aodh/ceilometer/storage/mongo/utils.py
Igor Degtiarov 8743e3d53a [Mongodb] Implement events on Mongodb and DB2
In this change events are written into database (Mongodb, DB2) and
retrieved from it.

Several methods were implemented for this purpose:
1. record_events --- store events into database
2. get_events, get_event_types, get_trait_types and get_traits --- get data
from db.
Add some attendant changes.

Implements: blueprint mongodb-events-feature
Change-Id: I8a525e5bf307efcc894f581e4de12094a39343e4
2014-07-11 12:05:15 +03:00

325 lines
11 KiB
Python

#
# Copyright Ericsson AB 2013. All rights reserved
#
# Authors: Ildiko Vancsa <ildiko.vancsa@ericsson.com>
# Balazs Gibizer <balazs.gibizer@ericsson.com>
#
# Licensed under the Apache License, Version 2.0 (the "License"); you may
# not use this file except in compliance with the License. You may obtain
# a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
# WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
# License for the specific language governing permissions and limitations
# under the License.
"""Common functions for MongoDB and DB2 backends
"""
import time
from oslo.config import cfg
import pymongo
import weakref
from ceilometer.openstack.common.gettextutils import _
from ceilometer.openstack.common import log
from ceilometer.openstack.common import network_utils
LOG = log.getLogger(__name__)
cfg.CONF.import_opt('max_retries', 'ceilometer.openstack.common.db.options',
group="database")
cfg.CONF.import_opt('retry_interval', 'ceilometer.openstack.common.db.options',
group="database")
EVENT_TRAIT_TYPES = {'none': 0, 'string': 1, 'integer': 2, 'float': 3,
'datetime': 4}
OP_SIGN = {'lt': '$lt', 'le': '$lte', 'ne': '$ne', 'gt': '$gt', 'ge': '$gte'}
def make_timestamp_range(start, end,
start_timestamp_op=None, end_timestamp_op=None):
"""Create the query document to find timestamps within that range.
This is done by given two possible datetimes and their operations.
By default, using $gte for the lower bound and $lt for the upper bound.
"""
ts_range = {}
if start:
if start_timestamp_op == 'gt':
start_timestamp_op = '$gt'
else:
start_timestamp_op = '$gte'
ts_range[start_timestamp_op] = start
if end:
if end_timestamp_op == 'le':
end_timestamp_op = '$lte'
else:
end_timestamp_op = '$lt'
ts_range[end_timestamp_op] = end
return ts_range
def make_events_query_from_filter(event_filter):
"""Return start and stop row for filtering and a query.
Query is based on the selected parameter.
:param event_filter: storage.EventFilter object.
"""
q = {}
ts_range = make_timestamp_range(event_filter.start_time,
event_filter.end_time)
if ts_range:
q['timestamp'] = ts_range
if event_filter.event_type:
q['event_type'] = event_filter.event_type
if event_filter.message_id:
q['_id'] = event_filter.message_id
if event_filter.traits_filter:
q.setdefault('traits')
for trait_filter in event_filter.traits_filter:
op = trait_filter.pop('op', 'eq')
dict_query = {}
for k, v in trait_filter.iteritems():
if v is not None:
# All parameters in EventFilter['traits'] are optional, so
# we need to check if they are in the query or no.
if k == 'key':
dict_query.setdefault('trait_name', v)
elif k in ['string', 'integer', 'datetime', 'float']:
dict_query.setdefault('trait_type',
EVENT_TRAIT_TYPES[k])
dict_query.setdefault('trait_value',
v if op == 'eq'
else {OP_SIGN[op]: v})
dict_query = {'$elemMatch': dict_query}
if q['traits'] is None:
q['traits'] = dict_query
elif q.get('$and') is None:
q.setdefault('$and', [{'traits': q.pop('traits')},
{'traits': dict_query}])
else:
q['$and'].append({'traits': dict_query})
return q
def make_query_from_filter(sample_filter, require_meter=True):
"""Return a query dictionary based on the settings in the filter.
:param sample_filter: SampleFilter instance
:param require_meter: If true and the filter does not have a meter,
raise an error.
"""
q = {}
if sample_filter.user:
q['user_id'] = sample_filter.user
if sample_filter.project:
q['project_id'] = sample_filter.project
if sample_filter.meter:
q['counter_name'] = sample_filter.meter
elif require_meter:
raise RuntimeError('Missing required meter specifier')
ts_range = make_timestamp_range(sample_filter.start,
sample_filter.end,
sample_filter.start_timestamp_op,
sample_filter.end_timestamp_op)
if ts_range:
q['timestamp'] = ts_range
if sample_filter.resource:
q['resource_id'] = sample_filter.resource
if sample_filter.source:
q['source'] = sample_filter.source
if sample_filter.message_id:
q['message_id'] = sample_filter.message_id
# so the samples call metadata resource_metadata, so we convert
# to that.
q.update(dict(('resource_%s' % k, v)
for (k, v) in sample_filter.metaquery.iteritems()))
return q
class ConnectionPool(object):
def __init__(self):
self._pool = {}
def connect(self, url):
connection_options = pymongo.uri_parser.parse_uri(url)
del connection_options['database']
del connection_options['username']
del connection_options['password']
del connection_options['collection']
pool_key = tuple(connection_options)
if pool_key in self._pool:
client = self._pool.get(pool_key)()
if client:
return client
splitted_url = network_utils.urlsplit(url)
log_data = {'db': splitted_url.scheme,
'nodelist': connection_options['nodelist']}
LOG.info(_('Connecting to %(db)s on %(nodelist)s') % log_data)
client = self._mongo_connect(url)
self._pool[pool_key] = weakref.ref(client)
return client
@staticmethod
def _mongo_connect(url):
max_retries = cfg.CONF.database.max_retries
retry_interval = cfg.CONF.database.retry_interval
attempts = 0
while True:
try:
client = pymongo.MongoClient(url, safe=True)
except pymongo.errors.ConnectionFailure as e:
if max_retries >= 0 and attempts >= max_retries:
LOG.error(_('Unable to connect to the database after '
'%(retries)d retries. Giving up.') %
{'retries': max_retries})
raise
LOG.warn(_('Unable to connect to the database server: '
'%(errmsg)s. Trying again in %(retry_interval)d '
'seconds.') %
{'errmsg': e, 'retry_interval': retry_interval})
attempts += 1
time.sleep(retry_interval)
else:
return client
class QueryTransformer(object):
operators = {"<": "$lt",
">": "$gt",
"<=": "$lte",
"=<": "$lte",
">=": "$gte",
"=>": "$gte",
"!=": "$ne",
"in": "$in"}
complex_operators = {"or": "$or",
"and": "$and"}
ordering_functions = {"asc": pymongo.ASCENDING,
"desc": pymongo.DESCENDING}
def transform_orderby(self, orderby):
orderby_filter = []
for field in orderby:
field_name = field.keys()[0]
ordering = self.ordering_functions[field.values()[0]]
orderby_filter.append((field_name, ordering))
return orderby_filter
@staticmethod
def _move_negation_to_leaf(condition):
"""Moves every not operator to the leafs.
Moving is going by applying the De Morgan rules and anihilating
double negations.
"""
def _apply_de_morgan(tree, negated_subtree, negated_op):
if negated_op == "and":
new_op = "or"
else:
new_op = "and"
tree[new_op] = [{"not": child}
for child in negated_subtree[negated_op]]
del tree["not"]
def transform(subtree):
op = subtree.keys()[0]
if op in ["and", "or"]:
[transform(child) for child in subtree[op]]
elif op == "not":
negated_tree = subtree[op]
negated_op = negated_tree.keys()[0]
if negated_op == "and":
_apply_de_morgan(subtree, negated_tree, negated_op)
transform(subtree)
elif negated_op == "or":
_apply_de_morgan(subtree, negated_tree, negated_op)
transform(subtree)
elif negated_op == "not":
# two consecutive not annihilates theirselves
new_op = negated_tree.values()[0].keys()[0]
subtree[new_op] = negated_tree[negated_op][new_op]
del subtree["not"]
transform(subtree)
transform(condition)
def transform_filter(self, condition):
# in Mongo not operator can only be applied to
# simple expressions so we have to move every
# not operator to the leafs of the expression tree
self._move_negation_to_leaf(condition)
return self._process_json_tree(condition)
def _handle_complex_op(self, complex_op, nodes):
element_list = []
for node in nodes:
element = self._process_json_tree(node)
element_list.append(element)
complex_operator = self.complex_operators[complex_op]
op = {complex_operator: element_list}
return op
def _handle_not_op(self, negated_tree):
# assumes that not is moved to the leaf already
# so we are next to a leaf
negated_op = negated_tree.keys()[0]
negated_field = negated_tree[negated_op].keys()[0]
value = negated_tree[negated_op][negated_field]
if negated_op == "=":
return {negated_field: {"$ne": value}}
elif negated_op == "!=":
return {negated_field: value}
else:
return {negated_field: {"$not":
{self.operators[negated_op]: value}}}
def _handle_simple_op(self, simple_op, nodes):
field_name = nodes.keys()[0]
field_value = nodes.values()[0]
# no operator for equal in Mongo
if simple_op == "=":
op = {field_name: field_value}
return op
operator = self.operators[simple_op]
op = {field_name: {operator: field_value}}
return op
def _process_json_tree(self, condition_tree):
operator_node = condition_tree.keys()[0]
nodes = condition_tree.values()[0]
if operator_node in self.complex_operators:
return self._handle_complex_op(operator_node, nodes)
if operator_node == "not":
negated_tree = condition_tree[operator_node]
return self._handle_not_op(negated_tree)
return self._handle_simple_op(operator_node, nodes)