Using GANGA with AMAAthena

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Introduction

This guide provides step-by-step instructions for running AMAAthena through GANGA. Users will run GANGA on a NIKHEF desktop (e.g. ribble.nikhef.nl) and submit AMAAthena jobs to Stoomboot (a PBS cluster) and to the LCG.

AMAAthena is an Athena package providing a framework for modular analysis. GANGA is an official tool for ATLAS distributed data analysis.

Preparation

Please follow https://twiki.cern.ch/twiki/bin/view/Atlas/AMAMainPage to setup CMT and checkout AMAAthena package.

Starting GANGA

Typing the following commands within the directory: PhysicsAnalysis/AnalysisCommon/AMA/AMAAthena/cmt in a clean shell environment (i.e. no environment setup for Athena and CMT). 

% source /project/atlas/nikhef/dq2/dq2_setup.sh.NIKHEF
% export DPNS_HOST=tbn18.nikhef.nl
% export LFC_HOST=lfc-atlas.grid.sara.nl
% source /project/atlas/nikhef/ganga/etc/setup.[c]sh
% ganga --config-path=/project/atlas/nikhef/ganga/config/Atlas.ini.nikhef

Every time you start with a clean shell, and you'll need to setup ganga with the lines given right above.

If you start ganga for the first time, type 

ganga -g

This creates a file, named '.gangarc'. Ganga will produce quite a lot of files during its runtime. The directory of the files can be changed by editing the '.gangarc' file and add the following line 

gangadir = /project/atlas/Users/yourusernamehere/gangadir

Now we can start the first time Ganga, by simply typing 

ganga

typing 

jobs

will give you an opverview of your jobs. Jobs can be killed and removed via 

jobs(JOBID).remove()

To quit again, just press CTRL-D.

HelloWorld jobs

Trying the following commands in the Ganga shell to gets your hands dirty :) 

In [n]: j = Job()
In [n]: j.backend=PBS()
In [n]: j.submit()
In [n]: jobs

In [n]: j = j.copy()
In [n]: j.backend=LCG()
In [n]: j.submit()
In [n]: jobs

GANGA magic functions for cmtsetup

Inside GANGA, one could deal with the complex CMT setup with two magic functions.

The following example shows how to setup the CMT environment for Athena 14.2.20 in 32 bit mode. 

In [n]: config.Athena.CMTHOME = '/path/to/your/cmthome'
In [n]: cmtsetup 14.2.20,32
In [n]: setup

Running AMAAthena in GANGA

The example below assumes:

  1. Users have the following Athena job option files in the run directory of the AMAAthena package
    • AMAAthena_jobOptions.py
    • Trigger_jobOptions.py
  2. Users have the following AMA driver configuration files in the run directory of the AMAAthena package
    • exampleaod.conf
    • reader.conf
  3. Analysis is performed on dataset: fdr08_run2.0052280.physics_Muon.merge.AOD.o3_f8_m10

Creating new GANGA job

In [n]: j = Job()

Setting application

In [n]: j.application = AMAAthena()
In [n]: j.application.option_file += [ File('../run/AMAAthena_jobOptions.py'), File('../run/Trigger_jobOptions.py') ]
In [n]: j.application.driver_config.config_file = File('../run/exampleaod.conf')
In [n]: j.application.driver_config.include_file += [ File('../run/reader.conf') ]
In [n]: j.application.prepare()

Setting input data

  • StagerDataset When using the StagerDataset, the AMAAthena job will use the Athena FileStager to copy dataset files from a grid storage. 
    In [n]: j.inputdata = StagerDataset()
In [n]: j.inputdata.dataset += [ 'fdr08_run2.0052280.physics_Muon.merge.AOD.o3_f8_m10' ]
  • DQ2Dataset When using the DQ2Dataset, GANGA will handle the file access externally from Athena. 
    In [n]: j.inputdata = DQ2Dataset()
In [n]: j.inputdata.dataset += [ 'fdr08_run2.0052280.physics_Muon.merge.AOD.o3_f8_m10' ]
In [n]: j.inputdata.type = 'DQ2_DOWNLOAD'

Setting job splitter (optional)

The examples below ask each subjob to process on 2 files in maximum.

  • using StagerJobSplitter with StagerDataset 
    In [n]: j.splitter = StagerJobSplitter()
In [n]: j.splitter.numfiles = 2
  • using DQ2JobSplitter with DQ2Dataset for jobs running on LCG 
    In [n]: j.splitter = DQ2JobSplitter()
In [n]: j.splitter.numfiles = 2

Setting computing backend

  • using Stoomboot cluster 
    In [n]: j.backend = PBS()

    For a long running job, please also do 

    In [n]: j.backend.queue = 'qlong'

    to avoid running over the walltime limitation of the default PBS queue.

  • using LCG 
    In [n]: j.backend = LCG()

    Be careful StagerDataset is not yet supported for jobs on LCG. Please using DQ2Dataset instead. For example: 

    1. In [n]: j.inputdata = DQ2Dataset()
In [n]: j.inputdata.dataset = []

    Be careful Starting from Ganga 5.0.7, jobs submitted to LCG backend require users to specify one of the following requirements: 

    1. In [n]: j.backend.requirements.cloud = 'NL'
In [n]: j.splitter = DQ2JobSpliter()

      meaning that let Ganga distribute the jobs within a particular computing cloud. 

    2. In [n]: j.backend.CE = 'gazon.nikhef.nl:2119/jobmanager-pbs-atlas'

      meaning that I want the job to be run on a particular computing element (I know what I am doing now!!).

Submitting job

In [n]: j.submit()

After job submission

Checking job status

GANGA automatically polls the up-to-date status of your jobs and updates local repository accordingly. A notification will pop up to the user when the job status is changed.

In addition, you can get a job summary table by: 

In [n]: jobs

or a summary table for subjobs: 

In [n]: j.subjobs

Result and output merging

For the moment, the completed (sub-)job returns an root summary file. The file is stored in the summary sub-directory in the job's output directory.

For jobs using StagerJobSplitter, the RootMerger is automatically attached with the job so that when the whole job is completed, the summary root files from sub-jobs are merged together.

For jobs using DQ2Dataset, the merging process can be done manually when the whole job is completed. For example, assuming each sub-job produces a root summary file called summary/summary_mySample_confFile_exampleaod.conf_nEvts_1000.root. To merge them, one can do: 

In [n]: merger = RootMerger()
In [n]: merger.files += ['summary/summary_mySample_confFile_exampleaod.conf_nEvts_1000.root']
In [n]: merger.overwrite = True
In [n]: merger.ignorefailed = True
In [n]: merger.merge(j)

The merged root file has the same name and it will be created in the job's outputdir.

Killing and removing jobs

You can kill a job by calling 

In [n]: j.kill()

or remove a job by 

In [n]: j.remove()

Advance usage

Restricting max. number of events

In [n]: j.application.max_events = '1000'

Running on more than one dataset

The StagerDataset supports wildcard specification in the dataset name. For example, if you want to run on all FDR2 Muon stream datasets, you can set the inputdata like the following: 

In [n]: j.inputdata.dataset += ['fdr08_run2*physics_Muon*']

Dealing with failed sub-jobs

It's very possible to have some failed sub-jobs. In this case, GANGA reports the whole job as failed. There is no necessary to resubmit the whole job, you can just resubmit the failed subjobs. Assuming you have a failed job, j: 

In [n]: j.subjobs.select(status='failed').resubmit()

Failing jobs manually

Some unexpected issues in the job may cause Ganga unable to update the job status to failed as it should be. In this case, you can manually fail the job in force 

In [n]: j.force_status("failed")

This can avoid Ganga to keep polling the status of the problematic job which may be gone from the backend system.

The basic trouble shooting

GANGA tries to bring the stdout/err back to the client side even when the job is failed remotely on the Grid. So for the failed jobs, you can check them as the following for trouble shooting: 

In [n]: j.peek('stdout','less')
In [n]: j.peek('stderr','cat')

or 

In [n]: j.peek('stdout.gz','zcat')
In [n]: j.peek('stdout.gz','zcat')

for the LCG jobs.

More information

Known issues/ToDo items

  • StagerDataset not supported for jobs on LCG

--Hclee 16:17, 13 Aug 2008 (MET DST)

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