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
# check if db lock exits
locked = stagerCore.dbInterface.get_object_lock('dummy_id_for_out_0',lock_interval=120)
if not locked:
tmpLog.debug('DB Already locked by another thread')
# 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)):
os.remove(harvester_config.db.database_filename)
except Exception:
pass
for loggerName, loggerObj in iteritems(logging.Logger.manager.loggerDict):
if loggerName.startswith('panda.log'):
if len(loggerObj.handlers) == 0:
continue
if loggerName.split('.')[-1] in ['db_proxy']:
continue
stdoutHandler = logging.StreamHandler(sys.stdout)
stdoutHandler.setFormatter(loggerObj.handlers[0].formatter)
loggerObj.addHandler(stdoutHandler)
queueConfigMapper = QueueConfigMapper()
proxy = DBProxy()
proxy.make_tables(queueConfigMapper)
job = JobSpec()
job.PandaID = 1
job.modificationTime = datetime.datetime.now()
proxy.insert_jobs([job])
newJob = proxy.get_job(1)
a = CommunicatorPool()
a.get_jobs('siteName', 'nodeName', 'prodSourceLabel', 'computingElement', 1,
{})
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
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
import time
import os
from pandaharvester.harvestercore.queue_config_mapper import QueueConfigMapper
from pandaharvester.harvestercore.job_spec import JobSpec
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__))
endPoint=queueConfig.stager['Globus_srcPath'],
scope=correctedscope,
hash1=hash_hex[0:2],
hash2=hash_hex[2:4],
lfn=assFileSpec.lfn)
if not os.path.exists(os.path.dirname(assFileSpec.path)):
print "os.makedirs({})".format(os.path.dirname(assFileSpec.path))
os.makedirs(os.path.dirname(assFileSpec.path))
oFile = open(assFileSpec.path, 'w')
oFile.write(''.join(
random.choice(string.ascii_uppercase + string.digits)
for _ in range(assFileSpec.fsize)))
oFile.close()
fileSpec.add_associated_file(assFileSpec)
jobSpec = JobSpec()
jobSpec.jobParams = {
'outFiles': fileSpec.lfn + ',log',
'scopeOut': 'panda',
'scopeLog': 'panda',
'logFile': 'log',
'realDatasets': 'panda.' + fileSpec.lfn,
'ddmEndPointOut': 'BNL-OSG2_DATADISK',
}
jobSpec.computingSite = queueName
jobSpec.PandaID = job_id
jobSpec.add_out_file(fileSpec)
print "file to transfer - {}".format(assFileSpec.path)
print "dump(jobSpec)"
#dump(jobSpec)
# check if db lock exits
locked = stagerCore.dbInterface.get_object_lock('dummy_id_for_out_0',
lock_interval=120)
if not locked:
tmpLog.debug('DB Already locked by another thread')
# 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)):
import sys
import time
from pandaharvester.harvestercore.queue_config_mapper import QueueConfigMapper
from pandaharvester.harvestercore.job_spec import JobSpec
from pilot.info.filespec import FileSpec
queueName = sys.argv[1]
queueConfigMapper = QueueConfigMapper()
queueConfig = queueConfigMapper.get_queue(queueName)
jobSpec = JobSpec()
new_file_data = {
'scope': 'test',
'lfn': 'TXT.19772875._044894.tar.gz.1',
'attemptNr': 0
}
new_file_spec = FileSpec(filetype='input', **new_file_data)
new_file_spec.attemptNr = 0
new_file_spec.path = '/home/psvirin/harvester3'
jobSpec.inFiles = {new_file_spec}
jobSpec.outFiles = {}
jobSpec.jobParams = {
'inFiles':
'TXT.19772875._044894.tar.gz.1',
'scopeIn':
'mc15_13TeV',
'fsize':
'658906675',
except Exception:
pass
for loggerName, loggerObj in iteritems(logging.Logger.manager.loggerDict):
if loggerName.startswith('panda.log'):
if len(loggerObj.handlers) == 0:
continue
if loggerName.split('.')[-1] in ['db_proxy']:
continue
stdoutHandler = logging.StreamHandler(sys.stdout)
stdoutHandler.setFormatter(loggerObj.handlers[0].formatter)
loggerObj.addHandler(stdoutHandler)
queueConfigMapper = QueueConfigMapper()
proxy = DBProxy()
proxy.make_tables(queueConfigMapper)
job = JobSpec()
job.PandaID = 1
job.modificationTime = datetime.datetime.now()
proxy.insert_jobs([job])
newJob = proxy.get_job(1)
a = CommunicatorPool()
a.get_jobs('siteName', 'nodeName', 'prodSourceLabel', 'computingElement', 1, {})
hash_hex = hash.hexdigest()
correctedscope = "/".join(scope.split('.'))
assFileSpec.path = "{endPoint}/{scope}/{hash1}/{hash2}/{lfn}".format(endPoint=queueConfig.stager['Globus_srcPath'],
scope=correctedscope,
hash1=hash_hex[0:2],
hash2=hash_hex[2:4],
lfn=assFileSpec.lfn)
if not os.path.exists(os.path.dirname(assFileSpec.path)):
print "os.makedirs({})".format(os.path.dirname(assFileSpec.path))
os.makedirs(os.path.dirname(assFileSpec.path))
oFile = open(assFileSpec.path, 'w')
oFile.write(''.join(random.choice(string.ascii_uppercase + string.digits) for _ in range(assFileSpec.fsize)))
oFile.close()
fileSpec.add_associated_file(assFileSpec)
jobSpec = JobSpec()
jobSpec.jobParams = {'outFiles': fileSpec.lfn + ',log',
'scopeOut': 'panda',
'scopeLog': 'panda',
'logFile': 'log',
'realDatasets': 'panda.' + fileSpec.lfn,
'ddmEndPointOut': 'BNL-OSG2_DATADISK',
}
jobSpec.computingSite = queueName
jobSpec.PandaID = job_id
jobSpec.add_out_file(fileSpec)
print "file to transfer - {}".format(assFileSpec.path)
print "dump(jobSpec)"
#dump(jobSpec)
queueConfig = queueConfigMapper.get_queue(queueName)
pluginFactory = PluginFactory()
com = CommunicatorPool()
# get job
jobSpecList = []
if queueConfig.mapType != WorkSpec.MT_NoJob:
jobs, errStr = com.get_jobs(queueConfig.queueName, 'nodeName', queueConfig.prodSourceLabel,
'computingElement', 1, None)
if len(jobs) == 0:
print ("Failed to get jobs at {0} due to {1}".format(queueConfig.queueName, errStr))
sys.exit(0)
jobSpec = JobSpec()
jobSpec.convert_job_json(jobs[0])
# set input file paths
inFiles = jobSpec.get_input_file_attributes()
for inLFN, inFile in iteritems(inFiles):
inFile['path'] = '{0}/{1}'.format(os.getcwd(), inLFN)
jobSpec.set_input_file_paths(inFiles)
jobSpecList.append(jobSpec)
maker = pluginFactory.get_plugin(queueConfig.workerMaker)
workSpec = maker.make_worker(jobSpecList, queueConfig, 'SCORE') # TODO: needs to be thought
workSpec.accessPoint = queueConfig.messenger['accessPoint']
workSpec.mapType = queueConfig.mapType
workSpec.computingSite = queueConfig.queueName
import json
import sys
import time
from pprint import pprint
#from pandaharvester.harvestercore.queue_config_mapper import QueueConfigMapper
from pandaharvester.harvestercore.job_spec import JobSpec
from pandaharvester.harvesterextractor.aux_extractor import AuxExtractor
job_data_json = """{"container_name": "atlas.athena:21.0.15_DBRelease-100.0.2_Patched", "PandaID": 4731765799, "jobsetID": 1,"taskID": 1, "transformation": "Sim_tf.py", "attemptNr": 1,"currentPriority": 1, "outFiles": "", "realDatasets": "", "ddmEndPointOut": "", "scopeOut": "", "scopeLog": "", "logFile": "", "logGUID": "", "files": [{"row_id": 30133581516, "pandaid": 4731765799, "modificationtime": "2020-05-18T10:29:21", "guid": "ADCF2DEC-3412-C64B-B8FB-E8629680AA4D", "lfn": "EVNT.21265061._000036.pool.root.1", "type": "input", "dataset": "mc16_13TeV.830011.H7EG_jetjet_JZ1.merge.EVNT.e7954_e7400_tid21265061_00", "status": "ready", "proddblock": "mc16_13TeV:mc16_13TeV.830011.H7EG_jetjet_JZ1.merge.EVNT.e7954_e7400_tid21265061_00", "proddblocktoken": "", "dispatchdblock": "", "dispatchdblocktoken": "", "destinationdblock": "", "destinationdblocktoken": "", "destinationse": "", "fsize": 307204932, "md5sum": "", "checksum": "ad:698afd11", "scope": "mc16_13TeV", "jeditaskid": 21265064, "datasetid": 311267780, "fileid": 21006488431, "attemptnr": 22, "destination": " ", "fsizemb": "292.97", "ruciodatasetname": "mc16_13TeV:mc16_13TeV.830011.H7EG_jetjet_JZ1.merge.EVNT.e7954_e7400_tid21265061_00", "datasetname": "mc16_13TeV:mc16_13TeV.830011.H7EG_jetjet_JZ1.merge.EVNT.e7954_e7400_tid21265061_00", "ddmsite": "LRZ-LMU", "creationdate": "2020-05-18T10:29:21", "oldfiletable": 1, "destinationdblock_vis": "", "maxattempt": 30}, {"row_id": 30133581517, "pandaid": 4731765799, "modificationtime": "2020-05-18T10:29:21", "guid": "819a609a-1650-455b-8980-9c190cb77064", "lfn": "352", "type": "pseudo_input", "dataset": "seq_number", "status": "unknown", "proddblock": "seq_number", "proddblocktoken": "", "dispatchdblock": "", "dispatchdblocktoken": "", "destinationdblock": "", "destinationdblocktoken": "", "destinationse": "", "fsize": 0, "md5sum": "", "checksum": "", "scope": "", "jeditaskid": 21265064, "datasetid": 311267781, "fileid": 21006489271, "attemptnr": 21, "destination": " ", "fsizemb": "0.00", "ruciodatasetname": "seq_number", "datasetname": "seq_number", "ddmsite": "LRZ-LMU", "creationdate": "2020-05-18T10:29:21", "oldfiletable": 1, "destinationdblock_vis": ""}, {"row_id": 30133581519, "pandaid": 4731765799, "modificationtime": "2020-05-18T10:29:21", "guid": "", "lfn": "HITS.21265064._002580.pool.root.1", "type": "output", "dataset": "mc16_13TeV.830011.H7EG_jetjet_JZ1.simul.HITS.e7954_e7400_s3126_tid21265064_00", "status": "failed", "proddblock": "", "proddblocktoken": "", "dispatchdblock": "", "dispatchdblocktoken": "", "destinationdblock": "mc16_13TeV.830011.NA.simul.HITS.21265064_sub2290908", "destinationdblocktoken": "dst:TOKYO-LCG2_DATADISK", "destinationse": "nucleus:TOKYO-LCG2", "fsize": 0, "md5sum": "", "checksum": "", "scope": "mc16_13TeV", "jeditaskid": 21265064, "datasetid": 311267782, "fileid": 21092403937, "attemptnr": 0, "destination": " ", "fsizemb": "0.00", "ruciodatasetname": "mc16_13TeV.830011.H7EG_jetjet_JZ1.simul.HITS.e7954_e7400_s3126_tid21265064_00", "datasetname": "mc16_13TeV.830011.H7EG_jetjet_JZ1.simul.HITS.e7954_e7400_s3126_tid21265064_00", "ddmsite": "TOKYO-LCG2", "dsttoken": "DATADISK", "creationdate": "2020-05-18T10:29:21", "oldfiletable": 1, "destinationdblock_vis": "sub2290908"}, {"row_id": 30133581518, "pandaid": 4731765799, "modificationtime": "2020-05-18T10:29:21", "guid": "73a868bd-acd5-4fb4-ade9-a66badd0e5a9", "lfn": "log.21265064._002580.job.log.tgz.1", "type": "log", "dataset": "mc16_13TeV.830011.H7EG_jetjet_JZ1.simul.log.e7954_e7400_s3126_tid21265064_00", "status": "failed", "proddblock": "", "proddblocktoken": "", "dispatchdblock": "", "dispatchdblocktoken": "", "destinationdblock": "mc16_13TeV.830011.NA.simul.log.21265064_sub2290905", "destinationdblocktoken": "ddd:LRZ-LMU_DATADISK", "destinationse": "LRZ-LMU_MUC", "fsize": 0, "md5sum": "", "checksum": "", "scope": "mc16_13TeV", "jeditaskid": 21265064, "datasetid": 311267783, "fileid": 21092403936, "attemptnr": 0, "destination": " ", "fsizemb": "0.00", "ruciodatasetname": "mc16_13TeV.830011.H7EG_jetjet_JZ1.simul.log.e7954_e7400_s3126_tid21265064_00", "datasetname": "mc16_13TeV.830011.H7EG_jetjet_JZ1.simul.log.e7954_e7400_s3126_tid21265064_00", "ddmsite": "LRZ-LMU", "creationdate": "2020-05-18T10:29:21", "oldfiletable": 1, "destinationdblock_vis": "sub2290905"}], "job": {"pandaid": 4731765799, "jobdefinitionid": 0, "schedulerid": "", "pilotid": "", "creationtime": "2020-05-18 03:42:54", "creationhost": "", "modificationtime": "2020-05-18 10:29:21", "modificationhost": "aipanda058.cern.ch", "atlasrelease": "Atlas-21.0.15", "transformation": "Sim_tf.py", "homepackage": "AtlasOffline/21.0.15", "prodserieslabel": "pandatest", "prodsourcelabel": "managed", "produserid": "dhirsch", "gshare": "Validation", "assignedpriority": 888, "currentpriority": 888, "attemptnr": 22, "maxattempt": 22, "jobname": "mc16_13TeV.830011.H7EG_jetjet_JZ1.simul.e7954_e7400_s3126.4727254713", "maxcpucount": 4611, "maxcpuunit": "kSI2kseconds", "maxdiskcount": 5255, "maxdiskunit": "MB ", "ipconnectivity": "yes ", "minramcount": 44100, "minramunit": "MB", "starttime": null, "endtime": "2020-05-18T10:29:21", "cpuconsumptiontime": 0, "cpuconsumptionunit": "", "commandtopilot": "tobekilled", "transexitcode": "", "piloterrorcode": 0, "piloterrordiag": "", "exeerrorcode": 0, "exeerrordiag": "", "superrorcode": 0, "superrordiag": "", "ddmerrorcode": 0, "ddmerrordiag": "", "brokerageerrorcode": 0, "brokerageerrordiag": "", "jobdispatchererrorcode": 0, "jobdispatchererrordiag": "", "taskbuffererrorcode": 100, "taskbuffererrordiag": "reassigned by JEDI", "computingsite": "LRZ-LMU_MUC", "computingelement": "", "jobparameters": "", "metadata": "", "proddblock": "mc16_13TeV:mc16_13TeV.830011.H7EG_jetjet_JZ1.merge.EVNT.e7954_e7400_tid21265061_00", "dispatchdblock": "", "destinationdblock": "mc16_13TeV.830011.H7EG_jetjet_JZ1.simul.log.e7954_e7400_s3126_tid21265064_00", "destinationse": "dst:TOKYO-LCG2_DATADISK/ATLASDATADISK", "nevents": 0, "grid": "", "cloud": "WORLD", "cpuconversion": null, "sourcesite": "", "destinationsite": "", "transfertype": "", "taskid": 21265064, "cmtconfig": "x86_64-slc6-gcc49-opt", "statechangetime": "2020-05-18 10:29:21", "proddbupdatetime": "2020-05-18T03:42:54", "lockedby": "jedi", "relocationflag": 1, "jobexecutionid": 0, "vo": "atlas", "pilottiming": "", "workinggroup": "AP_MCGN", "processingtype": "simul", "produsername": "******", "ninputfiles": null, "countrygroup": "", "batchid": "", "parentid": null, "specialhandling": "ddm:rucio,hc:DE,de", "jobsetid": 30864, "corecount": 96, "ninputdatafiles": 1, "inputfiletype": "EVNT", "inputfileproject": "mc16_13TeV", "inputfilebytes": 307204932, "noutputdatafiles": 0, "outputfilebytes": 0, "jobmetrics": "", "workqueue_id": 16, "jeditaskid": 21265064, "jobstatus": "closed", "actualcorecount": null, "reqid": 30864, "nucleus": "TOKYO-LCG2", "jobsubstatus": "toreassign", "eventservice": "ordinary", "hs06": 1920, "hs06sec": null, "maxrss": null, "maxvmem": null, "maxswap": null, "maxpss": null, "avgrss": null, "avgvmem": null, "avgswap": null, "avgpss": null, "maxwalltime": 4611, "resourcetype": "MCORE", "failedattempt": 4, "totrchar": null, "totwchar": null, "totrbytes": null, "totwbytes": null, "raterchar": null, "ratewchar": null, "raterbytes": null, "ratewbytes": null, "diskio": null, "memoryleak": null, "memoryleakx2": null, "container_name": "atlas.athena:21.0.15_DBRelease-100.0.2_Patched", "outputfiletype": "log", "homecloud": "DE", "errorinfo": "", "jobinfo": "", "duration": "", "durationsec": 0, "durationmin": 0, "waittime": "0:6:46:27", "priorityrange": "800:899", "jobsetrange": "30800:30899"}, "dsfiles": []}"""
job_data = json.loads(job_data_json)
job_data[
"jobPars"] = '--inputEVNTFile=EVNT.21265061._000036.pool.root.1 --maxEvents=1000 --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=1000 --firstEvent=331001 --outputHITSFile=HITS.21265064._002580.pool.root.1 --physicsList=FTFP_BERT_ATL_VALIDATION --randomSeed=352 --DBRelease="all:current" --conditionsTag "default:OFLCOND-MC16-SDR-14" --geometryVersion="default:ATLAS-R2-2016-01-00-01_VALIDATION" --runNumber=830011 --AMITag=s3126 --DataRunNumber=284500 --simulator=FullG4 --truthStrategy=MC15aPlus'
jobSpec = JobSpec()
jobSpec.convert_job_json(job_data)
#pprint(jobSpec.jobParams)
ae = AuxExtractor()
print(ae.get_aux_inputs(jobSpec))
fileSpec = FileSpec()
fileSpec.fileType = 'output'
fileSpec.lfn = file_prefix + uuid.uuid4().hex + '.gz'
fileSpec.fileAttributes = {'guid': str(uuid.uuid4())}
fileSpec.checksum = '0d439274'
assFileSpec = FileSpec()
assFileSpec.lfn = file_prefix + uuid.uuid4().hex
assFileSpec.fileType = 'es_output'
assFileSpec.fsize = random.randint(10, 100)
assFileSpec.path = os.getcwd() + '/' + assFileSpec.lfn
oFile = open(assFileSpec.lfn, 'w')
oFile.write(''.join(random.choice(string.ascii_uppercase + string.digits) for _ in range(assFileSpec.fsize)))
oFile.close()
fileSpec.add_associated_file(assFileSpec)
jobSpec = JobSpec()
jobSpec.jobParams = {'outFiles': fileSpec.lfn + ',log',
'scopeOut': 'panda',
'scopeLog': 'panda',
'logFile': 'log',
'realDatasets': 'panda.' + fileSpec.lfn,
'ddmEndPointOut': 'BNL-OSG2_DATADISK',
}
jobSpec.add_out_file(fileSpec)
pluginFactory = PluginFactory()
# get stage-out plugin
stagerCore = pluginFactory.get_plugin(queueConfig.stager)
print ("plugin={0}".format(stagerCore.__class__.__name__))
fileSpec.fileType = 'output'
fileSpec.lfn = file_prefix + uuid.uuid4().hex + '.gz'
fileSpec.fileAttributes = {'guid': str(uuid.uuid4())}
fileSpec.checksum = '0d439274'
assFileSpec = FileSpec()
assFileSpec.lfn = file_prefix + uuid.uuid4().hex
assFileSpec.fileType = 'es_output'
assFileSpec.fsize = random.randint(10, 100)
assFileSpec.path = os.getcwd() + '/' + assFileSpec.lfn
oFile = open(assFileSpec.lfn, 'w')
oFile.write(''.join(
random.choice(string.ascii_uppercase + string.digits)
for _ in range(assFileSpec.fsize)))
oFile.close()
fileSpec.add_associated_file(assFileSpec)
jobSpec = JobSpec()
jobSpec.jobParams = {
'outFiles': fileSpec.lfn + ',log',
'scopeOut': 'panda',
'scopeLog': 'panda',
'logFile': 'log',
'realDatasets': 'panda.' + fileSpec.lfn,
'ddmEndPointOut': 'BNL-OSG2_DATADISK',
}
jobSpec.add_out_file(fileSpec)
pluginFactory = PluginFactory()
# get stage-out plugin
stagerCore = pluginFactory.get_plugin(queueConfig.stager)
print("plugin={0}".format(stagerCore.__class__.__name__))
def make_worker(self, jobspec_list, queue_config, resource_type):
tmpLog = self.make_logger(_logger,
'queue={0}'.format(queue_config.queueName),
method_name='make_worker')
tmpLog.debug('jobspec_list: {0}'.format(jobspec_list))
workSpec = WorkSpec()
workSpec.creationTime = datetime.datetime.utcnow()
# get the queue configuration from the DB
panda_queues_dict = PandaQueuesDict()
queue_dict = panda_queues_dict.get(queue_config.queueName, {})
unified_queue = queue_dict.get('capability', '') == 'ucore'
# case of traditional (non-unified) queue: look at the queue configuration
if not unified_queue:
workSpec.nCore = queue_dict.get('corecount', 1) or 1
workSpec.minRamCount = queue_dict.get('maxrss', 1) or 1
# case of unified queue: look at the resource type and queue configuration
else:
catchall = queue_dict.get('catchall', '')
if 'useMaxRam' in catchall or queue_config.queueName in (
'Taiwan-LCG2-HPC2_Unified', 'Taiwan-LCG2-HPC_Unified',
'DESY-ZN_UCORE'):
# temporary hack to debug killed workers in Taiwan queues
site_corecount = queue_dict.get('corecount', 1) or 1
site_maxrss = queue_dict.get('maxrss', 1) or 1
# some cases need to overwrite those values
if 'SCORE' in resource_type:
# the usual pilot streaming use case
workSpec.nCore = 1
workSpec.minRamCount = int(
math.ceil(site_maxrss / site_corecount))
else:
# default values
workSpec.nCore = site_corecount
workSpec.minRamCount = site_maxrss
else:
workSpec.nCore, workSpec.minRamCount = self.rt_mapper.calculate_worker_requirements(
resource_type, queue_dict)
# parameters that are independent on traditional vs unified
workSpec.maxWalltime = queue_dict.get('maxtime', 1)
workSpec.maxDiskCount = queue_dict.get('maxwdir', 1)
walltimeLimit_default = getattr(queue_config, 'walltimeLimit', 0)
if len(jobspec_list) > 0:
# get info from jobs
nCore = 0
minRamCount = 0
maxDiskCount = 0
maxWalltime = 0
ioIntensity = 0
for jobSpec in jobspec_list:
job_corecount, job_memory = self.get_job_core_and_memory(
queue_dict, jobSpec)
nCore += job_corecount
minRamCount += job_memory
try:
maxDiskCount += jobSpec.jobParams['maxDiskCount']
except Exception:
pass
try:
ioIntensity += jobSpec.jobParams['ioIntensity']
except Exception:
pass
try:
# maxWallTime from AGIS or qconf, not trusting job currently
maxWalltime = queue_dict.get('maxtime', walltimeLimit_default)
except Exception:
pass
if (nCore > 0 and 'nCore' in self.jobAttributesToUse) \
or unified_queue:
workSpec.nCore = nCore
if (minRamCount > 0 and 'minRamCount' in self.jobAttributesToUse) \
or unified_queue:
workSpec.minRamCount = minRamCount
if maxDiskCount > 0 and 'maxDiskCount' in self.jobAttributesToUse:
workSpec.maxDiskCount = maxDiskCount
if maxWalltime > 0 and 'maxWalltime' in self.jobAttributesToUse:
workSpec.maxWalltime = maxWalltime
if ioIntensity > 0 and 'ioIntensity' in self.jobAttributesToUse:
workSpec.ioIntensity = ioIntensity
workSpec.pilotType = jobspec_list[0].get_pilot_type()
else:
# when no job
# randomize pilot type with weighting
pdpm = getattr(queue_config,
'prodSourceLabelRandomWeightsPermille', {})
choice_list = core_utils.make_choice_list(pdpm=pdpm,
default='managed')
tmp_prodsourcelabel = random.choice(choice_list)
fake_job = JobSpec()
fake_job.jobParams = {}
fake_job.jobParams['prodSourceLabel'] = tmp_prodsourcelabel
workSpec.pilotType = fake_job.get_pilot_type()
del fake_job
if workSpec.pilotType in ['RC', 'ALRB', 'PT']:
tmpLog.info('a worker has pilotType={0}'.format(
workSpec.pilotType))
# TODO: this needs to be improved with real resource types
if resource_type and resource_type != 'ANY':
workSpec.resourceType = resource_type
elif workSpec.nCore == 1:
workSpec.resourceType = 'SCORE'
else:
workSpec.resourceType = 'MCORE'
return workSpec
errStr = ''
if not tmpStatsrc:
errStr += ' source Endpoint not activated '
if not tmpStatdst:
errStr += ' destination Endpoint not activated '
tmpLog.error(errStr)
sys.exit(2)
# We are sending test files from our destination machine to the source machine
# both endpoints activated now prepare to transfer data
tdata = TransferData(tc, dstEndpoint, srcEndpoint, sync_level="checksum")
except:
errStat, errMsg = globus_utils.handle_globus_exception(tmpLog)
sys.exit(1)
# create JobSpec
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
ddmEndPointIn = 'BNL-OSG2_DATADISK'
inFiles_scope_str = ''
inFiles_str = ''
realDatasets_str = ''
realDatasetsIn_str = ''
ddmEndPointIn_str = ''
GUID_str = ''
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__))
errStr += ' source Endpoint not activated '
if not tmpStatdst :
errStr += ' destination Endpoint not activated '
tmpLog.error(errStr)
sys.exit(2)
# both endpoints activated now prepare to transfer data
# We are sending test files from our destination machine to the source machine
tdata = TransferData(tc,dstEndpoint,srcEndpoint,sync_level="checksum")
except:
errStat, errMsg = globus_utils.handle_globus_exception(tmpLog)
sys.exit(1)
# 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
ddmEndPointIn = 'BNL-OSG2_DATADISK'
inFiles_scope_str = ''
inFiles_str = ''
realDatasets_str = ''
realDatasetsIn_str = ''
ddmEndPointIn_str = ''
GUID_str = ''
pluginFactory = PluginFactory()
com = CommunicatorPool()
# get job
jobSpecList = []
if queueConfig.mapType != WorkSpec.MT_NoJob:
jobs, errStr = com.get_jobs(queueConfig.queueName, 'nodeName',
queueConfig.prodSourceLabel,
'computingElement', 1, None)
if len(jobs) == 0:
print("Failed to get jobs at {0} due to {1}".format(
queueConfig.queueName, errStr))
sys.exit(0)
jobSpec = JobSpec()
jobSpec.convert_job_json(jobs[0])
# set input file paths
inFiles = jobSpec.get_input_file_attributes()
for inLFN, inFile in iteritems(inFiles):
inFile['path'] = '{0}/{1}'.format(os.getcwd(), inLFN)
jobSpec.set_input_file_paths(inFiles)
jobSpecList.append(jobSpec)
maker = pluginFactory.get_plugin(queueConfig.workerMaker)
workSpec = maker.make_worker(jobSpecList, queueConfig, jobType,
resourceType)
workSpec.accessPoint = queueConfig.messenger['accessPoint']
workSpec.mapType = queueConfig.mapType
import sys
import uuid
from pandaharvester.harvestercore.job_spec import JobSpec
from pandaharvester.harvestercore.file_spec import FileSpec
from pandaharvester.harvestercore.event_spec import EventSpec
from pandaharvester.harvestercore.communicator_pool import CommunicatorPool
rID = sys.argv[1]
taskid = rID.split('-')[0]
pandaid = long(rID.split('-')[1])
job = JobSpec()
job.PandaID = pandaid
event = EventSpec()
file = FileSpec()
file.status = 'finished'
file.objstoreID = 9575
file.pathConvention = 1000
file.lfn = str(uuid.uuid4().hex) + '.zip'
file.fsize = 555
file.chksum = '0d2a9dc9'
event.eventRangeID = rID
event.eventStatus = 'finished'
job.zipEventMap = {1: {'events':[event],
'zip':file}}
a = CommunicatorPool()
a.update_jobs([job])