def algorithm(self, *args, **kwargs):
"""
_algorithm_
An event base splitting algorithm. All available files are split into a
set number of events per job.
"""
eventsPerJob = int(kwargs.get("events_per_job", 100))
eventsPerLumi = int(kwargs.get("events_per_lumi", eventsPerJob))
getParents = kwargs.get("include_parents", False)
lheInput = kwargs.get("lheInputFiles", False)
collectionName = kwargs.get('collectionName', None)
timePerEvent, sizePerEvent, memoryRequirement = \
self.getPerformanceParameters(kwargs.get('performance', {}))
acdcFileList = []
# If we have runLumi info, we need to load it from couch
if collectionName:
try:
from WMCore.ACDC.DataCollectionService import DataCollectionService
couchURL = kwargs.get('couchURL')
couchDB = kwargs.get('couchDB')
filesetName = kwargs.get('filesetName')
collectionName = kwargs.get('collectionName')
owner = kwargs.get('owner')
group = kwargs.get('group')
logging.info('Creating jobs for ACDC fileset %s' % filesetName)
dcs = DataCollectionService(couchURL, couchDB)
acdcFileList = dcs.getProductionACDCInfo(
collectionName, filesetName, owner, group)
except Exception, ex:
msg = "Exception while trying to load goodRunList\n"
msg += "Refusing to create any jobs.\n"
msg += str(ex)
msg += str(traceback.format_exc())
logging.error(msg)
return
def algorithm(self, *args, **kwargs):
"""
_algorithm_
An event base splitting algorithm. All available files are split into a
set number of events per job.
"""
eventsPerJob = int(kwargs.get("events_per_job", 100))
eventsPerLumi = int(kwargs.get("events_per_lumi", eventsPerJob))
getParents = kwargs.get("include_parents", False)
lheInput = kwargs.get("lheInputFiles", False)
collectionName = kwargs.get('collectionName', None)
timePerEvent, sizePerEvent, memoryRequirement = \
self.getPerformanceParameters(kwargs.get('performance', {}))
acdcFileList = []
# If we have runLumi info, we need to load it from couch
if collectionName:
try:
from WMCore.ACDC.DataCollectionService import DataCollectionService
couchURL = kwargs.get('couchURL')
couchDB = kwargs.get('couchDB')
filesetName = kwargs.get('filesetName')
collectionName = kwargs.get('collectionName')
owner = kwargs.get('owner')
group = kwargs.get('group')
logging.info('Creating jobs for ACDC fileset %s' % filesetName)
dcs = DataCollectionService(couchURL, couchDB)
acdcFileList = dcs.getProductionACDCInfo(collectionName, filesetName, owner, group)
except Exception, ex:
msg = "Exception while trying to load goodRunList\n"
msg += "Refusing to create any jobs.\n"
msg += str(ex)
msg += str(traceback.format_exc())
logging.error(msg)
return
def algorithm(self, *args, **kwargs):
"""
_algorithm_
An event base splitting algorithm. All available files are split into a
set number of events per job.
"""
eventsPerJob = int(kwargs.get("events_per_job", 100))
eventsPerLumi = int(kwargs.get("events_per_lumi", eventsPerJob))
getParents = kwargs.get("include_parents", False)
lheInput = kwargs.get("lheInputFiles", False)
collectionName = kwargs.get('collectionName', None)
timePerEvent, sizePerEvent, memoryRequirement = \
self.getPerformanceParameters(kwargs.get('performance', {}))
acdcFileList = []
deterministicPileup = kwargs.get('deterministicPileup', False)
if eventsPerJob <= 0 or eventsPerLumi <= 0:
msg = "events_per_job and events_per_lumi must be positive. Their values are: "
msg += "events_per_job: %d, events_per_lumi: %d" % (eventsPerJob, eventsPerLumi)
raise RuntimeError(msg)
if deterministicPileup and self.package == 'WMCore.WMBS':
getJobNumber = self.daoFactory(classname="Jobs.GetNumberOfJobsPerWorkflow")
self.nJobs = getJobNumber.execute(workflow=self.subscription.getWorkflow().id)
logging.info('Creating jobs in DeterministicPileup mode for %s',
self.subscription.workflowName())
# If we have runLumi info, we need to load it from couch
if collectionName:
try:
from WMCore.ACDC.DataCollectionService import DataCollectionService
couchURL = kwargs.get('couchURL')
couchDB = kwargs.get('couchDB')
filesetName = kwargs.get('filesetName')
collectionName = kwargs.get('collectionName')
logging.info('Loading ACDC info for collectionName: %s, with filesetName: %s', collectionName,
filesetName)
dcs = DataCollectionService(couchURL, couchDB)
acdcFileList = dcs.getProductionACDCInfo(collectionName, filesetName)
except Exception as ex:
msg = "Exception while trying to load goodRunList\n"
msg += "Refusing to create any jobs.\n"
msg += str(ex)
msg += str(traceback.format_exc())
logging.error(msg)
return
totalJobs = 0
locationDict = self.sortByLocation()
for location in locationDict:
self.newGroup()
fileList = locationDict[location]
getRunLumiInformation = False
for f in fileList:
if f['lfn'].startswith("MCFakeFile"):
# We have one MCFakeFile, then it needs run information
getRunLumiInformation = True
break
if getRunLumiInformation:
if self.package == 'WMCore.WMBS':
loadRunLumi = self.daoFactory(classname="Files.GetBulkRunLumi")
fileLumis = loadRunLumi.execute(files=fileList)
if not fileLumis:
logging.warning("Empty fileLumis dict for workflow %s, subs %s.",
self.subscription.workflowName(), self.subscription['id'])
for f in fileList:
lumiDict = fileLumis.get(f['id'], {})
for run in lumiDict:
f.addRun(run=Run(run, *lumiDict[run]))
for f in fileList:
currentEvent = f['first_event']
eventsInFile = f['events']
runs = list(f['runs'])
# We got the runs, clean the file.
f['runs'] = set()
if getParents:
parentLFNs = self.findParent(lfn=f['lfn'])
for lfn in parentLFNs:
parent = File(lfn=lfn)
f['parents'].add(parent)
if acdcFileList:
totalJobs = self.createACDCJobs(f, acdcFileList, timePerEvent,
sizePerEvent, memoryRequirement,
lheInput, eventsPerJob, eventsPerLumi,
deterministicPileup, totalJobs)
continue
if not f['lfn'].startswith("MCFakeFile"):
# there might be files with 0 event that still have to be processed
if eventsInFile == 0:
self.newJob(name=self.getJobName(length=totalJobs))
self.currentJob.addFile(f)
# Do not set LastEvent
self.currentJob["mask"].setMaxAndSkipEvents(None, currentEvent)
self.currentJob.addResourceEstimates(jobTime=0,
memory=memoryRequirement,
disk=0)
if deterministicPileup:
self.currentJob.addBaggageParameter("skipPileupEvents", (self.nJobs - 1) * eventsPerJob)
totalJobs += 1
logging.info("Job created for 0-event input file with %s", self.currentJob)
# Very very uncommon in production, but it has real input dataset
while eventsInFile:
self.newJob(name=self.getJobName(length=totalJobs))
self.currentJob.addFile(f)
if eventsInFile >= eventsPerJob:
jobTime = eventsPerJob * timePerEvent
diskRequired = eventsPerJob * sizePerEvent
self.currentJob["mask"].setMaxAndSkipEvents(eventsPerJob - 1, currentEvent)
else:
jobTime = eventsInFile * timePerEvent
diskRequired = eventsInFile * sizePerEvent
self.currentJob["mask"].setMaxAndSkipEvents(eventsInFile - 1, currentEvent)
eventsInFile = eventsPerJob
self.currentJob.addResourceEstimates(jobTime=jobTime,
memory=memoryRequirement,
disk=diskRequired)
if deterministicPileup:
self.currentJob.addBaggageParameter("skipPileupEvents", (self.nJobs - 1) * eventsPerJob)
eventsInFile -= eventsPerJob
currentEvent += eventsPerJob
totalJobs += 1
logging.debug("Job created for real input with %s", self.currentJob)
else:
# This assumes there's only one run which is the case for MC
lumis = runs[0].lumis
(firstLumi, lastLumi) = (min(lumis), max(lumis))
currentLumi = firstLumi
lumisPerJob = int(ceil(float(eventsPerJob) / eventsPerLumi))
while eventsInFile:
self.newJob(name=self.getJobName(length=totalJobs))
self.currentJob.addFile(f)
self.currentJob.addBaggageParameter("lheInputFiles", lheInput)
# Limit the number of events to a unsigned 32bit int
if (currentEvent + eventsPerJob - 1) > (2 ** 32 - 1) and \
(currentEvent + eventsInFile) > (2 ** 32 - 1):
currentEvent = 1
if eventsInFile >= eventsPerJob:
jobTime = eventsPerJob * timePerEvent
diskRequired = eventsPerJob * sizePerEvent
# Alan on 16/Apr/2019: inclusiveMask must be a real inclusiveMask, thus
# FirstEvent/FirstLumi and LastEvent/LastLumi are also processed by the job
self.currentJob["mask"].setMaxAndSkipEvents(eventsPerJob - 1, currentEvent)
self.currentJob["mask"].setMaxAndSkipLumis(lumisPerJob - 1, currentLumi)
else:
jobTime = eventsInFile * timePerEvent
diskRequired = eventsInFile * sizePerEvent
lumisPerJob = int(ceil(float(eventsInFile) / eventsPerLumi))
self.currentJob["mask"].setMaxAndSkipEvents(eventsInFile - 1, currentEvent)
self.currentJob["mask"].setMaxAndSkipLumis(lumisPerJob - 1, currentLumi)
eventsInFile = eventsPerJob
self.currentJob.addResourceEstimates(jobTime=jobTime,
memory=memoryRequirement,
disk=diskRequired)
if deterministicPileup:
self.currentJob.addBaggageParameter("skipPileupEvents", (self.nJobs - 1) * eventsPerJob)
eventsInFile -= eventsPerJob
currentEvent += eventsPerJob
currentLumi += lumisPerJob
totalJobs += 1
logging.info("Job created with mask: %s", self.currentJob['mask'])
return
def algorithm(self, *args, **kwargs):
"""
_algorithm_
An event base splitting algorithm. All available files are split into a
set number of events per job.
"""
eventsPerJob = int(kwargs.get("events_per_job", 100))
eventsPerLumi = int(kwargs.get("events_per_lumi", eventsPerJob))
getParents = kwargs.get("include_parents", False)
lheInput = kwargs.get("lheInputFiles", False)
collectionName = kwargs.get('collectionName', None)
timePerEvent, sizePerEvent, memoryRequirement = \
self.getPerformanceParameters(kwargs.get('performance', {}))
acdcFileList = []
deterministicPileup = kwargs.get('deterministicPileup', False)
if deterministicPileup and self.package == 'WMCore.WMBS':
getJobNumber = self.daoFactory(classname="Jobs.GetNumberOfJobsPerWorkflow")
self.nJobs = getJobNumber.execute(workflow=self.subscription.getWorkflow().id)
logging.info('Creating %d jobs in DeterministicPileup mode', self.nJobs)
# If we have runLumi info, we need to load it from couch
if collectionName:
try:
from WMCore.ACDC.DataCollectionService import DataCollectionService
couchURL = kwargs.get('couchURL')
couchDB = kwargs.get('couchDB')
filesetName = kwargs.get('filesetName')
collectionName = kwargs.get('collectionName')
owner = kwargs.get('owner')
group = kwargs.get('group')
logging.info('Creating jobs for ACDC fileset %s', filesetName)
dcs = DataCollectionService(couchURL, couchDB)
acdcFileList = dcs.getProductionACDCInfo(collectionName, filesetName, owner, group)
except Exception as ex:
msg = "Exception while trying to load goodRunList\n"
msg += "Refusing to create any jobs.\n"
msg += str(ex)
msg += str(traceback.format_exc())
logging.error(msg)
return
totalJobs = 0
locationDict = self.sortByLocation()
for location in locationDict:
self.newGroup()
fileList = locationDict[location]
getRunLumiInformation = False
for f in fileList:
if f['lfn'].startswith("MCFakeFile"):
# We have one MCFakeFile, then it needs run information
getRunLumiInformation = True
break
if getRunLumiInformation:
if self.package == 'WMCore.WMBS':
loadRunLumi = self.daoFactory(classname="Files.GetBulkRunLumi")
fileLumis = loadRunLumi.execute(files=fileList)
for f in fileList:
lumiDict = fileLumis.get(f['id'], {})
for run in lumiDict.keys():
f.addRun(run=Run(run, *lumiDict[run]))
for f in fileList:
currentEvent = f['first_event']
eventsInFile = f['events']
runs = list(f['runs'])
# We got the runs, clean the file.
f['runs'] = set()
if getParents:
parentLFNs = self.findParent(lfn=f['lfn'])
for lfn in parentLFNs:
parent = File(lfn=lfn)
f['parents'].add(parent)
if acdcFileList:
if f['lfn'] in [x['lfn'] for x in acdcFileList]:
totalJobs = self.createACDCJobs(f, acdcFileList, timePerEvent,
sizePerEvent, memoryRequirement,
lheInput, eventsPerJob, eventsPerLumi,
deterministicPileup, totalJobs)
continue
if not f['lfn'].startswith("MCFakeFile"):
# Very very uncommon, but it has real input dataset
if eventsInFile >= eventsPerJob:
while currentEvent < eventsInFile:
self.newJob(name=self.getJobName(length=totalJobs))
self.currentJob.addFile(f)
if eventsPerJob + currentEvent < eventsInFile:
jobTime = eventsPerJob * timePerEvent
diskRequired = eventsPerJob * sizePerEvent
self.currentJob["mask"].setMaxAndSkipEvents(eventsPerJob, currentEvent)
else:
jobTime = (eventsInFile - currentEvent) * timePerEvent
diskRequired = (eventsInFile - currentEvent) * sizePerEvent
self.currentJob["mask"].setMaxAndSkipEvents(None,
currentEvent)
self.currentJob.addResourceEstimates(jobTime=jobTime,
memory=memoryRequirement,
disk=diskRequired)
if deterministicPileup:
self.currentJob.addBaggageParameter("skipPileupEvents", (self.nJobs - 1) * eventsPerJob)
logging.debug("Job created for real input with %s", self.currentJob)
currentEvent += eventsPerJob
totalJobs += 1
else:
self.newJob(name=self.getJobName(length=totalJobs))
self.currentJob.addFile(f)
jobTime = eventsInFile * timePerEvent
diskRequired = eventsInFile * sizePerEvent
self.currentJob.addResourceEstimates(jobTime=jobTime,
memory=memoryRequirement,
disk=diskRequired)
if deterministicPileup:
self.currentJob.addBaggageParameter("skipPileupEvents", (self.nJobs - 1) * eventsPerJob)
logging.debug("Last job created for real input with %s", self.currentJob)
totalJobs += 1
else:
# This assumes there's only one run which is the case for MC
lumis = runs[0].lumis
(firstLumi, lastLumi) = (min(lumis), max(lumis))
currentLumi = firstLumi
totalEvents = 0
if eventsInFile >= eventsPerJob:
while totalEvents < eventsInFile:
self.newJob(name=self.getJobName(length=totalJobs))
self.currentJob.addFile(f)
self.currentJob.addBaggageParameter("lheInputFiles", lheInput)
lumisPerJob = int(ceil(float(eventsPerJob)
/ eventsPerLumi))
# Limit the number of events to a unsigned 32bit int
eventsRemaining = eventsInFile - totalEvents
if (currentEvent + eventsPerJob - 1) > (2 ** 32 - 1) and (
currentEvent + eventsRemaining - 1) > (2 ** 32 - 1):
currentEvent = 1
if eventsRemaining > eventsPerJob:
self.currentJob["mask"].setMaxAndSkipEvents(eventsPerJob,
currentEvent)
self.currentJob["mask"].setMaxAndSkipLumis(lumisPerJob,
currentLumi)
jobTime = eventsPerJob * timePerEvent
diskRequired = eventsPerJob * sizePerEvent
else:
jobTime = eventsRemaining * timePerEvent
diskRequired = eventsRemaining * sizePerEvent
lumisPerJob = int(ceil(float(eventsRemaining) / eventsPerLumi))
self.currentJob["mask"].setMaxAndSkipEvents(eventsRemaining,
currentEvent)
self.currentJob["mask"].setMaxAndSkipLumis(lumisPerJob,
currentLumi)
if deterministicPileup:
self.currentJob.addBaggageParameter("skipPileupEvents", (self.nJobs - 1) * eventsPerJob)
currentLumi += lumisPerJob
currentEvent += eventsPerJob
totalEvents += eventsPerJob
totalJobs += 1
self.currentJob.addResourceEstimates(jobTime=jobTime,
memory=memoryRequirement,
disk=diskRequired)
else:
self.newJob(name=self.getJobName(length=totalJobs))
self.currentJob.addFile(f)
# For MC we use firstEvent instead of skipEvents so set it to 1
# We must check for events going over 2**32 - 1 here too
if (eventsInFile + currentEvent - 1) > (2 ** 32 - 1):
currentEvent = 1
self.currentJob["mask"].setMaxAndSkipEvents(eventsInFile,
currentEvent)
self.currentJob["mask"].setMaxAndSkipLumis(lastLumi -
currentLumi + 1, currentLumi)
jobTime = eventsInFile * timePerEvent
diskRequired = eventsInFile * sizePerEvent
self.currentJob.addResourceEstimates(jobTime=jobTime,
memory=memoryRequirement,
disk=diskRequired)
if deterministicPileup:
self.currentJob.addBaggageParameter("skipPileupEvents", (self.nJobs - 1) * eventsPerJob)
totalJobs += 1
def algorithm(self, *args, **kwargs):
"""
_algorithm_
An event base splitting algorithm. All available files are split into a
set number of events per job.
"""
eventsPerJob = int(kwargs.get("events_per_job", 100))
eventsPerLumi = int(kwargs.get("events_per_lumi", eventsPerJob))
getParents = kwargs.get("include_parents", False)
lheInput = kwargs.get("lheInputFiles", False)
collectionName = kwargs.get('collectionName', None)
timePerEvent, sizePerEvent, memoryRequirement = \
self.getPerformanceParameters(kwargs.get('performance', {}))
acdcFileList = []
deterministicPileup = kwargs.get('deterministicPileup', False)
if eventsPerJob <= 0 or eventsPerLumi <= 0:
msg = "events_per_job and events_per_lumi must be positive. Their values are: "
msg += "events_per_job: %d, events_per_lumi: %d" % (eventsPerJob, eventsPerLumi)
raise RuntimeError(msg)
if deterministicPileup and self.package == 'WMCore.WMBS':
getJobNumber = self.daoFactory(classname="Jobs.GetNumberOfJobsPerWorkflow")
self.nJobs = getJobNumber.execute(workflow=self.subscription.getWorkflow().id)
logging.info('Creating jobs in DeterministicPileup mode for %s',
self.subscription.workflowName())
# If we have runLumi info, we need to load it from couch
if collectionName:
try:
from WMCore.ACDC.DataCollectionService import DataCollectionService
couchURL = kwargs.get('couchURL')
couchDB = kwargs.get('couchDB')
filesetName = kwargs.get('filesetName')
collectionName = kwargs.get('collectionName')
logging.info('Loading ACDC info for collectionName: %s, with filesetName: %s', collectionName,
filesetName)
dcs = DataCollectionService(couchURL, couchDB)
acdcFileList = dcs.getProductionACDCInfo(collectionName, filesetName)
except Exception as ex:
msg = "Exception while trying to load goodRunList\n"
msg += "Refusing to create any jobs.\n"
msg += str(ex)
msg += str(traceback.format_exc())
logging.error(msg)
return
totalJobs = 0
locationDict = self.sortByLocation()
for location in locationDict:
self.newGroup()
fileList = locationDict[location]
getRunLumiInformation = False
for f in fileList:
if f['lfn'].startswith("MCFakeFile"):
# We have one MCFakeFile, then it needs run information
getRunLumiInformation = True
break
if getRunLumiInformation:
if self.package == 'WMCore.WMBS':
loadRunLumi = self.daoFactory(classname="Files.GetBulkRunLumi")
fileLumis = loadRunLumi.execute(files=fileList)
if not fileLumis:
logging.warning("Empty fileLumis dict for workflow %s, subs %s.",
self.subscription.workflowName(), self.subscription['id'])
for f in fileList:
lumiDict = fileLumis.get(f['id'], {})
for run in lumiDict.keys():
f.addRun(run=Run(run, *lumiDict[run]))
for f in fileList:
currentEvent = f['first_event']
eventsInFile = f['events']
runs = list(f['runs'])
# We got the runs, clean the file.
f['runs'] = set()
if getParents:
parentLFNs = self.findParent(lfn=f['lfn'])
for lfn in parentLFNs:
parent = File(lfn=lfn)
f['parents'].add(parent)
if acdcFileList:
totalJobs = self.createACDCJobs(f, acdcFileList, timePerEvent,
sizePerEvent, memoryRequirement,
lheInput, eventsPerJob, eventsPerLumi,
deterministicPileup, totalJobs)
continue
if not f['lfn'].startswith("MCFakeFile"):
# there might be files with 0 event that still have to be processed
if eventsInFile == 0:
self.newJob(name=self.getJobName(length=totalJobs))
self.currentJob.addFile(f)
# Do not set LastEvent
self.currentJob["mask"].setMaxAndSkipEvents(None, currentEvent)
self.currentJob.addResourceEstimates(jobTime=0,
memory=memoryRequirement,
disk=0)
if deterministicPileup:
self.currentJob.addBaggageParameter("skipPileupEvents", (self.nJobs - 1) * eventsPerJob)
totalJobs += 1
logging.info("Job created for 0-event input file with %s", self.currentJob)
# Very very uncommon in production, but it has real input dataset
while eventsInFile:
self.newJob(name=self.getJobName(length=totalJobs))
self.currentJob.addFile(f)
if eventsInFile >= eventsPerJob:
jobTime = eventsPerJob * timePerEvent
diskRequired = eventsPerJob * sizePerEvent
self.currentJob["mask"].setMaxAndSkipEvents(eventsPerJob - 1, currentEvent)
else:
jobTime = eventsInFile * timePerEvent
diskRequired = eventsInFile * sizePerEvent
self.currentJob["mask"].setMaxAndSkipEvents(eventsInFile - 1, currentEvent)
eventsInFile = eventsPerJob
self.currentJob.addResourceEstimates(jobTime=jobTime,
memory=memoryRequirement,
disk=diskRequired)
if deterministicPileup:
self.currentJob.addBaggageParameter("skipPileupEvents", (self.nJobs - 1) * eventsPerJob)
eventsInFile -= eventsPerJob
currentEvent += eventsPerJob
totalJobs += 1
logging.debug("Job created for real input with %s", self.currentJob)
else:
# This assumes there's only one run which is the case for MC
lumis = runs[0].lumis
(firstLumi, lastLumi) = (min(lumis), max(lumis))
currentLumi = firstLumi
lumisPerJob = int(ceil(float(eventsPerJob) / eventsPerLumi))
while eventsInFile:
self.newJob(name=self.getJobName(length=totalJobs))
self.currentJob.addFile(f)
self.currentJob.addBaggageParameter("lheInputFiles", lheInput)
# Limit the number of events to a unsigned 32bit int
if (currentEvent + eventsPerJob - 1) > (2 ** 32 - 1) and \
(currentEvent + eventsInFile) > (2 ** 32 - 1):
currentEvent = 1
if eventsInFile >= eventsPerJob:
jobTime = eventsPerJob * timePerEvent
diskRequired = eventsPerJob * sizePerEvent
# Alan on 16/Apr/2019: inclusiveMask must be a real inclusiveMask, thus
# FirstEvent/FirstLumi and LastEvent/LastLumi are also processed by the job
self.currentJob["mask"].setMaxAndSkipEvents(eventsPerJob - 1, currentEvent)
self.currentJob["mask"].setMaxAndSkipLumis(lumisPerJob - 1, currentLumi)
else:
jobTime = eventsInFile * timePerEvent
diskRequired = eventsInFile * sizePerEvent
lumisPerJob = int(ceil(float(eventsInFile) / eventsPerLumi))
self.currentJob["mask"].setMaxAndSkipEvents(eventsInFile - 1, currentEvent)
self.currentJob["mask"].setMaxAndSkipLumis(lumisPerJob - 1, currentLumi)
eventsInFile = eventsPerJob
self.currentJob.addResourceEstimates(jobTime=jobTime,
memory=memoryRequirement,
disk=diskRequired)
if deterministicPileup:
self.currentJob.addBaggageParameter("skipPileupEvents", (self.nJobs - 1) * eventsPerJob)
eventsInFile -= eventsPerJob
currentEvent += eventsPerJob
currentLumi += lumisPerJob
totalJobs += 1
logging.info("Job created with mask: %s", self.currentJob['mask'])
return
