def utilisation(self):
if self._utilisation is not None:
return self._utilisation
self._utilisation = compute_load(self.df,
col_begin='starting_time',
col_end='finish_time',
col_cumsum='proc_alloc')
return self._utilisation
def utilisation(self):
if self._utilisation is not None:
return self._utilisation
self._utilisation = compute_load(self.df,
col_begin='starting_time',
col_end='finish_time',
col_cumsum='proc_alloc')
return self._utilisation
def queue(self):
'''
Calculate cluster queue size over time in number of procs.
:returns:
a time indexed serie that contain the number of used processors
'''
# Do not re-compute everytime
if self._queue is not None:
return self._queue
proc = "requested_number_of_processors"
self._queue = compute_load(self.df, 'submission_time', 'starting_time',
proc)
return self._queue
def queue(self):
'''
Calculate cluster queue size over time in number of procs.
:returns:
a time indexed serie that contain the number of used processors
'''
# Do not re-compute everytime
if self._queue is not None:
return self._queue
proc = "requested_number_of_resources"
self._queue = compute_load(self.df, 'submission_time', 'starting_time',
proc)
return self._queue
def utilisation(self):
'''
Calculate cluster utilisation over time:
nb procs used / nb procs available
:returns:
a time indexed serie that contain the number of used processors
It is based on real time
TODO: Add ID list of jobs running and ID list of jobs in queue to
the returned dataframe
'''
# Do not re-compute everytime
if self._utilisation is not None:
return self._utilisation
self._utilisation = compute_load(self.df, 'starting_time',
'finish_time', 'proc_alloc',
self.UnixStartTime)
return self._utilisation
def queue(self):
'''
Calculate cluster queue size over time in number of procs.
:returns:
a time indexed serie that contain the number of used processors
It is based on real time if UnixStartTime is defined
'''
# Do not re-compute everytime
if self._queue is not None:
return self._queue
# sometimes "proc_req" is not provided
if (self.df.proc_req == -1).any():
proc = "proc_alloc"
else:
proc = "proc_req"
self._queue = compute_load(self.df, 'submission_time', 'starting_time',
proc, self.UnixStartTime)
return self._queue
def queue(self):
'''
Calculate cluster queue size over time in number of procs.
:returns:
a time indexed serie that contain the number of used processors
It is based on real time if UnixStartTime is defined
'''
# Do not re-compute everytime
if self._queue is not None:
return self._queue
# sometimes "proc_req" is not provided
if (self.df.proc_req == -1).any():
proc = "proc_alloc"
else:
proc = "proc_req"
self._queue = compute_load(self.df, 'submission_time', 'starting_time',
proc, self.UnixStartTime)
return self._queue
def utilisation(self):
'''
Calculate cluster utilisation over time:
nb procs used / nb procs available
:returns:
a time indexed serie that contain the number of used processors
It is based on real time
TODO: Add ID list of jobs running and ID list of jobs in queue to
the returned dataframe
'''
# Do not re-compute everytime
if self._utilisation is not None:
return self._utilisation
self._utilisation = compute_load(self.df,
'starting_time',
'finish_time',
'proc_alloc', self.UnixStartTime)
return self._utilisation
