refactor db2 get_meter_statistics method to support mongodb and db2

db2 driver for get_meter_statistics method did not work against mongodb
which caused many test cases being skipped. This patch set will fix
that problem also made sure that all statistics functions are supported
by db2 driver against db2 and mongodb database

fixes: bug #1226079

Change-Id: I502aebbab51c51970ddb68641dab89944ce810d4
This commit is contained in:
Tong Li 2013-09-16 10:57:44 -04:00 committed by Gerrit Code Review
parent 5bf2072ac7
commit c60c129a6a
2 changed files with 74 additions and 28 deletions

View File

@ -21,16 +21,20 @@
"""DB2 storage backend
"""
from __future__ import division
import copy
import weakref
import itertools
import bson.code
import bson.objectid
import datetime
import pymongo
import sys
from ceilometer.openstack.common.gettextutils import _
from ceilometer.openstack.common import log
from ceilometer.openstack.common import timeutils
from ceilometer import storage
from ceilometer.storage import base
from ceilometer.storage import models
@ -182,6 +186,8 @@ class Connection(base.Connection):
SORT_OPERATION_MAP = {'desc': pymongo.DESCENDING, 'asc': pymongo.ASCENDING}
SECONDS_IN_A_DAY = 86400
def __init__(self, conf):
url = conf.database.connection
@ -291,6 +297,7 @@ class Connection(base.Connection):
# removal of all the empty dbs created during the test runs since
# test run is against mongodb on Jenkins
self.conn.drop_database(self.db)
self.conn.close()
def record_metering_data(self, data):
"""Write the data to the backend storage system.
@ -521,42 +528,81 @@ class Connection(base.Connection):
statistics described by the query parameters.
The filter must have a meter value set.
"""
if self._using_mongodb:
raise NotImplementedError("Statistics not implemented.")
if groupby:
raise NotImplementedError("Group by not implemented.")
if (groupby and
set(groupby) - set(['user_id', 'project_id',
'resource_id', 'source'])):
raise NotImplementedError("Unable to group by these fields")
q = make_query_from_filter(sample_filter)
if period:
raise NotImplementedError('Statistics for period not implemented.')
results = self.db.meter.aggregate([
{'$match': q},
{'$group': self.GROUP},
{'$project': self.PROJECT},
])
# Since there is no period grouping, there should be only one set in
# the results
rslt = results['result'][0]
duration = rslt['duration_end'] - rslt['duration_start']
if hasattr(duration, 'total_seconds'):
rslt['duration'] = duration.total_seconds()
if sample_filter.start:
period_start = sample_filter.start
else:
rslt['duration'] = duration.days * 3600 + duration.seconds
period_start = self.db.meter.find(
limit=1, sort=[('timestamp',
pymongo.ASCENDING)])[0]['timestamp']
rslt['period_start'] = rslt['duration_start']
rslt['period_end'] = rslt['duration_end']
# Period is not supported, set it to zero
rslt['period'] = 0
rslt['groupby'] = None
if groupby:
sort_keys = ['counter_name'] + groupby + ['timestamp']
else:
sort_keys = ['counter_name', 'timestamp']
return [models.Statistics(**(rslt))]
sort_instructions = self._build_sort_instructions(sort_keys=sort_keys,
sort_dir='asc')
meters = self.db.meter.find(q, sort=sort_instructions)
def _group_key(meter):
# the method to define a key for groupby call
key = {}
for y in sort_keys:
if y == 'timestamp' and period:
key[y] = (timeutils.delta_seconds(period_start,
meter[y]) // period)
elif y != 'timestamp':
key[y] = meter[y]
return key
def _to_offset(periods):
return {'days': (periods * period) // self.SECONDS_IN_A_DAY,
'seconds': (periods * period) % self.SECONDS_IN_A_DAY}
for key, grouped_meters in itertools.groupby(meters, key=_group_key):
stat = models.Statistics(None, sys.maxint, -sys.maxint, 0, 0, 0,
0, 0, 0, 0, 0, 0, None)
for meter in grouped_meters:
stat.unit = meter.get('counter_unit', '')
m_volume = meter.get('counter_volume')
if stat.min > m_volume:
stat.min = m_volume
if stat.max < m_volume:
stat.max = m_volume
stat.sum += m_volume
stat.count += 1
if stat.duration_start == 0:
stat.duration_start = meter['timestamp']
stat.duration_end = meter['timestamp']
if groupby and not stat.groupby:
stat.groupby = {}
for group_key in groupby:
stat.groupby[group_key] = meter[group_key]
stat.duration = timeutils.delta_seconds(stat.duration_start,
stat.duration_end)
stat.avg = stat.sum / stat.count
if period:
stat.period = period
periods = key.get('timestamp')
stat.period_start = period_start + \
datetime.timedelta(**(_to_offset(periods)))
stat.period_end = period_start + \
datetime.timedelta(**(_to_offset(periods + 1)))
else:
stat.period_start = stat.duration_start
stat.period_end = stat.duration_end
yield stat
@staticmethod
def _decode_matching_metadata(matching_metadata):

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@ -46,5 +46,5 @@ MongoDB Yes Yes Yes
MySQL Yes, except metadata querying Yes Yes
PostgreSQL Yes, except metadata querying Yes Yes
HBase Yes Yes, except groupby No
DB2 Yes No No
DB2 Yes Yes No
================== ============================= =================== ======