def distribution_with_subsampling(num:int=1,
interval:int=100,
pause:float=None,
duty:float=None,
subinterval:int=None,
vms=None):
""" Intervals are in ms. Duty cycle is in (0,1] range. """
from qemu import ipcistat # lazy loading
standard = defaultdict(list)
withskip = defaultdict(list)
assert not (pause and duty), "accepts either pause or duty"
if duty:
pause = (interval / duty) / 1000 # in seconds
elif not pause:
pause = 0.1
for _ in range(num):
print("step 1: {} out of {}".format(_+1, num))
# STEP 1: normal freezing approach
for vm in vms:
sleep(pause)
vm.exclusive()
try:
ipc = vm.ipcstat(interval)
standard[vm.bname].append(ipc)
#print("saving quasi to", vm.bname, ipc)
except NotCountedError:
print("missed data point for", vm.bname)
pass
vm.shared()
# STEP 2: approach with sub-sampling and skip
#print("step 2: {} out of {}".format(_+1, num))
for vm in vms:
sleep(pause)
try:
vm.exclusive()
ipc = ipcistat(vm, interval=interval, subinterval=subinterval)
withskip[vm.bname].append(ipc)
#print("saving sub-sampled to", vm.bname, ipc)
except NotCountedError:
print("missed data point for", vm.bname)
pass
finally:
vm.shared()
return Struct(standard=standard, withskip=withskip)
def distribution_with_subsampling2(num:int=1,
interval:int=100,
pause:float=None,
duty:float=None,
subinterval:int=None,
vms=None):
""" Intervals are in ms. Duty cycle is in (0,1] range. """
from qemu import ipcistat # lazy loading
assert not (pause and duty), "accepts either pause or duty"
if duty:
pause = (interval / duty) / 1000 # in seconds
elif not pause:
pause = 0.1
isolated = defaultdict(list)
frozen = defaultdict(list)
batch_size = 10
assert num % batch_size == 0, \
"number of samples should divide by 10, got %s" % num
iterations = num // batch_size
for i in range(iterations):
print("interval %s: %s out of %s" % (interval, i, iterations))
isolated_sampling(num=batch_size, interval=interval, pause=pause, result=isolated, vms=vms)
for i in range(num):
for vm in vms:
sleep(pause)
try:
vm.exclusive()
ipc = ipcistat(vm, interval=interval, subinterval=subinterval)
frozen[vm.bname].append(ipc)
#print("saving sub-sampled to", vm.bname, ipc)
except NotCountedError:
print("missed data point for", vm.bname)
pass
finally:
vm.shared()
freezing_sampling(num=batch_size, interval=interval, pause=pause, result=frozen, vms=vms)
return Struct(isolated=isolated, frozen=frozen)
