def setUp(self):
"""
_setUp_
Create two subscriptions: One that contains a single file and one that
contains multiple files.
"""
self.multipleFileFileset = Fileset(name="TestFileset1")
for i in range(10):
newFile = File(makeUUID(), size=1000, events=100)
newFile.setLocation('blenheim')
newFile.setLocation('malpaquet')
self.multipleFileFileset.addFile(newFile)
self.singleFileFileset = Fileset(name="TestFileset2")
newFile = File("/some/file/name", size=1000, events=100)
newFile.setLocation('blenheim')
self.singleFileFileset.addFile(newFile)
testWorkflow = Workflow()
self.multipleFileSubscription = Subscription(
fileset=self.multipleFileFileset,
workflow=testWorkflow,
split_algo="FileBased",
type="Processing")
self.singleFileSubscription = Subscription(
fileset=self.singleFileFileset,
workflow=testWorkflow,
split_algo="FileBased",
type="Processing")
#self.multipleFileSubscription.create()
#self.singleFileSubscription.create()
return
def setUp(self):
"""
_setUp_
Create two subscriptions: One that contains a single file and one that
contains multiple files.
"""
self.multipleFileFileset = Fileset(name="TestFileset1")
for i in range(10):
newFile = File(makeUUID(), size=1000, events=100)
newFile.addRun(Run(i, *[45 + i]))
self.multipleFileFileset.addFile(newFile)
self.singleFileFileset = Fileset(name="TestFileset2")
newFile = File("/some/file/name", size=1000, events=100)
newFile.addRun(Run(1, *[45]))
self.singleFileFileset.addFile(newFile)
self.multipleFileLumiset = Fileset(name="TestFileset3")
for i in range(10):
newFile = File(makeUUID(), size=1000, events=100)
newFile.addRun(Run(1, *[45 + i / 3]))
self.multipleFileLumiset.addFile(newFile)
self.singleLumiFileset = Fileset(name="TestFileset4")
for i in range(10):
newFile = File(makeUUID(), size=1000, events=100)
newFile.addRun(Run(1, *[45]))
self.singleLumiFileset.addFile(newFile)
testWorkflow = Workflow()
self.multipleFileSubscription = Subscription(
fileset=self.multipleFileFileset,
workflow=testWorkflow,
split_algo="FixedDelay",
type="Processing")
self.singleFileSubscription = Subscription(
fileset=self.singleFileFileset,
workflow=testWorkflow,
split_algo="FixedDelay",
type="Processing")
self.multipleLumiSubscription = Subscription(
fileset=self.multipleFileLumiset,
workflow=testWorkflow,
split_algo="FixedDelay",
type="Processing")
self.singleLumiSubscription = Subscription(
fileset=self.singleLumiFileset,
workflow=testWorkflow,
split_algo="FixedDelay",
type="Processing")
return
def setUp(self):
"""
_setUp_
Create two subscriptions: One that contains a single file and one that
contains multiple files.
"""
self.multipleFileFileset = Fileset(name="TestFileset1")
for i in range(10):
newFile = File(makeUUID(),
size=1000,
events=100,
locations=set(["somese.cern.ch"]))
self.multipleFileFileset.addFile(newFile)
self.singleFileFileset = Fileset(name="TestFileset2")
newFile = File("/some/file/name",
size=1000,
events=100,
locations=set(["somese.cern.ch"]))
self.singleFileFileset.addFile(newFile)
self.multipleSiteFileset = Fileset(name="TestFileset3")
for i in range(5):
newFile = File(makeUUID(),
size=1000,
events=100,
locations=set(["somese.cern.ch"]))
newFile.setLocation("somese.cern.ch")
self.multipleSiteFileset.addFile(newFile)
for i in range(5):
newFile = File(makeUUID(), size=1000, events=100)
newFile.setLocation(["somese.cern.ch", "otherse.cern.ch"])
self.multipleSiteFileset.addFile(newFile)
testWorkflow = Workflow()
self.multipleFileSubscription = Subscription(
fileset=self.multipleFileFileset,
workflow=testWorkflow,
split_algo="SizeBased",
type="Processing")
self.singleFileSubscription = Subscription(
fileset=self.singleFileFileset,
workflow=testWorkflow,
split_algo="SizeBased",
type="Processing")
self.multipleSiteSubscription = Subscription(
fileset=self.multipleSiteFileset,
workflow=testWorkflow,
split_algo="EventBased",
type="Processing")
return
def testProductionRunNumber(self):
"""
_testProductionRunNumber_
Verify that jobs created by production subscritpions have the correct
run number is their job mask. Also verify that non-production
subscriptions don't have modified run numbers.
"""
testWorkflow = Workflow(spec="spec.pkl",
owner="Steve",
name="TestWorkflow",
task="TestTask")
testFileset = Fileset(name="TestFileset")
testFile = File(lfn="someLFN")
testFileset.addFile(testFile)
testFileset.commit()
testSubscription = Subscription(fileset=testFileset,
workflow=testWorkflow,
split_algo="FileBased",
type="Production")
myJobFactory = JobFactory(subscription=testSubscription)
testJobGroups = myJobFactory()
self.assertTrue(len(testJobGroups) > 0)
for testJobGroup in testJobGroups:
self.assertTrue(len(testJobGroup.jobs) > 0)
for job in testJobGroup.jobs:
self.assertEqual(job["mask"]["FirstRun"], 1,
"Error: First run is wrong.")
self.assertEqual(job["mask"]["LastRun"], 1,
"Error: Last run is wrong.")
testSubscription = Subscription(fileset=testFileset,
workflow=testWorkflow,
split_algo="FileBased",
type="Processing")
myJobFactory = JobFactory(subscription=testSubscription)
testJobGroups = myJobFactory()
for testJobGroup in testJobGroups:
for job in testJobGroup.jobs:
self.assertEqual(job["mask"]["FirstRun"], None,
"Error: First run is wrong.")
self.assertEqual(job["mask"]["LastRun"], None,
"Error: Last run is wrong.")
return
def setUp(self):
"""
_setUp_
Create two subscriptions: One that contains a single file and one that
contains multiple files.
"""
self.multipleFileFileset = Fileset(name="TestFileset1")
for i in range(10):
newFile = File(makeUUID(), size=1000, events=100)
newFile.setLocation('se01')
self.multipleFileFileset.addFile(newFile)
self.singleFileFileset = Fileset(name="TestFileset2")
newFile = File("/some/file/name", size=1000, events=100)
newFile.setLocation('se02')
self.singleFileFileset.addFile(newFile)
self.emptyFileFileset = Fileset(name="TestFileset3")
newFile = File("/some/file/name", size=1000, events=0)
newFile.setLocation('se03')
self.emptyFileFileset.addFile(newFile)
testWorkflow = Workflow()
self.multipleFileSubscription = Subscription(
fileset=self.multipleFileFileset,
workflow=testWorkflow,
split_algo="EventBased",
type="Processing")
self.singleFileSubscription = Subscription(
fileset=self.singleFileFileset,
workflow=testWorkflow,
split_algo="EventBased",
type="Processing")
self.emptyFileSubscription = Subscription(
fileset=self.emptyFileFileset,
workflow=testWorkflow,
split_algo="EventBased",
type="Processing")
self.eventsPerJob = 100
self.performanceParams = {
'timePerEvent': None,
'memoryRequirement': 2300,
'sizePerEvent': 400
}
return
def testHardLimitSplittingOnly(self):
"""
_testHardLimitSplittingOnly_
Checks that we can split a set of files where every file has a single
lumi too big to fit in a runnable job
"""
splitter = SplitterFactory()
# Create 3 single-big-lumi files
testFileset = Fileset(name="FilesetA")
testFileA = self.createFile("/this/is/file1", 1000, 0, 1, "somese.cern.ch")
testFileB = self.createFile("/this/is/file2", 1000, 1, 1, "somese.cern.ch")
testFileC = self.createFile("/this/is/file3", 1000, 2, 1, "somese.cern.ch")
testFileset.addFile(testFileA)
testFileset.addFile(testFileB)
testFileset.addFile(testFileC)
testSubscription = Subscription(fileset=testFileset, workflow=self.testWorkflow,
split_algo="EventAwareLumiByWork", type="Processing")
jobFactory = splitter(package="WMCore.DataStructs", subscription=testSubscription)
# Fail single lumis with more than 800 events and put 550 events per job
jobGroups = jobFactory(halt_job_on_file_boundaries=True, splitOnRun=True, events_per_job=550,
job_time_limit=9600, performance=self.performanceParams)
self.assertEqual(len(jobGroups), 1)
jobs = jobGroups[0].jobs
self.assertEqual(len(jobs), 3)
for job in jobs:
self.assertTrue(job['failedOnCreation'])
self.assertIn(' with too many events 1000 and it woud take 12000 sec to run', job['failedReason'])
return
def generateFakeMCFile(self,
numEvents=100,
firstEvent=1,
lastEvent=100,
firstLumi=1,
lastLumi=10,
existingSub=None):
# MC comes with only one MCFakeFile
newFile = File("MCFakeFileTest", size=1000, events=numEvents)
newFile.setLocation('se01')
if firstLumi == lastLumi:
newFile.addRun(Run(1, *range(firstLumi, lastLumi + 1)))
else:
newFile.addRun(Run(1, *range(firstLumi, lastLumi)))
newFile["first_event"] = firstEvent
newFile["last_event"] = lastEvent
if existingSub is None:
singleMCFileset = Fileset(name="MCTestFileset")
singleMCFileset.addFile(newFile)
testWorkflow = Workflow()
existingSub = Subscription(fileset=singleMCFileset,
workflow=testWorkflow,
split_algo="EventBased",
type="Production")
else:
existingSub['fileset'].addFile(newFile)
return existingSub
def testG_LumiMask(self):
"""
_testG_LumiMask_
Test that we can use a lumi-mask to filter good runs/lumis.
"""
splitter = SplitterFactory()
# Create 3 files with 100 events per lumi:
# - file1 with 1 run of 8 lumis
# - file2 with 2 runs of 2 lumis each
# - file3 with 1 run of 5 lumis
fileA = File(lfn="/this/is/file1", size=1000, events=800)
fileB = File(lfn="/this/is/file2", size=1000, events=400)
fileC = File(lfn="/this/is/file3", size=1000, events=500)
lumiListA = []
for lumi in range(8):
lumiListA.append(10 + lumi)
fileA.addRun(Run(1, *lumiListA))
fileA.setLocation("somese.cern.ch")
lumiListB1 = []
lumiListB2 = []
for lumi in range(2):
lumiListB1.append(20 + lumi)
lumiListB2.append(30 + lumi)
fileB.addRun(Run(2, *lumiListB1))
fileB.addRun(Run(3, *lumiListB2))
fileB.setLocation("somese.cern.ch")
lumiListC = []
for lumi in range(5):
lumiListC.append(40 + lumi)
fileC.addRun(Run(4, *lumiListC))
fileC.setLocation("somese.cern.ch")
testFileset = Fileset(name='Fileset')
testFileset.addFile(fileA)
testFileset.addFile(fileB)
testFileset.addFile(fileC)
testSubscription = Subscription(fileset=testFileset,
workflow=self.testWorkflow,
split_algo="EventAwareLumiBased",
type="Processing")
jobFactory = splitter(package="WMCore.DataStructs",
subscription=testSubscription)
# Use a lumi-mask = {1: [[10,14]], 2: [[20,21]], 4: [[40,41]]}
jobGroups = jobFactory(halt_job_on_file_boundaries=False,
splitOnRun=False,
events_per_job=850,
runs=['1', '2', '4'],
lumis=['10,14', '20,21', '40,41'],
performance=self.performanceParams)
self.assertEqual(len(jobGroups), 1, "There should be only one job group")
jobs = jobGroups[0].jobs
self.assertEqual(len(jobs), 2, "Two jobs must be in the jobgroup")
self.assertEqual(jobs[0]['mask'].getRunAndLumis(), {1: [[10, 14]], 2: [[20, 21]], 4: [[40, 40]]})
self.assertEqual(jobs[1]['mask'].getRunAndLumis(), {4: [[41, 41]]})
def execute(self, *args, **kwargs):
wmwork = Workflow(name=kwargs['task']['tm_taskname'])
wmsubs = Subscription(fileset=args[0], workflow=wmwork,
split_algo=kwargs['task']['tm_split_algo'],
type=self.jobtypeMapper[kwargs['task']['tm_job_type']])
splitter = SplitterFactory()
jobfactory = splitter(subscription=wmsubs)
splitparam = kwargs['task']['tm_split_args']
splitparam['algorithm'] = kwargs['task']['tm_split_algo']
factory = jobfactory(**splitparam)
if len(factory) == 0:
# Understanding that no jobs could be created given the splitting arguments
# with the given input dataset information: NO IDEA WHY.
# NB: we assume that split can't happen, then task is failed
msg = "Splitting %s on %s with %s does not generate any job" %(kwargs['task']['tm_taskname'],
kwargs['task']['tm_input_dataset'],
kwargs['task']['tm_split_algo'])
self.logger.error("Setting %s as failed" % str(kwargs['task']['tm_taskname']))
configreq = {'workflow': kwargs['task']['tm_taskname'],
'status': "FAILED",
'subresource': 'failure',
'failure': b64encode(msg)}
self.server.post(self.resturl, data = urllib.urlencode(configreq))
raise StopHandler(msg)
return Result(task=kwargs['task'], result=factory)
def createSubscription(self,
nFiles,
lumisPerFile,
twoSites=False,
nEventsPerFile=100):
"""
_createSubscription_
Create a subscription for testing
"""
baseName = makeUUID()
testFileset = Fileset(name=baseName)
for i in range(nFiles):
newFile = self.createFile('%s_%i' % (baseName, i), nEventsPerFile,
i, lumisPerFile, 'blenheim')
testFileset.addFile(newFile)
if twoSites:
for i in range(nFiles):
newFile = self.createFile('%s_%i_2' % (baseName, i),
nEventsPerFile, i, lumisPerFile,
'malpaquet')
testFileset.addFile(newFile)
testSubscription = Subscription(fileset=testFileset,
workflow=self.testWorkflow,
split_algo="EventAwareLumiBased",
type="Processing")
return testSubscription
def testF_HardLimitSplittingOnly(self):
"""
_testF_HardLimitSplittingOnly_
Checks that we can split a set of files where every file has a single
lumi too big to fit in a runnable job
"""
splitter = SplitterFactory()
# Create 3 single-big-lumi files
testFileset = Fileset(name="FilesetA")
testFileA = self.createFile("/this/is/file1", 1000, 0, 1,
"somese.cern.ch")
testFileB = self.createFile("/this/is/file2", 1000, 1, 1,
"somese.cern.ch")
testFileC = self.createFile("/this/is/file3", 1000, 2, 1,
"somese.cern.ch")
testFileset.addFile(testFileA)
testFileset.addFile(testFileB)
testFileset.addFile(testFileC)
testSubscription = Subscription(fileset=testFileset,
workflow=self.testWorkflow,
split_algo="EventAwareLumiBased",
type="Processing")
jobFactory = splitter(package="WMCore.DataStructs",
subscription=testSubscription)
# Settings are to split on job boundaries, to fail sing lumis with more than 800 events
# and to put 550 events per job
jobGroups = jobFactory(halt_job_on_file_boundaries=True,
splitOnRun=True,
events_per_job=550,
job_time_limit=9600,
performance=self.performanceParams)
self.assertEqual(len(jobGroups), 1,
"There should be only one job group")
jobs = jobGroups[0].jobs
self.assertEqual(len(jobs), 3, "Three jobs must be in the jobgroup")
for i in range(0, 3):
self.assertTrue(jobs[i]['failedOnCreation'],
"It should have been marked as failed")
runNums = jobs[i]['mask']['runAndLumis'].keys()
self.assertEqual(len(runNums), 1)
lumiNums = jobs[i]['mask']['runAndLumis'].values()[0]
self.assertEqual(len(lumiNums), 1)
finalLumi = []
for pair in lumiNums:
finalLumi.extend(range(pair[0], pair[1] + 1))
self.assertEqual(len(finalLumi), 1)
self.assertEqual(
jobs[i]['failedReason'],
"File /this/is/file%d has a single lumi %s, in run %s with too many events 1000 and it woud take 12000 sec to run"
% (i + 1, finalLumi[0], runNums[0]))
return
def setUp(self):
"""
_setUp_
Create two subscriptions: One that contains a single file and one that
contains multiple files.
"""
self.multipleFileFileset = Fileset(name="TestFileset1")
for i in range(10):
newFile = File(makeUUID(), size=1000, events=100)
newFile.setLocation('blenheim')
newFile.setLocation('malpaquet')
lumis = []
for lumi in range(20):
lumis.append((i * 100) + lumi)
newFile.addRun(Run(i, *lumis))
self.multipleFileFileset.addFile(newFile)
self.singleFileFileset = Fileset(name="TestFileset2")
newFile = File("/some/file/name", size=1000, events=100)
newFile.setLocation('blenheim')
lumis = list(range(50, 60)) + list(range(70, 80))
newFile.addRun(Run(13, *lumis))
self.singleFileFileset.addFile(newFile)
testWorkflow = Workflow()
self.multipleFileSubscription = Subscription(
fileset=self.multipleFileFileset,
workflow=testWorkflow,
split_algo="FileBased",
type="Processing")
self.singleFileSubscription = Subscription(
fileset=self.singleFileFileset,
workflow=testWorkflow,
split_algo="FileBased",
type="Processing")
#self.multipleFileSubscription.create()
#self.singleFileSubscription.create()
self.performanceParams = {
'timePerEvent': 12,
'memoryRequirement': 2300,
'sizePerEvent': 400
}
return
def processDataset(self):
"""
_processDataset_
Import the Dataset contents and create a set of jobs from it
"""
# //
# // Now create the job definitions
#//
logging.debug("SplitSize = %s" % self.splitSize)
logging.debug("AllowedSites = %s" % self.allowedSites)
thefiles = Fileset(name='FilesToSplit')
reader = DBSReader(self.dbsUrl)
fileList = reader.dbs.listFiles(
analysisDataset=self.inputDataset(),
retriveList=['retrive_block', 'retrive_run'])
blocks = {}
for f in fileList:
block = f['Block']['Name']
if not blocks.has_key(block):
blocks[block] = reader.listFileBlockLocation(block)
f['Block']['StorageElementList'].extend(blocks[block])
wmbsFile = File(f['LogicalFileName'])
[wmbsFile['locations'].add(x) for x in blocks[block]]
wmbsFile['block'] = block
thefiles.addFile(wmbsFile)
work = Workflow()
subs = Subscription(fileset=thefiles,
workflow=work,
split_algo='FileBased',
type="Processing")
splitter = SplitterFactory()
jobfactory = splitter(subs)
jobs = jobfactory(files_per_job=self.splitSize)
jobDefs = []
for job in jobs.jobs:
#job.mask.setMaxAndSkipEvents(-1, 0)
jobDef = JobDefinition()
jobDef['LFNS'].extend(job.listLFNs())
jobDef['SkipEvents'] = 0
jobDef['MaxEvents'] = -1
[
jobDef['SENames'].extend(list(x['locations']))
for x in job.listFiles()
]
jobDefs.append(jobDef)
return jobDefs
def execute(self, *args, **kwargs):
wmwork = Workflow(name=kwargs['task']['tm_taskname'])
wmsubs = Subscription(
fileset=args[0],
workflow=wmwork,
split_algo=kwargs['task']['tm_split_algo'],
type=self.jobtypeMapper[kwargs['task']['tm_job_type']])
splitter = SplitterFactory()
jobfactory = splitter(subscription=wmsubs)
splitparam = kwargs['task']['tm_split_args']
splitparam['algorithm'] = kwargs['task']['tm_split_algo']
if kwargs['task']['tm_job_type'] == 'Analysis':
if kwargs['task']['tm_split_algo'] == 'FileBased':
splitparam['total_files'] = kwargs['task']['tm_totalunits']
elif kwargs['task']['tm_split_algo'] == 'LumiBased':
splitparam['total_lumis'] = kwargs['task']['tm_totalunits']
elif kwargs['task']['tm_job_type'] == 'PrivateMC':
if 'tm_events_per_lumi' in kwargs['task'] and kwargs['task'][
'tm_events_per_lumi']:
splitparam['events_per_lumi'] = kwargs['task'][
'tm_events_per_lumi']
if 'tm_generator' in kwargs['task'] and kwargs['task'][
'tm_generator'] == 'lhe':
splitparam['lheInputFiles'] = True
splitparam['applyLumiCorrection'] = True
factory = jobfactory(**splitparam)
if len(factory) == 0:
raise TaskWorkerException("The CRAB3 server backend could not submit any job to the Grid scheduler:\n"+\
"splitting task %s on dataset %s with %s method does not generate any job")
#printing duplicated lumis if any
lumiChecker = getattr(jobfactory, 'lumiChecker', None)
if lumiChecker and lumiChecker.splitLumiFiles:
self.logger.warning(
"The input dataset contains the following duplicated lumis %s"
% lumiChecker.splitLumiFiles.keys())
try:
configreq = {
'subresource':
'addwarning',
'workflow':
kwargs['task']['tm_taskname'],
'warning':
b64encode(
'The CRAB3 server backend detected lumis split across files in the input dataset.'
' Will apply the necessary corrections in the splitting algorithms'
)
}
self.server.post(self.restURInoAPI + '/task',
data=urllib.urlencode(configreq))
except Exception, e:
self.logger.error(e.headers)
self.logger.warning(
"Cannot add warning to REST after finding duplicates")
def setUp(self):
"""
_setUp_
Create two subscriptions: One that contains a single file and one that
contains multiple files.
"""
self.multipleFileFileset = Fileset(name="TestFileset1")
for i in range(10):
newFile = File(makeUUID(), size=1000, events=100)
newFile.setLocation('se01')
self.multipleFileFileset.addFile(newFile)
self.singleFileFileset = Fileset(name="TestFileset2")
newFile = File("/some/file/name", size=1000, events=100)
newFile.setLocation('se02')
self.singleFileFileset.addFile(newFile)
self.emptyFileFileset = Fileset(name="TestFileset3")
newFile = File("/some/file/name", size=1000, events=0)
newFile.setdefault('se03')
self.emptyFileFileset.addFile(newFile)
testWorkflow = Workflow()
self.multipleFileSubscription = Subscription(
fileset=self.multipleFileFileset,
workflow=testWorkflow,
split_algo="EventBased",
type="Processing")
self.singleFileSubscription = Subscription(
fileset=self.singleFileFileset,
workflow=testWorkflow,
split_algo="EventBased",
type="Processing")
self.emptyFileSubscription = Subscription(
fileset=self.emptyFileFileset,
workflow=testWorkflow,
split_algo="EventBased",
type="Processing")
return
def testF_HardLimitSplittingOnly(self):
"""
_testF_HardLimitSplittingOnly_
Checks that we can split a set of files where every file has a single
lumi too big to fit in a runnable job
"""
splitter = SplitterFactory()
#Create 3 single-big-lumi files
testFileset = Fileset(name="FilesetA")
testFileA = self.createFile("/this/is/file1", 1000, 0, 1,
"somese.cern.ch")
testFileB = self.createFile("/this/is/file2", 1000, 1, 1,
"somese.cern.ch")
testFileC = self.createFile("/this/is/file3", 1000, 2, 1,
"somese.cern.ch")
testFileset.addFile(testFileA)
testFileset.addFile(testFileB)
testFileset.addFile(testFileC)
testSubscription = Subscription(fileset=testFileset,
workflow=self.testWorkflow,
split_algo="EventAwareLumiBased",
type="Processing")
jobFactory = splitter(package="WMCore.DataStructs",
subscription=testSubscription)
#Settings are to split on job boundaries, to fail sing lumis with more than 800 events
#and to put 550 events per job
jobGroups = jobFactory(halt_job_on_file_boundaries=True,
splitOnRun=True,
events_per_job=550,
max_events_per_lumi=800,
performance=self.performanceParams)
self.assertEqual(len(jobGroups), 1,
"There should be only one job group")
jobs = jobGroups[0].jobs
self.assertEqual(len(jobs), 3, "Three jobs must be in the jobgroup")
for i in range(1, 4):
self.assertTrue(
jobs[i - 1]['failedOnCreation'],
"The job processing the second file should me marked for failure"
)
self.assertEqual(
jobs[i - 1]['failedReason'],
"File /this/is/file%d has too many events (1000) in 1 lumi(s)"
% i, "The reason for the failure is not accurate")
return
def testHardLimitSplitting(self):
"""
_testHardLimitSplitting_
Test that we can specify a event limit, the
algorithm shall take single lumi files with more events than the limit
and mark them for failure
"""
splitter = SplitterFactory()
# Create 3 files, the one in the middle is a "bad" file
testFileset = Fileset(name="FilesetA")
testFileA = self.createFile("/this/is/file1", 1000, 0, 5, "blenheim")
testFileB = self.createFile("/this/is/file2", 1000, 1, 1, "blenheim")
testFileC = self.createFile("/this/is/file3", 1000, 2, 2, "blenheim")
testFileset.addFile(testFileA)
testFileset.addFile(testFileB)
testFileset.addFile(testFileC)
testSubscription = Subscription(fileset=testFileset,
workflow=self.testWorkflow,
split_algo="EventAwareLumiByWork",
type="Processing")
jobFactory = splitter(package="WMCore.DataStructs",
subscription=testSubscription)
# Settings are to split on job boundaries, to fail single lumis with more than 800 events
# and to put 550 events per job
jobGroups = jobFactory(halt_job_on_file_boundaries=True,
splitOnRun=True,
events_per_job=550,
job_time_limit=9600,
performance=self.performanceParams)
self.assertEqual(len(jobGroups), 1)
jobs = jobGroups[0].jobs
self.assertEqual(len(jobs), 5)
# One job should be failed, the rest should be fine
for jobNum in (0, 1, 3, 4):
self.assertFalse(jobs[jobNum].get('failedOnCreation'))
self.assertTrue(jobs[2]['failedOnCreation'])
self.assertEqual(
jobs[2]['failedReason'],
'File /this/is/file2 has a single lumi 1, in run 1 with too many events 1000 and it woud take 12000 sec to run'
)
return
def generateFakeMCFile(self, numEvents = 100, firstEvent = 1,
lastEvent = 100, firstLumi = 1, lastLumi = 10):
#MC comes with only one MCFakeFile
singleMCFileset = Fileset(name = "MCTestFileset")
newFile = File("MCFakeFileTest", size = 1000, events = numEvents)
newFile.setLocation('se01')
newFile.addRun(Run(1, *range(firstLumi, lastLumi + 1)))
newFile["first_event"] = firstEvent
newFile["last_event"] = lastEvent
testWorkflow = Workflow()
singleMCFileset.addFile(newFile)
singleMCFileSubscription = Subscription(fileset = singleMCFileset,
workflow = testWorkflow,
split_algo = "EventBased",
type = "Production")
return singleMCFileSubscription
def testCreate(self):
"""
_testCreate_
Test the JobGroup constructor and passing different job containers
into it.
"""
testSubscription = Subscription()
testJobGroupA = JobGroup(subscription = testSubscription)
assert testJobGroupA.subscription == testSubscription, \
"ERROR: Failed to pass subscription in constructor"
assert len(testJobGroupA.jobs) == 0 and len(testJobGroupA.newjobs) == 0, \
"ERROR: JobGroup not empty on creation"
testJobA = Job()
testJobB = Job()
testJobGroupB = JobGroup(jobs = [testJobA, testJobB])
assert testJobGroupB.jobs == [], \
"ERROR: Jobs committed to jobgroup too soon."
jobGroupJobs = testJobGroupB.newjobs
goldenJobs = [testJobA, testJobB]
for job in jobGroupJobs:
assert job in goldenJobs, \
"ERROR: Extra job in job group"
goldenJobs.remove(job)
assert len(goldenJobs) == 0, \
"ERROR: Job missing from job group"
testJobGroupC = JobGroup(jobs = testJobA)
assert testJobGroupC.jobs == [], \
"ERROR: Jobs committed to jobgroup too soon."
jobGroupJobs = testJobGroupC.newjobs
assert len(jobGroupJobs) == 1, \
"ERROR: Wrong number of jobs in jobgroup."
assert testJobA in jobGroupJobs, \
"ERROR: Wrong job in jobgroup."
return
def testE_HardLimitSpltting(self):
"""
_testE_HardLimitSplitting_
Test that we can specify a event limit, the
algorithm shall take single lumi files with more events than the limit
and mark them for failure
"""
splitter = SplitterFactory()
#Create 3 files, the one in the middle is a "bad" file
testFileset = Fileset(name="FilesetA")
testFileA = self.createFile("/this/is/file1", 1000, 0, 5, "blenheim")
testFileB = self.createFile("/this/is/file2", 1000, 1, 1, "blenheim")
testFileC = self.createFile("/this/is/file3", 1000, 2, 2, "blenheim")
testFileset.addFile(testFileA)
testFileset.addFile(testFileB)
testFileset.addFile(testFileC)
testSubscription = Subscription(fileset=testFileset,
workflow=self.testWorkflow,
split_algo="EventAwareLumiBased",
type="Processing")
jobFactory = splitter(package="WMCore.DataStructs",
subscription=testSubscription)
#Settings are to split on job boundaries, to fail sing lumis with more than 800 events
#and to put 550 events per job
jobGroups = jobFactory(halt_job_on_file_boundaries=True,
splitOnRun=True,
events_per_job=550,
max_events_per_lumi=800,
performance=self.performanceParams)
self.assertEqual(len(jobGroups), 1,
"There should be only one job group")
jobs = jobGroups[0].jobs
self.assertEqual(len(jobs), 6, "Six jobs must be in the jobgroup")
self.assertTrue(
jobs[3]['failedOnCreation'],
"The job processing the second file should me marked for failure")
self.assertEqual(
jobs[3]['failedReason'],
"File /this/is/file2 has too many events (1000) in 1 lumi(s)",
"The reason for the failure is not accurate")
return
def setUp(self):
"""
Initial Setup for Subscription Testcase
Set a dummy Subscription with a fileset composed of one file inside it
and a dummy workflow using the default constructor of the Workflow class
"""
self.dummyFile = File('/tmp/dummyfile', 9999, 0, 0, 0)
self.dummySet = set()
self.dummySet.add(self.dummyFile)
self.dummyFileSet = Fileset(name='SubscriptionTestFileset',
files=self.dummySet)
self.dummyWorkFlow = Workflow()
self.dummySubscription = Subscription(fileset=self.dummyFileSet,
workflow=self.dummyWorkFlow)
return
def testI_DisableHardLimitSplitting(self):
"""
_testI_DisableHardLimitSplitting_
Test that we can bypass the job time limit when allowCreationFailure is
set to False. The algorithm shall take single lumi files with time per
lumi greater than the job time limit but not mark them for failure
"""
splitter = SplitterFactory()
# Create 3 files, the one in the middle is a "bad" file
testFileset = Fileset(name="FilesetA")
testFileA = self.createFile("/this/is/file1", 1000, 0, 5, "blenheim")
testFileB = self.createFile("/this/is/file2", 1000, 1, 1, "blenheim")
testFileC = self.createFile("/this/is/file3", 1000, 2, 2, "blenheim")
testFileset.addFile(testFileA)
testFileset.addFile(testFileB)
testFileset.addFile(testFileC)
testSubscription = Subscription(fileset=testFileset,
workflow=self.testWorkflow,
split_algo="EventAwareLumiBased",
type="Processing")
jobFactory = splitter(package="WMCore.DataStructs",
subscription=testSubscription)
# Settings are to split on job boundaries, to fail sing lumis with more than 800 events
# and to put 550 events per job
jobGroups = jobFactory(halt_job_on_file_boundaries=True,
splitOnRun=True,
events_per_job=550,
job_time_limit=9600,
allowCreationFailure=False,
performance=self.performanceParams)
self.assertEqual(len(jobGroups), 1,
"There should be only one job group")
jobs = jobGroups[0].jobs
self.assertEqual(len(jobs), 6, "Six jobs must be in the jobgroup")
failedJobs = [
job for job in jobs if job.get('failedOnCreation', False)
]
self.assertEqual(len(failedJobs), 0, "There should be no failed jobs")
return
def createSubscriptions(self, task, fileset):
"""
Create a subscription based on a task
"""
taskType = task.taskType()
work = task.makeWorkflow()
sub = Subscription(fileset=fileset,
workflow=work,
split_algo="FileBased",
type=taskType)
package = self.createWMBSJobs(subscription=sub, task=task)
packName = os.path.join(self.testDir, 'packages',
'%sJobPackage.pkl' % (task.name()))
package.save(packName)
return sub
def testMetaData(self):
"""
_testMetaData_
Make sure that the workflow name, task, owner and white and black lists
make it into each job object.
"""
testWorkflow = Workflow(spec="spec.pkl",
owner="Steve",
name="TestWorkflow",
task="TestTask")
testFileset = Fileset(name="TestFileset")
testFile = File(lfn="someLFN")
testFileset.addFile(testFile)
testFileset.commit()
testSubscription = Subscription(fileset=testFileset,
workflow=testWorkflow,
split_algo="FileBased")
myJobFactory = JobFactory(subscription=testSubscription)
testJobGroups = myJobFactory(siteWhitelist=["site1"],
siteBlacklist=["site2"])
self.assertTrue(len(testJobGroups) > 0)
for testJobGroup in testJobGroups:
self.assertTrue(len(testJobGroup.jobs) > 0)
for job in testJobGroup.jobs:
self.assertEqual(job["task"], "TestTask",
"Error: Task is wrong.")
self.assertEqual(job["workflow"], "TestWorkflow",
"Error: Workflow is wrong.")
self.assertEqual(job["owner"], "Steve",
"Error: Owner is wrong.")
self.assertEqual(job["siteWhitelist"], ["site1"],
"Error: Site white list is wrong.")
self.assertEqual(job["siteBlacklist"], ["site2"],
"Error: Site black list is wrong.")
return
def oneHundredFiles(self,
splittingAlgo="EventBased",
jobType="Processing"):
"""
_oneHundredFiles_
Generate a WMBS data stack representing 100 files for job splitter
testing
"""
fileset1 = Fileset(name='EventBasedFiles1')
for i in range(0, 100):
f = File(
"/store/MultipleFileSplit%s.root" % i, # lfn
1000, # size
100, # events
10 + i, # run
12312 # lumi
)
f['locations'].add("BULLSHIT")
fileset1.addFile(f)
work = Workflow()
subscription1 = Subscription(fileset=fileset1,
workflow=work,
split_algo=splittingAlgo,
type=jobType)
splitter = SplitterFactory()
jobfactory = splitter(subscription1)
jobs = jobfactory(events_per_job=100)
#for jobGroup in jobs:
# yield jobGroup
self.manager.addGenerator("RandomSeeder", **self.seedlistForRandom)
self.manager.addGenerator("RunAndLumiSeeder")
return jobs
def createSubscription(self, nFiles, lumisPerFile, twoSites=False):
"""
_createSubscription_
Create a subscription for testing
"""
baseName = makeUUID()
testFileset = Fileset(name=baseName)
for i in range(nFiles):
newFile = File(lfn='%s_%i' % (baseName, i), size=1000, events=100)
lumis = []
for lumi in range(lumisPerFile):
lumis.append((i * 100) + lumi)
newFile.addRun(Run(i, *lumis))
newFile.setLocation('blenheim')
testFileset.addFile(newFile)
if twoSites:
for i in range(nFiles):
newFile = File(lfn='%s_%i_2' % (baseName, i),
size=1000,
events=100)
lumis = []
for lumi in range(lumisPerFile):
lumis.append(5 + 10 * (i * 100) +
lumi) #lumis should be different
newFile.addRun(Run(i, *lumis))
newFile.setLocation('malpaquet')
testFileset.addFile(newFile)
testSubscription = Subscription(fileset=testFileset,
workflow=self.testWorkflow,
split_algo="LumiBased",
type="Processing")
return testSubscription
def testRunWhiteList(self):
"""
_testRunWhiteList_
Test that we can use a run white list to filter good runs/lumis.
"""
splitter = SplitterFactory()
# Create 3 files with 100 events per lumi:
# - file1 with 1 run of 8 lumis
# - file2 with 2 runs of 2 lumis each
# - file3 with 1 run of 5 lumis
fileA = File(lfn="/this/is/file1", size=1000, events=800)
fileB = File(lfn="/this/is/file2", size=1000, events=400)
fileC = File(lfn="/this/is/file3", size=1000, events=500)
lumiListA = []
for lumi in range(8):
lumiListA.append(10 + lumi)
fileA.addRun(Run(1, *lumiListA))
fileA.setLocation("somese.cern.ch")
lumiListB1 = []
lumiListB2 = []
for lumi in range(2):
lumiListB1.append(20 + lumi)
lumiListB2.append(30 + lumi)
fileB.addRun(Run(2, *lumiListB1))
fileB.addRun(Run(3, *lumiListB2))
fileB.setLocation("somese.cern.ch")
lumiListC = []
for lumi in range(5):
lumiListC.append(40 + lumi)
fileC.addRun(Run(4, *lumiListC))
fileC.setLocation("somese.cern.ch")
testFileset = Fileset(name='Fileset')
testFileset.addFile(fileA)
testFileset.addFile(fileB)
testFileset.addFile(fileC)
testSubscription = Subscription(fileset=testFileset,
workflow=self.testWorkflow,
split_algo="EventAwareLumiByWork",
type="Processing")
jobFactory = splitter(package="WMCore.DataStructs",
subscription=testSubscription)
# Split with no breaks
jobGroups = jobFactory(halt_job_on_file_boundaries=False,
splitOnRun=False,
events_per_job=725,
runWhitelist=[1, 4],
performance=self.performanceParams)
self.assertEqual(len(jobGroups), 1)
jobs = jobGroups[0].jobs
self.assertEqual(len(jobs), 2)
for job in jobs:
for run in job['mask'].getRunAndLumis().keys():
self.assertIn(run, [1, 4])
# Re-split with a break on runs
jobGroups = jobFactory(halt_job_on_file_boundaries=False,
splitOnRun=True,
events_per_job=595,
runWhitelist=[1, 3, 4],
performance=self.performanceParams)
self.assertEqual(len(jobGroups), 1)
jobs = jobGroups[0].jobs
self.assertEqual(len(jobs), 4)
self.enforceLimits(jobs=jobs, runsPerJob=1)
for job in jobs:
for run in job['mask'].getRunAndLumis().keys():
self.assertIn(run, [1, 3, 4])
# Re-split with a break on files
jobGroups = jobFactory(halt_job_on_file_boundaries=True,
splitOnRun=False,
events_per_job=595,
runWhitelist=[1, 2, 3],
performance=self.performanceParams)
self.assertEqual(len(jobGroups), 1)
jobs = jobGroups[0].jobs
self.assertEqual(len(jobs), 3)
self.enforceLimits(jobs=jobs, filesPerJob=1)
for job in jobs:
for run in job['mask'].getRunAndLumis().keys():
self.assertIn(run, [1, 2, 3])
def testD_NoFileSplitNoHardLimit(self):
"""
_testD_NoFileSplitNoHardLimit_
In this case we don't split on file boundaries, check different combination of files
make sure we make the most of the splitting, e.g. include many zero event files in
a single job.
"""
splitter = SplitterFactory()
#Create 100 files with 7 lumi per file and 0 events per lumi on average.
testSubscription = self.createSubscription(nFiles=100,
lumisPerFile=7,
twoSites=False,
nEventsPerFile=0)
jobFactory = splitter(package="WMCore.DataStructs",
subscription=testSubscription)
#First test, the optimal settings are 360 events per job
#As we have files with 0 events per lumi, this will configure the splitting to
#a single job containing all files
jobGroups = jobFactory(halt_job_on_file_boundaries=False,
splitOnRun=False,
events_per_job=360)
self.assertEqual(len(jobGroups), 1,
"There should be only one job group")
jobs = jobGroups[0].jobs
self.assertEqual(len(jobs), 1, "There should be 1 job")
self.assertEqual(len(jobs[0]['input_files']), 100,
"All 100 files must be in the job")
#Create 7 files, each one with different lumi/event distributions
testFileset = Fileset(name="FilesetA")
testFileA = self.createFile("/this/is/file1", 250, 0, 5, "blenheim")
testFileB = self.createFile("/this/is/file2", 600, 1, 1, "blenheim")
testFileC = self.createFile("/this/is/file3", 1200, 2, 2, "blenheim")
testFileD = self.createFile("/this/is/file4", 100, 3, 1, "blenheim")
testFileE = self.createFile("/this/is/file5", 30, 4, 1, "blenheim")
testFileF = self.createFile("/this/is/file6", 10, 5, 1, "blenheim")
testFileG = self.createFile("/this/is/file7", 151, 6, 3, "blenheim")
testFileset.addFile(testFileA)
testFileset.addFile(testFileB)
testFileset.addFile(testFileC)
testFileset.addFile(testFileD)
testFileset.addFile(testFileE)
testFileset.addFile(testFileF)
testFileset.addFile(testFileG)
testSubscription = Subscription(fileset=testFileset,
workflow=self.testWorkflow,
split_algo="EventAwareLumiBased",
type="Processing")
jobFactory = splitter(package="WMCore.DataStructs",
subscription=testSubscription)
#Optimal settings are: jobs with 150 events per job
#This means, the first file must be splitted in 3 lumis per job which would leave room
#for another lumi in the second job, but the second file has a lumi too big for that
#The 3rd job only contains the second file, the fourth and fifth job split the third file
jobGroups = jobFactory(halt_job_on_file_boundaries=False,
splitOnRun=False,
events_per_job=150)
self.assertEqual(len(jobGroups), 1,
"There should be only one job group")
jobs = jobGroups[0].jobs
self.assertEqual(len(jobs), 8, "Eight jobs must be in the jobgroup")
self.assertEqual(jobs[0]["mask"].getRunAndLumis(), {0L: [[0L, 2L]]},
"Wrong mask for the first job")
self.assertEqual(jobs[1]["mask"].getRunAndLumis(), {0L: [[3L, 4L]]},
"Wrong mask for the second job")
self.assertEqual(jobs[2]["mask"].getRunAndLumis(), {1L: [[1L, 1L]]},
"Wrong mask for the third job")
self.assertEqual(jobs[3]["mask"].getRunAndLumis(), {2L: [[4L, 4L]]},
"Wrong mask for the fourth job")
self.assertEqual(jobs[4]["mask"].getRunAndLumis(), {2L: [[5L, 5L]]},
"Wrong mask for the fifth job")
self.assertEqual(jobs[5]["mask"].getRunAndLumis(), {
3L: [[3L, 3L]],
4L: [[4L, 4L]],
5L: [[5L, 5L]]
}, "Wrong mask for the sixth job")
self.assertEqual(jobs[6]["mask"].getRunAndLumis(), {6L: [[18L, 19L]]},
"Wrong mask for the seventh job")
self.assertEqual(jobs[7]["mask"].getRunAndLumis(), {6L: [[20L, 20L]]},
"Wrong mask for the seventh job")
#Test interactions of this algorithm with splitOnRun = True
#Make 2 files, one with 3 runs and a second one with the last run of the first
fileA = File(lfn="/this/is/file1", size=1000, events=2400)
lumiListA = []
lumiListB = []
lumiListC = []
for lumi in range(8):
lumiListA.append(1 + lumi)
lumiListB.append(1 + lumi)
lumiListC.append(1 + lumi)
fileA.addRun(Run(1, *lumiListA))
fileA.addRun(Run(2, *lumiListA))
fileA.addRun(Run(3, *lumiListA))
fileA.setLocation("malpaquet")
fileB = self.createFile('/this/is/file2', 200, 3, 5, "malpaquet")
testFileset = Fileset(name='FilesetB')
testFileset.addFile(fileA)
testFileset.addFile(fileB)
testSubscription = Subscription(fileset=testFileset,
workflow=self.testWorkflow,
split_algo="EventAwareLumiBased",
type="Processing")
jobFactory = splitter(package="WMCore.DataStructs",
subscription=testSubscription)
#The settings for this splitting are 700 events per job
jobGroups = jobFactory(splitOnRun=True,
halt_job_on_file_boundaries=False,
events_per_job=700)
self.assertEqual(len(jobGroups), 1,
"There should be only one job group")
jobs = jobGroups[0].jobs
self.assertEqual(len(jobs), 6, "Six jobs must be in the jobgroup")
def execute(self, *args, **kwargs):
wmwork = Workflow(name=kwargs['task']['tm_taskname'])
wmsubs = Subscription(
fileset=args[0],
workflow=wmwork,
split_algo=kwargs['task']['tm_split_algo'],
type=self.jobtypeMapper[kwargs['task']['tm_job_type']])
splitter = SplitterFactory()
jobfactory = splitter(subscription=wmsubs)
splitparam = kwargs['task']['tm_split_args']
splitparam['algorithm'] = kwargs['task']['tm_split_algo']
if kwargs['task']['tm_job_type'] == 'Analysis':
if kwargs['task']['tm_split_algo'] == 'FileBased':
splitparam['total_files'] = kwargs['task']['tm_totalunits']
elif kwargs['task']['tm_split_algo'] == 'LumiBased':
splitparam['total_lumis'] = kwargs['task']['tm_totalunits']
elif kwargs['task']['tm_split_algo'] == 'EventAwareLumiBased':
splitparam['total_events'] = kwargs['task']['tm_totalunits']
elif kwargs['task']['tm_job_type'] == 'PrivateMC':
if 'tm_events_per_lumi' in kwargs['task'] and kwargs['task'][
'tm_events_per_lumi']:
splitparam['events_per_lumi'] = kwargs['task'][
'tm_events_per_lumi']
if 'tm_generator' in kwargs['task'] and kwargs['task'][
'tm_generator'] == 'lhe':
splitparam['lheInputFiles'] = True
splitparam['applyLumiCorrection'] = True
factory = jobfactory(**splitparam)
numJobs = sum([len(jobgroup.getJobs()) for jobgroup in factory])
maxJobs = getattr(self.config.TaskWorker, 'maxJobsPerTask', 10000)
if numJobs == 0:
msg = "The CRAB3 server backend could not submit any job to the Grid scheduler:"
msg += " Splitting task %s" % (kwargs['task']['tm_taskname'])
if kwargs['task']['tm_input_dataset']:
msg += " on dataset %s" % (kwargs['task']['tm_input_dataset'])
msg += " with %s method does not generate any job" % (
kwargs['task']['tm_split_algo'])
raise TaskWorkerException(msg)
elif numJobs > maxJobs:
raise TaskWorkerException(
"The splitting on your task generated %s jobs. The maximum number of jobs in each task is %s"
% (numJobs, maxJobs))
#printing duplicated lumis if any
lumiChecker = getattr(jobfactory, 'lumiChecker', None)
if lumiChecker and lumiChecker.splitLumiFiles:
self.logger.warning(
"The input dataset contains the following duplicated lumis %s"
% lumiChecker.splitLumiFiles.keys())
#TODO use self.uploadWarning
try:
userServer = HTTPRequests(self.server['host'],
kwargs['task']['user_proxy'],
kwargs['task']['user_proxy'])
configreq = {
'subresource':
'addwarning',
'workflow':
kwargs['task']['tm_taskname'],
'warning':
b64encode(
'The CRAB3 server backend detected lumis split across files in the input dataset.'
' Will apply the necessary corrections in the splitting algorithms. You can ignore this message.'
)
}
userServer.post(self.restURInoAPI + '/task',
data=urllib.urlencode(configreq))
except HTTPException as hte:
self.logger.error(hte.headers)
self.logger.warning(
"Cannot add warning to REST after finding duplicates")
return Result(task=kwargs['task'], result=factory)
def testNoFileSplitNoHardLimit(self):
"""
_testNoFileSplitNoHardLimit_
In this case we don't split on file boundaries, check different combination of files
make sure we make the most of the splitting, e.g. include many zero event files in
a single job.
"""
splitter = SplitterFactory()
# Create 100 files with 7 lumi per file and 0 events per lumi on average.
testSubscription = self.createSubscription(nFiles=100,
lumisPerFile=7,
twoSites=False,
nEventsPerFile=0)
jobFactory = splitter(package="WMCore.DataStructs",
subscription=testSubscription)
# First test, the optimal settings are 360 events per job. As we have files with 0 events per lumi, this will
# configure the splitting to a single job containing all files
jobGroups = jobFactory(halt_job_on_file_boundaries=False,
splitOnRun=False,
events_per_job=360,
performance=self.performanceParams)
# One job in one job group with 100 files
self.assertEqual(len(jobGroups), 1)
jobs = jobGroups[0].jobs
self.assertEqual(len(jobs), 1)
self.assertEqual(len(jobs[0]['input_files']), 100)
# Create 7 files, each one with different lumi/event distributions
testFileset = Fileset(name="FilesetA")
testFileA = self.createFile("/this/is/file1", 250, 0, 5, "blenheim")
testFileB = self.createFile("/this/is/file2", 600, 1, 1, "blenheim")
testFileC = self.createFile("/this/is/file3", 1200, 2, 2, "blenheim")
testFileD = self.createFile("/this/is/file4", 100, 3, 1, "blenheim")
testFileE = self.createFile("/this/is/file5", 30, 4, 1, "blenheim")
testFileF = self.createFile("/this/is/file6", 10, 5, 1, "blenheim")
testFileG = self.createFile("/this/is/file7", 153, 6, 3, "blenheim")
testFileset.addFile(testFileA)
testFileset.addFile(testFileB)
testFileset.addFile(testFileC)
testFileset.addFile(testFileD)
testFileset.addFile(testFileE)
testFileset.addFile(testFileF)
testFileset.addFile(testFileG)
testSubscription = Subscription(fileset=testFileset,
workflow=self.testWorkflow,
split_algo="EventAwareLumiByWork",
type="Processing")
jobFactory = splitter(package="WMCore.DataStructs",
subscription=testSubscription)
# Split the work targeting 150 events per job
jobGroups = jobFactory(halt_job_on_file_boundaries=False,
splitOnRun=False,
events_per_job=150,
performance=self.performanceParams)
self.assertEqual(len(jobGroups), 1)
jobs = jobGroups[0].jobs
self.assertEqual(len(jobs), 7)
# Test interactions of this algorithm with splitOnRun = True
# Make 2 files, one with 3 runs and a second one with the last run of the first
fileA = File(lfn="/this/is/file1", size=1000, events=2400)
lumiListA = []
lumiListB = []
lumiListC = []
for lumi in range(8):
lumiListA.append(1 + lumi)
lumiListB.append(1 + lumi)
lumiListC.append(1 + lumi)
fileA.addRun(Run(1, *lumiListA))
fileA.addRun(Run(2, *lumiListA))
fileA.addRun(Run(3, *lumiListA))
fileA.setLocation("malpaquet")
fileB = self.createFile('/this/is/file2', 200, 3, 5, "malpaquet")
testFileset = Fileset(name='FilesetB')
testFileset.addFile(fileA)
testFileset.addFile(fileB)
testSubscription = Subscription(fileset=testFileset,
workflow=self.testWorkflow,
split_algo="EventAwareLumiByWork",
type="Processing")
jobFactory = splitter(package="WMCore.DataStructs",
subscription=testSubscription)
# The settings for this splitting are 700 events per job
jobGroups = jobFactory(splitOnRun=True,
halt_job_on_file_boundaries=False,
events_per_job=700,
performance=self.performanceParams)
self.assertEqual(len(jobGroups), 1)
jobs = jobGroups[0].jobs
self.assertEqual(len(jobs), 7)
# Make sure each job has one run
for job in jobs:
self.assertEqual(len(job['mask'].getRunAndLumis()), 1)
