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) if job.inputdata: m = re.search('(.*)\.(.*)\.(.*)\.(.*)\.(.*)\.(.*)', job.inputdata.dataset[0]) if not m: logger.error("Error retrieving run number from dataset name") #raise ApplicationConfigurationError(None, "Error retrieving run number from dataset name") runnumber = 105200 else: runnumber = int(m.group(2)) if jspec.transformation.endswith("_tf.py") or jspec.transformation.endswith("_tf"): jspec.jobParameters += ' --runNumber %d' % runnumber else: jspec.jobParameters += ' RunNumber=%d' % runnumber # Output files. randomized_lfns = [] ilfn = 0 for lfn, lfntype in zip(app.output_files,app.output_type): ofspec = FileSpec() if app.randomize_lfns: randomized_lfn = lfn + ('.%s.%d.%s' % (job.backend.site, int(time.time()), commands.getoutput('uuidgen 2> /dev/null')[:4] ) ) else: randomized_lfn = lfn ofspec.lfn = randomized_lfn randomized_lfns.append(randomized_lfn) ofspec.destinationDBlock = jspec.destinationDBlock ofspec.destinationSE = jspec.destinationSE ofspec.dataset = jspec.destinationDBlock ofspec.type = 'output' jspec.addFile(ofspec) if jspec.transformation.endswith("_tf.py") or jspec.transformation.endswith("_tf"): jspec.jobParameters += ' --output%sFile %s' % (lfntype, randomized_lfns[ilfn]) else: jspec.jobParameters += ' output%sFile=%s' % (lfntype, randomized_lfns[ilfn]) ilfn=ilfn+1 # Input files. 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): ifspec = FileSpec() ifspec.lfn = lfn ifspec.GUID = guid ifspec.fsize = size ifspec.md5sum = checksum ifspec.scope = scope ifspec.dataset = jspec.prodDBlock ifspec.prodDBlock = jspec.prodDBlock ifspec.type = 'input' jspec.addFile(ifspec) if app.input_type: itype = app.input_type else: itype = m.group(5) if jspec.transformation.endswith("_tf.py") or jspec.transformation.endswith("_tf"): jspec.jobParameters += ' --input%sFile %s' % (itype, ','.join(job.inputdata.names)) else: jspec.jobParameters += ' input%sFile=%s' % (itype, ','.join(job.inputdata.names)) # Log files. lfspec = FileSpec() lfspec.lfn = '%s.job.log.tgz' % jspec.jobName lfspec.destinationDBlock = jspec.destinationDBlock lfspec.destinationSE = jspec.destinationSE lfspec.dataset = jspec.destinationDBlock lfspec.type = 'log' jspec.addFile(lfspec) return jspec
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) if job.inputdata: m = re.search('(.*)\.(.*)\.(.*)\.(.*)\.(.*)\.(.*)', job.inputdata.dataset[0]) if not m: logger.error("Error retrieving run number from dataset name") #raise ApplicationConfigurationError(None, "Error retrieving run number from dataset name") runnumber = 105200 else: runnumber = int(m.group(2)) if jspec.transformation.endswith( "_tf.py") or jspec.transformation.endswith("_tf"): jspec.jobParameters += ' --runNumber %d' % runnumber else: jspec.jobParameters += ' RunNumber=%d' % runnumber # Output files. randomized_lfns = [] ilfn = 0 for lfn, lfntype in zip(app.output_files, app.output_type): ofspec = FileSpec() if app.randomize_lfns: randomized_lfn = lfn + ( '.%s.%d.%s' % (job.backend.site, int(time.time()), commands.getoutput('uuidgen 2> /dev/null')[:4])) else: randomized_lfn = lfn ofspec.lfn = randomized_lfn randomized_lfns.append(randomized_lfn) ofspec.destinationDBlock = jspec.destinationDBlock ofspec.destinationSE = jspec.destinationSE ofspec.dataset = jspec.destinationDBlock ofspec.type = 'output' jspec.addFile(ofspec) if jspec.transformation.endswith( "_tf.py") or jspec.transformation.endswith("_tf"): jspec.jobParameters += ' --output%sFile %s' % ( lfntype, randomized_lfns[ilfn]) else: jspec.jobParameters += ' output%sFile=%s' % ( lfntype, randomized_lfns[ilfn]) ilfn = ilfn + 1 # Input files. 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): ifspec = FileSpec() ifspec.lfn = lfn ifspec.GUID = guid ifspec.fsize = size ifspec.md5sum = checksum ifspec.scope = scope ifspec.dataset = jspec.prodDBlock ifspec.prodDBlock = jspec.prodDBlock ifspec.type = 'input' jspec.addFile(ifspec) if app.input_type: itype = app.input_type else: itype = m.group(5) if jspec.transformation.endswith( "_tf.py") or jspec.transformation.endswith("_tf"): jspec.jobParameters += ' --input%sFile %s' % (itype, ','.join( job.inputdata.names)) else: jspec.jobParameters += ' input%sFile=%s' % (itype, ','.join( job.inputdata.names)) # Log files. lfspec = FileSpec() lfspec.lfn = '%s.job.log.tgz' % jspec.jobName lfspec.destinationDBlock = jspec.destinationDBlock lfspec.destinationSE = jspec.destinationSE lfspec.dataset = jspec.destinationDBlock lfspec.type = 'log' jspec.addFile(lfspec) return jspec
def send_job(jobid, siteid): _logger.debug('Jobid: ' + str(jobid)) site = sites_.get(siteid) job = jobs_.get(int(jobid)) cont = job.container files_catalog = cont.files fscope = getScope(job.owner.username) datasetName = '{}:{}'.format(fscope, cont.guid) distributive = job.distr.name release = job.distr.release # Prepare runScript parameters = job.distr.command parameters = parameters.replace("$COMMAND$", job.params) parameters = parameters.replace("$USERNAME$", job.owner.username) parameters = parameters.replace("$WORKINGGROUP$", job.owner.working_group) # Prepare metadata metadata = dict(user=job.owner.username) # Prepare PanDA Object pandajob = JobSpec() pandajob.jobDefinitionID = int(time.time()) % 10000 pandajob.jobName = cont.guid pandajob.transformation = client_config.DEFAULT_TRF pandajob.destinationDBlock = datasetName pandajob.destinationSE = site.se pandajob.currentPriority = 1000 pandajob.prodSourceLabel = 'user' pandajob.computingSite = site.ce pandajob.cloud = 'RU' pandajob.VO = 'atlas' pandajob.prodDBlock = "%s:%s" % (fscope, pandajob.jobName) pandajob.coreCount = job.corecount pandajob.metadata = json.dumps(metadata) #pandajob.workingGroup = job.owner.working_group if site.encode_commands: # It requires script wrapper on cluster side pandajob.jobParameters = '%s %s %s "%s"' % (cont.guid, release, distributive, parameters) else: pandajob.jobParameters = parameters has_input = False for fcc in files_catalog: if fcc.type == 'input': f = fcc.file guid = f.guid fileIT = FileSpec() fileIT.lfn = f.lfn fileIT.dataset = pandajob.prodDBlock fileIT.prodDBlock = pandajob.prodDBlock fileIT.type = 'input' fileIT.scope = fscope fileIT.status = 'ready' fileIT.GUID = guid pandajob.addFile(fileIT) has_input = True if fcc.type == 'output': f = fcc.file fileOT = FileSpec() fileOT.lfn = f.lfn fileOT.destinationDBlock = pandajob.prodDBlock fileOT.destinationSE = pandajob.destinationSE fileOT.dataset = pandajob.prodDBlock fileOT.type = 'output' fileOT.scope = fscope fileOT.GUID = f.guid pandajob.addFile(fileOT) # Save replica meta fc.new_replica(f, site) if not has_input: # Add fake input fileIT = FileSpec() fileIT.lfn = "fake.input" fileIT.dataset = pandajob.prodDBlock fileIT.prodDBlock = pandajob.prodDBlock fileIT.type = 'input' fileIT.scope = fscope fileIT.status = 'ready' fileIT.GUID = "fake.guid" pandajob.addFile(fileIT) # Prepare lof file fileOL = FileSpec() fileOL.lfn = "%s.log.tgz" % pandajob.jobName fileOL.destinationDBlock = pandajob.destinationDBlock fileOL.destinationSE = pandajob.destinationSE fileOL.dataset = '{}:logs'.format(fscope) fileOL.type = 'log' fileOL.scope = 'panda' pandajob.addFile(fileOL) # Save log meta log = File() log.scope = fscope log.lfn = fileOL.lfn log.guid = getGUID(log.scope, log.lfn) log.type = 'log' log.status = 'defined' files_.save(log) # Save replica meta fc.new_replica(log, site) # Register file in container fc.reg_file_in_cont(log, cont, 'log') # Submit job o = submitJobs([pandajob]) x = o[0] try: #update PandaID PandaID = int(x[0]) job.pandaid = PandaID job.ce = site.ce except: job.status = 'submit_error' jobs_.save(job) return 0