# Copyright 2012 New Dream Network, LLC (DreamHost)
# Copyright 2013 eNovance
# Copyright 2013 IBM Corp
#
# 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.
"""DB2 storage backend
"""

from __future__ import division
import copy
import datetime
import itertools
import sys

import bson.code
import bson.objectid
from oslo_config import cfg
from oslo_utils import timeutils
import pymongo
import six

import ceilometer
from ceilometer.openstack.common import log
from ceilometer import storage
from ceilometer.storage import base
from ceilometer.storage import models
from ceilometer.storage.mongo import utils as pymongo_utils
from ceilometer.storage import pymongo_base
from ceilometer import utils

LOG = log.getLogger(__name__)


AVAILABLE_CAPABILITIES = {
    'resources': {'query': {'simple': True,
                            'metadata': True}},
    'statistics': {'groupby': True,
                   'query': {'simple': True,
                             'metadata': True},
                   'aggregation': {'standard': True}}
}


class Connection(pymongo_base.Connection):
    """The db2 storage for Ceilometer

    Collections::

        - 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} ]
            }
    """

    CAPABILITIES = utils.update_nested(pymongo_base.Connection.CAPABILITIES,
                                       AVAILABLE_CAPABILITIES)
    CONNECTION_POOL = pymongo_utils.ConnectionPool()

    GROUP = {'_id': '$counter_name',
             'unit': {'$min': '$counter_unit'},
             'min': {'$min': '$counter_volume'},
             'max': {'$max': '$counter_volume'},
             'sum': {'$sum': '$counter_volume'},
             'count': {'$sum': 1},
             'duration_start': {'$min': '$timestamp'},
             'duration_end': {'$max': '$timestamp'},
             }

    PROJECT = {'_id': 0, 'unit': 1,
               'min': 1, 'max': 1, 'sum': 1, 'count': 1,
               'avg': {'$divide': ['$sum', '$count']},
               'duration_start': 1,
               'duration_end': 1,
               }

    SORT_OPERATION_MAP = {'desc': pymongo.DESCENDING, 'asc': pymongo.ASCENDING}

    SECONDS_IN_A_DAY = 86400

    def __init__(self, url):

        # Since we are using pymongo, even though we are connecting to DB2
        # we still have to make sure that the scheme which used to distinguish
        # db2 driver from mongodb driver be replaced so that pymongo will not
        # produce an exception on the scheme.
        url = url.replace('db2:', 'mongodb:', 1)
        self.conn = self.CONNECTION_POOL.connect(url)

        # Require MongoDB 2.2 to use aggregate(), since we are using mongodb
        # as backend for test, the following code is necessary to make sure
        # that the test wont try aggregate on older mongodb during the test.
        # For db2, the versionArray won't be part of the server_info, so there
        # will not be exception when real db2 gets used as backend.
        server_info = self.conn.server_info()
        if server_info.get('sysInfo'):
            self._using_mongodb = True
        else:
            self._using_mongodb = False

        if self._using_mongodb and server_info.get('versionArray') < [2, 2]:
            raise storage.StorageBadVersion("Need at least MongoDB 2.2")

        connection_options = pymongo.uri_parser.parse_uri(url)
        self.db = getattr(self.conn, connection_options['database'])
        if connection_options.get('username'):
            self.db.authenticate(connection_options['username'],
                                 connection_options['password'])

        self.upgrade()

    @classmethod
    def _build_sort_instructions(cls, sort_keys=None, sort_dir='desc'):
        """Returns a sort_instruction.

        Sort instructions are used in the query to determine what attributes
        to sort on and what direction to use.
        :param q: The query dict passed in.
        :param sort_keys: array of attributes by which results be sorted.
        :param sort_dir: direction in which results be sorted (asc, desc).
        :return: sort parameters
        """
        sort_keys = sort_keys or []
        sort_instructions = []
        _sort_dir = cls.SORT_OPERATION_MAP.get(
            sort_dir, cls.SORT_OPERATION_MAP['desc'])

        for _sort_key in sort_keys:
            _instruction = (_sort_key, _sort_dir)
            sort_instructions.append(_instruction)

        return sort_instructions

    def _generate_random_str(self, str_len):
        init_str = str(bson.objectid.ObjectId())
        objectid_len = len(init_str)
        if str_len >= objectid_len:
            init_str = (init_str * int(str_len/objectid_len) +
                        'x' * int(str_len % objectid_len))
        return init_str

    def upgrade(self, version=None):
        # 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.
        if self.db.resource.index_information() == {}:
            # Initializing a longer resource id to workaround DB2 nosql issue.
            # Longer resource id is required by compute node's resource as
            # their id is '<hostname>_<nodename>'. DB2 creates a VARCHAR(70)
            # for resource id when its length < 70. But DB2 can create a
            # VARCHAR(n) for the resource id which has n(n>70) characters.
            # Users can adjust 'db2nosql_resource_id_maxlen'(default is 512)
            # for their ENV.
            resource_id = self._generate_random_str(
                cfg.CONF.database.db2nosql_resource_id_maxlen)
            self.db.resource.insert({'_id': resource_id,
                                     'no_key': resource_id})
            meter_id = str(bson.objectid.ObjectId())
            timestamp = timeutils.utcnow()
            self.db.meter.insert({'_id': meter_id,
                                  'no_key': meter_id,
                                  'timestamp': timestamp})

            self.db.resource.ensure_index([
                ('user_id', pymongo.ASCENDING),
                ('project_id', pymongo.ASCENDING),
                ('source', pymongo.ASCENDING)], name='resource_idx')

            self.db.meter.ensure_index([
                ('resource_id', pymongo.ASCENDING),
                ('user_id', pymongo.ASCENDING),
                ('project_id', pymongo.ASCENDING),
                ('counter_name', pymongo.ASCENDING),
                ('timestamp', pymongo.ASCENDING),
                ('source', pymongo.ASCENDING)], name='meter_idx')

            self.db.meter.ensure_index([('timestamp',
                                         pymongo.DESCENDING)],
                                       name='timestamp_idx')

            self.db.resource.remove({'_id': resource_id})
            self.db.meter.remove({'_id': meter_id})

        # remove API v1 related table
        self.db.user.drop()
        self.db.project.drop()

    def clear(self):
        # db2 does not support drop_database, remove all collections
        for col in ['resource', 'meter']:
            self.db[col].drop()
        # drop_database command does nothing on db2 database since this has
        # not been implemented. However calling this method is important for
        # 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.name)
        self.conn.close()

    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
        """
        # Record the updated resource metadata
        data = copy.deepcopy(data)
        data['resource_metadata'] = pymongo_utils.improve_keys(
            data.pop('resource_metadata'))
        self.db.resource.update(
            {'_id': data['resource_id']},
            {'$set': {'project_id': data['project_id'],
                      'user_id': data['user_id'] or 'null',
                      'metadata': data['resource_metadata'],
                      'source': data['source'],
                      },
             '$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 meter. 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)
        record['recorded_at'] = timeutils.utcnow()
        # Make sure that the data does have field _id which db2 wont add
        # automatically.
        if record.get('_id') is None:
            record['_id'] = str(bson.objectid.ObjectId())
        self.db.meter.insert(record)

    def get_resources(self, user=None, project=None, source=None,
                      start_timestamp=None, start_timestamp_op=None,
                      end_timestamp=None, end_timestamp_op=None,
                      metaquery=None, resource=None, pagination=None):
        """Return an iterable of models.Resource instances

        :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 start_timestamp_op: Optional start time operator, like gt, ge.
        :param end_timestamp: Optional modified timestamp end range.
        :param end_timestamp_op: Optional end time operator, like lt, le.
        :param metaquery: Optional dict with metadata to match on.
        :param resource: Optional resource filter.
        :param pagination: Optional pagination query.
        """
        if pagination:
            raise ceilometer.NotImplementedError('Pagination not implemented')

        metaquery = pymongo_utils.improve_keys(metaquery, metaquery=True) or {}

        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 six.iteritems(metaquery)))

        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 = pymongo_utils.make_timestamp_range(start_timestamp,
                                                          end_timestamp,
                                                          start_timestamp_op,
                                                          end_timestamp_op)
            if ts_range:
                q['timestamp'] = ts_range

        sort_keys = base._handle_sort_key('resource', 'timestamp')
        sort_keys.insert(0, 'resource_id')
        sort_instructions = self._build_sort_instructions(sort_keys=sort_keys,
                                                          sort_dir='desc')
        resource = lambda x: x['resource_id']
        meters = self.db.meter.find(q, sort=sort_instructions)
        for resource_id, r_meters in itertools.groupby(meters, key=resource):
            # Because we have to know first/last timestamp, and we need a full
            # list of references to the resource's meters, we need a tuple
            # here.
            r_meters = tuple(r_meters)
            latest_meter = r_meters[0]
            last_ts = latest_meter['timestamp']
            first_ts = r_meters[-1]['timestamp']

            yield models.Resource(resource_id=latest_meter['resource_id'],
                                  project_id=latest_meter['project_id'],
                                  first_sample_timestamp=first_ts,
                                  last_sample_timestamp=last_ts,
                                  source=latest_meter['source'],
                                  user_id=latest_meter['user_id'],
                                  metadata=pymongo_utils.unquote_keys(
                latest_meter['resource_metadata']))

    def get_meter_statistics(self, sample_filter, period=None, groupby=None,
                             aggregate=None):
        """Return an iterable of models.Statistics instance.

        Items are containing meter statistics described by the query
        parameters. The filter must have a meter value set.
        """
        if (groupby and
                set(groupby) - set(['user_id', 'project_id',
                                    'resource_id', 'source'])):
            raise ceilometer.NotImplementedError(
                "Unable to group by these fields")

        if aggregate:
            raise ceilometer.NotImplementedError(
                'Selectable aggregates not implemented')

        q = pymongo_utils.make_query_from_filter(sample_filter)

        if period:
            if sample_filter.start_timestamp:
                period_start = sample_filter.start_timestamp
            else:
                period_start = self.db.meter.find(
                    limit=1, sort=[('timestamp',
                                    pymongo.ASCENDING)])[0]['timestamp']

        if groupby:
            sort_keys = ['counter_name'] + groupby + ['timestamp']
        else:
            sort_keys = ['counter_name', 'timestamp']

        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(unit=None,
                                     min=sys.maxsize, max=-sys.maxsize,
                                     avg=0, sum=0, count=0,
                                     period=0, period_start=0, period_end=0,
                                     duration=0, duration_start=0,
                                     duration_end=0, groupby=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