job.setCommandline('R --no-readline --no-restore --no-save -f '+path_to_inputfile)
batch_job.addJob(job)
batch_job.addInputFile('/home/markus/Desktop/R/'+inputfilename)
batch_job.setDefaultNoCpus(1)
batch_job.setDefaultWalltimeInSeconds(walltime)
print 'preparing jobs on backend...'
batch_job.prepareAndCreateJobs(redistribute)
if redistribute:
print 'job distribution:'
print batch_job.getOptimizationResult()
print 'submitting jobs to grid...'
batch_job.submit(True)
print 'submission finished...'
# now we add an input file that is common to all jobs
batchJob.addInputFile(inputFile1Url)
batchJob.addInputFile(inputFile2Url)
batchJob.addInputFile(inputFile3Url)
# we don't want to submit to tpac because it doesn't work
#multiPartJob.setSitesToExclude(["uq", "hpsc", "auckland", "canterbury"]);
try:
print "Creating jobs on the backend and staging files..."
batchJob.prepareAndCreateJobs(True)
except (JobsException), error:
for job in error.getFailures().keySet():
print "Job: " + job.getJobname() + ", Error: " + error.getFailures(
).get(job).getLocalizedMessage()
sys.exit()
# this is not really needed
print "Job distribution:"
for subLoc in batchJob.getOptimizationResult().keySet():
print subLoc + " : " + batchJob.getOptimizationResult().get(subLoc)
print "Submitting jobs..."
batchJob.submit(True)
print 'Submission finished.'
print 'Name of submitted batchjob: ' + batchJobName
# don't forget to exit properly. this cleans up possible existing threads/executors
sys.exit()
# this can be finetuned by exluding or including sites. another option would be to specifying the submission location
# for every single job and setting "False" below (this would make job submission faster since jobs don't need to be re-distributed/moved on the backend).
batch_job.prepareAndCreateJobs(True)
except (JobsException), error:
for job in error.getFailures().keySet():
print "Job: " + job.getJobname() + ", Error: " + error.getFailures(
).get(job).getLocalizedMessage()
sys.exit()
print "Job distribution:"
for subLoc in batch_job.getOptimizationResult().keySet():
print subLoc + " : " + batch_job.getOptimizationResult().get(subLoc)
print "Submitting jobs..."
batch_job.submit()
restarted = False
# now we wait for all jobs to finish. Actually, we probably should test whether the job was successful as well...
while not batch_job.isFinished(True):
# printing some stats
print batch_job.getProgress()
# restart failed jobs everytime
failedpolicy = DefaultResubmitPolicy()
# to only resubmit failed jobs, we have to remove the waiting jobs resubmission that is set by default
batch_job.restart(failedpolicy, True)
# restart once after the jobsubmission is finished to optimize job distributions to queues where the job actually runs
if not restarted:
except (JobsException), error:
print ("HALT: Exception submitting jobs from BatchJobObject " + batch_jobs.getJobname() + "!")
for job in error.getFailures().keySet():
print "Job: " + job.getJobname() + ", Error: " + error.getFailures().get(job).getLocalizedMessage()
sys.exit(1)
except (BackendException), error:
print ("HALT: Exception from grisu backend " + backend + "!")
print (error.getLocalizedMessage())
print ("========================")
time.sleep(3)
error.printStackTrace()
sys.exit(1)
time.sleep(3)
print "INFO: Submitting jobs in batch " + batch_jobs.getJobname()
batch_jobs.submit()
restarted = False
print "INFO: Waiting for batch " + batch_jobs.getJobname() + " to finish"
while not batch_jobs.isFinished(True):
print "\rWAITING: Running " + str(job_count) + " jobs:",
print " Waiting [" + str(batch_jobs.getNumberOfWaitingJobs()) + "]",
print " Active [" + str(batch_jobs.getNumberOfRunningJobs()) + "]",
print " Successful [" + str(batch_jobs.getNumberOfSuccessfulJobs()) + "]",
print " Failed [" + str(batch_jobs.getNumberOfFailedJobs()) + "]",
time.sleep(3)
# Refresh status one last time
print "\rWAITING: Running " + str(job_count) + " jobs:",
print " Waiting [" + str(batch_jobs.getNumberOfWaitingJobs()) + "]",
# by specifying "True" we tell the backend to automatically distribute the jobs to all available submission locations
# this can be finetuned by exluding or including sites. another option would be to specifying the submission location
# for every single job and setting "False" below (this would make job submission faster since jobs don't need to be re-distributed/moved on the backend).
batch_job.prepareAndCreateJobs(True)
except (JobsException), error:
for job in error.getFailures().keySet():
print "Job: "+job.getJobname()+", Error: "+error.getFailures().get(job).getLocalizedMessage()
sys.exit()
print "Job distribution:"
print batch_job.getOptimizationResult()
print "Submitting jobs..."
batch_job.submit()
# now we wait for all jobs to be finished, checking for updates every 10 seconds. in real life we would set a much higher check intervall since we don't want to overload
# the backend and also it's not really necessary
batch_job.waitForJobToFinish(10)
print "BatchJob "+batch_job.getJobname()+" finished."
# finally, everything is ready. We could do a lot more here, but you get the idea...
for job in batch_job.getJobs():
print "Job: "+job.getJobname()+", Status: "+job.getStatusString(False)
print "Submitted to: "+job.getJobProperty(Constants.SUBMISSION_SITE_KEY)
print
print "Stdout: "
print job.getStdOutContent()
print 'jobname on backend: ' + batch_job_name
path_to_inputfile = batch_job.pathToInputFiles() + inputfilename
for i in range(1, gen_jobs + 1):
job = JobObject(si)
job.setEmail_address(email)
job.setEmail_on_job_finish(True)
job.setCommandline('R --no-readline --no-restore --no-save -f ' +
path_to_inputfile)
batch_job.addJob(job)
batch_job.addInputFile('/home/markus/Desktop/R/' + inputfilename)
batch_job.setDefaultNoCpus(1)
batch_job.setDefaultWalltimeInSeconds(walltime)
print 'preparing jobs on backend...'
batch_job.prepareAndCreateJobs(redistribute)
if redistribute:
print 'job distribution:'
print batch_job.getOptimizationResult()
print 'submitting jobs to grid...'
batch_job.submit(True)
print 'submission finished...'
# now we add an input file that is common to all jobs
batchJob.addInputFile(inputFile1Url);
batchJob.addInputFile(inputFile2Url);
batchJob.addInputFile(inputFile3Url);
# we don't want to submit to tpac because it doesn't work
#multiPartJob.setSitesToExclude(["uq", "hpsc", "auckland", "canterbury"]);
try:
print "Creating jobs on the backend and staging files..."
batchJob.prepareAndCreateJobs(True)
except (JobsException), error:
for job in error.getFailures().keySet():
print "Job: "+job.getJobname()+", Error: "+error.getFailures().get(job).getLocalizedMessage()
sys.exit()
# this is not really needed
print "Job distribution:"
for subLoc in batchJob.getOptimizationResult().keySet():
print subLoc + " : " +batchJob.getOptimizationResult().get(subLoc)
print "Submitting jobs..."
batchJob.submit(True)
print 'Submission finished.'
print 'Name of submitted batchjob: '+batchJobName
# don't forget to exit properly. this cleans up possible existing threads/executors
sys.exit()
batch_jobs.getJobname() + "!")
for job in error.getFailures().keySet():
print "Job: " + job.getJobname() + ", Error: " + error.getFailures(
).get(job).getLocalizedMessage()
sys.exit(1)
except (BackendException), error:
print("HALT: Exception from grisu backend " + backend + "!")
print(error.getLocalizedMessage())
print("========================")
time.sleep(3)
error.printStackTrace()
sys.exit(1)
time.sleep(3)
print "INFO: Submitting jobs in batch " + batch_jobs.getJobname()
batch_jobs.submit()
restarted = False
print "INFO: Waiting for batch " + batch_jobs.getJobname() + " to finish"
while not batch_jobs.isFinished(True):
print "\rWAITING: Running " + str(job_count) + " jobs:",
print " Waiting [" + str(batch_jobs.getNumberOfWaitingJobs()) + "]",
print " Active [" + str(batch_jobs.getNumberOfRunningJobs()) + "]",
print " Successful [" + str(batch_jobs.getNumberOfSuccessfulJobs()) + "]",
print " Failed [" + str(batch_jobs.getNumberOfFailedJobs()) + "]",
time.sleep(3)
# Refresh status one last time
print "\rWAITING: Running " + str(job_count) + " jobs:",
print " Waiting [" + str(batch_jobs.getNumberOfWaitingJobs()) + "]",
