# -*- encoding: utf-8 -*- # # Copyright © 2012 New Dream Network, LLC (DreamHost) # Copyright © 2013 eNovance # # Author: Doug Hellmann # Julien Danjou # # Licensed under the Apache License, Version 2.0 (the "License"); you may # not use this file except in compliance with the License. You may obtain # a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, WITHOUT # WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the # License for the specific language governing permissions and limitations # under the License. """MongoDB storage backend """ import copy import datetime import nose import operator import os import re import urlparse import bson.code import pymongo from ceilometer.openstack.common import log from ceilometer.storage import base LOG = log.getLogger(__name__) class MongoDBStorage(base.StorageEngine): """Put the data into a MongoDB database Collections:: - user - { _id: user id source: [ array of source ids reporting for the user ] } - project - { _id: project id source: [ array of source ids reporting for the project ] } - meter - the raw incoming data - resource - the metadata for resources - { _id: uuid of resource, metadata: metadata dictionaries user_id: uuid project_id: uuid meter: [ array of {counter_name: string, counter_type: string, counter_unit: string} ] } """ OPTIONS = [] def register_opts(self, conf): """Register any configuration options used by this engine. """ conf.register_opts(self.OPTIONS) def get_connection(self, conf): """Return a Connection instance based on the configuration settings. """ return Connection(conf) def make_timestamp_range(start, end): """Given two possible datetimes, create the query document to find timestamps within that range using $gte for the lower bound and $lt for the upper bound. """ ts_range = {} if start: ts_range['$gte'] = start if end: ts_range['$lt'] = end return ts_range def make_query_from_filter(event_filter, require_meter=True): """Return a query dictionary based on the settings in the filter. :param filter: EventFilter instance :param require_meter: If true and the filter does not have a meter, raise an error. """ q = {} if event_filter.user: q['user_id'] = event_filter.user if event_filter.project: q['project_id'] = event_filter.project if event_filter.meter: q['counter_name'] = event_filter.meter elif require_meter: raise RuntimeError('Missing required meter specifier') ts_range = make_timestamp_range(event_filter.start, event_filter.end) if ts_range: q['timestamp'] = ts_range if event_filter.resource: q['resource_id'] = event_filter.resource if event_filter.source: q['source'] = event_filter.source # so the samples call metadata resource_metadata, so we convert # to that. q.update(dict(('resource_%s' % k, v) for (k, v) in event_filter.metaquery.iteritems())) return q class Connection(base.Connection): """MongoDB connection. """ _mim_instance = None # JavaScript function for doing map-reduce to get a counter volume # total. MAP_COUNTER_VOLUME = bson.code.Code(""" function() { emit(this.resource_id, this.counter_volume); } """) # JavaScript function for doing map-reduce to get a maximum value # from a range. (from # http://cookbook.mongodb.org/patterns/finding_max_and_min/) REDUCE_MAX = bson.code.Code(""" function (key, values) { return Math.max.apply(Math, values); } """) # JavaScript function for doing map-reduce to get a sum. REDUCE_SUM = bson.code.Code(""" function (key, values) { var total = 0; for (var i = 0; i < values.length; i++) { total += values[i]; } return total; } """) # MAP_TIMESTAMP and REDUCE_MIN_MAX are based on the recipe # http://cookbook.mongodb.org/patterns/finding_max_and_min_values_for_a_key MAP_TIMESTAMP = bson.code.Code(""" function () { emit('timestamp', { min : this.timestamp, max : this.timestamp } ) } """) REDUCE_MIN_MAX = bson.code.Code(""" function (key, values) { var res = values[0]; for ( var i=1; i res.max ) res.max = values[i].max; } return res; } """) MAP_STATS = bson.code.Code(""" function () { emit('statistics', { min : this.counter_volume, max : this.counter_volume, sum : this.counter_volume, count : NumberInt(1), duration_start : this.timestamp, duration_end : this.timestamp, period_start : this.timestamp, period_end : this.timestamp} ) } """) MAP_STATS_PERIOD = bson.code.Code(""" function () { var period = %d * 1000; var period_first = %d * 1000; var period_start = period_first + (Math.floor(new Date(this.timestamp.getTime() - period_first) / period) * period); emit(period_start, { min : this.counter_volume, max : this.counter_volume, sum : this.counter_volume, count : NumberInt(1), duration_start : this.timestamp, duration_end : this.timestamp, period_start : new Date(period_start), period_end : new Date(period_start + period) } ) } """) REDUCE_STATS = bson.code.Code(""" function (key, values) { var res = values[0]; for ( var i=1; i res.max ) res.max = values[i].max; res.count += values[i].count; res.sum += values[i].sum; if ( values[i].duration_start < res.duration_start ) res.duration_start = values[i].duration_start; if ( values[i].duration_end > res.duration_end ) res.duration_end = values[i].duration_end; } return res; } """) FINALIZE_STATS = bson.code.Code(""" function (key, value) { value.avg = value.sum / value.count; value.duration = (value.duration_end - value.duration_start) / 1000; value.period = NumberInt((value.period_end - value.period_start) / 1000); return value; }""") def __init__(self, conf): opts = self._parse_connection_url(conf.database_connection) LOG.info('connecting to MongoDB on %s:%s', opts['host'], opts['port']) if opts['host'] == '__test__': url = os.environ.get('CEILOMETER_TEST_MONGODB_URL') if url: opts = self._parse_connection_url(url) self.conn = pymongo.Connection(opts['host'], opts['port'], safe=True) else: # MIM will die if we have too many connections, so use a # Singleton if Connection._mim_instance is None: try: from ming import mim except ImportError: raise nose.SkipTest("Ming not found") LOG.debug('Creating a new MIM Connection object') Connection._mim_instance = mim.Connection() self.conn = Connection._mim_instance LOG.debug('Using MIM for test connection') else: self.conn = pymongo.Connection(opts['host'], opts['port'], safe=True) self.db = getattr(self.conn, opts['dbname']) if 'username' in opts: self.db.authenticate(opts['username'], opts['password']) # Establish indexes # # We need variations for user_id vs. project_id because of the # way the indexes are stored in b-trees. The user_id and # project_id values are usually mutually exclusive in the # queries, so the database won't take advantage of an index # including both. for primary in ['user_id', 'project_id']: self.db.resource.ensure_index([ (primary, pymongo.ASCENDING), ('source', pymongo.ASCENDING), ], name='resource_idx') self.db.meter.ensure_index([ ('resource_id', pymongo.ASCENDING), (primary, pymongo.ASCENDING), ('counter_name', pymongo.ASCENDING), ('timestamp', pymongo.ASCENDING), ('source', pymongo.ASCENDING), ], name='meter_idx') def upgrade(self, version=None): pass def clear(self): if self._mim_instance is not None: # Don't want to use drop_database() because # may end up running out of spidermonkey instances. # http://davisp.lighthouseapp.com/projects/26898/tickets/22 self.db.clear() else: self.conn.drop_database(self.db) def _parse_connection_url(self, url): opts = {} result = urlparse.urlparse(url) opts['dbtype'] = result.scheme opts['dbname'] = result.path.replace('/', '') netloc_match = re.match(r'(?:(\w+:\w+)@)?(.*)', result.netloc) auth = netloc_match.group(1) netloc = netloc_match.group(2) if auth: opts['username'], opts['password'] = auth.split(':') if ':' in netloc: opts['host'], port = netloc.split(':') else: opts['host'] = netloc port = 27017 opts['port'] = port and int(port) or 27017 return opts def record_metering_data(self, data): """Write the data to the backend storage system. :param data: a dictionary such as returned by ceilometer.meter.meter_message_from_counter """ # Make sure we know about the user and project self.db.user.update( {'_id': data['user_id']}, {'$addToSet': {'source': data['source'], }, }, upsert=True, ) self.db.project.update( {'_id': data['project_id']}, {'$addToSet': {'source': data['source'], }, }, upsert=True, ) # Record the updated resource metadata self.db.resource.update( {'_id': data['resource_id']}, {'$set': {'project_id': data['project_id'], 'user_id': data['user_id'], 'metadata': data['resource_metadata'], 'source': data['source'], }, '$addToSet': {'meter': {'counter_name': data['counter_name'], 'counter_type': data['counter_type'], 'counter_unit': data['counter_unit'], }, }, }, upsert=True, ) # Record the raw data for the event. Use a copy so we do not # modify a data structure owned by our caller (the driver adds # a new key '_id'). record = copy.copy(data) self.db.meter.insert(record) return def get_users(self, source=None): """Return an iterable of user id strings. :param source: Optional source filter. """ q = {} if source is not None: q['source'] = source return sorted(self.db.user.find(q).distinct('_id')) def get_projects(self, source=None): """Return an iterable of project id strings. :param source: Optional source filter. """ q = {} if source is not None: q['source'] = source return sorted(self.db.project.find(q).distinct('_id')) def get_resources(self, user=None, project=None, source=None, start_timestamp=None, end_timestamp=None, metaquery={}, resource=None): """Return an iterable of dictionaries containing resource information. { 'resource_id': UUID of the resource, 'project_id': UUID of project owning the resource, 'user_id': UUID of user owning the resource, 'timestamp': UTC datetime of last update to the resource, 'metadata': most current metadata for the resource, 'meter': list of the meters reporting data for the resource, } :param user: Optional ID for user that owns the resource. :param project: Optional ID for project that owns the resource. :param source: Optional source filter. :param start_timestamp: Optional modified timestamp start range. :param end_timestamp: Optional modified timestamp end range. :param metaquery: Optional dict with metadata to match on. :param resource: Optional resource filter. """ q = {} if user is not None: q['user_id'] = user if project is not None: q['project_id'] = project if source is not None: q['source'] = source if resource is not None: q['resource_id'] = resource # Add resource_ prefix so it matches the field in the db q.update(dict(('resource_' + k, v) for (k, v) in metaquery.iteritems())) # FIXME(dhellmann): This may not perform very well, # but doing any better will require changing the database # schema and that will need more thought than I have time # to put into it today. if start_timestamp or end_timestamp: # Look for resources matching the above criteria and with # samples in the time range we care about, then change the # resource query to return just those resources by id. ts_range = make_timestamp_range(start_timestamp, end_timestamp) if ts_range: q['timestamp'] = ts_range # FIXME(jd): We should use self.db.meter.group() and not use the # resource collection, but that's not supported by MIM, so it's not # easily testable yet. Since it was bugged before anyway, it's still # better for now. resource_ids = self.db.meter.find(q).distinct('resource_id') q = {'_id': {'$in': resource_ids}} for resource in self.db.resource.find(q): r = {} r.update(resource) # Replace the '_id' key with 'resource_id' to meet the # caller's expectations. r['resource_id'] = r['_id'] del r['_id'] yield r def get_meters(self, user=None, project=None, resource=None, source=None, metaquery={}): """Return an iterable of dictionaries containing meter information. { 'name': name of the meter, 'type': type of the meter (guage, counter), 'unit': unit of the meter, 'resource_id': UUID of the resource, 'project_id': UUID of project owning the resource, 'user_id': UUID of user owning the resource, } :param user: Optional ID for user that owns the resource. :param project: Optional ID for project that owns the resource. :param resource: Optional resource filter. :param source: Optional source filter. :param metaquery: Optional dict with metadata to match on. """ q = {} if user is not None: q['user_id'] = user if project is not None: q['project_id'] = project if resource is not None: q['_id'] = resource if source is not None: q['source'] = source q.update(metaquery) for r in self.db.resource.find(q): for r_meter in r['meter']: m = {} m['name'] = r_meter['counter_name'] m['type'] = r_meter['counter_type'] # Return empty string if 'counter_unit' is not valid for # backward compaitiblity. m['unit'] = r_meter.get('counter_unit', '') m['resource_id'] = r['_id'] m['project_id'] = r['project_id'] m['user_id'] = r['user_id'] yield m def get_samples(self, event_filter): """Return an iterable of samples as created by :func:`ceilometer.meter.meter_message_from_counter`. """ q = make_query_from_filter(event_filter, require_meter=False) samples = self.db.meter.find(q) for s in samples: # Remove the ObjectId generated by the database when # the event was inserted. It is an implementation # detail that should not leak outside of the driver. del s['_id'] yield s def get_meter_statistics(self, event_filter, period=None): """Return a dictionary containing meter statistics. described by the query parameters. The filter must have a meter value set. { 'min': 'max': 'avg': 'sum': 'count': 'period': 'period_start': 'period_end': 'duration': 'duration_start': 'duration_end': } """ q = make_query_from_filter(event_filter) if period: map_stats = self.MAP_STATS_PERIOD % \ (period, int(event_filter.start.strftime('%s')) if event_filter.start else 0) else: map_stats = self.MAP_STATS results = self.db.meter.map_reduce( map_stats, self.REDUCE_STATS, {'inline': 1}, finalize=self.FINALIZE_STATS, query=q, ) return sorted((r['value'] for r in results['results']), key=operator.itemgetter('period_start')) def get_volume_sum(self, event_filter): """Return the sum of the volume field for the samples described by the query parameters. """ q = make_query_from_filter(event_filter) results = self.db.meter.map_reduce(self.MAP_COUNTER_VOLUME, self.REDUCE_SUM, {'inline': 1}, query=q, ) return ({'resource_id': r['_id'], 'value': r['value']} for r in results['results']) def get_volume_max(self, event_filter): """Return the maximum of the volume field for the samples described by the query parameters. """ q = make_query_from_filter(event_filter) results = self.db.meter.map_reduce(self.MAP_COUNTER_VOLUME, self.REDUCE_MAX, {'inline': 1}, query=q, ) return ({'resource_id': r['_id'], 'value': r['value']} for r in results['results']) def _fix_interval_min_max(self, a_min, a_max): if hasattr(a_min, 'valueOf') and a_min.valueOf is not None: # NOTE (dhellmann): HACK ALERT # # The real MongoDB server can handle Date objects and # the driver converts them to datetime instances # correctly but the in-memory implementation in MIM # (used by the tests) returns a spidermonkey.Object # representing the "value" dictionary and there # doesn't seem to be a way to recursively introspect # that object safely to convert the min and max values # back to datetime objects. In this method, we know # what type the min and max values are expected to be, # so it is safe to do the conversion # here. JavaScript's time representation uses # different units than Python's, so we divide to # convert to the right units and then create the # datetime instances to return. # # The issue with MIM is documented at # https://sourceforge.net/p/merciless/bugs/3/ # a_min = datetime.datetime.fromtimestamp( a_min.valueOf() // 1000) a_max = datetime.datetime.fromtimestamp( a_max.valueOf() // 1000) return (a_min, a_max) def get_event_interval(self, event_filter): """Return the min and max timestamps from samples, using the event_filter to limit the samples seen. ( datetime.datetime(), datetime.datetime() ) """ q = make_query_from_filter(event_filter) results = self.db.meter.map_reduce(self.MAP_TIMESTAMP, self.REDUCE_MIN_MAX, {'inline': 1}, query=q, ) if results['results']: answer = results['results'][0]['value'] return self._fix_interval_min_max(answer['min'], answer['max']) return (None, None) def require_map_reduce(conn): """Raises SkipTest if the connection is using mim. """ # NOTE(dhellmann): mim requires spidermonkey to implement the # map-reduce functions, so if we can't import it then just # skip these tests unless we aren't using mim. try: import spidermonkey except BaseException: if isinstance(conn.conn, mim.Connection): raise nose.SkipTest('requires spidermonkey')