Cluster Class Reference

Inheritance diagram for Cluster:

Public Member Functions
def	__init__ (self)
	The default constructor.
def	adjust_path (self, str path)
	This method can be used if path names are different on submission and execution hosts.
def	available (self)
	The cluster should always be available to accept new jobs.
def	execute (self, Script job, options="", dry=False, tag="current")
	Takes a Script object and a string with options and runs it on the cluster, either with ROOT or with basf2, depending on the file type.
def	is_job_finished (self, Script job)
	Checks whether the '.done'-file has been created for a job.

Static Public Member Functions
def	is_supported ()
def	name ()
def	description ()

Public Attributes
	native_spec
	The command to submit a job.
	requirement_vmem
	required vmem by the job in GB, required on DESY NAF, otherwise jobs get killed due to memory consumption
	requirement_storage
	the storage IO in GB which can be performed by each job.
	queuename
	Queue best suitable for execution at DESY NAF.

Detailed Description

A class that provides the controls for running jobs on a (remote)
Sun Grid Engine cluster. It provides two methods:
- is_job_finished(job): Returns True or False, depending on whether the job
    has finished execution
- execute(job): Takes a job and executes it by sending it to the cluster

Definition at line 19 of file clustercontroldrmaa.py.

Constructor & Destructor Documentation

__init__()

def __init__

(

self

)

The default constructor.

• Holds the current working directory, which is also the location of the shellscripts that are being sent to the cluster.
• Initializes a logger which writes to validate_basf2.py's log.
• Finds the revision of basf2 that will be set up on the cluster.

Reimplemented from ClusterBase.

Definition at line 62 of file clustercontroldrmaa.py.

    def __init__(self):
        """!
        The default constructor.
        - Holds the current working directory, which is also the location of
          the shellscripts that are being sent to the cluster.
        - Initializes a logger which writes to validate_basf2.py's log.
        - Finds the revision of basf2 that will be set up on the cluster.
        """
 
        
        self.native_spec = (
            "-l h_vmem={requirement_vmem}G,h_fsize={"
            "requirement_storage}G "
            "-q {queuename} -V"
        )
 
        
        self.requirement_vmem = 4
 
        
        self.requirement_storage = 50
 
        
        self.queuename = "short.q"
 
        # call the base constructor, which will setup the batch cluster
        # common stuff
        super().__init__()
 

Member Function Documentation

adjust_path()

def adjust_path	(		self,
		str	path
	)

This method can be used if path names are different on submission and execution hosts.

Parameters

path	The past that needs to be adjusted

Returns

: The adjusted path

Reimplemented from ClusterBase.

Definition at line 96 of file clustercontroldrmaa.py.

    def adjust_path(self, path: str):
        """!
        This method can be used if path names are different on submission
        and execution hosts.
        @param path: The past that needs to be adjusted
        @return: The adjusted path
        """
 
        return path
 

available()

def available

(

self

)

The cluster should always be available to accept new jobs.

Returns

: Will always return True if the function can be called

Definition at line 107 of file clustercontroldrmaa.py.

    def available(self):
        """!
        The cluster should always be available to accept new jobs.
        @return: Will always return True if the function can be called
        """
 
        return True
 

description()

def description ( )

static

Returns description of this job control

Definition at line 56 of file clustercontroldrmaa.py.

    def description():
        """
        Returns description of this job control
        """
        return "Batch submission via the drmaa interface to Grid Engine"
 

execute()

def execute	(		self,
		Script	job,
			options = "",
			dry = False,
			tag = "current"
	)

Takes a Script object and a string with options and runs it on the cluster, either with ROOT or with basf2, depending on the file type.

Parameters

job	The steering file object that should be executed
options	Options that will be given to the basf2 command
dry	Whether to perform a dry run or not
tag	The folder within the results directory

Returns

: None

Definition at line 115 of file clustercontroldrmaa.py.

    def execute(self, job: Script, options="", dry=False, tag="current"):
        """!
        Takes a Script object and a string with options and runs it on the
        cluster, either with ROOT or with basf2, depending on the file type.
 
        @param job: The steering file object that should be executed
        @param options: Options that will be given to the basf2 command
        @param dry: Whether to perform a dry run or not
        @param tag: The folder within the results directory
        @return: None
        """
 
        # import here first so the whole module can also be imported on python
        # installations which have no drmaa at all
        import drmaa
 
        print(str(drmaa.Session()))
 
        with drmaa.Session() as session:
            print("got session ")
            print(str(session))
 
            shell_script_name = self.prepareSubmission(job, options, tag)
 
            # native specification with all the good settings for the batch
            # server
            native_spec_string = self.native_spec.format(
                requirement_storage=self.requirement_storage,
                requirement_vmem=self.requirement_vmem,
                queuename=self.queuename,
            )
            print(
                f"Creating job template for wrapper script {shell_script_name}"
            )
            jt = session.createJobTemplate()
            jt.remoteCommand = shell_script_name
            jt.joinFiles = True
            jt.nativeSpecification = native_spec_string
 
            if not dry:
                jobid = session.runJob(jt)
                self.logger.debug(
                    f"Script {job.name} started with job id {jobid}"
                )
                job.job_id = jobid
 
            session.deleteJobTemplate(jt)
        return
 

is_job_finished()

def is_job_finished	(		self,
		Script	job
	)

Checks whether the '.done'-file has been created for a job.

If so, it returns True, else it returns False. Also deletes the .done-File once it has returned True.

Parameters

job	The job of which we want to know if it finished

Returns

: (True if the job has finished, exit code). If we can't find the exit code in the '.done'-file, the returncode will be -654. If the job is not finished, the exit code is returned as 0.

Definition at line 164 of file clustercontroldrmaa.py.

    def is_job_finished(self, job: Script):
        """!
        Checks whether the '.done'-file has been created for a job. If so, it
        returns True, else it returns False.
        Also deletes the .done-File once it has returned True.
 
        @param job: The job of which we want to know if it finished
        @return: (True if the job has finished, exit code). If we can't find the
            exit code in the '.done'-file, the returncode will be -654.
            If the job is not finished, the exit code is returned as 0.
        """
 
        # import here first so the whole module can also be imported on python
        # installations which have no drmaa at all
        import drmaa
 
        if job.job_id is None:
            print(
                "Job has not been started with cluster drmaaa because "
                "job id is missing"
            )
            sys.exit(0)
 
        with drmaa.Session() as session:
 
            # some batch server will forget completed jobs right away
            try:
                status = session.jobStatus(job.job_id)
            except drmaa.errors.InvalidJobException:
                print(
                    f"Job info for jobid {job.job_id} cannot be retrieved, assuming job has terminated"
                )
 
                (donefile_exists, donefile_returncode) = self.checkDoneFile(job)
 
                # always return the job es complete even if there is no done
                #  file at this point tho job is also not longer
                # running/queued on the cluster
                return [True, donefile_returncode]
 
            # Return that the job is finished + the return code for it
            # depending when we look for the job this might never be used,
            # because the jobs disappear from qstat before we can query them
            #  ..
            if status == drmaa.JobState.DONE:
                # todo: return code
                return [True, 0]
            if status == drmaa.JobState.FAILED:
                return [True, 1]
 
            return [False, 0]

is_supported()

def is_supported ( )

static

Check if qsub is available

Definition at line 29 of file clustercontroldrmaa.py.

    def is_supported():
        """
        Check if qsub is available
        """
        try:
            import drmaa  # noqa
 
            return True
        except ImportError:
            print(
                "drmaa library is not installed, please use 'pip3 install "
                "drmaa'"
            )
            return False
        except RuntimeError as re:
            print("drmaa library not properly configured")
            print(str(re))
            return False
 

name()

def name ( )

static

Returns name of this job control

Definition at line 49 of file clustercontroldrmaa.py.

    def name():
        """
        Returns name of this job control
        """
        return "cluster-drmaa"
 

Member Data Documentation

native_spec

native_spec

The command to submit a job.

'LOGFILE' will be replaced by the actual log file name

Definition at line 73 of file clustercontroldrmaa.py.

queuename

queuename

Queue best suitable for execution at DESY NAF.

Definition at line 89 of file clustercontroldrmaa.py.

requirement_storage

requirement_storage

the storage IO in GB which can be performed by each job.

By default, this is 3GB at DESY which is to small for some validation scripts

Definition at line 86 of file clustercontroldrmaa.py.

requirement_vmem

requirement_vmem

required vmem by the job in GB, required on DESY NAF, otherwise jobs get killed due to memory consumption

Definition at line 81 of file clustercontroldrmaa.py.

---

The documentation for this class was generated from the following file:

• validation/scripts/clustercontroldrmaa.py