def fitness(self, job, resource_conf):
# Simply call fitness function from super class and add
# queued time fitness value afterwards
job_fitness = BestFitScheduler.fitness(self, job, resource_conf)
self.logger.debug('fitness: %f without queue time', job_fitness)
queue_time = time.mktime(time.gmtime())\
- time.mktime(job['QUEUED_TIMESTAMP'])
expire_after = self.conf.expire_after
if expire_after == 0:
# No risk of expiry so we use pure aging
job_fitness += queue_time * self.age_mult
self.logger.debug('fitness: %f with queue time %f',
job_fitness, queue_time)
else:
# Aging relies on risk of job expiry
expire_risk = 1 - abs(expire_after - queue_time)\
/ expire_after
job_fitness += expire_risk * self.expire_mult
# self.logger.level = 10
self.logger.debug('fitness: %f with expire risk %f',
job_fitness, expire_risk)
# self.logger.level = 20
return job_fitness
def fitness(self, job, resource_conf):
# Simply call fitness function from super class and add
# absolute and relative queue time fitness bonus afterwards
job_fitness = BestFitScheduler.fitness(self, job, resource_conf)
self.logger.debug('fitness: %f without time bonus', job_fitness)
queue_time = time.mktime(time.gmtime()) - \
time.mktime(job['QUEUED_TIMESTAMP'])
job_time = int(job.get('CPUTIME', 60))
# Force rel_bonus between 0 and 1 to avoid very short job "gaming"
rel_bonus = 10.0 / max(job_time, 10)
# Always apply a mix of absolute and relative aging
job_fitness += self.age_mult * queue_time * (1 + rel_bonus)
self.logger.debug('fitness: %f with queue / job time %f / %f (%f)',
job_fitness, queue_time, job_time, rel_bonus)
return job_fitness
def __init__(self, logger, config):
BestFitScheduler.__init__(self, logger, config)
self.name = 'FairFitScheduler'
def __init__(self, logger, config):
BestFitScheduler.__init__(self, logger, config)
self.name = 'FairFitScheduler'