(r4) RunningGangaWithPanda < ATLAS

ATLAS Web>RunningGangaWithPanda (revision 4) (raw view)~~EditAttach~~
-- Main.ThomasDoherty - 2009-10-26
---++++ %MAKETEXT{"<strong>Using Ganga to submit jobs to the Panda backend</strong>" }%

References:

[[https://twiki.cern.ch/twiki/bin/view/Atlas/FullGangaAtlasTutorial][Full Ganga Atlas Tutorial]]

[[https://twiki.cern.ch/twiki/bin/view/Atlas/DataPreparationReprocessing#Submitting_the_job_with_GANGA][Data preparation reprocessing - using Ganga]]

1. In a clean shell, setup Ganga.
<pre><verbatim>  source /afs/cern.ch/sw/ganga/install/etc/setup-atlas.sh
</verbatim>
</pre>

2. Setup the athena release.

NOTE: To set up for any release one must be familar with using CMT (bootstrap procedures and requirement files) - see [[https://twiki.cern.ch/twiki/bin/view/Atlas/WorkBookSetAccount][here]] for more information. In this case once your requirements file is set up and a directory in your test area for 14.5.2.6 is created then try:
<pre><verbatim>  source cmthome/setup.sh -tag=14.5.2.6,32,AtlasProduction
</verbatim>
</pre>

3. Setup any checked out packages you use in your code.

For this example check out (and compile) the UserAnalysis package as in the "HelloWorld"example [[https://twiki.cern.ch/twiki/bin/view/Atlas/WorkBookRunAthenaHelloWorld][here]] or [[https://twiki.cern.ch/twiki/bin/view/Atlas/FullGangaAtlasTutorial#4_2_Setting_up_a_Basic_Analysis][here]].
<pre><verbatim>  cd $TEST/PhysicsAnalysis/AnalysisCommon/UserAnalysis/cmt
  source setup.sh
</verbatim>
</pre>

4. Go to run directory and start ganga.
<pre><verbatim>   cd ../run
   ganga
</verbatim>
</pre>

5. Execute your Ganga job script while Ganga is running (where an example of what the 'pandaBackend_test.py' would look like is below in other words have this [[http://ppewww.physics.gla.ac.uk/~tdoherty/GangaPanda/pandaBackend_test.py][file]] in your run directory) and type:
<pre><verbatim>    execfile('pandaBackend_test.py')
</verbatim>
</pre>

6. You can monitor your job's progress by typing *jobs* inside Ganga or, if you submitted to the Panda backend by http://panda.cern.ch:25880/server/pandamon/query.

7. Once your job has finished you can copy the output data using the dq2 tools.
<pre>          <verbatim>source /afs/cern.ch/atlas/offline/external/GRID/ddm/DQ2Clients/setup.sh
   dq2-get "your_dataset_name"
</verbatim>
</pre>

Where "your_dataset_name" is given to you by Ganga once the job completes. And 'pandaBackend_test.py' could look like this (without line numbers):
<pre><verbatim>1    j = Job()
2    j.application = Athena()
3    j.application.atlas_dbrelease = 'ddo.000001.Atlas.Ideal.DBRelease.v06060101:DBRelease-6.6.1.1.tar.gz'
4    j.application.option_file = 'AnalysisSkeleton_topOptions.py'
5    j.application.athena_compile = False
6    j.application.prepare()
7    j.inputdata = DQ2Dataset()
8    j.inputdata.dataset = "data08_cos.00092051.physics_IDCosmic.recon.ESD.o4_r653/"
9    j.outputdata = DQ2OutputDataset()
10   j.backend = Panda()
11   j.splitter = DQ2JobSplitter()
12   j.splitter.numsubjobs = 20
13   j.submit()

</verbatim>
</pre>

NOTE: Line 3 is an example of overriding a database release to match the one needed to read ESD/DPD. In the case of the spring cosmic reprocessing,the DB release is 6.6.1.1. If the database releases don't match the jobs fail on the Grid ( remove this line if it is not necessary). Line 4 corresponds to your Athena jobOptions. You can use the top job options copied from your UserAnalysis packages share directory.
<verbatim>cp ../share/AnalysisSkeleton_topOptions.py .</verbatim>

BUT to prepare your code for running on the Grid there are some changes needed for this Athena JO - please add these lines:
<verbatim>______________________________________________________________________________

include("RecExCommission/RecExCommissionFlags_jobOptions.py" )
ATLASCosmicFlags.useLocalCOOL  = True
# setup DBReplicaSvc to choose closest Oracle replica, configurables style
from AthenaCommon.AppMgr import ServiceMgr
from PoolSvc.PoolSvcConf import PoolSvc
ServiceMgr+=PoolSvc(SortReplicas=True)
from DBReplicaSvc.DBReplicaSvcConf import DBReplicaSvc
ServiceMgr+=DBReplicaSvc(UseCOOLSQLite=False) 

_____________________________________________________________________________
</verbatim>

Also remember to remove (or comment out) the input data line and if you are running a reprocessing job change the geometry tag and the conditions DB tag to match those used in the reprocessing cycle (see details for each reprocessing campaign on this page [[https://twiki.cern.ch/twiki/bin/view/Atlas/DataPreparationReprocessing#How_to_submit_jobs_to_the_Grid][here]]. For example:
<pre><verbatim>globalflags.ConditionsTag.set_Value_and_Lock('COMCOND-REPC-002-13')</verbatim>
</pre>

Back to the Ganga JO script:
<pre><verbatim>Line 5 is set to False because we have already compiled the packages locally.
Line 6 tells Ganga to tar your user area and send it with the job.
Line 10 specifies the backend to which you are sending your job. There are three options: LCG, 
Panda and NorduGrid. In the example above Panda was chosen because the data existed only in BNLPANDA,
a site in the US cloud. 
Line 12 corresponds to the number of subjobs you want to split your job into. 
Finally in Line 13 you submit your job.</verbatim>
</pre>
Topic revision: r4 - 2009-10-27 - ThomasDoherty
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