7497363a02
According to the OpenStack translation policy, available at https://wiki.openstack.org/wiki/LoggingStandards, debug messages should not be translated. Change-Id: Icdf5ea14767d98d2dd4f32bd5b60130a8bca540a Closes-Bug: #1317856
703 lines
29 KiB
Python
703 lines
29 KiB
Python
#
|
|
# Copyright 2012 New Dream Network, LLC (DreamHost)
|
|
# Copyright 2013 eNovance
|
|
# Copyright 2014 Red Hat, Inc
|
|
#
|
|
# Authors: Doug Hellmann <doug.hellmann@dreamhost.com>
|
|
# Julien Danjou <julien@danjou.info>
|
|
# Eoghan Glynn <eglynn@redhat.com>
|
|
#
|
|
# 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.
|
|
"""MongoDB storage backend"""
|
|
|
|
import copy
|
|
import datetime
|
|
import uuid
|
|
|
|
import bson.code
|
|
import bson.objectid
|
|
from oslo_config import cfg
|
|
from oslo_log import log
|
|
from oslo_utils import timeutils
|
|
import pymongo
|
|
import six
|
|
|
|
import ceilometer
|
|
from ceilometer import storage
|
|
from ceilometer.storage import base
|
|
from ceilometer.storage import models
|
|
from ceilometer.storage.mongo import utils as pymongo_utils
|
|
from ceilometer.storage import pymongo_base
|
|
from ceilometer import utils
|
|
|
|
LOG = log.getLogger(__name__)
|
|
|
|
|
|
AVAILABLE_CAPABILITIES = {
|
|
'resources': {'query': {'simple': True,
|
|
'metadata': True}},
|
|
'statistics': {'groupby': True,
|
|
'query': {'simple': True,
|
|
'metadata': True},
|
|
'aggregation': {'standard': True,
|
|
'selectable': {'max': True,
|
|
'min': True,
|
|
'sum': True,
|
|
'avg': True,
|
|
'count': True,
|
|
'stddev': True,
|
|
'cardinality': True}}}
|
|
}
|
|
|
|
|
|
class Connection(pymongo_base.Connection):
|
|
"""Put the data into a MongoDB database
|
|
|
|
Collections::
|
|
|
|
- meter
|
|
- the raw incoming data
|
|
- resource
|
|
- the metadata for resources
|
|
- { _id: uuid of resource,
|
|
metadata: metadata dictionaries
|
|
user_id: uuid
|
|
project_id: uuid
|
|
meter: [ array of {counter_name: string, counter_type: string,
|
|
counter_unit: string} ]
|
|
}
|
|
"""
|
|
|
|
CAPABILITIES = utils.update_nested(pymongo_base.Connection.CAPABILITIES,
|
|
AVAILABLE_CAPABILITIES)
|
|
CONNECTION_POOL = pymongo_utils.ConnectionPool()
|
|
|
|
STANDARD_AGGREGATES = dict([(a.name, a) for a in [
|
|
pymongo_utils.SUM_AGGREGATION, pymongo_utils.AVG_AGGREGATION,
|
|
pymongo_utils.MIN_AGGREGATION, pymongo_utils.MAX_AGGREGATION,
|
|
pymongo_utils.COUNT_AGGREGATION,
|
|
]])
|
|
|
|
AGGREGATES = dict([(a.name, a) for a in [
|
|
pymongo_utils.SUM_AGGREGATION,
|
|
pymongo_utils.AVG_AGGREGATION,
|
|
pymongo_utils.MIN_AGGREGATION,
|
|
pymongo_utils.MAX_AGGREGATION,
|
|
pymongo_utils.COUNT_AGGREGATION,
|
|
pymongo_utils.STDDEV_AGGREGATION,
|
|
pymongo_utils.CARDINALITY_AGGREGATION,
|
|
]])
|
|
|
|
SORT_OPERATION_MAPPING = {'desc': (pymongo.DESCENDING, '$lt'),
|
|
'asc': (pymongo.ASCENDING, '$gt')}
|
|
|
|
MAP_RESOURCES = bson.code.Code("""
|
|
function () {
|
|
emit(this.resource_id,
|
|
{user_id: this.user_id,
|
|
project_id: this.project_id,
|
|
source: this.source,
|
|
first_timestamp: this.timestamp,
|
|
last_timestamp: this.timestamp,
|
|
metadata: this.resource_metadata})
|
|
}""")
|
|
|
|
REDUCE_RESOURCES = bson.code.Code("""
|
|
function (key, values) {
|
|
var merge = {user_id: values[0].user_id,
|
|
project_id: values[0].project_id,
|
|
source: values[0].source,
|
|
first_timestamp: values[0].first_timestamp,
|
|
last_timestamp: values[0].last_timestamp,
|
|
metadata: values[0].metadata}
|
|
values.forEach(function(value) {
|
|
if (merge.first_timestamp - value.first_timestamp > 0) {
|
|
merge.first_timestamp = value.first_timestamp;
|
|
merge.user_id = value.user_id;
|
|
merge.project_id = value.project_id;
|
|
merge.source = value.source;
|
|
} else if (merge.last_timestamp - value.last_timestamp <= 0) {
|
|
merge.last_timestamp = value.last_timestamp;
|
|
merge.metadata = value.metadata;
|
|
}
|
|
});
|
|
return merge;
|
|
}""")
|
|
|
|
_GENESIS = datetime.datetime(year=datetime.MINYEAR, month=1, day=1)
|
|
_APOCALYPSE = datetime.datetime(year=datetime.MAXYEAR, month=12, day=31,
|
|
hour=23, minute=59, second=59)
|
|
|
|
def __init__(self, url):
|
|
|
|
# NOTE(jd) Use our own connection pooling on top of the Pymongo one.
|
|
# We need that otherwise we overflow the MongoDB instance with new
|
|
# connection since we instantiate a Pymongo client each time someone
|
|
# requires a new storage connection.
|
|
self.conn = self.CONNECTION_POOL.connect(url)
|
|
self.version = self.conn.server_info()['versionArray']
|
|
# Require MongoDB 2.4 to use $setOnInsert
|
|
if self.version < pymongo_utils.MINIMUM_COMPATIBLE_MONGODB_VERSION:
|
|
raise storage.StorageBadVersion(
|
|
"Need at least MongoDB %s" %
|
|
pymongo_utils.MINIMUM_COMPATIBLE_MONGODB_VERSION)
|
|
|
|
connection_options = pymongo.uri_parser.parse_uri(url)
|
|
self.db = getattr(self.conn, connection_options['database'])
|
|
if connection_options.get('username'):
|
|
self.db.authenticate(connection_options['username'],
|
|
connection_options['password'])
|
|
|
|
# NOTE(jd) Upgrading is just about creating index, so let's do this
|
|
# on connection to be sure at least the TTL is correctly updated if
|
|
# needed.
|
|
self.upgrade()
|
|
|
|
@staticmethod
|
|
def update_ttl(ttl, ttl_index_name, index_field, coll):
|
|
"""Update or create time_to_live indexes.
|
|
|
|
:param ttl: time to live in seconds.
|
|
:param ttl_index_name: name of the index we want to update or create.
|
|
:param index_field: field with the index that we need to update.
|
|
:param coll: collection which indexes need to be updated.
|
|
"""
|
|
indexes = coll.index_information()
|
|
if ttl <= 0:
|
|
if ttl_index_name in indexes:
|
|
coll.drop_index(ttl_index_name)
|
|
return
|
|
|
|
if ttl_index_name in indexes:
|
|
return coll.database.command(
|
|
'collMod', coll.name,
|
|
index={'keyPattern': {index_field: pymongo.ASCENDING},
|
|
'expireAfterSeconds': ttl})
|
|
|
|
coll.create_index([(index_field, pymongo.ASCENDING)],
|
|
expireAfterSeconds=ttl,
|
|
name=ttl_index_name)
|
|
|
|
def upgrade(self):
|
|
# Establish indexes
|
|
#
|
|
# We need variations for user_id vs. project_id because of the
|
|
# way the indexes are stored in b-trees. The user_id and
|
|
# project_id values are usually mutually exclusive in the
|
|
# queries, so the database won't take advantage of an index
|
|
# including both.
|
|
|
|
# create collection if not present
|
|
if 'resource' not in self.db.conn.collection_names():
|
|
self.db.conn.create_collection('resource')
|
|
if 'meter' not in self.db.conn.collection_names():
|
|
self.db.conn.create_collection('meter')
|
|
|
|
name_qualifier = dict(user_id='', project_id='project_')
|
|
background = dict(user_id=False, project_id=True)
|
|
for primary in ['user_id', 'project_id']:
|
|
name = 'meter_%sidx' % name_qualifier[primary]
|
|
self.db.meter.create_index([
|
|
('resource_id', pymongo.ASCENDING),
|
|
(primary, pymongo.ASCENDING),
|
|
('counter_name', pymongo.ASCENDING),
|
|
('timestamp', pymongo.ASCENDING),
|
|
], name=name, background=background[primary])
|
|
|
|
self.db.meter.create_index([('timestamp', pymongo.DESCENDING)],
|
|
name='timestamp_idx')
|
|
|
|
# NOTE(ityaptin) This index covers get_resource requests sorting
|
|
# and MongoDB uses part of this compound index for different
|
|
# queries based on any of user_id, project_id, last_sample_timestamp
|
|
# fields
|
|
self.db.resource.create_index([('user_id', pymongo.DESCENDING),
|
|
('project_id', pymongo.DESCENDING),
|
|
('last_sample_timestamp',
|
|
pymongo.DESCENDING)],
|
|
name='resource_user_project_timestamp',)
|
|
self.db.resource.create_index([('last_sample_timestamp',
|
|
pymongo.DESCENDING)],
|
|
name='last_sample_timestamp_idx')
|
|
|
|
# update or create time_to_live index
|
|
ttl = cfg.CONF.database.metering_time_to_live
|
|
self.update_ttl(ttl, 'meter_ttl', 'timestamp', self.db.meter)
|
|
self.update_ttl(ttl, 'resource_ttl', 'last_sample_timestamp',
|
|
self.db.resource)
|
|
|
|
def clear(self):
|
|
self.conn.drop_database(self.db.name)
|
|
# Connection will be reopened automatically if needed
|
|
self.conn.close()
|
|
|
|
def record_metering_data(self, data):
|
|
"""Write the data to the backend storage system.
|
|
|
|
:param data: a dictionary such as returned by
|
|
ceilometer.meter.meter_message_from_counter
|
|
"""
|
|
# Record the updated resource metadata - we use $setOnInsert to
|
|
# unconditionally insert sample timestamps and resource metadata
|
|
# (in the update case, this must be conditional on the sample not
|
|
# being out-of-order)
|
|
data = copy.deepcopy(data)
|
|
data['resource_metadata'] = pymongo_utils.improve_keys(
|
|
data.pop('resource_metadata'))
|
|
resource = self.db.resource.find_one_and_update(
|
|
{'_id': data['resource_id']},
|
|
{'$set': {'project_id': data['project_id'],
|
|
'user_id': data['user_id'],
|
|
'source': data['source'],
|
|
},
|
|
'$setOnInsert': {'metadata': data['resource_metadata'],
|
|
'first_sample_timestamp': data['timestamp'],
|
|
'last_sample_timestamp': data['timestamp'],
|
|
},
|
|
'$addToSet': {'meter': {'counter_name': data['counter_name'],
|
|
'counter_type': data['counter_type'],
|
|
'counter_unit': data['counter_unit'],
|
|
},
|
|
},
|
|
},
|
|
upsert=True,
|
|
return_document=pymongo.ReturnDocument.AFTER,
|
|
)
|
|
|
|
# only update last sample timestamp if actually later (the usual
|
|
# in-order case)
|
|
last_sample_timestamp = resource.get('last_sample_timestamp')
|
|
if (last_sample_timestamp is None or
|
|
last_sample_timestamp <= data['timestamp']):
|
|
self.db.resource.update_one(
|
|
{'_id': data['resource_id']},
|
|
{'$set': {'metadata': data['resource_metadata'],
|
|
'last_sample_timestamp': data['timestamp']}}
|
|
)
|
|
|
|
# only update first sample timestamp if actually earlier (the unusual
|
|
# out-of-order case)
|
|
# NOTE: a null first sample timestamp is not updated as this indicates
|
|
# a pre-existing resource document dating from before we started
|
|
# recording these timestamps in the resource collection
|
|
first_sample_timestamp = resource.get('first_sample_timestamp')
|
|
if (first_sample_timestamp is not None and
|
|
first_sample_timestamp > data['timestamp']):
|
|
self.db.resource.update_one(
|
|
{'_id': data['resource_id']},
|
|
{'$set': {'first_sample_timestamp': data['timestamp']}}
|
|
)
|
|
|
|
# Record the raw data for the meter. Use a copy so we do not
|
|
# modify a data structure owned by our caller (the driver adds
|
|
# a new key '_id').
|
|
record = copy.copy(data)
|
|
record['recorded_at'] = timeutils.utcnow()
|
|
|
|
self.db.meter.insert_one(record)
|
|
|
|
def clear_expired_metering_data(self, ttl):
|
|
"""Clear expired data from the backend storage system.
|
|
|
|
Clearing occurs with native MongoDB time-to-live feature.
|
|
"""
|
|
LOG.debug("Clearing expired metering data is based on native "
|
|
"MongoDB time to live feature and going in background.")
|
|
|
|
@staticmethod
|
|
def _get_marker(db_collection, marker_pairs):
|
|
"""Return the mark document according to the attribute-value pairs.
|
|
|
|
:param db_collection: Database collection that be query.
|
|
:param maker_pairs: Attribute-value pairs filter.
|
|
"""
|
|
if db_collection is None:
|
|
return
|
|
if not marker_pairs:
|
|
return
|
|
ret = db_collection.find(marker_pairs, limit=2)
|
|
|
|
if ret.count() == 0:
|
|
raise base.NoResultFound
|
|
elif ret.count() > 1:
|
|
raise base.MultipleResultsFound
|
|
else:
|
|
_ret = ret.__getitem__(0)
|
|
return _ret
|
|
|
|
@classmethod
|
|
def _recurse_sort_keys(cls, sort_keys, marker, flag):
|
|
_first = sort_keys[0]
|
|
value = marker[_first]
|
|
if len(sort_keys) == 1:
|
|
return {_first: {flag: value}}
|
|
else:
|
|
criteria_equ = {_first: {'eq': value}}
|
|
criteria_cmp = cls._recurse_sort_keys(sort_keys[1:], marker, flag)
|
|
return dict(criteria_equ, ** criteria_cmp)
|
|
|
|
@classmethod
|
|
def _build_sort_instructions(cls, sort_keys=None, sort_dir='desc'):
|
|
"""Returns a sort_instruction and paging operator.
|
|
|
|
Sort instructions are used in the query to determine what attributes
|
|
to sort on and what direction to use.
|
|
:param q: The query dict passed in.
|
|
:param sort_keys: array of attributes by which results be sorted.
|
|
:param sort_dir: direction in which results be sorted (asc, desc).
|
|
:return: sort instructions and paging operator
|
|
"""
|
|
sort_keys = sort_keys or []
|
|
sort_instructions = []
|
|
_sort_dir, operation = cls.SORT_OPERATION_MAPPING.get(
|
|
sort_dir, cls.SORT_OPERATION_MAPPING['desc'])
|
|
|
|
for _sort_key in sort_keys:
|
|
_instruction = (_sort_key, _sort_dir)
|
|
sort_instructions.append(_instruction)
|
|
|
|
return sort_instructions, operation
|
|
|
|
def _get_time_constrained_resources(self, query,
|
|
start_timestamp, start_timestamp_op,
|
|
end_timestamp, end_timestamp_op,
|
|
metaquery, resource, limit):
|
|
"""Return an iterable of models.Resource instances
|
|
|
|
Items are constrained by sample timestamp.
|
|
:param query: project/user/source query
|
|
:param start_timestamp: modified timestamp start range.
|
|
:param start_timestamp_op: start time operator, like gt, ge.
|
|
:param end_timestamp: modified timestamp end range.
|
|
:param end_timestamp_op: end time operator, like lt, le.
|
|
:param metaquery: dict with metadata to match on.
|
|
:param resource: resource filter.
|
|
"""
|
|
if resource is not None:
|
|
query['resource_id'] = resource
|
|
|
|
# Add resource_ prefix so it matches the field in the db
|
|
query.update(dict(('resource_' + k, v)
|
|
for (k, v) in six.iteritems(metaquery)))
|
|
|
|
# FIXME(dhellmann): This may not perform very well,
|
|
# but doing any better will require changing the database
|
|
# schema and that will need more thought than I have time
|
|
# to put into it today.
|
|
# Look for resources matching the above criteria and with
|
|
# samples in the time range we care about, then change the
|
|
# resource query to return just those resources by id.
|
|
ts_range = pymongo_utils.make_timestamp_range(start_timestamp,
|
|
end_timestamp,
|
|
start_timestamp_op,
|
|
end_timestamp_op)
|
|
if ts_range:
|
|
query['timestamp'] = ts_range
|
|
|
|
sort_keys = base._handle_sort_key('resource')
|
|
sort_instructions = self._build_sort_instructions(sort_keys)[0]
|
|
|
|
# use a unique collection name for the results collection,
|
|
# as result post-sorting (as oppposed to reduce pre-sorting)
|
|
# is not possible on an inline M-R
|
|
out = 'resource_list_%s' % uuid.uuid4()
|
|
self.db.meter.map_reduce(self.MAP_RESOURCES,
|
|
self.REDUCE_RESOURCES,
|
|
out=out,
|
|
sort={'resource_id': 1},
|
|
query=query)
|
|
|
|
try:
|
|
if limit is not None:
|
|
results = self.db[out].find(sort=sort_instructions,
|
|
limit=limit)
|
|
else:
|
|
results = self.db[out].find(sort=sort_instructions)
|
|
for r in results:
|
|
resource = r['value']
|
|
yield models.Resource(
|
|
resource_id=r['_id'],
|
|
user_id=resource['user_id'],
|
|
project_id=resource['project_id'],
|
|
first_sample_timestamp=resource['first_timestamp'],
|
|
last_sample_timestamp=resource['last_timestamp'],
|
|
source=resource['source'],
|
|
metadata=pymongo_utils.unquote_keys(resource['metadata']))
|
|
finally:
|
|
self.db[out].drop()
|
|
|
|
def _get_floating_resources(self, query, metaquery, resource, limit):
|
|
"""Return an iterable of models.Resource instances
|
|
|
|
Items are unconstrained by timestamp.
|
|
:param query: project/user/source query
|
|
:param metaquery: dict with metadata to match on.
|
|
:param resource: resource filter.
|
|
"""
|
|
if resource is not None:
|
|
query['_id'] = resource
|
|
|
|
query.update(dict((k, v)
|
|
for (k, v) in six.iteritems(metaquery)))
|
|
|
|
keys = base._handle_sort_key('resource')
|
|
sort_keys = ['last_sample_timestamp' if i == 'timestamp' else i
|
|
for i in keys]
|
|
sort_instructions = self._build_sort_instructions(sort_keys)[0]
|
|
|
|
if limit is not None:
|
|
results = self.db.resource.find(query, sort=sort_instructions,
|
|
limit=limit)
|
|
else:
|
|
results = self.db.resource.find(query, sort=sort_instructions)
|
|
|
|
for r in results:
|
|
yield models.Resource(
|
|
resource_id=r['_id'],
|
|
user_id=r['user_id'],
|
|
project_id=r['project_id'],
|
|
first_sample_timestamp=r.get('first_sample_timestamp',
|
|
self._GENESIS),
|
|
last_sample_timestamp=r.get('last_sample_timestamp',
|
|
self._APOCALYPSE),
|
|
source=r['source'],
|
|
metadata=pymongo_utils.unquote_keys(r['metadata']))
|
|
|
|
def get_resources(self, user=None, project=None, source=None,
|
|
start_timestamp=None, start_timestamp_op=None,
|
|
end_timestamp=None, end_timestamp_op=None,
|
|
metaquery=None, resource=None, limit=None):
|
|
"""Return an iterable of models.Resource instances
|
|
|
|
:param user: Optional ID for user that owns the resource.
|
|
:param project: Optional ID for project that owns the resource.
|
|
:param source: Optional source filter.
|
|
:param start_timestamp: Optional modified timestamp start range.
|
|
:param start_timestamp_op: Optional start time operator, like gt, ge.
|
|
:param end_timestamp: Optional modified timestamp end range.
|
|
:param end_timestamp_op: Optional end time operator, like lt, le.
|
|
:param metaquery: Optional dict with metadata to match on.
|
|
:param resource: Optional resource filter.
|
|
:param limit: Maximum number of results to return.
|
|
"""
|
|
if limit == 0:
|
|
return
|
|
metaquery = pymongo_utils.improve_keys(metaquery, metaquery=True) or {}
|
|
|
|
query = {}
|
|
if user is not None:
|
|
query['user_id'] = user
|
|
if project is not None:
|
|
query['project_id'] = project
|
|
if source is not None:
|
|
query['source'] = source
|
|
|
|
if start_timestamp or end_timestamp:
|
|
return self._get_time_constrained_resources(query,
|
|
start_timestamp,
|
|
start_timestamp_op,
|
|
end_timestamp,
|
|
end_timestamp_op,
|
|
metaquery, resource,
|
|
limit)
|
|
else:
|
|
return self._get_floating_resources(query, metaquery, resource,
|
|
limit)
|
|
|
|
@staticmethod
|
|
def _make_period_dict(period, first_ts):
|
|
"""Create a period field for _id of grouped fields.
|
|
|
|
:param period: Period duration in seconds
|
|
:param first_ts: First timestamp for first period
|
|
:return:
|
|
"""
|
|
if period >= 0:
|
|
period_unique_dict = {
|
|
"period_start":
|
|
{
|
|
"$divide": [
|
|
{"$subtract": [
|
|
{"$subtract": ["$timestamp",
|
|
first_ts]},
|
|
{"$mod": [{"$subtract": ["$timestamp",
|
|
first_ts]},
|
|
period * 1000]
|
|
}
|
|
]},
|
|
period * 1000
|
|
]
|
|
}
|
|
|
|
}
|
|
else:
|
|
# Note(ityaptin) Hack for older MongoDB versions (2.4.+ and older).
|
|
# Since 2.6+ we could use $literal operator
|
|
period_unique_dict = {"$period_start": {"$add": [0, 0]}}
|
|
return period_unique_dict
|
|
|
|
def get_meter_statistics(self, sample_filter, period=None, groupby=None,
|
|
aggregate=None):
|
|
"""Return an iterable of models.Statistics instance.
|
|
|
|
Items are containing meter statistics described by the query
|
|
parameters. The filter must have a meter value set.
|
|
"""
|
|
|
|
if (groupby and set(groupby) -
|
|
set(['user_id', 'project_id', 'resource_id', 'source',
|
|
'resource_metadata.instance_type'])):
|
|
raise ceilometer.NotImplementedError(
|
|
"Unable to group by these fields")
|
|
q = pymongo_utils.make_query_from_filter(sample_filter)
|
|
|
|
group_stage = {}
|
|
project_stage = {
|
|
"unit": "$_id.unit",
|
|
"name": "$_id.name",
|
|
"first_timestamp": "$first_timestamp",
|
|
"last_timestamp": "$last_timestamp",
|
|
"period_start": "$_id.period_start",
|
|
}
|
|
|
|
# Add timestamps to $group stage
|
|
group_stage.update({"first_timestamp": {"$min": "$timestamp"},
|
|
"last_timestamp": {"$max": "$timestamp"}})
|
|
|
|
# Define a _id field for grouped documents
|
|
unique_group_field = {"name": "$counter_name",
|
|
"unit": "$counter_unit"}
|
|
|
|
# Define a first timestamp for periods
|
|
if sample_filter.start_timestamp:
|
|
first_timestamp = sample_filter.start_timestamp
|
|
else:
|
|
first_timestamp_cursor = self.db.meter.find(
|
|
limit=1, sort=[('timestamp',
|
|
pymongo.ASCENDING)])
|
|
if first_timestamp_cursor.count():
|
|
first_timestamp = first_timestamp_cursor[0]['timestamp']
|
|
else:
|
|
first_timestamp = utils.EPOCH_TIME
|
|
|
|
# Add a start_period field to unique identifier of grouped documents
|
|
if period:
|
|
period_dict = self._make_period_dict(period,
|
|
first_timestamp)
|
|
unique_group_field.update(period_dict)
|
|
|
|
# Add a groupby fields to unique identifier of grouped documents
|
|
if groupby:
|
|
unique_group_field.update(dict((field.replace(".", "/"),
|
|
"$%s" % field)
|
|
for field in groupby))
|
|
|
|
group_stage.update({"_id": unique_group_field})
|
|
|
|
self._compile_aggregate_stages(aggregate, group_stage, project_stage)
|
|
|
|
# Aggregation stages list. It's work one by one and uses documents
|
|
# from previous stages.
|
|
aggregation_query = [{'$match': q},
|
|
{"$sort": {"timestamp": 1}},
|
|
{"$group": group_stage},
|
|
{"$sort": {"_id.period_start": 1}},
|
|
{"$project": project_stage}]
|
|
|
|
# results is dict in pymongo<=2.6.3 and CommandCursor in >=3.0
|
|
results = self.db.meter.aggregate(aggregation_query,
|
|
**self._make_aggregation_params())
|
|
return [self._stats_result_to_model(point, groupby, aggregate,
|
|
period, first_timestamp)
|
|
for point in self._get_results(results)]
|
|
|
|
def _stats_result_aggregates(self, result, aggregate):
|
|
stats_args = {}
|
|
for attr in Connection.STANDARD_AGGREGATES.keys():
|
|
if attr in result:
|
|
stats_args[attr] = result[attr]
|
|
|
|
if aggregate:
|
|
stats_args['aggregate'] = {}
|
|
for agr in aggregate:
|
|
stats_args['aggregate'].update(
|
|
Connection.AGGREGATES[agr.func].finalize(
|
|
result, agr.param, self.version))
|
|
return stats_args
|
|
|
|
def _stats_result_to_model(self, result, groupby, aggregate, period,
|
|
first_timestamp):
|
|
if period is None:
|
|
period = 0
|
|
first_timestamp = pymongo_utils.from_unix_timestamp(first_timestamp)
|
|
stats_args = self._stats_result_aggregates(result, aggregate)
|
|
|
|
stats_args['unit'] = result['unit']
|
|
stats_args['duration'] = (result["last_timestamp"] -
|
|
result["first_timestamp"]).total_seconds()
|
|
stats_args['duration_start'] = result['first_timestamp']
|
|
stats_args['duration_end'] = result['last_timestamp']
|
|
stats_args['period'] = period
|
|
start = result.get("period_start", 0) * period
|
|
|
|
stats_args['period_start'] = (first_timestamp +
|
|
datetime.timedelta(seconds=start))
|
|
stats_args['period_end'] = (first_timestamp +
|
|
datetime.timedelta(seconds=start + period)
|
|
if period else result['last_timestamp'])
|
|
|
|
stats_args['groupby'] = (
|
|
dict((g, result['_id'].get(g.replace(".", "/")))
|
|
for g in groupby) if groupby else None)
|
|
return models.Statistics(**stats_args)
|
|
|
|
def _compile_aggregate_stages(self, aggregate, group_stage, project_stage):
|
|
if not aggregate:
|
|
for aggregation in Connection.STANDARD_AGGREGATES.values():
|
|
group_stage.update(
|
|
aggregation.group(version_array=self.version)
|
|
)
|
|
project_stage.update(
|
|
aggregation.project(
|
|
version_array=self.version
|
|
)
|
|
)
|
|
else:
|
|
for description in aggregate:
|
|
aggregation = Connection.AGGREGATES.get(description.func)
|
|
if aggregation:
|
|
if not aggregation.validate(description.param):
|
|
raise storage.StorageBadAggregate(
|
|
'Bad aggregate: %s.%s' % (description.func,
|
|
description.param))
|
|
group_stage.update(
|
|
aggregation.group(description.param,
|
|
version_array=self.version)
|
|
)
|
|
project_stage.update(
|
|
aggregation.project(description.param,
|
|
version_array=self.version)
|
|
)
|
|
|
|
@staticmethod
|
|
def _get_results(results):
|
|
if isinstance(results, dict):
|
|
return results.get('result', [])
|
|
else:
|
|
return results
|
|
|
|
def _make_aggregation_params(self):
|
|
if self.version >= pymongo_utils.COMPLETE_AGGREGATE_COMPATIBLE_VERSION:
|
|
return {"allowDiskUse": True}
|
|
return {}
|