def test_SSCChain( self ):
""" full test of functionalities
"""
ssc = SandboxStoreClient()
smDB = SandboxMetadataDB()
exeScriptLocation = find_all( 'exe-script.py', '.', 'WorkloadManagementSystem' )[0]
fileList = [exeScriptLocation]
res = ssc.uploadFilesAsSandbox( fileList )
self.assert_( res['OK'] )
# SEPFN = res['Value'].split( '|' )[1]
res = ssc.uploadFilesAsSandboxForJob( fileList, 1, 'Input' )
self.assert_( res['OK'] )
# res = ssc.downloadSandboxForJob( 1, 'Input' ) #to run this would need the RSS on
# self.assert_( res['OK'] )
# only ones needing the DB
res = smDB.getUnusedSandboxes()
self.assert_( res['OK'] )
def test_SSCChain():
"""full test of functionalities"""
ssc = SandboxStoreClient()
smDB = SandboxMetadataDB()
exeScriptLocation = find_all("exe-script.py", "..", "/DIRAC/tests/Integration")[0]
fileList = [exeScriptLocation]
res = ssc.uploadFilesAsSandbox(fileList)
assert res["OK"] is True, res["Message"]
# SEPFN = res['Value'].split( '|' )[1]
res = ssc.uploadFilesAsSandboxForJob(fileList, 1, "Input")
assert res["OK"] is True, res["Message"]
res = ssc.downloadSandboxForJob(1, "Input") # to run this we need the RSS on
print(res) # for debug...
assert res["OK"] is True, res["Message"]
# only ones needing the DB
res = smDB.getUnusedSandboxes()
print(res)
assert res["OK"] is True, res["Message"]
def test_SSCChain(self):
""" full test of functionalities
"""
ssc = SandboxStoreClient()
smDB = SandboxMetadataDB()
exeScriptLocation = find_all('exe-script.py', '..', '/DIRAC/tests/Integration')[0]
fileList = [exeScriptLocation]
res = ssc.uploadFilesAsSandbox(fileList)
assert res['OK'] is True
# SEPFN = res['Value'].split( '|' )[1]
res = ssc.uploadFilesAsSandboxForJob(fileList, 1, 'Input')
assert res['OK'] is True
res = ssc.downloadSandboxForJob(1, 'Input') # to run this we need the RSS on
print res # for debug...
assert res['OK'] is True
# only ones needing the DB
res = smDB.getUnusedSandboxes()
print res
assert res['OK'] is True
def test_SSCChain(self):
""" full test of functionalities
"""
ssc = SandboxStoreClient()
smDB = SandboxMetadataDB()
exeScriptLocation = find_all('exe-script.py', '..',
'/DIRAC/tests/Integration')[0]
fileList = [exeScriptLocation]
res = ssc.uploadFilesAsSandbox(fileList)
assert res['OK'] is True
# SEPFN = res['Value'].split( '|' )[1]
res = ssc.uploadFilesAsSandboxForJob(fileList, 1, 'Input')
assert res['OK'] is True
res = ssc.downloadSandboxForJob(1,
'Input') # to run this we need the RSS on
print(res) # for debug...
assert res['OK'] is True
# only ones needing the DB
res = smDB.getUnusedSandboxes()
print(res)
assert res['OK'] is True
class InteractiveJobMonitorThread ( threading.Thread ):
def __init__( self, user , publicIP, looptime , parentthread, output, getinfo ):
threading.Thread.__init__( self )
self.sshConnect = ConnectionUtils( user , publicIP )
self.looptime = looptime
self.parentthread = parentthread
self.output = output
self.getinfo = getinfo
"""
#SandBox Settings
"""
self.sandboxClient = SandboxStoreClient()
self.failedFlag = True
self.sandboxSizeLimit = 1024 * 1024 * 10
def run( self ):
self.log = gLogger.getSubLogger( "InteractiveJobMonitorThread" )
self.monitoring( self.looptime, self.parentthread, self.output )
def monitoring( self, loop, parentthread, output ):
self.initialTiming = os.times()
accountingReport = AccountingJob()
accountingReport.setStartTime()
numberJobsFlag = True
numberJobs = 0
numberStartedJobsDict = {}
numberEndingJobsDict = {}
job_pattern = re.compile( 'Job =.*?,' )
job_pattern_2 = re.compile( 'Job =.*?\n' )
jobid = int( re.split( "_", re.split( "/", output )[int( len( re.split( "/", output ) ) - 1 )] )[0] )
cmd = '/bin/chmod 555 ' + self.getinfo
returned = self.commandLaunch( cmd )
while parentthread.isAlive():
time.sleep( loop )
if numberJobsFlag:
cmd = self.getinfo + ' -c step1'
returned = self.commandLaunch( cmd )
self.log.info( 'InteractiveJobMonitorThread:step1:numJobs:', returned )
if returned != None:
if ( returned['Value'][1] != "" ):
if re.split( "=", returned['Value'][1] )[1].strip().isdigit():
numberJobs = int( re.split( "=", returned['Value'][1] )[1] )
if ( numberJobs != 0 ):
numberJobsFlag = False
BigDataDB.setJobStatus( jobid, "Running" )
else:
cmd = self.getinfo + ' -c step2'
returned = self.commandLaunch( cmd )
self.log.info( 'InteractiveJobMonitorThread:step2:startedJobs:', returned )
if returned != "":
if ( returned['Value'][1] != "" ):
startedJobs = job_pattern.findall( returned['Value'][1] )
self.log.info( 'step2:startedJobs:', startedJobs )
cmd = self.getinfo + ' -c step3'
returned = self.commandLaunch( cmd )
self.log.info( 'InteractiveJobMonitorThread:step3:endedJobs:', returned )
if returned != "":
if ( returned['Value'][1] != "" ):
finishedJobs = job_pattern_2.findall( returned['Value'][1] )
self.log.info( 'step3:finishedJobs:', finishedJobs )
if ( len( finishedJobs ) == numberJobs ):
BigDataDB.setJobStatus( jobid, "Done" )
BigDataDB.setHadoopID( jobid, finishedJobs )
self.__updateSandBox( jobid, output )
#Update Accounting
EXECUTION_RESULT = {}
EXECUTION_RESULT['CPU'] = []
finalStat = os.times()
for i in range( len( finalStat ) ):
EXECUTION_RESULT['CPU'].append( finalStat[i] - self.initialTiming[i] )
utime, stime, cutime, cstime, elapsed = EXECUTION_RESULT['CPU']
cpuTime = utime + stime + cutime + cstime
execTime = elapsed
result = jobDB.getJobAttributes( jobid )
getting = result['Value']
acData = {
'User' : getting['Owner'],
'UserGroup' : getting['OwnerGroup'],
'JobGroup' : 'cesga',
'JobType' : 'User',
'JobClass' : 'unknown',
'ProcessingType' : 'unknown',
'FinalMajorStatus' : getting['Status'],
'FinalMinorStatus' : getting['MinorStatus'],
'CPUTime' : cpuTime,
'Site' : getting['Site'],
# Based on the factor to convert raw CPU to Normalized units (based on the CPU Model)
'NormCPUTime' : 0,
'ExecTime' : cpuTime,
'InputDataSize' : 0,
'OutputDataSize' : 0,
'InputDataFiles' : 0,
'OutputDataFiles' : 0,
'DiskSpace' : 0,
'InputSandBoxSize' : 0,
'OutputSandBoxSize' : 0,
'ProcessedEvents' : 0
}
accountingReport.setEndTime()
accountingReport.setValuesFromDict( acData )
result = accountingReport.commit()
def commandLaunch( self, cmd ):
return self.sshConnect.sshCall( 100, cmd )
def __updateSandBox( self, jobid, output ):
jobInfo = BigDataDB.getJobIDInfo( jobid )
result = self.sshConnect.scpCall( 100, output, output, False )
if not result['OK']:
self.log.error( 'Error to get the data from BigData Software DFS:', result )
file_paths = []
file_paths.append( output )
outputSandbox = file_paths
resolvedSandbox = self.__resolveOutputSandboxFiles( outputSandbox )
if not resolvedSandbox['OK']:
self.log.warn( 'Output sandbox file resolution failed:' )
self.log.warn( resolvedSandbox['Message'] )
self.__report( 'Failed', 'Resolving Output Sandbox' )
fileList = resolvedSandbox['Value']['Files']
missingFiles = resolvedSandbox['Value']['Missing']
if missingFiles:
self.jobReport.setJobParameter( 'OutputSandboxMissingFiles', ', '.join( missingFiles ), sendFlag = False )
if fileList and jobid:
self.outputSandboxSize = getGlobbedTotalSize( fileList )
self.log.info( 'Attempting to upload Sandbox with limit:', self.sandboxSizeLimit )
result = self.sandboxClient.uploadFilesAsSandboxForJob( fileList, jobid,
'Output', self.sandboxSizeLimit ) # 1024*1024*10
if not result['OK']:
self.log.error( 'Output sandbox upload failed with message', result['Message'] )
if result.has_key( 'SandboxFileName' ):
outputSandboxData = result['SandboxFileName']
self.log.info( 'Attempting to upload %s as output data' % ( outputSandboxData ) )
outputData.append( outputSandboxData )
self.jobReport.setJobParameter( 'OutputSandbox', 'Sandbox uploaded to grid storage', sendFlag = False )
self.jobReport.setJobParameter( 'OutputSandboxLFN',
self.__getLFNfromOutputFile( outputSandboxData )[0], sendFlag = False )
else:
self.log.info( 'Could not get SandboxFileName to attempt upload to Grid storage' )
return S_ERROR( 'Output sandbox upload failed and no file name supplied for failover to Grid storage' )
else:
# Do not overwrite in case of Error
if not self.failedFlag:
self.__report( 'Completed', 'Output Sandbox Uploaded' )
self.log.info( 'Sandbox uploaded successfully' )
return "OK"
def __resolveOutputSandboxFiles( self, outputSandbox ):
"""Checks the output sandbox file list and resolves any specified wildcards.
Also tars any specified directories.
"""
missing = []
okFiles = []
for i in outputSandbox:
self.log.verbose( 'Looking at OutputSandbox file/directory/wildcard: %s' % i )
globList = glob.glob( i )
for check in globList:
if os.path.isfile( check ):
self.log.verbose( 'Found locally existing OutputSandbox file: %s' % check )
okFiles.append( check )
if os.path.isdir( check ):
self.log.verbose( 'Found locally existing OutputSandbox directory: %s' % check )
cmd = ['tar', 'cf', '%s.tar' % check, check]
result = systemCall( 60, cmd )
if not result['OK']:
self.log.error( 'Failed to create OutputSandbox tar', result['Message'] )
elif result['Value'][0]:
self.log.error( 'Failed to create OutputSandbox tar', result['Value'][2] )
if os.path.isfile( '%s.tar' % ( check ) ):
self.log.verbose( 'Appending %s.tar to OutputSandbox' % check )
okFiles.append( '%s.tar' % ( check ) )
else:
self.log.warn( 'Could not tar OutputSandbox directory: %s' % check )
missing.append( check )
for i in outputSandbox:
if not i in okFiles:
if not '%s.tar' % i in okFiles:
if not re.search( '\*', i ):
if not i in missing:
missing.append( i )
result = {'Missing':missing, 'Files':okFiles}
return S_OK( result )
class BigDataJobMonitoring(AgentModule):
def initialize(self):
""" Standard constructor
"""
import threading
self.am_setOption("PollingTime", 5)
self.am_setOption("ThreadStartDelay", 1)
self.am_setOption("SubmitPools", [])
self.am_setOption("DefaultSubmitPools", [])
self.am_setOption("minThreadsInPool", 0)
self.am_setOption("maxThreadsInPool", 2)
self.am_setOption("totalThreadsInPool", 40)
self.callBackLock = threading.Lock()
self.pendingJobs = {}
self.monitoringEndPoints = {}
"""
#SandBox Settings
"""
self.__tmpSandBoxDir = "/tmp/"
self.sandboxClient = SandboxStoreClient()
self.failedFlag = True
self.sandboxSizeLimit = 1024 * 1024 * 10
self.fileList = 0
self.outputSandboxSize = 0
self.cleanDataAfterFinish = True
return DIRAC.S_OK()
def execute(self):
"""Main Agent code:
1.- Query BigDataDB for existing Running, Queue, or Submitted jobs
2.- Ask about the status
3.- Change the status into DB in the case of had changed
"""
self.pendingJobs["Submitted"] = BigDataDB.getBigDataJobsByStatus("Submitted")
self.pendingJobs["Running"] = BigDataDB.getBigDataJobsByStatus("Running")
self.pendingJobs["Unknown"] = BigDataDB.getBigDataJobsByStatus("Unknown")
self.__getMonitoringPools()
self.log.verbose("monitoring pools", self.monitoringEndPoints)
for status in self.pendingJobs:
self.log.verbose("Analizing %s jobs" % status)
JobStatus = 0
if self.pendingJobs[status]["OK"]:
for jobId in self.pendingJobs[status]["Value"]:
self.log.verbose("Analizing job %s" % jobId)
getSoftIdAndSiteName = BigDataDB.getSoftwareJobIDByJobID(jobId[0])
self.log.verbose("Site and SoftID:", getSoftIdAndSiteName)
for runningEndPoint in self.monitoringEndPoints:
if (self.monitoringEndPoints[runningEndPoint]["NameNode"] == getSoftIdAndSiteName[0][1]) and (
getSoftIdAndSiteName[0][0] != ""
):
# Depending on the BigData Software the Query should be different
if self.monitoringEndPoints[runningEndPoint]["BigDataSoftware"] == "hadoop":
if self.monitoringEndPoints[runningEndPoint]["BigDataSoftwareVersion"] == "hdv1":
if (
self.monitoringEndPoints[runningEndPoint]["HighLevelLanguage"]["HLLName"]
== "none"
):
self.log.info(
"Hadoop V.1 Monitoring submmission command with Hadoop jobID: ",
getSoftIdAndSiteName[0][0],
)
from BigDataDIRAC.WorkloadManagementSystem.Client.HadoopV1Client import (
HadoopV1Client,
)
HadoopV1cli = HadoopV1Client(
self.monitoringEndPoints[runningEndPoint]["User"],
self.monitoringEndPoints[runningEndPoint]["PublicIP"],
self.monitoringEndPoints[runningEndPoint]["Port"],
)
JobStatus = HadoopV1cli.jobStatus(
getSoftIdAndSiteName[0][0],
self.monitoringEndPoints[runningEndPoint]["User"],
self.monitoringEndPoints[runningEndPoint]["PublicIP"],
)
if (JobStatus["OK"] == True) and (
self.monitoringEndPoints[runningEndPoint]["IsInteractive"] == "1"
):
if JobStatus["Value"][1].strip() == "Succeded":
result = HadoopV1cli.newJob(
self.__tmpSandBoxDir, jobId[0], getSoftIdAndSiteName[0][0]
)
if result["OK"] == True:
result = BigDataDB.updateHadoopIDAndJobStatus(
jobId[0], result["Value"]
)
BigDataDB.setJobStatus(jobId[0], "Running")
JobStatus["OK"] = False
else:
self.log.info("New result from new Job", result)
if JobStatus["OK"] == True:
if JobStatus["Value"][1].strip() == "Succeded":
BigDataDB.setJobStatus(jobId[0], "Done")
if self.monitoringEndPoints[runningEndPoint]["IsInteractive"] == "1":
self.__updateInteractiveSandBox(
jobId[0],
self.monitoringEndPoints[runningEndPoint]["BigDataSoftware"],
self.monitoringEndPoints[runningEndPoint][
"BigDataSoftwareVersion"
],
self.monitoringEndPoints[runningEndPoint]["HighLevelLanguage"][
"HLLName"
],
self.monitoringEndPoints[runningEndPoint]["HighLevelLanguage"][
"HLLVersion"
],
HadoopV1cli,
)
else:
self.__updateSandBox(
jobId[0],
self.monitoringEndPoints[runningEndPoint]["BigDataSoftware"],
self.monitoringEndPoints[runningEndPoint][
"BigDataSoftwareVersion"
],
self.monitoringEndPoints[runningEndPoint]["HighLevelLanguage"][
"HLLName"
],
self.monitoringEndPoints[runningEndPoint]["HighLevelLanguage"][
"HLLVersion"
],
HadoopV1cli,
)
getStatus = HadoopV1cli.jobCompleteStatus(getSoftIdAndSiteName[0][0])
if getStatus["OK"]:
result = self.getJobFinalStatusInfo(getStatus["Value"][1])
if result["OK"]:
self.sendJobAccounting(result["Value"], jobId[0])
if self.cleanDataAfterFinish:
self.__deleteData(jobId[0], HadoopV1cli)
if JobStatus["Value"][1].strip() == "Unknown":
BigDataDB.setJobStatus(jobId[0], "Submitted")
if JobStatus["Value"][1].strip() == "Running":
BigDataDB.setJobStatus(jobId[0], "Running")
if self.monitoringEndPoints[runningEndPoint]["BigDataSoftware"] == "hadoop":
if self.monitoringEndPoints[runningEndPoint]["BigDataSoftwareVersion"] == "hdv2":
if (
self.monitoringEndPoints[runningEndPoint]["HighLevelLanguage"]["HLLName"]
== "none"
):
self.log.info(
"Hadoop V.2 Monitoring submmission command with Hadoop jobID: ",
getSoftIdAndSiteName[0][0],
)
from BigDataDIRAC.WorkloadManagementSystem.Client.HadoopV2Client import (
HadoopV2Client,
)
HadoopV2cli = HadoopV2Client(
self.monitoringEndPoints[runningEndPoint]["User"],
self.monitoringEndPoints[runningEndPoint]["PublicIP"],
)
JobStatus = HadoopV2cli.jobStatus(
getSoftIdAndSiteName[0][0],
self.monitoringEndPoints[runningEndPoint]["User"],
self.monitoringEndPoints[runningEndPoint]["PublicIP"],
)
if (JobStatus["OK"] == True) and (
self.monitoringEndPoints[runningEndPoint]["IsInteractive"] == "1"
):
if JobStatus["Value"].strip() == "Succeded":
result = HadoopV2cli.newJob(
self.__tmpSandBoxDir, jobId[0], getSoftIdAndSiteName[0][0]
)
if result["OK"] == True:
result = BigDataDB.updateHadoopIDAndJobStatus(
jobId[0], result["Value"]
)
BigDataDB.setJobStatus(jobId[0], "Running")
JobStatus["OK"] = False
else:
self.log.info("New result from new Job", result)
if JobStatus["OK"] == True:
if JobStatus["Value"] == "Succeded":
BigDataDB.setJobStatus(jobId[0], "Done")
if self.monitoringEndPoints[runningEndPoint]["IsInteractive"] == "1":
self.__updateInteractiveSandBox(
jobId[0],
self.monitoringEndPoints[runningEndPoint]["BigDataSoftware"],
self.monitoringEndPoints[runningEndPoint][
"BigDataSoftwareVersion"
],
self.monitoringEndPoints[runningEndPoint]["HighLevelLanguage"][
"HLLName"
],
self.monitoringEndPoints[runningEndPoint]["HighLevelLanguage"][
"HLLVersion"
],
HadoopV2cli,
)
else:
self.__updateSandBox(
jobId[0],
self.monitoringEndPoints[runningEndPoint]["BigDataSoftware"],
self.monitoringEndPoints[runningEndPoint][
"BigDataSoftwareVersion"
],
self.monitoringEndPoints[runningEndPoint]["HighLevelLanguage"][
"HLLName"
],
self.monitoringEndPoints[runningEndPoint]["HighLevelLanguage"][
"HLLVersion"
],
HadoopV2cli,
)
getStatus = HadoopV2cli.jobCompleteStatus(getSoftIdAndSiteName[0][0])
if getStatus["OK"]:
result = self.getJobFinalStatusInfo(getStatus["Value"][1])
if result["OK"]:
self.sendJobAccounting(result["Value"], jobId[0])
# if self.cleanDataAfterFinish:
# self.__deleteData( jobId[0], HadoopV2cli )
if JobStatus["Value"] == "Unknown":
BigDataDB.setJobStatus(jobId[0], "Submitted")
if JobStatus["Value"] == "Running":
BigDataDB.setJobStatus(jobId[0], "Running")
return DIRAC.S_OK()
def sendJobAccounting(self, dataFromBDSoft, jobId):
accountingReport = AccountingJob()
accountingReport.setStartTime()
result = jobDB.getJobAttributes(jobId)
getting = result["Value"]
if dataFromBDSoft["CPUTime"] == 0:
cpuTime = 0
if getting["EndExecTime"] != "None":
epoch = datetime(1970, 1, 1)
td = datetime.strptime(getting["EndExecTime"], "%Y-%m-%d %H:%M:%S") - epoch
EndExecTime = (td.microseconds + (td.seconds + td.days * 24 * 3600) * 10 ** 6) / 1e6
td = datetime.strptime(getting["SubmissionTime"], "%Y-%m-%d %H:%M:%S") - epoch
SubmissionTime = (td.microseconds + (td.seconds + td.days * 24 * 3600) * 10 ** 6) / 1e6
cpuTime = EndExecTime - SubmissionTime
else:
cpuTime = dataFromBDSoft["CPUTime"] / 1000
acData = {
"User": getting["Owner"],
"UserGroup": getting["OwnerGroup"],
"JobGroup": "cesga",
"JobType": "User",
"JobClass": "unknown",
"ProcessingType": "unknown",
"FinalMajorStatus": getting["Status"],
"FinalMinorStatus": getting["MinorStatus"],
"CPUTime": cpuTime,
"Site": getting["Site"],
# Based on the factor to convert raw CPU to Normalized units (based on the CPU Model)
"NormCPUTime": 0,
"ExecTime": cpuTime,
"InputDataSize": dataFromBDSoft["InputDataSize"],
"OutputDataSize": dataFromBDSoft["OutputDataSize"],
"InputDataFiles": dataFromBDSoft["InputDataFiles"],
"OutputDataFiles": len(self.fileList),
"DiskSpace": 0,
"InputSandBoxSize": 0,
"OutputSandBoxSize": self.outputSandboxSize,
"ProcessedEvents": 0,
}
accountingReport.setEndTime()
accountingReport.setValuesFromDict(acData)
self.log.debug("Info for accounting: ", acData)
result = accountingReport.commit()
self.log.debug("Accounting insertion: ", result)
return result
def getJobFinalStatusInfo(self, jobData):
JobOutputInfo = {}
resulting = re.search("Read=(\d+)", jobData)
if resulting != None:
JobOutputInfo["InputDataSize"] = int(resulting.group(0).split("=")[1])
else:
JobOutputInfo["InputDataSize"] = 0
resulting = re.search("Written=(\d+)", jobData)
if resulting != None:
JobOutputInfo["OutputDataSize"] = int(resulting.group(0).split("=")[1])
else:
JobOutputInfo["OutputDataSize"] = 0
resulting = re.search("Map input records=(\d+)", jobData)
if resulting != None:
JobOutputInfo["InputDataFiles"] = int(resulting.group(0).split("=")[1])
else:
JobOutputInfo["InputDataFiles"] = 0
resulting = re.search("CPU.*?=(\d+)", jobData)
if resulting != None:
JobOutputInfo["CPUTime"] = int(resulting.group(0).split("=")[1])
else:
JobOutputInfo["CPUTime"] = 0
JobOutputInfo["ExecTime"] = 0
return S_OK(JobOutputInfo)
def __deleteData(self, jobid, cli):
source = self.__tmpSandBoxDir + str(jobid)
shutil.rmtree(source)
result = cli.delData(source)
if not result["OK"]:
self.log.error("Error the data on BigData cluster could not be deleted", result)
return S_ERROR("Data can not be deleted")
return "Data deleted"
def __updateInteractiveSandBox(self, jobid, software, version, hll, hllversion, cli):
# Detele content of InputSandbox
jobInfo = BigDataDB.getJobIDInfo(jobid)
source = self.__tmpSandBoxDir + str(jobid) + "/*_out"
dest = self.__tmpSandBoxDir + str(jobid)
result = 0
result = cli.delHadoopData(self.__tmpSandBoxDir + str(jobid) + "/InputSandbox" + str(jobid))
self.log.debug("ATENTION::Deleting InputSandBox Contain:", result)
result = cli.getdata(dest, source)
self.log.debug("Step 0:getting data from hadoop:", result)
if not result["OK"]:
self.log.error("Error to get the data from BigData Cluster to DIRAC:", result)
self.log.debug("Step:1:GetFilePaths:")
outputSandbox = self.get_filepaths(self.__tmpSandBoxDir + str(jobid))
self.log.debug("Step:2:OutputSandBox:", self.__tmpSandBoxDir + str(jobid))
self.log.debug("Step:2:OutputSandBox:", outputSandbox)
resolvedSandbox = self.__resolveOutputSandboxFiles(outputSandbox)
self.log.debug("Step:3:ResolveSandbox:", resolvedSandbox)
if not resolvedSandbox["OK"]:
self.log.warn("Output sandbox file resolution failed:")
self.log.warn(resolvedSandbox["Message"])
self.__report("Failed", "Resolving Output Sandbox")
self.fileList = resolvedSandbox["Value"]["Files"]
missingFiles = resolvedSandbox["Value"]["Missing"]
if missingFiles:
self.jobReport.setJobParameter("OutputSandboxMissingFiles", ", ".join(missingFiles), sendFlag=False)
if self.fileList and jobid:
self.outputSandboxSize = getGlobbedTotalSize(self.fileList)
self.log.info("Attempting to upload Sandbox with limit:", self.sandboxSizeLimit)
result = self.sandboxClient.uploadFilesAsSandboxForJob(
self.fileList, jobid, "Output", self.sandboxSizeLimit
) # 1024*1024*10
if not result["OK"]:
self.log.error("Output sandbox upload failed with message", result["Message"])
if result.has_key("SandboxFileName"):
outputSandboxData = result["SandboxFileName"]
self.log.info("Attempting to upload %s as output data" % (outputSandboxData))
outputData.append(outputSandboxData)
self.jobReport.setJobParameter("OutputSandbox", "Sandbox uploaded to grid storage", sendFlag=False)
self.jobReport.setJobParameter(
"OutputSandboxLFN", self.__getLFNfromOutputFile(outputSandboxData)[0], sendFlag=False
)
else:
self.log.info("Could not get SandboxFileName to attempt upload to Grid storage")
return S_ERROR(
"Output sandbox upload failed and no file name supplied for failover to Grid storage"
)
else:
# Do not overwrite in case of Error
if not self.failedFlag:
self.__report("Completed", "Output Sandbox Uploaded")
self.log.info("Sandbox uploaded successfully")
return "OK"
def __updateSandBox(self, jobid, software, version, hll, hllversion, cli):
jobInfo = BigDataDB.getJobIDInfo(jobid)
source = (
self.__tmpSandBoxDir
+ str(jobid)
+ "/InputSandbox"
+ str(jobid)
+ "/"
+ self.__getJobName(jobInfo[0][0]).replace(" ", "")
+ "_"
+ str(jobid)
)
dest = (
self.__tmpSandBoxDir
+ str(jobid)
+ "/"
+ self.__getJobName(jobInfo[0][0]).replace(" ", "")
+ "_"
+ str(jobid)
)
result = 0
if (software == "hadoop") and (version == "hdv1") and (hll == "none"):
result = cli.getData(source, dest)
if (software == "hadoop") and (version == "hdv2") and (hll == "none"):
result = cli.getData(source, dest)
if not result["OK"]:
self.log.error("Error to get the data from BigData Software DFS:", result)
result = cli.getdata(dest, dest)
if not result["OK"]:
self.log.error("Error to get the data from BigData Cluster to DIRAC:", result)
outputSandbox = self.get_filepaths(dest)
resolvedSandbox = self.__resolveOutputSandboxFiles(outputSandbox)
if not resolvedSandbox["OK"]:
self.log.warn("Output sandbox file resolution failed:")
self.log.warn(resolvedSandbox["Message"])
self.__report("Failed", "Resolving Output Sandbox")
self.fileList = resolvedSandbox["Value"]["Files"]
missingFiles = resolvedSandbox["Value"]["Missing"]
if missingFiles:
self.jobReport.setJobParameter("OutputSandboxMissingFiles", ", ".join(missingFiles), sendFlag=False)
if self.fileList and jobid:
self.outputSandboxSize = getGlobbedTotalSize(self.fileList)
self.log.info("Attempting to upload Sandbox with limit:", self.sandboxSizeLimit)
result = self.sandboxClient.uploadFilesAsSandboxForJob(
self.fileList, jobid, "Output", self.sandboxSizeLimit
) # 1024*1024*10
if not result["OK"]:
self.log.error("Output sandbox upload failed with message", result["Message"])
if result.has_key("SandboxFileName"):
outputSandboxData = result["SandboxFileName"]
self.log.info("Attempting to upload %s as output data" % (outputSandboxData))
outputData.append(outputSandboxData)
self.jobReport.setJobParameter("OutputSandbox", "Sandbox uploaded to grid storage", sendFlag=False)
self.jobReport.setJobParameter(
"OutputSandboxLFN", self.__getLFNfromOutputFile(outputSandboxData)[0], sendFlag=False
)
else:
self.log.info("Could not get SandboxFileName to attempt upload to Grid storage")
return S_ERROR(
"Output sandbox upload failed and no file name supplied for failover to Grid storage"
)
else:
# Do not overwrite in case of Error
if not self.failedFlag:
self.__report("Completed", "Output Sandbox Uploaded")
self.log.info("Sandbox uploaded successfully")
return "OK"
def __getLFNfromOutputFile(self, outputFile, outputPath=""):
"""Provides a generic convention for VO output data
files if no path is specified.
"""
if not re.search("^LFN:", outputFile):
localfile = outputFile
initial = self.owner[:1]
vo = getVOForGroup(self.userGroup)
if not vo:
vo = "dirac"
basePath = "/" + vo + "/user/" + initial + "/" + self.owner
if outputPath:
# If output path is given, append it to the user path and put output files in this directory
if outputPath.startswith("/"):
outputPath = outputPath[1:]
else:
# By default the output path is constructed from the job id
subdir = str(self.jobID / 1000)
outputPath = subdir + "/" + str(self.jobID)
lfn = os.path.join(basePath, outputPath, os.path.basename(localfile))
else:
# if LFN is given, take it as it is
localfile = os.path.basename(outputFile.replace("LFN:", ""))
lfn = outputFile.replace("LFN:", "")
return (lfn, localfile)
def get_filepaths(self, directory):
"""
This function will generate the file names in a directory
"""
file_paths = []
for root, directories, files in os.walk(directory):
for filename in files:
filepath = os.path.join(root, filename)
file_paths.append(filepath)
return file_paths
def __resolveOutputSandboxFiles(self, outputSandbox):
"""Checks the output sandbox file list and resolves any specified wildcards.
Also tars any specified directories.
"""
missing = []
okFiles = []
for i in outputSandbox:
self.log.verbose("Looking at OutputSandbox file/directory/wildcard: %s" % i)
globList = glob.glob(i)
for check in globList:
if os.path.isfile(check):
self.log.verbose("Found locally existing OutputSandbox file: %s" % check)
okFiles.append(check)
if os.path.isdir(check):
self.log.verbose("Found locally existing OutputSandbox directory: %s" % check)
cmd = ["tar", "cf", "%s.tar" % check, check]
result = systemCall(60, cmd)
if not result["OK"]:
self.log.error("Failed to create OutputSandbox tar", result["Message"])
elif result["Value"][0]:
self.log.error("Failed to create OutputSandbox tar", result["Value"][2])
if os.path.isfile("%s.tar" % (check)):
self.log.verbose("Appending %s.tar to OutputSandbox" % check)
okFiles.append("%s.tar" % (check))
else:
self.log.warn("Could not tar OutputSandbox directory: %s" % check)
missing.append(check)
for i in outputSandbox:
if not i in okFiles:
if not "%s.tar" % i in okFiles:
if not re.search("\*", i):
if not i in missing:
missing.append(i)
result = {"Missing": missing, "Files": okFiles}
return S_OK(result)
def __getJobName(self, jobName):
result = re.split("_", jobName)
return result[0]
def __getMonitoringPools(self):
for monitoringPool in self.am_getOption("SubmitPools"):
self.log.verbose("Monitoring Pools", monitoringPool)
pathPools = self.am_getModuleParam("section") + "/" + monitoringPool + "/EndPointMonitoring"
monitorings = gConfig.getValue(pathPools)
splitted = re.split(",", monitorings)
for endpoint in splitted:
self.configureFromSection("/Resources/BigDataEndpoints/", endpoint)
return "OK"
def configureFromSection(self, mySection, endPoint):
"""
get CS for monitoring endpoints
"""
self.log.debug("Configuring from %s" % mySection)
monitoringBDEndPointDict = BigDataDB.getRunningEnPointDict(endPoint)
if not monitoringBDEndPointDict["OK"]:
self.log.error("Error in RunninggBDEndPointDict: %s" % monitoringBDEndPointDict["Message"])
return monitoringBDEndPointDict
self.log.verbose("Trying to configure RunningBDEndPointDict:", monitoringBDEndPointDict)
monitoringBDEndPointDict = monitoringBDEndPointDict["Value"]
for option in [
"NameNode",
"Port",
"SiteName",
"BigDataSoftware",
"BigDataSoftwareVersion",
"HighLevelLanguage",
"LimitQueueJobsEndPoint",
"URL",
"PublicIP",
]:
if option not in monitoringBDEndPointDict.keys():
self.log.error('Missing option in "%s" EndPoint definition:' % endPoint, option)
continue
self.monitoringEndPoints[endPoint] = {}
self.monitoringEndPoints[endPoint]["NameNode"] = monitoringBDEndPointDict["NameNode"]
self.monitoringEndPoints[endPoint]["Port"] = int(monitoringBDEndPointDict["Port"])
self.monitoringEndPoints[endPoint]["SiteName"] = monitoringBDEndPointDict["SiteName"]
self.monitoringEndPoints[endPoint]["BigDataSoftware"] = monitoringBDEndPointDict["BigDataSoftware"]
self.monitoringEndPoints[endPoint]["BigDataSoftwareVersion"] = monitoringBDEndPointDict[
"BigDataSoftwareVersion"
]
self.monitoringEndPoints[endPoint]["LimitQueueJobsEndPoint"] = int(
monitoringBDEndPointDict["LimitQueueJobsEndPoint"]
)
self.monitoringEndPoints[endPoint]["URL"] = monitoringBDEndPointDict["URL"]
self.monitoringEndPoints[endPoint]["User"] = monitoringBDEndPointDict["User"]
self.monitoringEndPoints[endPoint]["PublicIP"] = monitoringBDEndPointDict["PublicIP"]
self.monitoringEndPoints[endPoint]["IsInteractive"] = monitoringBDEndPointDict["IsInteractive"]
self.monitoringEndPoints[endPoint]["HighLevelLanguage"] = monitoringBDEndPointDict["HighLevelLanguage"]
