Python JobSpec.processingType方法代码示例

# 需要导入模块: from taskbuffer.JobSpec import JobSpec [as 别名]
# 或者: from taskbuffer.JobSpec.JobSpec import processingType [as 别名]

#.........这里部分代码省略.........
        elif job.splitter._name not in ['DQ2JobSplitter', 'ArgSplitter', 'ArgSplitterTask']:
            raise ApplicationConfigurationError('Panda splitter must be DQ2JobSplitter or ArgSplitter')
        
        if job.backend.site == 'AUTO':
            raise ApplicationConfigurationError('site is still AUTO after brokerage!')

#       output dataset
        if job.outputdata:
            if job.outputdata._name != 'DQ2OutputDataset':
                raise ApplicationConfigurationError('Panda backend supports only DQ2OutputDataset')
        else:
            logger.info('Adding missing DQ2OutputDataset')
            job.outputdata = DQ2OutputDataset()

        job.outputdata.datasetname,outlfn = dq2outputdatasetname(job.outputdata.datasetname, job.id, job.outputdata.isGroupDS, job.outputdata.groupname)

        self.outDsLocation = Client.PandaSites[job.backend.site]['ddm']

        try:
            Client.addDataset(job.outputdata.datasetname,False,location=self.outDsLocation)
            logger.info('Output dataset %s registered at %s'%(job.outputdata.datasetname,self.outDsLocation))
            dq2_set_dataset_lifetime(job.outputdata.datasetname, location=self.outDsLocation)
        except exceptions.SystemExit:
            raise BackendError('Panda','Exception in Client.addDataset %s: %s %s'%(job.outputdata.datasetname,sys.exc_info()[0],sys.exc_info()[1]))

        # handle the libds
        if job.backend.libds:
            self.libDataset = job.backend.libds
            self.fileBO = getLibFileSpecFromLibDS(self.libDataset)
            self.library = self.fileBO.lfn
        elif job.backend.bexec:
            self.libDataset = job.outputdata.datasetname+'.lib'
            self.library = '%s.tgz' % self.libDataset
            try:
                Client.addDataset(self.libDataset,False,location=self.outDsLocation)
                dq2_set_dataset_lifetime(self.libDataset, location=self.outDsLocation)
                logger.info('Lib dataset %s registered at %s'%(self.libDataset,self.outDsLocation))
            except exceptions.SystemExit:
                raise BackendError('Panda','Exception in Client.addDataset %s: %s %s'%(self.libDataset,sys.exc_info()[0],sys.exc_info()[1]))

        # collect extOutFiles
        self.extOutFile = []
        for tmpName in job.outputdata.outputdata:
            if tmpName != '':
                self.extOutFile.append(tmpName)

        for tmpName in job.outputsandbox:
            if tmpName != '':
                self.extOutFile.append(tmpName)

        for tmpName in job.backend.extOutFile:
            if tmpName != '':
                self.extOutFile.append(tmpName)

        # create build job
        if job.backend.bexec != '':
            jspec = JobSpec()
            jspec.jobDefinitionID   = job.id
            jspec.jobName           = commands.getoutput('uuidgen 2> /dev/null')
            jspec.transformation    = '%s/buildGen-00-00-01' % Client.baseURLSUB
            if Client.isDQ2free(job.backend.site):
                jspec.destinationDBlock = '%s/%s' % (job.outputdata.datasetname,self.libDataset)
                jspec.destinationSE     = 'local'
            else:
                jspec.destinationDBlock = self.libDataset
                jspec.destinationSE     = job.backend.site
            jspec.prodSourceLabel   = configPanda['prodSourceLabelBuild']
            jspec.processingType    = configPanda['processingType']
            jspec.assignedPriority  = configPanda['assignedPriorityBuild']
            jspec.computingSite     = job.backend.site
            jspec.cloud             = job.backend.requirements.cloud
            jspec.jobParameters     = '-o %s' % (self.library)
            if self.inputsandbox:
                jspec.jobParameters     += ' -i %s' % (self.inputsandbox)
            else:
                raise ApplicationConfigurationError('Executable on Panda with build job defined, but inputsandbox is emtpy !')
            matchURL = re.search('(http.*://[^/]+)/',Client.baseURLCSRVSSL)
            if matchURL:
                jspec.jobParameters += ' --sourceURL %s ' % matchURL.group(1)
            if job.backend.bexec != '':
                jspec.jobParameters += ' --bexec "%s" ' % urllib.quote(job.backend.bexec)
                jspec.jobParameters += ' -r %s ' % '.'
                

            fout = FileSpec()
            fout.lfn  = self.library
            fout.type = 'output'
            fout.dataset = self.libDataset
            fout.destinationDBlock = self.libDataset
            jspec.addFile(fout)

            flog = FileSpec()
            flog.lfn = '%s.log.tgz' % self.libDataset
            flog.type = 'log'
            flog.dataset = self.libDataset
            flog.destinationDBlock = self.libDataset
            jspec.addFile(flog)
            return jspec
        else:
            return None

# 需要导入模块: from taskbuffer.JobSpec import JobSpec [as 别名]
# 或者: from taskbuffer.JobSpec.JobSpec import processingType [as 别名]
 def doBrokerage(self,inputList,vo,prodSourceLabel,workQueue):
     # list with a lock
     inputListWorld = ListWithLock([])
     # variables for submission
     maxBunchTask = 100
     # make logger
     tmpLog = MsgWrapper(logger)
     tmpLog.debug('start doBrokerage')
     # return for failure
     retFatal    = self.SC_FATAL
     retTmpError = self.SC_FAILED
     tmpLog.debug('vo={0} label={1} queue={2} nTasks={3}'.format(vo,prodSourceLabel,
                                                                 workQueue.queue_name,
                                                                 len(inputList)))
     # loop over all tasks
     allRwMap    = {}
     prioMap     = {}
     tt2Map      = {}
     expRWs      = {}
     jobSpecList = []
     for tmpJediTaskID,tmpInputList in inputList:
         for taskSpec,cloudName,inputChunk in tmpInputList:
             # collect tasks for WORLD
             if taskSpec.useWorldCloud():
                 inputListWorld.append((taskSpec,inputChunk))
                 continue
             # make JobSpec to be submitted for TaskAssigner
             jobSpec = JobSpec()
             jobSpec.taskID     = taskSpec.jediTaskID
             jobSpec.jediTaskID = taskSpec.jediTaskID
             # set managed to trigger TA
             jobSpec.prodSourceLabel  = 'managed'
             jobSpec.processingType   = taskSpec.processingType
             jobSpec.workingGroup     = taskSpec.workingGroup
             jobSpec.metadata         = taskSpec.processingType
             jobSpec.assignedPriority = taskSpec.taskPriority
             jobSpec.currentPriority  = taskSpec.currentPriority
             jobSpec.maxDiskCount     = (taskSpec.getOutDiskSize() + taskSpec.getWorkDiskSize()) / 1024 / 1024
             if taskSpec.useWorldCloud():
                 # use destinationSE to trigger task brokerage in WORLD cloud
                 jobSpec.destinationSE = taskSpec.cloud
             prodDBlock = None
             setProdDBlock = False
             for datasetSpec in inputChunk.getDatasets():
                 prodDBlock = datasetSpec.datasetName
                 if datasetSpec.isMaster():
                     jobSpec.prodDBlock = datasetSpec.datasetName
                     setProdDBlock = True
                 for fileSpec in datasetSpec.Files:
                     tmpInFileSpec = fileSpec.convertToJobFileSpec(datasetSpec)
                     jobSpec.addFile(tmpInFileSpec)
             # use secondary dataset name as prodDBlock
             if setProdDBlock == False and prodDBlock != None:
                 jobSpec.prodDBlock = prodDBlock
             # append
             jobSpecList.append(jobSpec)
             prioMap[jobSpec.taskID] = jobSpec.currentPriority
             tt2Map[jobSpec.taskID]  = jobSpec.processingType
             # get RW for a priority
             if not allRwMap.has_key(jobSpec.currentPriority):
                 tmpRW = self.taskBufferIF.calculateRWwithPrio_JEDI(vo,prodSourceLabel,workQueue,
                                                                    jobSpec.currentPriority) 
                 if tmpRW == None:
                     tmpLog.error('failed to calculate RW with prio={0}'.format(jobSpec.currentPriority))
                     return retTmpError
                 allRwMap[jobSpec.currentPriority] = tmpRW
             # get expected RW
             expRW = self.taskBufferIF.calculateTaskRW_JEDI(jobSpec.jediTaskID)
             if expRW == None:
                 tmpLog.error('failed to calculate RW for jediTaskID={0}'.format(jobSpec.jediTaskID))
                 return retTmpError
             expRWs[jobSpec.taskID] = expRW
     # for old clouds
     if jobSpecList != []:
         # get fullRWs
         fullRWs = self.taskBufferIF.calculateRWwithPrio_JEDI(vo,prodSourceLabel,None,None)
         if fullRWs == None:
             tmpLog.error('failed to calculate full RW')
             return retTmpError
         # set metadata
         for jobSpec in jobSpecList:
             rwValues = allRwMap[jobSpec.currentPriority]
             jobSpec.metadata = "%s;%s;%s;%s;%s;%s" % (jobSpec.metadata,
                                                       str(rwValues),str(expRWs),
                                                       str(prioMap),str(fullRWs),
                                                       str(tt2Map))
         tmpLog.debug('run task assigner for {0} tasks'.format(len(jobSpecList)))
         nBunchTask = 0
         while nBunchTask < len(jobSpecList):
             # get a bunch
             jobsBunch = jobSpecList[nBunchTask:nBunchTask+maxBunchTask]
             strIDs = 'jediTaskID='
             for tmpJobSpec in jobsBunch:
                 strIDs += '{0},'.format(tmpJobSpec.taskID)
             strIDs = strIDs[:-1]
             tmpLog.debug(strIDs)
             # increment index
             nBunchTask += maxBunchTask
             # run task brokerge
             stS,outSs = PandaClient.runTaskAssignment(jobsBunch)
#.........这里部分代码省略.........

# 需要导入模块: from taskbuffer.JobSpec import JobSpec [as 别名]
# 或者: from taskbuffer.JobSpec.JobSpec import processingType [as 别名]
    def prepare(self,app,appsubconfig,appmasterconfig,jobmasterconfig):
        '''prepare the subjob specific configuration'''
 
        from pandatools import Client
        from taskbuffer.JobSpec import JobSpec
        from taskbuffer.FileSpec import FileSpec

        job = app._getParent()
        logger.debug('AthenaPandaRTHandler prepare called for %s', job.getFQID('.'))

#       in case of a simple job get the dataset content, otherwise subjobs are filled by the splitter
        if job.inputdata and not job._getRoot().subjobs:

            if not job.inputdata.names:
                
                contents = job.inputdata.get_contents(overlap=False, size=True)

                for ds in contents.keys():

                    for f in contents[ds]:
                        job.inputdata.guids.append( f[0] )
                        job.inputdata.names.append( f[1][0] )
                        job.inputdata.sizes.append( f[1][1] )
                        job.inputdata.checksums.append( f[1][2] )
                        job.inputdata.scopes.append( f[1][3] )


        site = job._getRoot().backend.site
        job.backend.site = site
        job.backend.actualCE = site
        cloud = job._getRoot().backend.requirements.cloud
        job.backend.requirements.cloud = cloud

#       if no outputdata are given
        if not job.outputdata:
            job.outputdata = DQ2OutputDataset()
            job.outputdata.datasetname = job._getRoot().outputdata.datasetname
        #if not job.outputdata.datasetname:
        else:
            job.outputdata.datasetname = job._getRoot().outputdata.datasetname

        if not job.outputdata.datasetname:
            raise ApplicationConfigurationError('DQ2OutputDataset has no datasetname')

        jspec = JobSpec()
        jspec.jobDefinitionID   = job._getRoot().id
        jspec.jobName           = commands.getoutput('uuidgen 2> /dev/null')
        jspec.transformation    = '%s/runGen-00-00-02' % Client.baseURLSUB
        if job.inputdata:
            jspec.prodDBlock    = job.inputdata.dataset[0]
        else:
            jspec.prodDBlock    = 'NULL'
        jspec.destinationDBlock = job.outputdata.datasetname
        if job.outputdata.location:
            if not job._getRoot().subjobs or job.id == 0:
                logger.warning('You have specified outputdata.location. Note that Panda may not support writing to a user-defined output location.')
            jspec.destinationSE = job.outputdata.location
        else:
            jspec.destinationSE = site
        jspec.prodSourceLabel   = configPanda['prodSourceLabelRun']
        jspec.processingType    = configPanda['processingType']
        jspec.assignedPriority  = configPanda['assignedPriorityRun']
        jspec.cloud             = cloud
        # memory
        if job.backend.requirements.memory != -1:
            jspec.minRamCount = job.backend.requirements.memory
        # cputime     
        if job.backend.requirements.cputime != -1:
            jspec.maxCpuCount = job.backend.requirements.cputime
        jspec.computingSite     = site

#       library (source files)
        if job.backend.libds:
            flib = FileSpec()
            flib.lfn            = self.fileBO.lfn
            flib.GUID           = self.fileBO.GUID
            flib.type           = 'input'
            flib.status         = self.fileBO.status
            flib.dataset        = self.fileBO.destinationDBlock
            flib.dispatchDBlock = self.fileBO.destinationDBlock
            jspec.addFile(flib)
        elif job.backend.bexec:
            flib = FileSpec()
            flib.lfn            = self.library
            flib.type           = 'input'
            flib.dataset        = self.libDataset
            flib.dispatchDBlock = self.libDataset
            jspec.addFile(flib)

#       input files FIXME: many more input types
        if job.inputdata:            
            for guid, lfn, size, checksum, scope in zip(job.inputdata.guids,job.inputdata.names,job.inputdata.sizes, job.inputdata.checksums, job.inputdata.scopes):
                finp = FileSpec()
                finp.lfn            = lfn
                finp.GUID           = guid
                finp.scope          = scope
                
#            finp.fsize =
#            finp.md5sum =
                finp.dataset        = job.inputdata.dataset[0]
#.........这里部分代码省略.........

# 需要导入模块: from taskbuffer.JobSpec import JobSpec [as 别名]
# 或者: from taskbuffer.JobSpec.JobSpec import processingType [as 别名]
    def prepare(self, app, appsubconfig, appmasterconfig, jobmasterconfig):
        """Prepare the specific aspec of each subjob.
           Returns: subjobconfig list of objects understood by backends."""

        from pandatools import Client
        from pandatools import AthenaUtils
        from taskbuffer.JobSpec import JobSpec
        from taskbuffer.FileSpec import FileSpec
        from GangaAtlas.Lib.ATLASDataset.DQ2Dataset import dq2_set_dataset_lifetime
        from GangaPanda.Lib.Panda.Panda import refreshPandaSpecs
        
        # make sure we have the correct siteType
        refreshPandaSpecs()

        job = app._getParent()
        masterjob = job._getRoot()

        logger.debug('ProdTransPandaRTHandler prepare called for %s',
                     job.getFQID('.'))

        job.backend.actualCE = job.backend.site
        job.backend.requirements.cloud = Client.PandaSites[job.backend.site]['cloud']

        # check that the site is in a submit-able status
        if not job.splitter or job.splitter._name != 'DQ2JobSplitter':
            allowed_sites = job.backend.list_ddm_sites()

        try:
            outDsLocation = Client.PandaSites[job.backend.site]['ddm']
            tmpDsExist = False
            if (configPanda['processingType'].startswith('gangarobot') or configPanda['processingType'].startswith('hammercloud')):
                #if Client.getDatasets(job.outputdata.datasetname):
                if getDatasets(job.outputdata.datasetname):
                    tmpDsExist = True
                    logger.info('Re-using output dataset %s'%job.outputdata.datasetname)
            if not configPanda['specialHandling']=='ddm:rucio' and not  configPanda['processingType'].startswith('gangarobot') and not configPanda['processingType'].startswith('hammercloud') and not configPanda['processingType'].startswith('rucio_test'):
                Client.addDataset(job.outputdata.datasetname,False,location=outDsLocation,allowProdDisk=True,dsExist=tmpDsExist)
            logger.info('Output dataset %s registered at %s'%(job.outputdata.datasetname,outDsLocation))
            dq2_set_dataset_lifetime(job.outputdata.datasetname, outDsLocation)
        except exceptions.SystemExit:
            raise BackendError('Panda','Exception in adding dataset %s: %s %s'%(job.outputdata.datasetname,sys.exc_info()[0],sys.exc_info()[1]))
        
        # JobSpec.
        jspec = JobSpec()
        jspec.currentPriority = app.priority
        jspec.jobDefinitionID = masterjob.id
        jspec.jobName = commands.getoutput('uuidgen 2> /dev/null')
        jspec.coreCount = app.core_count
        jspec.AtlasRelease = 'Atlas-%s' % app.atlas_release
        jspec.homepackage = app.home_package
        jspec.transformation = app.transformation
        jspec.destinationDBlock = job.outputdata.datasetname
        if job.outputdata.location:
            jspec.destinationSE = job.outputdata.location
        else:
            jspec.destinationSE = job.backend.site
        if job.inputdata:
            jspec.prodDBlock = job.inputdata.dataset[0]
        else:
            jspec.prodDBlock = 'NULL'
        if app.prod_source_label:
            jspec.prodSourceLabel = app.prod_source_label
        else:
            jspec.prodSourceLabel = configPanda['prodSourceLabelRun']
        jspec.processingType = configPanda['processingType']
        jspec.specialHandling = configPanda['specialHandling']
        jspec.computingSite = job.backend.site
        jspec.cloud = job.backend.requirements.cloud
        jspec.cmtConfig = app.atlas_cmtconfig
        if app.dbrelease == 'LATEST':
            try:
                latest_dbrelease = getLatestDBReleaseCaching()
            except:
                from pandatools import Client
                latest_dbrelease = Client.getLatestDBRelease()
            m = re.search('(.*):DBRelease-(.*)\.tar\.gz', latest_dbrelease)
            if m:
                self.dbrelease_dataset = m.group(1)
                self.dbrelease = m.group(2)
            else:
                raise ApplicationConfigurationError(None, "Error retrieving LATEST DBRelease. Try setting application.dbrelease manually.")
        else:
            self.dbrelease_dataset = app.dbrelease_dataset
            self.dbrelease = app.dbrelease
        jspec.jobParameters = app.job_parameters

        if self.dbrelease:
            if self.dbrelease == 'current':
                jspec.jobParameters += ' --DBRelease=current' 
            else:
                if jspec.transformation.endswith("_tf.py") or jspec.transformation.endswith("_tf"):
                    jspec.jobParameters += ' --DBRelease=DBRelease-%s.tar.gz' % (self.dbrelease,)
                else:
                    jspec.jobParameters += ' DBRelease=DBRelease-%s.tar.gz' % (self.dbrelease,)
                dbspec = FileSpec()
                dbspec.lfn = 'DBRelease-%s.tar.gz' % self.dbrelease
                dbspec.dataset = self.dbrelease_dataset
                dbspec.prodDBlock = jspec.prodDBlock
                dbspec.type = 'input'
                jspec.addFile(dbspec)
#.........这里部分代码省略.........

# 需要导入模块: from taskbuffer.JobSpec import JobSpec [as 别名]
# 或者: from taskbuffer.JobSpec.JobSpec import processingType [as 别名]
 def doBrokerage(self, inputList, vo, prodSourceLabel, workQueue):
     # variables for submission
     maxBunchTask = 100
     # make logger
     tmpLog = MsgWrapper(logger)
     tmpLog.debug("start doBrokerage")
     # return for failure
     retFatal = self.SC_FATAL
     retTmpError = self.SC_FAILED
     tmpLog.debug("vo={0} label={1} queue={2}".format(vo, prodSourceLabel, workQueue.queue_name))
     # loop over all tasks
     allRwMap = {}
     prioMap = {}
     tt2Map = {}
     expRWs = {}
     jobSpecList = []
     for tmpJediTaskID, tmpInputList in inputList:
         for taskSpec, cloudName, inputChunk in tmpInputList:
             # make JobSpec to be submitted for TaskAssigner
             jobSpec = JobSpec()
             jobSpec.taskID = taskSpec.jediTaskID
             jobSpec.jediTaskID = taskSpec.jediTaskID
             # set managed to trigger TA
             jobSpec.prodSourceLabel = "managed"
             jobSpec.processingType = taskSpec.processingType
             jobSpec.workingGroup = taskSpec.workingGroup
             jobSpec.metadata = taskSpec.processingType
             jobSpec.assignedPriority = taskSpec.taskPriority
             jobSpec.currentPriority = taskSpec.currentPriority
             jobSpec.maxDiskCount = (taskSpec.getOutDiskSize() + taskSpec.getWorkDiskSize()) / 1024 / 1024
             if taskSpec.useWorldCloud():
                 # use destinationSE to trigger task brokerage in WORLD cloud
                 jobSpec.destinationSE = taskSpec.cloud
             prodDBlock = None
             setProdDBlock = False
             for datasetSpec in inputChunk.getDatasets():
                 prodDBlock = datasetSpec.datasetName
                 if datasetSpec.isMaster():
                     jobSpec.prodDBlock = datasetSpec.datasetName
                     setProdDBlock = True
                 for fileSpec in datasetSpec.Files:
                     tmpInFileSpec = fileSpec.convertToJobFileSpec(datasetSpec)
                     jobSpec.addFile(tmpInFileSpec)
             # use secondary dataset name as prodDBlock
             if setProdDBlock == False and prodDBlock != None:
                 jobSpec.prodDBlock = prodDBlock
             # append
             jobSpecList.append(jobSpec)
             prioMap[jobSpec.taskID] = jobSpec.currentPriority
             tt2Map[jobSpec.taskID] = jobSpec.processingType
             # get RW for a priority
             if not allRwMap.has_key(jobSpec.currentPriority):
                 tmpRW = self.taskBufferIF.calculateRWwithPrio_JEDI(
                     vo, prodSourceLabel, workQueue, jobSpec.currentPriority
                 )
                 if tmpRW == None:
                     tmpLog.error("failed to calculate RW with prio={0}".format(jobSpec.currentPriority))
                     return retTmpError
                 allRwMap[jobSpec.currentPriority] = tmpRW
             # get expected RW
             expRW = self.taskBufferIF.calculateTaskRW_JEDI(jobSpec.jediTaskID)
             if expRW == None:
                 tmpLog.error("failed to calculate RW for jediTaskID={0}".format(jobSpec.jediTaskID))
                 return retTmpError
             expRWs[jobSpec.taskID] = expRW
     # get fullRWs
     fullRWs = self.taskBufferIF.calculateRWwithPrio_JEDI(vo, prodSourceLabel, None, None)
     if fullRWs == None:
         tmpLog.error("failed to calculate full RW")
         return retTmpError
     # set metadata
     for jobSpec in jobSpecList:
         rwValues = allRwMap[jobSpec.currentPriority]
         jobSpec.metadata = "%s;%s;%s;%s;%s;%s" % (
             jobSpec.metadata,
             str(rwValues),
             str(expRWs),
             str(prioMap),
             str(fullRWs),
             str(tt2Map),
         )
     tmpLog.debug("run task assigner for {0} tasks".format(len(jobSpecList)))
     nBunchTask = 0
     while nBunchTask < len(jobSpecList):
         # get a bunch
         jobsBunch = jobSpecList[nBunchTask : nBunchTask + maxBunchTask]
         strIDs = "jediTaskID="
         for tmpJobSpec in jobsBunch:
             strIDs += "{0},".format(tmpJobSpec.taskID)
         strIDs = strIDs[:-1]
         tmpLog.debug(strIDs)
         # increment index
         nBunchTask += maxBunchTask
         # run task brokerge
         stS, outSs = PandaClient.runTaskAssignment(jobsBunch)
         tmpLog.debug("{0}:{1}".format(stS, str(outSs)))
     # return
     tmpLog.debug("done")
     return self.SC_SUCCEEDED

# 需要导入模块: from taskbuffer.JobSpec import JobSpec [as 别名]
# 或者: from taskbuffer.JobSpec.JobSpec import processingType [as 别名]
index = 0
for lfn in files.keys():
    index += 1
    job = JobSpec()
    job.jobDefinitionID   = (time.time()) % 10000
    job.jobName           = "%s_%d" % (commands.getoutput('uuidgen'),index)
    job.AtlasRelease      = 'Atlas-17.0.5'
    job.homepackage       = 'AtlasProduction/17.0.5.6'
    job.transformation    = 'AtlasG4_trf.py'
    job.destinationDBlock = datasetName
    job.computingSite     = site
    job.prodDBlock        = prodDBlock
    
    job.prodSourceLabel   = 'test'
    job.processingType    = 'test'
    job.currentPriority   = 10000
    job.cloud             = cloud
    job.cmtConfig         = 'i686-slc5-gcc43-opt'

    fileI = FileSpec()
    fileI.dataset    = job.prodDBlock
    fileI.prodDBlock = job.prodDBlock
    fileI.lfn = lfn
    fileI.type = 'input'
    job.addFile(fileI)

    fileD = FileSpec()
    fileD.dataset    = 'ddo.000001.Atlas.Ideal.DBRelease.v170602'
    fileD.prodDBlock = fileD.dataset
    fileD.lfn = 'DBRelease-17.6.2.tar.gz'

# 需要导入模块: from taskbuffer.JobSpec import JobSpec [as 别名]
# 或者: from taskbuffer.JobSpec.JobSpec import processingType [as 别名]
job.transformation    = 'http://pandawms.org/pandawms-jobcache/lsst-trf.sh'
job.destinationDBlock = datasetName
job.destinationSE     = 'local' 
job.currentPriority   = 1000
job.prodSourceLabel = 'panda'
job.jobParameters = ' --lsstJobParams="%s" ' % lsstJobParams
if prodUserName is not None:
    job.prodUserName = prodUserName
else:
    job.prodUserName = prodUserNameDefault
if PIPELINE_PROCESSINSTANCE is not None:
    job.taskID = PIPELINE_PROCESSINSTANCE
if PIPELINE_EXECUTIONNUMBER is not None:
    job.attemptNr = PIPELINE_EXECUTIONNUMBER
if PIPELINE_TASK is not None:
    job.processingType = PIPELINE_TASK
job.computingSite = site
job.VO = "lsst"

fileOL = FileSpec()
fileOL.lfn = "%s.job.log.tgz" % job.jobName
fileOL.destinationDBlock = job.destinationDBlock
fileOL.destinationSE     = job.destinationSE
fileOL.dataset           = job.destinationDBlock
fileOL.type = 'log'
job.addFile(fileOL)


s,o = Client.submitJobs([job],srvID=aSrvID)
print s
for x in o:

# 需要导入模块: from taskbuffer.JobSpec import JobSpec [as 别名]
# 或者: from taskbuffer.JobSpec.JobSpec import processingType [as 别名]
index = 0
for lfn in files.keys():
    index += 1
    job = JobSpec()
    job.jobDefinitionID   = int(time.time()) % 10000
    job.jobName           = "%s_%d" % (commands.getoutput('uuidgen'),index)
    job.AtlasRelease      = 'Atlas-14.4.0'
    job.homepackage       = 'AtlasTier0/14.4.0.2'
    job.transformation    = 'Reco_trf.py'
    job.destinationDBlock = datasetName
    job.destinationSE     = destName
    job.computingSite     = site
    job.prodDBlock        = 'data08_cos.00092045.physics_RPCwBeam.daq.RAW.o4_T1224560091' 
    
    job.prodSourceLabel   = 'test'
    job.processingType    = 'reprocessing'        
    job.currentPriority   = 10000
    job.cloud = cloud
    job.cmtConfig         = 'i686-slc4-gcc34-opt'

    origParams = """inputBSFile=daq.ATLAS.0092045.physics.RPCwBeam.LB0016.SFO-2._0009.data maxEvents=5 skipEvents=0 autoConfiguration=FieldAndGeo preInclude=RecExCommission/RecExCommission.py,RecExCommission/MinimalCommissioningSetup.py,RecJobTransforms/UseOracle.py preExec="jetFlags.Enabled.set_Value_and_Lock(False)" DBRelease=DBRelease-6.2.1.5.tar.gz conditionsTag=COMCOND-ES1C-000-00 RunNumber=92045 beamType=cosmics AMITag=r595 projectName=data08_cos trigStream=physics_RPCwBeam outputTypes=DPDCOMM outputESDFile=ESD.029868._01110.pool.root outputTAGComm=TAG_COMM.029868._01110.pool.root outputAODFile=AOD.029868._01110.pool.root outputMergedDQMonitorFile=DQM_MERGED.029868._01110.root DPD_PIXELCOMM=DPD_PIXELCOMM.029868._01110.pool.root DPD_SCTCOMM=DPD_SCTCOMM.029868._01110.pool.root DPD_IDCOMM=DPD_IDCOMM.029868._01110.pool.root DPD_IDPROJCOMM=DPD_IDPROJCOMM.029868._01110.pool.root DPD_CALOCOMM=DPD_CALOCOMM.029868._01110.pool.root DPD_TILECOMM=DPD_TILECOMM.029868._01110.pool.root DPD_EMCLUSTCOMM=DPD_EMCLUSTCOMM.029868._01110.pool.root DPD_EGAMMACOMM=DPD_EGAMMACOMM.029868._01110.pool.root DPD_RPCCOMM=DPD_RPCCOMM.029868._01110.pool.root DPD_TGCCOMM=DPD_TGCCOMM.029868._01110.pool.root --ignoreunknown"""

    match = re.findall("([^\s]+=[^\s]+)",origParams)
    outMap = {}
    for item in match:
        arg = item.split('=')[0]
        var = item.split('=')[-1]
        # output
        if arg.startswith('output') or arg.startswith('DPD_'):
            # skip some keys
            if arg in ['outputTypes']: