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#
# Licensed under the Apache License, Version 2.0 (the "License"); you may
# not use this file except in compliance with the License. You may obtain
# a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
# WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
# License for the specific language governing permissions and limitations
# under the License.
from cliff import lister
from gnocchiclient import utils
class CliAggregates(lister.Lister):
"""Get measurements of aggregated metrics."""
COLS = ('name', 'timestamp', 'granularity', 'value')
def get_parser(self, prog_name):
parser = super(CliAggregates, self).get_parser(prog_name)
parser.add_argument("operations",
help="Operations to apply to time series")
utils.add_query_argument("search", parser, nargs="?", default=None)
parser.add_argument("--resource-type", default="generic",
help="Resource type to query"),
parser.add_argument("--start",
help="beginning of the period")
parser.add_argument("--stop",
help="end of the period")
parser.add_argument("--granularity",
help="granularity to retrieve")
parser.add_argument("--needed-overlap", type=float,
help=("percentage of overlap across datapoints"))
parser.add_argument("--groupby",
action='append',
help="Attribute to use to group resources"),
parser.add_argument("--fill",
help=("Value to use when backfilling timestamps "
"with missing values in a subset of series. "
"Value should be a float or 'null'.")),
parser.add_argument("--use-history", default=False,
help=("Indicates if Gnocchi server should respond "
"with the resource tags history for the "
"aggregation query. If set to `False`, only "
"the latest tag values will be returned. "
"Otherwise, the measures will be split "
"proportionally if a tag has been changed "
"in the `granularity` requested.")
)
return parser
def take_action(self, parsed_args):
aggregates = utils.get_client(self).aggregates.fetch(
operations=parsed_args.operations,
resource_type=parsed_args.resource_type,
search=parsed_args.search,
start=parsed_args.start,
stop=parsed_args.stop,
granularity=parsed_args.granularity,
needed_overlap=parsed_args.needed_overlap,
groupby=parsed_args.groupby,
fill=parsed_args.fill,
use_history=parsed_args.use_history
)
if parsed_args.search and parsed_args.groupby:
ms = []
for g in aggregates:
group_name = ", ".join("%s: %s" % (k, g['group'][k])
for k in sorted(g['group']))
for row in self.flatten_measures(g["measures"]["measures"]):
ms.append((group_name, ) + row)
return ('group',) + self.COLS, ms
return self.COLS, list(self.flatten_measures(aggregates["measures"]))
@classmethod
def flatten_measures(cls, data, labels=None):
if labels is None:
labels = tuple()
for key in data:
if isinstance(data[key], list):
name = "/".join(labels + (key, ))
for ts, g, value in data[key]:
yield (name, ts.isoformat(), g, value)
else:
for row in cls.flatten_measures(data[key], labels + (key,)):
yield row
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