mirror of
https://github.com/valitydev/yandex-tank.git
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177 lines
4.7 KiB
Python
177 lines
4.7 KiB
Python
from itertools import cycle, chain
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from util import parse_duration
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import re
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class InstanceLP(object):
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'''Base class for all instance plans'''
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def __init__(self, duration=0):
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self.duration = float(duration)
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def get_duration(self):
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'''Return step duration in milliseconds'''
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return self.duration
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def get_rps_list(self):
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return []
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class Empty(InstanceLP):
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'''Load plan with no timestamp (for instance_schedule)'''
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def __iter__(self):
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return cycle([0])
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class Composite(InstanceLP):
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'''Load plan with multiple steps'''
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def __init__(self, steps):
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self.steps = steps
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def __iter__(self):
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base = 0
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for step in self.steps:
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for ts in step:
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yield int(ts + base)
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base += step.get_duration()
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for item in cycle([0]):
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yield item
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def get_duration(self):
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'''Return total duration in milliseconds'''
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return sum(step.get_duration() for step in self.steps)
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def get_rps_list(self):
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return list(chain.from_iterable(step.get_rps_list() for step in self.steps))
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class Line(InstanceLP):
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'''
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Starts some instances linearly
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>>> from util import take
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>>> take(10, Line(5, 5000))
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[1000, 2000, 3000, 4000, 5000]
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'''
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def __init__(self, instances, duration):
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self.instances = instances
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self.duration = float(duration)
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def __iter__(self):
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interval = float(self.duration) / self.instances
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return (int(i * interval) for i in xrange(1, self.instances + 1))
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class Ramp(InstanceLP):
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'''
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Starts <instance_count> instances, one each <interval> seconds
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>>> from util import take
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>>> take(10, Ramp(5, 5000))
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[0, 5000, 10000, 15000, 20000]
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'''
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def __init__(self, instance_count, interval):
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self.duration = instance_count * interval
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self.instance_count = instance_count
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self.interval = interval
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def __iter__(self):
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return ((int(i * self.interval) for i in xrange(0, self.instance_count)))
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class Wait(InstanceLP):
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'''
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Don't start any instances for the definded duration
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'''
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def __init__(self, duration):
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self.duration = duration
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def __iter__(self):
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return iter([])
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class Stairway(InstanceLP):
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def __init__(self, minrps, maxrps, increment, duration):
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raise NotImplementedError(
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'We have no support for this load type in instances_schedule yet')
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class StepFactory(object):
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@staticmethod
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def line(params):
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template = re.compile('(\d+),\s*(\d+),\s*([0-9.]+[dhms]?)+\)')
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minrps, maxrps, duration = template.search(params).groups()
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# note that we don't use minrps at all and use maxrps
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# as the number of instances we gonna start
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return Line(int(maxrps) - int(minrps), parse_duration(duration))
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@staticmethod
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def ramp(params):
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template = re.compile('(\d+),\s*([0-9.]+[dhms]?)+\)')
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instances, interval = template.search(params).groups()
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return Ramp(int(instances), parse_duration(interval))
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@staticmethod
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def wait(params):
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template = re.compile('([0-9.]+[dhms]?)+\)')
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duration = template.search(params).groups()[0]
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return Wait(parse_duration(duration))
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@staticmethod
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def stairway(params):
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template = re.compile('(\d+),\s*(\d+),\s*(\d+),\s*([0-9.]+[dhms]?)+\)')
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minrps, maxrps, increment, duration = template.search(params).groups()
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return Stairway(int(minrps), int(maxrps), int(increment), parse_duration(duration))
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@staticmethod
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def produce(step_config):
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_plans = {
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'line': StepFactory.line,
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'step': StepFactory.stairway,
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'ramp': StepFactory.ramp,
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'wait': StepFactory.wait,
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}
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load_type, params = step_config.split('(')
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load_type = load_type.strip()
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if load_type in _plans:
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return _plans[load_type](params)
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else:
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raise NotImplementedError(
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'No such load type implemented for instances_schedule: "%s"' % load_type)
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def create(instances_schedule):
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'''
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Creates load plan timestamps generator
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>>> from util import take
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>>> take(7, create(['ramp(5, 5s)']))
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[0, 5000, 10000, 15000, 20000, 0, 0]
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>>> take(12, create(['ramp(5, 5s)', 'wait(5s)', 'ramp(5,5s)']))
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[0, 5000, 10000, 15000, 20000, 30000, 35000, 40000, 45000, 50000, 0, 0]
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>>> take(7, create(['wait(5s)', 'ramp(5, 0)']))
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[5000, 5000, 5000, 5000, 5000, 0, 0]
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'''
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if len(instances_schedule) > 1:
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steps = [StepFactory.produce(step_config)
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for step_config in instances_schedule]
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else:
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steps = [StepFactory.produce(instances_schedule[0])]
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return Composite(steps)
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