d65dd17016
This change is needed to make Ceilometer code both Python 2.x and 3.x compatible in some future. Oslo modules are left without changes in this change, that will be done directly in the oslo-incubator code. Partially-Implements: blueprint ceilometer-py33-support Change-Id: Ic7fe5819f85524bb36f04dec6cad10d4cf2b935d
396 lines
16 KiB
Python
396 lines
16 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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# Author: Doug Hellmann <doug.hellmann@dreamhost.com>
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# Julien Danjou <julien@danjou.info>
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# Tong Li <litong01@us.ibm.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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"""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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import pymongo
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import six
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from ceilometer.openstack.common import log
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from ceilometer.openstack.common import timeutils
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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 upgrade(self, version=None):
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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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resource_id = str(bson.objectid.ObjectId())
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self.db.resource.insert({'_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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self.db.meter.insert({'_id': meter_id,
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'no_key': meter_id})
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self.db.resource.ensure_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.ensure_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.ensure_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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# remove API v1 related table
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self.db.user.drop()
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self.db.project.drop()
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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)
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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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self.db.resource.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'] 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(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, pagination=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 pagination: Optional pagination query.
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"""
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if pagination:
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raise NotImplementedError('Pagination not implemented')
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metaquery = metaquery 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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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=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 NotImplementedError("Unable to group by these fields")
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if aggregate:
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raise NotImplementedError('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:
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period_start = sample_filter.start
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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.maxint, max=-sys.maxint,
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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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