1852eaf48e
unrestricted listing of resources can require significant memory. this patch implements mandatory limit on resource-list Change-Id: I5820ce759b20757febc1b92c100f584234b36b68 Implements: blueprint mandatory-limit
423 lines
18 KiB
Python
423 lines
18 KiB
Python
# Copyright 2012 New Dream Network, LLC (DreamHost)
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# Copyright 2013 eNovance
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# Copyright 2013 IBM Corp
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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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"""DB2 storage backend
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"""
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from __future__ import division
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import copy
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import datetime
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import itertools
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import sys
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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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}
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class Connection(pymongo_base.Connection):
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"""The db2 storage for Ceilometer
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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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GROUP = {'_id': '$counter_name',
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'unit': {'$min': '$counter_unit'},
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'min': {'$min': '$counter_volume'},
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'max': {'$max': '$counter_volume'},
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'sum': {'$sum': '$counter_volume'},
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'count': {'$sum': 1},
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'duration_start': {'$min': '$timestamp'},
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'duration_end': {'$max': '$timestamp'},
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}
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PROJECT = {'_id': 0, 'unit': 1,
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'min': 1, 'max': 1, 'sum': 1, 'count': 1,
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'avg': {'$divide': ['$sum', '$count']},
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'duration_start': 1,
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'duration_end': 1,
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}
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SORT_OPERATION_MAP = {'desc': pymongo.DESCENDING, 'asc': pymongo.ASCENDING}
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SECONDS_IN_A_DAY = 86400
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def __init__(self, url):
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# Since we are using pymongo, even though we are connecting to DB2
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# we still have to make sure that the scheme which used to distinguish
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# db2 driver from mongodb driver be replaced so that pymongo will not
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# produce an exception on the scheme.
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url = url.replace('db2:', 'mongodb:', 1)
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self.conn = self.CONNECTION_POOL.connect(url)
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# Require MongoDB 2.2 to use aggregate(), since we are using mongodb
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# as backend for test, the following code is necessary to make sure
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# that the test wont try aggregate on older mongodb during the test.
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# For db2, the versionArray won't be part of the server_info, so there
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# will not be exception when real db2 gets used as backend.
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server_info = self.conn.server_info()
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if server_info.get('sysInfo'):
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self._using_mongodb = True
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else:
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self._using_mongodb = False
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if self._using_mongodb and server_info.get('versionArray') < [2, 2]:
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raise storage.StorageBadVersion("Need at least MongoDB 2.2")
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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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self.upgrade()
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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.
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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 parameters
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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 = cls.SORT_OPERATION_MAP.get(
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sort_dir, cls.SORT_OPERATION_MAP['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
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def _generate_random_str(self, str_len):
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init_str = str(bson.objectid.ObjectId())
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objectid_len = len(init_str)
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if str_len >= objectid_len:
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init_str = (init_str * int(str_len/objectid_len) +
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'x' * int(str_len % objectid_len))
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return init_str
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def upgrade(self, version=None):
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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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# 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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if self.db.resource.index_information() == {}:
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# Initializing a longer resource id to workaround DB2 nosql issue.
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# Longer resource id is required by compute node's resource as
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# their id is '<hostname>_<nodename>'. DB2 creates a VARCHAR(70)
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# for resource id when its length < 70. But DB2 can create a
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# VARCHAR(n) for the resource id which has n(n>70) characters.
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# Users can adjust 'db2nosql_resource_id_maxlen'(default is 512)
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# for their ENV.
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resource_id = self._generate_random_str(
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cfg.CONF.database.db2nosql_resource_id_maxlen)
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self.db.resource.insert_one({'_id': resource_id,
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'no_key': resource_id})
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meter_id = str(bson.objectid.ObjectId())
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timestamp = timeutils.utcnow()
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self.db.meter.insert_one({'_id': meter_id,
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'no_key': meter_id,
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'timestamp': timestamp})
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self.db.resource.create_index([
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('user_id', pymongo.ASCENDING),
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('project_id', pymongo.ASCENDING),
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('source', pymongo.ASCENDING)], name='resource_idx')
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self.db.meter.create_index([
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('resource_id', pymongo.ASCENDING),
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('user_id', pymongo.ASCENDING),
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('project_id', pymongo.ASCENDING),
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('counter_name', pymongo.ASCENDING),
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('timestamp', pymongo.ASCENDING),
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('source', pymongo.ASCENDING)], name='meter_idx')
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self.db.meter.create_index([('timestamp',
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pymongo.DESCENDING)],
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name='timestamp_idx')
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self.db.resource.remove({'_id': resource_id})
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self.db.meter.remove({'_id': meter_id})
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def clear(self):
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# db2 does not support drop_database, remove all collections
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for col in ['resource', 'meter']:
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self.db[col].drop()
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# drop_database command does nothing on db2 database since this has
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# not been implemented. However calling this method is important for
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# removal of all the empty dbs created during the test runs since
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# test run is against mongodb on Jenkins
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self.conn.drop_database(self.db.name)
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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
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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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self.db.resource.update_one(
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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'] or 'null',
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'metadata': data['resource_metadata'],
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'source': data['source'],
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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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)
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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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# Make sure that the data does have field _id which db2 wont add
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# automatically.
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if record.get('_id') is None:
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record['_id'] = str(bson.objectid.ObjectId())
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self.db.meter.insert_one(record)
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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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q = {}
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if user is not None:
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q['user_id'] = user
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if project is not None:
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q['project_id'] = project
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if source is not None:
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q['source'] = source
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if resource is not None:
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q['resource_id'] = resource
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# Add resource_ prefix so it matches the field in the db
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q.update(dict(('resource_' + k, v)
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for (k, v) in six.iteritems(metaquery)))
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if start_timestamp or end_timestamp:
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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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q['timestamp'] = ts_range
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sort_keys = base._handle_sort_key('resource', 'timestamp')
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sort_keys.insert(0, 'resource_id')
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sort_instructions = self._build_sort_instructions(sort_keys=sort_keys,
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sort_dir='desc')
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resource = lambda x: x['resource_id']
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if limit is not None:
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meters = self.db.meter.find(q, sort=sort_instructions,
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limit=limit)
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else:
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meters = self.db.meter.find(q, sort=sort_instructions)
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for resource_id, r_meters in itertools.groupby(meters, key=resource):
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# Because we have to know first/last timestamp, and we need a full
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# list of references to the resource's meters, we need a tuple
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# here.
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r_meters = tuple(r_meters)
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latest_meter = r_meters[0]
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last_ts = latest_meter['timestamp']
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first_ts = r_meters[-1]['timestamp']
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yield models.Resource(resource_id=latest_meter['resource_id'],
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project_id=latest_meter['project_id'],
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first_sample_timestamp=first_ts,
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last_sample_timestamp=last_ts,
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source=latest_meter['source'],
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user_id=latest_meter['user_id'],
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metadata=pymongo_utils.unquote_keys(
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latest_meter['resource_metadata']))
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def get_meter_statistics(self, sample_filter, period=None, groupby=None,
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aggregate=None):
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"""Return an iterable of models.Statistics instance.
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Items are containing meter statistics described by the query
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parameters. The filter must have a meter value set.
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"""
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if (groupby and
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set(groupby) - set(['user_id', 'project_id',
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'resource_id', 'source'])):
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raise ceilometer.NotImplementedError(
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"Unable to group by these fields")
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if aggregate:
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raise ceilometer.NotImplementedError(
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'Selectable aggregates not implemented')
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q = pymongo_utils.make_query_from_filter(sample_filter)
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if period:
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if sample_filter.start_timestamp:
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period_start = sample_filter.start_timestamp
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else:
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period_start = self.db.meter.find(
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limit=1, sort=[('timestamp',
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pymongo.ASCENDING)])[0]['timestamp']
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if groupby:
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sort_keys = ['counter_name'] + groupby + ['timestamp']
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else:
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sort_keys = ['counter_name', 'timestamp']
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sort_instructions = self._build_sort_instructions(sort_keys=sort_keys,
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sort_dir='asc')
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meters = self.db.meter.find(q, sort=sort_instructions)
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def _group_key(meter):
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# the method to define a key for groupby call
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key = {}
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for y in sort_keys:
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if y == 'timestamp' and period:
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key[y] = (timeutils.delta_seconds(period_start,
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meter[y]) // period)
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elif y != 'timestamp':
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key[y] = meter[y]
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return key
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def _to_offset(periods):
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return {'days': (periods * period) // self.SECONDS_IN_A_DAY,
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'seconds': (periods * period) % self.SECONDS_IN_A_DAY}
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for key, grouped_meters in itertools.groupby(meters, key=_group_key):
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stat = models.Statistics(unit=None,
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min=sys.maxsize, max=-sys.maxsize,
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avg=0, sum=0, count=0,
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period=0, period_start=0, period_end=0,
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duration=0, duration_start=0,
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duration_end=0, groupby=None)
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for meter in grouped_meters:
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stat.unit = meter.get('counter_unit', '')
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m_volume = meter.get('counter_volume')
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if stat.min > m_volume:
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stat.min = m_volume
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if stat.max < m_volume:
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stat.max = m_volume
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stat.sum += m_volume
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stat.count += 1
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if stat.duration_start == 0:
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stat.duration_start = meter['timestamp']
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stat.duration_end = meter['timestamp']
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if groupby and not stat.groupby:
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stat.groupby = {}
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for group_key in groupby:
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stat.groupby[group_key] = meter[group_key]
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stat.duration = timeutils.delta_seconds(stat.duration_start,
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stat.duration_end)
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stat.avg = stat.sum / stat.count
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if period:
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stat.period = period
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periods = key.get('timestamp')
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stat.period_start = (period_start +
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datetime.
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timedelta(**(_to_offset(periods))))
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stat.period_end = (period_start +
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datetime.
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timedelta(**(_to_offset(periods + 1))))
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else:
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stat.period_start = stat.duration_start
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stat.period_end = stat.duration_end
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yield stat
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