/usr/lib/python2.7/dist-packages/gnocchi/storage/__init__.py is in python-gnocchi 3.0.4-3.
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#
# Copyright © 2014-2015 eNovance
#
# 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.
import operator
from oslo_config import cfg
from oslo_log import log
from stevedore import driver
from gnocchi import exceptions
from gnocchi import indexer
OPTS = [
cfg.StrOpt('driver',
default='file',
help='Storage driver to use'),
cfg.IntOpt('metric_processing_delay',
default=60,
help="How many seconds to wait between "
"scheduling new metrics to process"),
cfg.IntOpt('metric_reporting_delay',
default=120,
help="How many seconds to wait between "
"metric ingestion reporting"),
cfg.IntOpt('metric_cleanup_delay',
default=300,
help="How many seconds to wait between "
"cleaning of expired data"),
]
LOG = log.getLogger(__name__)
class Measure(object):
def __init__(self, timestamp, value):
self.timestamp = timestamp
self.value = value
def __iter__(self):
"""Allow to transform measure to tuple."""
yield self.timestamp
yield self.value
class Metric(object):
def __init__(self, id, archive_policy,
created_by_user_id=None,
created_by_project_id=None,
name=None,
resource_id=None):
self.id = id
self.archive_policy = archive_policy
self.created_by_user_id = created_by_user_id
self.created_by_project_id = created_by_project_id
self.name = name
self.resource_id = resource_id
def __repr__(self):
return '<%s %s>' % (self.__class__.__name__, self.id)
def __str__(self):
return str(self.id)
def __eq__(self, other):
return (isinstance(other, Metric)
and self.id == other.id
and self.archive_policy == other.archive_policy
and self.created_by_user_id == other.created_by_user_id
and self.created_by_project_id == other.created_by_project_id
and self.name == other.name
and self.resource_id == other.resource_id)
__hash__ = object.__hash__
class StorageError(Exception):
pass
class InvalidQuery(StorageError):
pass
class MetricDoesNotExist(StorageError):
"""Error raised when this metric does not exist."""
def __init__(self, metric):
self.metric = metric
super(MetricDoesNotExist, self).__init__(
"Metric %s does not exist" % metric)
class AggregationDoesNotExist(StorageError):
"""Error raised when the aggregation method doesn't exists for a metric."""
def __init__(self, metric, method):
self.metric = metric
self.method = method
super(AggregationDoesNotExist, self).__init__(
"Aggregation method '%s' for metric %s does not exist" %
(method, metric))
class GranularityDoesNotExist(StorageError):
"""Error raised when the granularity doesn't exist for a metric."""
def __init__(self, metric, granularity):
self.metric = metric
self.granularity = granularity
super(GranularityDoesNotExist, self).__init__(
"Granularity '%s' for metric %s does not exist" %
(granularity, metric))
class MetricAlreadyExists(StorageError):
"""Error raised when this metric already exists."""
def __init__(self, metric):
self.metric = metric
super(MetricAlreadyExists, self).__init__(
"Metric %s already exists" % metric)
class MetricUnaggregatable(StorageError):
"""Error raised when metrics can't be aggregated."""
def __init__(self, metrics, reason):
self.metrics = metrics
self.reason = reason
super(MetricUnaggregatable, self).__init__(
"Metrics %s can't be aggregated: %s"
% (", ".join((str(m.id) for m in metrics)), reason))
def get_driver_class(conf):
"""Return the storage driver class.
:param conf: The conf to use to determine the driver.
"""
return driver.DriverManager('gnocchi.storage',
conf.storage.driver).driver
def get_driver(conf):
"""Return the configured driver."""
return get_driver_class(conf)(conf.storage)
class StorageDriver(object):
@staticmethod
def __init__(conf):
pass
@staticmethod
def stop():
pass
@staticmethod
def upgrade(index):
pass
def process_background_tasks(self, index, metrics, sync=False):
"""Process background tasks for this storage.
This calls :func:`process_new_measures` to process new measures
:param index: An indexer to be used for querying metrics
:param block_size: number of metrics to process
:param sync: If True, then process everything synchronously and raise
on error
:type sync: bool
"""
LOG.debug("Processing new measures")
try:
self.process_new_measures(index, metrics, sync)
except Exception:
if sync:
raise
LOG.error("Unexpected error during measures processing",
exc_info=True)
def expunge_metrics(self, index, sync=False):
"""Remove deleted metrics
:param index: An indexer to be used for querying metrics
:param sync: If True, then delete everything synchronously and raise
on error
:type sync: bool
"""
metrics_to_expunge = index.list_metrics(status='delete')
for m in metrics_to_expunge:
try:
self.delete_metric(m, sync)
except Exception:
if sync:
raise
LOG.error("Unable to expunge metric %s from storage" % m,
exc_info=True)
continue
try:
index.expunge_metric(m.id)
except indexer.NoSuchMetric:
# It's possible another process deleted the metric in the mean
# time, not a big deal
pass
@staticmethod
def add_measures(metric, measures):
"""Add a measure to a metric.
:param metric: The metric measured.
:param measures: The actual measures.
"""
raise exceptions.NotImplementedError
@staticmethod
def process_new_measures(indexer, metrics, sync=False):
"""Process added measures in background.
Some drivers might need to have a background task running that process
the measures sent to metrics. This is used for that.
"""
@staticmethod
def measures_report(details=True):
"""Return a report of pending to process measures.
Only useful for drivers that process measurements in background
:return: {'summary': {'metrics': count, 'measures': count},
'details': {metric_id: pending_measures_count}}
"""
raise exceptions.NotImplementedError
@staticmethod
def get_measures(metric, from_timestamp=None, to_timestamp=None,
aggregation='mean', granularity=None):
"""Get a measure to a metric.
:param metric: The metric measured.
:param from timestamp: The timestamp to get the measure from.
:param to timestamp: The timestamp to get the measure to.
:param aggregation: The type of aggregation to retrieve.
:param granularity: The granularity to retrieve.
"""
if aggregation not in metric.archive_policy.aggregation_methods:
raise AggregationDoesNotExist(metric, aggregation)
@staticmethod
def delete_metric(metric, sync=False):
raise exceptions.NotImplementedError
@staticmethod
def get_cross_metric_measures(metrics, from_timestamp=None,
to_timestamp=None, aggregation='mean',
reaggregation=None,
granularity=None,
needed_overlap=None):
"""Get aggregated measures of multiple entities.
:param entities: The entities measured to aggregate.
:param from timestamp: The timestamp to get the measure from.
:param to timestamp: The timestamp to get the measure to.
:param granularity: The granularity to retrieve.
:param aggregation: The type of aggregation to retrieve.
:param reaggregation: The type of aggregation to compute
on the retrieved measures.
"""
for metric in metrics:
if aggregation not in metric.archive_policy.aggregation_methods:
raise AggregationDoesNotExist(metric, aggregation)
if (granularity is not None and granularity
not in set(d.granularity
for d in metric.archive_policy.definition)):
raise GranularityDoesNotExist(metric, granularity)
@staticmethod
def search_value(metrics, query, from_timestamp=None,
to_timestamp=None,
aggregation='mean'):
"""Search for an aggregated value that realizes a predicate.
:param metrics: The list of metrics to look into.
:param query: The query being sent.
:param from_timestamp: The timestamp to get the measure from.
:param to_timestamp: The timestamp to get the measure to.
:param aggregation: The type of aggregation to retrieve.
"""
raise exceptions.NotImplementedError
class MeasureQuery(object):
binary_operators = {
u"=": operator.eq,
u"==": operator.eq,
u"eq": operator.eq,
u"<": operator.lt,
u"lt": operator.lt,
u">": operator.gt,
u"gt": operator.gt,
u"<=": operator.le,
u"≤": operator.le,
u"le": operator.le,
u">=": operator.ge,
u"≥": operator.ge,
u"ge": operator.ge,
u"!=": operator.ne,
u"≠": operator.ne,
u"ne": operator.ne,
u"%": operator.mod,
u"mod": operator.mod,
u"+": operator.add,
u"add": operator.add,
u"-": operator.sub,
u"sub": operator.sub,
u"*": operator.mul,
u"×": operator.mul,
u"mul": operator.mul,
u"/": operator.truediv,
u"÷": operator.truediv,
u"div": operator.truediv,
u"**": operator.pow,
u"^": operator.pow,
u"pow": operator.pow,
}
multiple_operators = {
u"or": any,
u"∨": any,
u"and": all,
u"∧": all,
}
def __init__(self, tree):
self._eval = self.build_evaluator(tree)
def __call__(self, value):
return self._eval(value)
def build_evaluator(self, tree):
try:
operator, nodes = list(tree.items())[0]
except Exception:
return lambda value: tree
try:
op = self.multiple_operators[operator]
except KeyError:
try:
op = self.binary_operators[operator]
except KeyError:
raise InvalidQuery("Unknown operator %s" % operator)
return self._handle_binary_op(op, nodes)
return self._handle_multiple_op(op, nodes)
def _handle_multiple_op(self, op, nodes):
elements = [self.build_evaluator(node) for node in nodes]
return lambda value: op((e(value) for e in elements))
def _handle_binary_op(self, op, node):
try:
iterator = iter(node)
except Exception:
return lambda value: op(value, node)
nodes = list(iterator)
if len(nodes) != 2:
raise InvalidQuery(
"Binary operator %s needs 2 arguments, %d given" %
(op, len(nodes)))
node0 = self.build_evaluator(node[0])
node1 = self.build_evaluator(node[1])
return lambda value: op(node0(value), node1(value))
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