def test_uniq(self):
class DriverA(object):
source = 'class_A'
func = 'func_A'
param = 'param_A'
class DriverB(object):
source = 'class_A'
func = 'func_A'
param = 'param_B'
class DriverC(object):
source = 'class_A'
func = 'func_C'
param = 'param_C'
driver_list = [DriverA(), DriverB(), DriverC()]
uniq_driver_a = utils.uniq(driver_list, ['source'])
self.assertEqual(len(uniq_driver_a), 1)
uniq_driver_b = utils.uniq(driver_list, ['source', 'func'])
self.assertEqual(len(uniq_driver_b), 2)
uniq_driver_c = utils.uniq(driver_list, ['source', 'func', 'param'])
self.assertEqual(len(uniq_driver_c), 3)
def get_all(self,
q=None,
meter=None,
groupby=None,
period=None,
aggregate=None):
"""Retrieve all statistics for all meters
:param q: Filter rules for the statistics to be returned.
"""
rbac.enforce('compute_statistics', pecan.request)
q = q or []
meter = meter or []
groupby = groupby or []
aggregate = aggregate or []
if period and period < 0:
raise base.ClientSideError(_("Period must be positive."))
g = meters._validate_groupby_fields(groupby)
# TO DO: break out the meter names and invoke multiple calls
kwargs = v2_utils.query_to_kwargs(q, storage.SampleFilter.__init__)
aggregate = utils.uniq(aggregate, ['func', 'param'])
# Find the original timestamp in the query to use for clamping
# the duration returned in the statistics.
start = end = None
for i in q:
if i.field == 'timestamp' and i.op in ('lt', 'le'):
end = timeutils.parse_isotime(i.value).replace(tzinfo=None)
elif i.field == 'timestamp' and i.op in ('gt', 'ge'):
start = timeutils.parse_isotime(i.value).replace(tzinfo=None)
ret = []
kwargs['meter'] = meter
f = storage.SampleFilter(**kwargs)
try:
computed = pecan.request.storage_conn.get_meter_statistics(
f, period, g, aggregate)
dbStats = [
ScopedStatistics(start_timestamp=start,
end_timestamp=end,
**c.as_dict()) for c in computed
]
ret += dbStats
except OverflowError:
LOG.exception("Problem processing meters %s" % meter)
return ret
def statistics(self, q=None, groupby=None, period=None, aggregate=None):
"""Computes the statistics of the samples in the time range given.
:param q: Filter rules for the data to be returned.
:param groupby: Fields for group by aggregation
:param period: Returned result will be an array of statistics for a
period long of that number of seconds.
:param aggregate: The selectable aggregation functions to be applied.
"""
rbac.enforce('compute_statistics', pecan.request)
q = q or []
groupby = groupby or []
aggregate = aggregate or []
if period and period < 0:
raise base.ClientSideError(_("Period must be positive."))
kwargs = v2_utils.query_to_kwargs(q, storage.SampleFilter.__init__)
kwargs['meter'] = self.meter_name
f = storage.SampleFilter(**kwargs)
g = _validate_groupby_fields(groupby)
aggregate = utils.uniq(aggregate, ['func', 'param'])
# Find the original timestamp in the query to use for clamping
# the duration returned in the statistics.
start = end = None
for i in q:
if i.field == 'timestamp' and i.op in ('lt', 'le'):
end = timeutils.parse_isotime(i.value).replace(
tzinfo=None)
elif i.field == 'timestamp' and i.op in ('gt', 'ge'):
start = timeutils.parse_isotime(i.value).replace(
tzinfo=None)
try:
computed = pecan.request.storage_conn.get_meter_statistics(
f, period, g, aggregate)
LOG.debug(_('computed value coming from %r'),
pecan.request.storage_conn)
return [Statistics(start_timestamp=start,
end_timestamp=end,
**c.as_dict())
for c in computed]
except OverflowError as e:
params = dict(period=period, err=e)
raise base.ClientSideError(
_("Invalid period %(period)s: %(err)s") % params)
def statistics(self, q=None, groupby=None, period=None, aggregate=None):
"""Computes the statistics of the samples in the time range given.
:param q: Filter rules for the data to be returned.
:param groupby: Fields for group by aggregation
:param period: Returned result will be an array of statistics for a
period long of that number of seconds.
:param aggregate: The selectable aggregation functions to be applied.
"""
rbac.enforce('compute_statistics', pecan.request)
q = q or []
groupby = groupby or []
aggregate = aggregate or []
if period and period < 0:
raise base.ClientSideError(_("Period must be positive."))
kwargs = v2_utils.query_to_kwargs(q, storage.SampleFilter.__init__)
kwargs['meter'] = self.meter_name
f = storage.SampleFilter(**kwargs)
g = _validate_groupby_fields(groupby)
aggregate = utils.uniq(aggregate, ['func', 'param'])
# Find the original timestamp in the query to use for clamping
# the duration returned in the statistics.
start = end = None
for i in q:
if i.field == 'timestamp' and i.op in ('lt', 'le'):
end = timeutils.parse_isotime(i.value).replace(tzinfo=None)
elif i.field == 'timestamp' and i.op in ('gt', 'ge'):
start = timeutils.parse_isotime(i.value).replace(tzinfo=None)
try:
computed = pecan.request.storage_conn.get_meter_statistics(
f, period, g, aggregate)
LOG.debug(_('computed value coming from %r'),
pecan.request.storage_conn)
return [
Statistics(start_timestamp=start,
end_timestamp=end,
**c.as_dict()) for c in computed
]
except OverflowError as e:
params = dict(period=period, err=e)
raise base.ClientSideError(
_("Invalid period %(period)s: %(err)s") % params)