pdpm=pdpm, default=default_prodSourceLabel)
prodSourceLabel = random.choice(choice_list)
tmpLog.debug('getting {0} jobs for prodSourceLabel {1}'.format(
nJobs, prodSourceLabel))
sw = core_utils.get_stopwatch()
siteName = queueConfig.siteName
jobs, errStr = self.communicator.get_jobs(
siteName, self.nodeName, prodSourceLabel, self.nodeName,
nJobs, queueConfig.getJobCriteria)
tmpLog.info('got {0} jobs with {1} {2}'.format(
len(jobs), errStr, sw.get_elapsed_time()))
# convert to JobSpec
if len(jobs) > 0:
# get extractor plugin
if hasattr(queueConfig, 'extractor'):
extractorCore = self.pluginFactory.get_plugin(
queueConfig.extractor)
else:
extractorCore = None
jobSpecs = []
fileStatMap = dict()
sw_startconvert = core_utils.get_stopwatch()
for job in jobs:
timeNow = datetime.datetime.utcnow()
jobSpec = JobSpec()
jobSpec.convert_job_json(job)
jobSpec.computingSite = queueName
jobSpec.status = 'starting'
jobSpec.subStatus = 'fetched'
jobSpec.creationTime = timeNow
jobSpec.stateChangeTime = timeNow
jobSpec.configID = queueConfig.configID
jobSpec.set_one_attribute(
'schedulerID', 'harvester-{0}'.format(
harvester_config.master.harvester_id))
if queueConfig.zipPerMB is not None and jobSpec.zipPerMB is None:
jobSpec.zipPerMB = queueConfig.zipPerMB
fileGroupDictList = [
jobSpec.get_input_file_attributes()
]
if extractorCore is not None:
fileGroupDictList.append(
extractorCore.get_aux_inputs(jobSpec))
for fileGroupDict in fileGroupDictList:
for tmpLFN, fileAttrs in iteritems(fileGroupDict):
# check file status
if tmpLFN not in fileStatMap:
fileStatMap[
tmpLFN] = self.dbProxy.get_file_status(
tmpLFN, 'input',
queueConfig.ddmEndpointIn,
'starting')
# make file spec
fileSpec = FileSpec()
fileSpec.PandaID = jobSpec.PandaID
fileSpec.taskID = jobSpec.taskID
fileSpec.lfn = tmpLFN
fileSpec.endpoint = queueConfig.ddmEndpointIn
fileSpec.scope = fileAttrs['scope']
# set preparing to skip stage-in if the file is (being) taken care of by another job
if 'ready' in fileStatMap[tmpLFN] or 'preparing' in fileStatMap[tmpLFN] \
or 'to_prepare' in fileStatMap[tmpLFN]:
fileSpec.status = 'preparing'
else:
fileSpec.status = 'to_prepare'
if fileSpec.status not in fileStatMap[tmpLFN]:
fileStatMap[tmpLFN][fileSpec.status] = 0
fileStatMap[tmpLFN][fileSpec.status] += 1
if 'INTERNAL_FileType' in fileAttrs:
fileSpec.fileType = fileAttrs[
'INTERNAL_FileType']
jobSpec.auxInput = JobSpec.AUX_hasAuxInput
else:
fileSpec.fileType = 'input'
if 'INTERNAL_URL' in fileAttrs:
fileSpec.url = fileAttrs['INTERNAL_URL']
jobSpec.add_in_file(fileSpec)
jobSpec.trigger_propagation()
jobSpecs.append(jobSpec)
# insert to DB
tmpLog.debug("Converting of {0} jobs {1}".format(
len(jobs), sw_startconvert.get_elapsed_time()))
sw_insertdb = core_utils.get_stopwatch()
self.dbProxy.insert_jobs(jobSpecs)
tmpLog.debug('Insert of {0} jobs {1}'.format(
len(jobSpecs), sw_insertdb.get_elapsed_time()))
mainLog.debug('done')
# check if being terminated
if self.terminated(harvester_config.jobfetcher.sleepTime):
mainLog.debug('terminated')
return
def run(self):
while True:
mainLog = self.make_logger(_logger,
'id={0}'.format(self.ident),
method_name='run')
mainLog.debug('getting number of jobs to be fetched')
# get number of jobs to be fetched
nJobsPerQueue = self.dbProxy.get_num_jobs_to_fetch(
harvester_config.jobfetcher.nQueues,
harvester_config.jobfetcher.lookupTime)
mainLog.debug('got {0} queues'.format(len(nJobsPerQueue)))
# loop over all queues
for queueName, nJobs in iteritems(nJobsPerQueue):
# check queue
if not self.queueConfigMapper.has_queue(queueName):
continue
tmpLog = self.make_logger(_logger,
'queueName={0}'.format(queueName),
method_name='run')
# get queue
queueConfig = self.queueConfigMapper.get_queue(queueName)
# upper limit
if nJobs > harvester_config.jobfetcher.maxJobs:
nJobs = harvester_config.jobfetcher.maxJobs
# get jobs
tmpLog.debug('getting {0} jobs'.format(nJobs))
siteName = queueConfig.siteName
jobs, errStr = self.communicator.get_jobs(
siteName, self.nodeName, queueConfig.get_source_label(),
self.nodeName, nJobs, queueConfig.getJobCriteria)
tmpLog.info('got {0} jobs with {1}'.format(len(jobs), errStr))
# convert to JobSpec
if len(jobs) > 0:
jobSpecs = []
fileStatMap = dict()
for job in jobs:
timeNow = datetime.datetime.utcnow()
jobSpec = JobSpec()
jobSpec.convert_job_json(job)
jobSpec.computingSite = queueName
jobSpec.status = 'starting'
jobSpec.subStatus = 'fetched'
jobSpec.creationTime = timeNow
jobSpec.stateChangeTime = timeNow
jobSpec.configID = queueConfig.configID
jobSpec.set_one_attribute(
'schedulerID', 'harvester-{0}'.format(
harvester_config.master.harvester_id))
if queueConfig.zipPerMB is not None and jobSpec.zipPerMB is None:
jobSpec.zipPerMB = queueConfig.zipPerMB
for tmpLFN, fileAttrs in iteritems(
jobSpec.get_input_file_attributes()):
# check file status
if tmpLFN not in fileStatMap:
fileStatMap[
tmpLFN] = self.dbProxy.get_file_status(
tmpLFN, 'input',
queueConfig.ddmEndpointIn, 'starting')
# make file spec
fileSpec = FileSpec()
fileSpec.PandaID = jobSpec.PandaID
fileSpec.taskID = jobSpec.taskID
fileSpec.lfn = tmpLFN
fileSpec.endpoint = queueConfig.ddmEndpointIn
fileSpec.scope = fileAttrs['scope']
# set preparing to skip stage-in if the file is (being) taken care of by another job
if 'ready' in fileStatMap[tmpLFN] or 'preparing' in fileStatMap[tmpLFN] \
or 'to_prepare' in fileStatMap[tmpLFN]:
fileSpec.status = 'preparing'
else:
fileSpec.status = 'to_prepare'
if fileSpec.status not in fileStatMap[tmpLFN]:
fileStatMap[tmpLFN][fileSpec.status] = 0
fileStatMap[tmpLFN][fileSpec.status] += 1
fileSpec.fileType = 'input'
jobSpec.add_in_file(fileSpec)
jobSpec.trigger_propagation()
jobSpecs.append(jobSpec)
# insert to DB
self.dbProxy.insert_jobs(jobSpecs)
mainLog.debug('done')
# check if being terminated
if self.terminated(harvester_config.jobfetcher.sleepTime):
mainLog.debug('terminated')
return