1d73a6f12f
Currently statistics requests fail with type errors. It causes by the fact that pymongo returns bson.Int64 instead of float or int for big nums. It affects a `cpu` meter usually. Change-Id: I744a9f79a4bbc3b2ecdd73c126b0859f3f8a733c Closes-bug: #1532661
672 lines
28 KiB
Python
672 lines
28 KiB
Python
#
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# Copyright 2012 New Dream Network, LLC (DreamHost)
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# Copyright 2013 eNovance
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# Copyright 2014 Red Hat, Inc
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#
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# Authors: Doug Hellmann <doug.hellmann@dreamhost.com>
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# Julien Danjou <julien@danjou.info>
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# Eoghan Glynn <eglynn@redhat.com>
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#
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# Licensed under the Apache License, Version 2.0 (the "License"); you may
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# not use this file except in compliance with the License. You may obtain
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# a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
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# WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
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# License for the specific language governing permissions and limitations
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# under the License.
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"""MongoDB storage backend"""
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import copy
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import datetime
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import uuid
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import bson.code
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import bson.objectid
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from oslo_config import cfg
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from oslo_log import log
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from oslo_utils import timeutils
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import pymongo
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import six
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import ceilometer
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from ceilometer import storage
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from ceilometer.storage import base
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from ceilometer.storage import models
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from ceilometer.storage.mongo import utils as pymongo_utils
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from ceilometer.storage import pymongo_base
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from ceilometer import utils
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LOG = log.getLogger(__name__)
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AVAILABLE_CAPABILITIES = {
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'resources': {'query': {'simple': True,
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'metadata': True}},
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'statistics': {'groupby': True,
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'query': {'simple': True,
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'metadata': True},
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'aggregation': {'standard': True,
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'selectable': {'max': True,
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'min': True,
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'sum': True,
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'avg': True,
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'count': True,
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'stddev': True,
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'cardinality': True}}}
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}
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class Connection(pymongo_base.Connection):
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"""Put the data into a MongoDB database
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Collections::
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- meter
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- the raw incoming data
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- resource
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- the metadata for resources
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- { _id: uuid of resource,
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metadata: metadata dictionaries
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user_id: uuid
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project_id: uuid
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meter: [ array of {counter_name: string, counter_type: string,
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counter_unit: string} ]
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}
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"""
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CAPABILITIES = utils.update_nested(pymongo_base.Connection.CAPABILITIES,
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AVAILABLE_CAPABILITIES)
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CONNECTION_POOL = pymongo_utils.ConnectionPool()
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STANDARD_AGGREGATES = dict([(a.name, a) for a in [
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pymongo_utils.SUM_AGGREGATION, pymongo_utils.AVG_AGGREGATION,
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pymongo_utils.MIN_AGGREGATION, pymongo_utils.MAX_AGGREGATION,
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pymongo_utils.COUNT_AGGREGATION,
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]])
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AGGREGATES = dict([(a.name, a) for a in [
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pymongo_utils.SUM_AGGREGATION,
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pymongo_utils.AVG_AGGREGATION,
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pymongo_utils.MIN_AGGREGATION,
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pymongo_utils.MAX_AGGREGATION,
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pymongo_utils.COUNT_AGGREGATION,
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pymongo_utils.STDDEV_AGGREGATION,
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pymongo_utils.CARDINALITY_AGGREGATION,
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]])
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SORT_OPERATION_MAPPING = {'desc': (pymongo.DESCENDING, '$lt'),
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'asc': (pymongo.ASCENDING, '$gt')}
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MAP_RESOURCES = bson.code.Code("""
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function () {
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emit(this.resource_id,
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{user_id: this.user_id,
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project_id: this.project_id,
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source: this.source,
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first_timestamp: this.timestamp,
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last_timestamp: this.timestamp,
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metadata: this.resource_metadata})
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}""")
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REDUCE_RESOURCES = bson.code.Code("""
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function (key, values) {
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var merge = {user_id: values[0].user_id,
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project_id: values[0].project_id,
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source: values[0].source,
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first_timestamp: values[0].first_timestamp,
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last_timestamp: values[0].last_timestamp,
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metadata: values[0].metadata}
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values.forEach(function(value) {
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if (merge.first_timestamp - value.first_timestamp > 0) {
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merge.first_timestamp = value.first_timestamp;
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merge.user_id = value.user_id;
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merge.project_id = value.project_id;
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merge.source = value.source;
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} else if (merge.last_timestamp - value.last_timestamp <= 0) {
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merge.last_timestamp = value.last_timestamp;
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merge.metadata = value.metadata;
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}
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});
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return merge;
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}""")
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_GENESIS = datetime.datetime(year=datetime.MINYEAR, month=1, day=1)
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_APOCALYPSE = datetime.datetime(year=datetime.MAXYEAR, month=12, day=31,
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hour=23, minute=59, second=59)
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def __init__(self, url):
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# NOTE(jd) Use our own connection pooling on top of the Pymongo one.
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# We need that otherwise we overflow the MongoDB instance with new
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# connection since we instantiate a Pymongo client each time someone
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# requires a new storage connection.
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self.conn = self.CONNECTION_POOL.connect(url)
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self.version = self.conn.server_info()['versionArray']
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# Require MongoDB 2.4 to use $setOnInsert
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if self.version < pymongo_utils.MINIMUM_COMPATIBLE_MONGODB_VERSION:
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raise storage.StorageBadVersion(
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"Need at least MongoDB %s" %
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pymongo_utils.MINIMUM_COMPATIBLE_MONGODB_VERSION)
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connection_options = pymongo.uri_parser.parse_uri(url)
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self.db = getattr(self.conn, connection_options['database'])
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if connection_options.get('username'):
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self.db.authenticate(connection_options['username'],
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connection_options['password'])
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# NOTE(jd) Upgrading is just about creating index, so let's do this
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# on connection to be sure at least the TTL is correctly updated if
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# needed.
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self.upgrade()
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@staticmethod
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def update_ttl(ttl, ttl_index_name, index_field, coll):
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"""Update or create time_to_live indexes.
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:param ttl: time to live in seconds.
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:param ttl_index_name: name of the index we want to update or create.
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:param index_field: field with the index that we need to update.
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:param coll: collection which indexes need to be updated.
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"""
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indexes = coll.index_information()
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if ttl <= 0:
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if ttl_index_name in indexes:
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coll.drop_index(ttl_index_name)
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return
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if ttl_index_name in indexes:
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return coll.database.command(
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'collMod', coll.name,
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index={'keyPattern': {index_field: pymongo.ASCENDING},
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'expireAfterSeconds': ttl})
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coll.create_index([(index_field, pymongo.ASCENDING)],
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expireAfterSeconds=ttl,
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name=ttl_index_name)
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def upgrade(self):
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# Establish indexes
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#
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# We need variations for user_id vs. project_id because of the
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# way the indexes are stored in b-trees. The user_id and
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# project_id values are usually mutually exclusive in the
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# queries, so the database won't take advantage of an index
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# including both.
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# create collection if not present
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if 'resource' not in self.db.conn.collection_names():
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self.db.conn.create_collection('resource')
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if 'meter' not in self.db.conn.collection_names():
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self.db.conn.create_collection('meter')
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name_qualifier = dict(user_id='', project_id='project_')
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background = dict(user_id=False, project_id=True)
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for primary in ['user_id', 'project_id']:
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name = 'meter_%sidx' % name_qualifier[primary]
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self.db.meter.create_index([
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('resource_id', pymongo.ASCENDING),
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(primary, pymongo.ASCENDING),
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('counter_name', pymongo.ASCENDING),
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('timestamp', pymongo.ASCENDING),
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], name=name, background=background[primary])
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self.db.meter.create_index([('timestamp', pymongo.DESCENDING)],
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name='timestamp_idx')
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# NOTE(ityaptin) This index covers get_resource requests sorting
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# and MongoDB uses part of this compound index for different
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# queries based on any of user_id, project_id, last_sample_timestamp
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# fields
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self.db.resource.create_index([('user_id', pymongo.DESCENDING),
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('project_id', pymongo.DESCENDING),
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('last_sample_timestamp',
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pymongo.DESCENDING)],
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name='resource_user_project_timestamp',)
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self.db.resource.create_index([('last_sample_timestamp',
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pymongo.DESCENDING)],
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name='last_sample_timestamp_idx')
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# update or create time_to_live index
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ttl = cfg.CONF.database.metering_time_to_live
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self.update_ttl(ttl, 'meter_ttl', 'timestamp', self.db.meter)
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self.update_ttl(ttl, 'resource_ttl', 'last_sample_timestamp',
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self.db.resource)
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def clear(self):
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self.conn.drop_database(self.db.name)
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# Connection will be reopened automatically if needed
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self.conn.close()
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def record_metering_data(self, data):
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"""Write the data to the backend storage system.
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:param data: a dictionary such as returned by
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ceilometer.meter.meter_message_from_counter
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"""
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# Record the updated resource metadata - we use $setOnInsert to
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# unconditionally insert sample timestamps and resource metadata
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# (in the update case, this must be conditional on the sample not
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# being out-of-order)
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data = copy.deepcopy(data)
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data['resource_metadata'] = pymongo_utils.improve_keys(
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data.pop('resource_metadata'))
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resource = self.db.resource.find_one_and_update(
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{'_id': data['resource_id']},
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{'$set': {'project_id': data['project_id'],
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'user_id': data['user_id'],
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'source': data['source'],
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},
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'$setOnInsert': {'metadata': data['resource_metadata'],
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'first_sample_timestamp': data['timestamp'],
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'last_sample_timestamp': data['timestamp'],
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},
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'$addToSet': {'meter': {'counter_name': data['counter_name'],
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'counter_type': data['counter_type'],
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'counter_unit': data['counter_unit'],
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},
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},
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},
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upsert=True,
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return_document=pymongo.ReturnDocument.AFTER,
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)
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# only update last sample timestamp if actually later (the usual
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# in-order case)
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last_sample_timestamp = resource.get('last_sample_timestamp')
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if (last_sample_timestamp is None or
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last_sample_timestamp <= data['timestamp']):
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self.db.resource.update_one(
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{'_id': data['resource_id']},
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{'$set': {'metadata': data['resource_metadata'],
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'last_sample_timestamp': data['timestamp']}}
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)
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# only update first sample timestamp if actually earlier (the unusual
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# out-of-order case)
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# NOTE: a null first sample timestamp is not updated as this indicates
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# a pre-existing resource document dating from before we started
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# recording these timestamps in the resource collection
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first_sample_timestamp = resource.get('first_sample_timestamp')
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if (first_sample_timestamp is not None and
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first_sample_timestamp > data['timestamp']):
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self.db.resource.update_one(
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{'_id': data['resource_id']},
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{'$set': {'first_sample_timestamp': data['timestamp']}}
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)
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# Record the raw data for the meter. Use a copy so we do not
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# modify a data structure owned by our caller (the driver adds
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# a new key '_id').
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record = copy.copy(data)
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record['recorded_at'] = timeutils.utcnow()
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self.db.meter.insert_one(record)
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def clear_expired_metering_data(self, ttl):
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"""Clear expired data from the backend storage system.
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Clearing occurs with native MongoDB time-to-live feature.
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"""
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LOG.debug("Clearing expired metering data is based on native "
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"MongoDB time to live feature and going in background.")
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@classmethod
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def _build_sort_instructions(cls, sort_keys=None, sort_dir='desc'):
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"""Returns a sort_instruction and paging operator.
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Sort instructions are used in the query to determine what attributes
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to sort on and what direction to use.
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:param q: The query dict passed in.
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:param sort_keys: array of attributes by which results be sorted.
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:param sort_dir: direction in which results be sorted (asc, desc).
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:return: sort instructions and paging operator
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"""
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sort_keys = sort_keys or []
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sort_instructions = []
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_sort_dir, operation = cls.SORT_OPERATION_MAPPING.get(
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sort_dir, cls.SORT_OPERATION_MAPPING['desc'])
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for _sort_key in sort_keys:
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_instruction = (_sort_key, _sort_dir)
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sort_instructions.append(_instruction)
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return sort_instructions, operation
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def _get_time_constrained_resources(self, query,
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start_timestamp, start_timestamp_op,
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end_timestamp, end_timestamp_op,
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metaquery, resource, limit):
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"""Return an iterable of models.Resource instances
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Items are constrained by sample timestamp.
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:param query: project/user/source query
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:param start_timestamp: modified timestamp start range.
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:param start_timestamp_op: start time operator, like gt, ge.
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:param end_timestamp: modified timestamp end range.
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:param end_timestamp_op: end time operator, like lt, le.
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:param metaquery: dict with metadata to match on.
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:param resource: resource filter.
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"""
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if resource is not None:
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query['resource_id'] = resource
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# Add resource_ prefix so it matches the field in the db
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query.update(dict(('resource_' + k, v)
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for (k, v) in six.iteritems(metaquery)))
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# FIXME(dhellmann): This may not perform very well,
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# but doing any better will require changing the database
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# schema and that will need more thought than I have time
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# to put into it today.
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# Look for resources matching the above criteria and with
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# samples in the time range we care about, then change the
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# resource query to return just those resources by id.
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ts_range = pymongo_utils.make_timestamp_range(start_timestamp,
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end_timestamp,
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start_timestamp_op,
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end_timestamp_op)
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if ts_range:
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query['timestamp'] = ts_range
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sort_keys = base._handle_sort_key('resource')
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sort_instructions = self._build_sort_instructions(sort_keys)[0]
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# use a unique collection name for the results collection,
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# as result post-sorting (as oppposed to reduce pre-sorting)
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# is not possible on an inline M-R
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out = 'resource_list_%s' % uuid.uuid4()
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self.db.meter.map_reduce(self.MAP_RESOURCES,
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self.REDUCE_RESOURCES,
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out=out,
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sort={'resource_id': 1},
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query=query)
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try:
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if limit is not None:
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results = self.db[out].find(sort=sort_instructions,
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limit=limit)
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else:
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results = self.db[out].find(sort=sort_instructions)
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for r in results:
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resource = r['value']
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yield models.Resource(
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resource_id=r['_id'],
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user_id=resource['user_id'],
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project_id=resource['project_id'],
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first_sample_timestamp=resource['first_timestamp'],
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last_sample_timestamp=resource['last_timestamp'],
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source=resource['source'],
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metadata=pymongo_utils.unquote_keys(resource['metadata']))
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finally:
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self.db[out].drop()
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def _get_floating_resources(self, query, metaquery, resource, limit):
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"""Return an iterable of models.Resource instances
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Items are unconstrained by timestamp.
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:param query: project/user/source query
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:param metaquery: dict with metadata to match on.
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:param resource: resource filter.
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"""
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if resource is not None:
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query['_id'] = resource
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query.update(dict((k, v)
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for (k, v) in six.iteritems(metaquery)))
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keys = base._handle_sort_key('resource')
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sort_keys = ['last_sample_timestamp' if i == 'timestamp' else i
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for i in keys]
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sort_instructions = self._build_sort_instructions(sort_keys)[0]
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if limit is not None:
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results = self.db.resource.find(query, sort=sort_instructions,
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limit=limit)
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else:
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results = self.db.resource.find(query, sort=sort_instructions)
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for r in results:
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yield models.Resource(
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resource_id=r['_id'],
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user_id=r['user_id'],
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project_id=r['project_id'],
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first_sample_timestamp=r.get('first_sample_timestamp',
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self._GENESIS),
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last_sample_timestamp=r.get('last_sample_timestamp',
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self._APOCALYPSE),
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source=r['source'],
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metadata=pymongo_utils.unquote_keys(r['metadata']))
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def get_resources(self, user=None, project=None, source=None,
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start_timestamp=None, start_timestamp_op=None,
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end_timestamp=None, end_timestamp_op=None,
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metaquery=None, resource=None, limit=None):
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"""Return an iterable of models.Resource instances
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:param user: Optional ID for user that owns the resource.
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:param project: Optional ID for project that owns the resource.
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:param source: Optional source filter.
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:param start_timestamp: Optional modified timestamp start range.
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:param start_timestamp_op: Optional start time operator, like gt, ge.
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:param end_timestamp: Optional modified timestamp end range.
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:param end_timestamp_op: Optional end time operator, like lt, le.
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:param metaquery: Optional dict with metadata to match on.
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:param resource: Optional resource filter.
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:param limit: Maximum number of results to return.
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"""
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if limit == 0:
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return
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metaquery = pymongo_utils.improve_keys(metaquery, metaquery=True) or {}
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query = {}
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if user is not None:
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query['user_id'] = user
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if project is not None:
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query['project_id'] = project
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if source is not None:
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query['source'] = source
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if start_timestamp or end_timestamp:
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return self._get_time_constrained_resources(query,
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start_timestamp,
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start_timestamp_op,
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end_timestamp,
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end_timestamp_op,
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metaquery, resource,
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limit)
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else:
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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, func in Connection.STANDARD_AGGREGATES.items():
|
|
if attr in result:
|
|
stats_args.update(func.finalize(result,
|
|
version_array=self.version))
|
|
|
|
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 {}
|