be88b00e90
In EventFilter we have an optional parameter 'op' in traits_filter part. But up to date usage of this param has been implemented only in Hbase and Mongodb backends. However in API we can use only 'op'='eq'. This change improves usage of parameter 'op' in query for events in api, and adds possibility to use comparison in query with SQL backend. Some tests are also added to cover using of this new feature. Closes-bug: #1354009 Change-Id: I4824800eac7270bcfa10882a735e48d80bf32712
899 lines
37 KiB
Python
899 lines
37 KiB
Python
#
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# Author: John Tran <jhtran@att.com>
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# Julien Danjou <julien@danjou.info>
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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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"""SQLAlchemy storage backend."""
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from __future__ import absolute_import
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import datetime
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import operator
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import os
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from oslo.config import cfg
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from oslo.db import exception as dbexc
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from oslo.db.sqlalchemy import migration
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from oslo.db.sqlalchemy import session as db_session
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from oslo.utils import timeutils
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import six
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from sqlalchemy import and_
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from sqlalchemy import distinct
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from sqlalchemy import func
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from sqlalchemy.orm import aliased
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from ceilometer.openstack.common.gettextutils import _
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from ceilometer.openstack.common import log
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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 as api_models
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from ceilometer.storage.sqlalchemy import models
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from ceilometer.storage.sqlalchemy import utils as sql_utils
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from ceilometer import utils
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LOG = log.getLogger(__name__)
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STANDARD_AGGREGATES = dict(
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avg=func.avg(models.Sample.volume).label('avg'),
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sum=func.sum(models.Sample.volume).label('sum'),
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min=func.min(models.Sample.volume).label('min'),
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max=func.max(models.Sample.volume).label('max'),
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count=func.count(models.Sample.volume).label('count')
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)
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UNPARAMETERIZED_AGGREGATES = dict(
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stddev=func.stddev_pop(models.Sample.volume).label('stddev')
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)
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PARAMETERIZED_AGGREGATES = dict(
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validate=dict(
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cardinality=lambda p: p in ['resource_id', 'user_id', 'project_id']
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),
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compute=dict(
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cardinality=lambda p: func.count(
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distinct(getattr(models.Sample, p))
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).label('cardinality/%s' % p)
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)
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)
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AVAILABLE_CAPABILITIES = {
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'meters': {'query': {'simple': True,
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'metadata': True}},
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'resources': {'query': {'simple': True,
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'metadata': True}},
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'samples': {'pagination': True,
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'groupby': True,
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'query': {'simple': True,
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'metadata': True,
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'complex': 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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'selectable': {
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'max': True,
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'min': True,
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'sum': True,
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'avg': True,
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'count': True,
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'stddev': True,
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'cardinality': True}}
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},
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'events': {'query': {'simple': True}},
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}
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AVAILABLE_STORAGE_CAPABILITIES = {
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'storage': {'production_ready': True},
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}
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def apply_metaquery_filter(session, query, metaquery):
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"""Apply provided metaquery filter to existing query.
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:param session: session used for original query
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:param query: Query instance
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:param metaquery: dict with metadata to match on.
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"""
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for k, value in six.iteritems(metaquery):
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key = k[9:] # strip out 'metadata.' prefix
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try:
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_model = sql_utils.META_TYPE_MAP[type(value)]
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except KeyError:
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raise NotImplementedError('Query on %(key)s is of %(value)s '
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'type and is not supported' %
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{"key": k, "value": type(value)})
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else:
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meta_alias = aliased(_model)
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on_clause = and_(models.Sample.id == meta_alias.id,
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meta_alias.meta_key == key)
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# outer join is needed to support metaquery
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# with or operator on non existent metadata field
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# see: test_query_non_existing_metadata_with_result
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# test case.
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query = query.outerjoin(meta_alias, on_clause)
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query = query.filter(meta_alias.value == value)
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return query
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def make_query_from_filter(session, query, sample_filter, require_meter=True):
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"""Return a query dictionary based on the settings in the filter.
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:param session: session used for original query
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:param query: Query instance
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:param sample_filter: SampleFilter instance
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:param require_meter: If true and the filter does not have a meter,
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raise an error.
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"""
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if sample_filter.meter:
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query = query.filter(models.Meter.name == sample_filter.meter)
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elif require_meter:
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raise RuntimeError('Missing required meter specifier')
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if sample_filter.source:
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query = query.filter(
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models.Sample.source_id == sample_filter.source)
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if sample_filter.start:
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ts_start = sample_filter.start
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if sample_filter.start_timestamp_op == 'gt':
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query = query.filter(models.Sample.timestamp > ts_start)
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else:
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query = query.filter(models.Sample.timestamp >= ts_start)
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if sample_filter.end:
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ts_end = sample_filter.end
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if sample_filter.end_timestamp_op == 'le':
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query = query.filter(models.Sample.timestamp <= ts_end)
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else:
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query = query.filter(models.Sample.timestamp < ts_end)
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if sample_filter.user:
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query = query.filter(models.Sample.user_id == sample_filter.user)
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if sample_filter.project:
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query = query.filter(
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models.Sample.project_id == sample_filter.project)
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if sample_filter.resource:
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query = query.filter(
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models.Sample.resource_id == sample_filter.resource)
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if sample_filter.message_id:
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query = query.filter(
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models.Sample.message_id == sample_filter.message_id)
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if sample_filter.metaquery:
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query = apply_metaquery_filter(session, query,
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sample_filter.metaquery)
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return query
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class Connection(base.Connection):
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"""Put the data into a SQLAlchemy database.
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Tables::
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- meter
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- meter definition
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- { id: meter def id
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name: meter name
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type: meter type
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unit: meter unit
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}
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- sample
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- the raw incoming data
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- { id: sample id
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meter_id: meter id (->meter.id)
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user_id: user uuid
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project_id: project uuid
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resource_id: resource uuid
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source_id: source id
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resource_metadata: metadata dictionaries
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volume: sample volume
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timestamp: datetime
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message_signature: message signature
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message_id: message uuid
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}
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"""
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CAPABILITIES = utils.update_nested(base.Connection.CAPABILITIES,
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AVAILABLE_CAPABILITIES)
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STORAGE_CAPABILITIES = utils.update_nested(
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base.Connection.STORAGE_CAPABILITIES,
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AVAILABLE_STORAGE_CAPABILITIES,
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)
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def __init__(self, url):
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self._engine_facade = db_session.EngineFacade(
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url,
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**dict(cfg.CONF.database.items())
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)
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def upgrade(self):
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path = os.path.join(os.path.abspath(os.path.dirname(__file__)),
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'sqlalchemy', 'migrate_repo')
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migration.db_sync(self._engine_facade.get_engine(), path)
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def clear(self):
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engine = self._engine_facade.get_engine()
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for table in reversed(models.Base.metadata.sorted_tables):
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engine.execute(table.delete())
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self._engine_facade._session_maker.close_all()
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engine.dispose()
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@staticmethod
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def _create_meter(session, name, type, unit):
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try:
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nested = session.connection().dialect.name != 'sqlite'
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with session.begin(nested=nested,
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subtransactions=not nested):
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obj = (session.query(models.Meter)
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.filter(models.Meter.name == name)
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.filter(models.Meter.type == type)
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.filter(models.Meter.unit == unit).first())
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if obj is None:
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obj = models.Meter(name=name, type=type, unit=unit)
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session.add(obj)
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except dbexc.DBDuplicateEntry:
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# retry function to pick up duplicate committed object
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obj = Connection._create_meter(session, name, type, unit)
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return obj
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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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session = self._engine_facade.get_session()
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with session.begin():
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# Record the raw data for the sample.
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rmetadata = data['resource_metadata']
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meter = self._create_meter(session,
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data['counter_name'],
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data['counter_type'],
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data['counter_unit'])
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sample = models.Sample(meter_id=meter.id)
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session.add(sample)
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sample.resource_id = data['resource_id']
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sample.project_id = data['project_id']
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sample.user_id = data['user_id']
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sample.timestamp = data['timestamp']
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sample.resource_metadata = rmetadata
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sample.volume = data['counter_volume']
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sample.message_signature = data['message_signature']
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sample.message_id = data['message_id']
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sample.source_id = data['source']
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session.flush()
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if rmetadata:
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if isinstance(rmetadata, dict):
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for key, v in utils.dict_to_keyval(rmetadata):
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try:
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_model = sql_utils.META_TYPE_MAP[type(v)]
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except KeyError:
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LOG.warn(_("Unknown metadata type. Key (%s) will "
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"not be queryable."), key)
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else:
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session.add(_model(id=sample.id,
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meta_key=key,
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value=v))
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def clear_expired_metering_data(self, ttl):
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"""Clear expired data from the backend storage system.
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Clearing occurs according to the time-to-live.
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:param ttl: Number of seconds to keep records for.
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"""
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session = self._engine_facade.get_session()
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with session.begin():
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end = timeutils.utcnow() - datetime.timedelta(seconds=ttl)
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sample_q = (session.query(models.Sample)
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.filter(models.Sample.timestamp < end))
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sample_subq = sample_q.subquery()
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for table in [models.MetaText, models.MetaBigInt,
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models.MetaFloat, models.MetaBool]:
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(session.query(table)
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.join(sample_subq, sample_subq.c.id == table.id)
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.delete())
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rows = sample_q.delete()
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# remove Meter definitions with no matching samples
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(session.query(models.Meter)
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.filter(~models.Meter.samples.any())
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.delete(synchronize_session='fetch'))
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LOG.info(_("%d samples removed from database"), rows)
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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 api_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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s_filter = storage.SampleFilter(user=user,
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project=project,
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source=source,
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start=start_timestamp,
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start_timestamp_op=start_timestamp_op,
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end=end_timestamp,
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end_timestamp_op=end_timestamp_op,
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metaquery=metaquery,
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resource=resource)
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session = self._engine_facade.get_session()
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# get list of resource_ids
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res_q = session.query(distinct(models.Sample.resource_id))
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res_q = make_query_from_filter(session, res_q, s_filter,
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require_meter=False)
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for res_id in res_q.all():
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# get latest Sample
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max_q = (session.query(models.Sample)
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.filter(models.Sample.resource_id == res_id[0]))
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max_q = make_query_from_filter(session, max_q, s_filter,
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require_meter=False)
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max_q = max_q.order_by(models.Sample.timestamp.desc(),
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models.Sample.id.desc()).limit(1)
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# get the min timestamp value.
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min_q = (session.query(models.Sample.timestamp)
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.filter(models.Sample.resource_id == res_id[0]))
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min_q = make_query_from_filter(session, min_q, s_filter,
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require_meter=False)
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min_q = min_q.order_by(models.Sample.timestamp.asc()).limit(1)
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sample = max_q.first()
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if sample:
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yield api_models.Resource(
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resource_id=sample.resource_id,
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project_id=sample.project_id,
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first_sample_timestamp=min_q.first().timestamp,
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last_sample_timestamp=sample.timestamp,
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source=sample.source_id,
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user_id=sample.user_id,
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metadata=sample.resource_metadata
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)
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def get_meters(self, user=None, project=None, resource=None, source=None,
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metaquery=None, pagination=None):
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"""Return an iterable of api_models.Meter 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 resource: Optional ID of the resource.
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:param source: Optional source filter.
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:param metaquery: Optional dict with metadata to match on.
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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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s_filter = storage.SampleFilter(user=user,
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project=project,
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source=source,
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metaquery=metaquery,
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resource=resource)
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session = self._engine_facade.get_session()
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# sample_subq is used to reduce sample records
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# by selecting a record for each (resource_id, meter_id).
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# max() is used to choice a sample record, so the latest record
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# is selected for each (resource_id, meter_id).
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sample_subq = (session.query(
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func.max(models.Sample.id).label('id'))
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.group_by(models.Sample.meter_id,
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models.Sample.resource_id))
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sample_subq = sample_subq.subquery()
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# SELECT sample.* FROM sample INNER JOIN
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# (SELECT max(sample.id) AS id FROM sample
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# GROUP BY sample.resource_id, sample.meter_id) AS anon_2
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# ON sample.id = anon_2.id
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query_sample = (session.query(models.MeterSample).
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join(sample_subq, models.MeterSample.id ==
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sample_subq.c.id))
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query_sample = make_query_from_filter(session, query_sample, s_filter,
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require_meter=False)
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for sample in query_sample.all():
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yield api_models.Meter(
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name=sample.counter_name,
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type=sample.counter_type,
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unit=sample.counter_unit,
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resource_id=sample.resource_id,
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project_id=sample.project_id,
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source=sample.source_id,
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user_id=sample.user_id)
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def _retrieve_samples(self, query):
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samples = query.all()
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for s in samples:
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# Remove the id generated by the database when
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# the sample was inserted. It is an implementation
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# detail that should not leak outside of the driver.
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yield api_models.Sample(
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source=s.source_id,
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counter_name=s.counter_name,
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counter_type=s.counter_type,
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counter_unit=s.counter_unit,
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counter_volume=s.counter_volume,
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user_id=s.user_id,
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project_id=s.project_id,
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resource_id=s.resource_id,
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timestamp=s.timestamp,
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recorded_at=s.recorded_at,
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resource_metadata=s.resource_metadata,
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message_id=s.message_id,
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message_signature=s.message_signature,
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)
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|
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def get_samples(self, sample_filter, limit=None):
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"""Return an iterable of api_models.Samples.
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|
|
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:param sample_filter: Filter.
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:param limit: Maximum number of results to return.
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"""
|
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if limit == 0:
|
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return []
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|
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table = models.MeterSample
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session = self._engine_facade.get_session()
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query = session.query(table)
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query = make_query_from_filter(session, query, sample_filter,
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require_meter=False)
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transformer = sql_utils.QueryTransformer(table, query)
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transformer.apply_options(None,
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limit)
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return self._retrieve_samples(transformer.get_query())
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|
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def query_samples(self, filter_expr=None, orderby=None, limit=None):
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if limit == 0:
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return []
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|
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session = self._engine_facade.get_session()
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query = session.query(models.MeterSample)
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transformer = sql_utils.QueryTransformer(models.MeterSample, query)
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if filter_expr is not None:
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transformer.apply_filter(filter_expr)
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transformer.apply_options(orderby,
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limit)
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return self._retrieve_samples(transformer.get_query())
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|
|
@staticmethod
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|
def _get_aggregate_functions(aggregate):
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|
if not aggregate:
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return [f for f in STANDARD_AGGREGATES.values()]
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|
|
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functions = []
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|
|
for a in aggregate:
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|
if a.func in STANDARD_AGGREGATES:
|
|
functions.append(STANDARD_AGGREGATES[a.func])
|
|
elif a.func in UNPARAMETERIZED_AGGREGATES:
|
|
functions.append(UNPARAMETERIZED_AGGREGATES[a.func])
|
|
elif a.func in PARAMETERIZED_AGGREGATES['compute']:
|
|
validate = PARAMETERIZED_AGGREGATES['validate'].get(a.func)
|
|
if not (validate and validate(a.param)):
|
|
raise storage.StorageBadAggregate('Bad aggregate: %s.%s'
|
|
% (a.func, a.param))
|
|
compute = PARAMETERIZED_AGGREGATES['compute'][a.func]
|
|
functions.append(compute(a.param))
|
|
else:
|
|
raise NotImplementedError('Selectable aggregate function %s'
|
|
' is not supported' % a.func)
|
|
|
|
return functions
|
|
|
|
def _make_stats_query(self, sample_filter, groupby, aggregate):
|
|
|
|
select = [
|
|
models.Meter.unit,
|
|
func.min(models.Sample.timestamp).label('tsmin'),
|
|
func.max(models.Sample.timestamp).label('tsmax'),
|
|
]
|
|
|
|
select.extend(self._get_aggregate_functions(aggregate))
|
|
|
|
session = self._engine_facade.get_session()
|
|
|
|
if groupby:
|
|
group_attributes = [getattr(models.Sample, g) for g in groupby]
|
|
select.extend(group_attributes)
|
|
|
|
query = (session.query(*select).join(
|
|
models.Sample, models.Meter.id == models.Sample.meter_id).
|
|
group_by(models.Meter.unit))
|
|
|
|
if groupby:
|
|
query = query.group_by(*group_attributes)
|
|
|
|
return make_query_from_filter(session, query, sample_filter)
|
|
|
|
@staticmethod
|
|
def _stats_result_aggregates(result, aggregate):
|
|
stats_args = {}
|
|
if isinstance(result.count, (int, long)):
|
|
stats_args['count'] = result.count
|
|
for attr in ['min', 'max', 'sum', 'avg']:
|
|
if hasattr(result, attr):
|
|
stats_args[attr] = getattr(result, attr)
|
|
if aggregate:
|
|
stats_args['aggregate'] = {}
|
|
for a in aggregate:
|
|
key = '%s%s' % (a.func, '/%s' % a.param if a.param else '')
|
|
stats_args['aggregate'][key] = getattr(result, key)
|
|
return stats_args
|
|
|
|
@staticmethod
|
|
def _stats_result_to_model(result, period, period_start,
|
|
period_end, groupby, aggregate):
|
|
stats_args = Connection._stats_result_aggregates(result, aggregate)
|
|
stats_args['unit'] = result.unit
|
|
duration = (timeutils.delta_seconds(result.tsmin, result.tsmax)
|
|
if result.tsmin is not None and result.tsmax is not None
|
|
else None)
|
|
stats_args['duration'] = duration
|
|
stats_args['duration_start'] = result.tsmin
|
|
stats_args['duration_end'] = result.tsmax
|
|
stats_args['period'] = period
|
|
stats_args['period_start'] = period_start
|
|
stats_args['period_end'] = period_end
|
|
stats_args['groupby'] = (dict(
|
|
(g, getattr(result, g)) for g in groupby) if groupby else None)
|
|
return api_models.Statistics(**stats_args)
|
|
|
|
def get_meter_statistics(self, sample_filter, period=None, groupby=None,
|
|
aggregate=None):
|
|
"""Return an iterable of api_models.Statistics instances.
|
|
|
|
Items are containing meter statistics described by the query
|
|
parameters. The filter must have a meter value set.
|
|
"""
|
|
if groupby:
|
|
for group in groupby:
|
|
if group not in ['user_id', 'project_id', 'resource_id']:
|
|
raise NotImplementedError('Unable to group by '
|
|
'these fields')
|
|
|
|
if not period:
|
|
for res in self._make_stats_query(sample_filter,
|
|
groupby,
|
|
aggregate):
|
|
if res.count:
|
|
yield self._stats_result_to_model(res, 0,
|
|
res.tsmin, res.tsmax,
|
|
groupby,
|
|
aggregate)
|
|
return
|
|
|
|
if not sample_filter.start or not sample_filter.end:
|
|
res = self._make_stats_query(sample_filter,
|
|
None,
|
|
aggregate).first()
|
|
if not res:
|
|
# NOTE(liusheng):The 'res' may be NoneType, because no
|
|
# sample has found with sample filter(s).
|
|
return
|
|
|
|
query = self._make_stats_query(sample_filter, groupby, aggregate)
|
|
# HACK(jd) This is an awful method to compute stats by period, but
|
|
# since we're trying to be SQL agnostic we have to write portable
|
|
# code, so here it is, admire! We're going to do one request to get
|
|
# stats by period. We would like to use GROUP BY, but there's no
|
|
# portable way to manipulate timestamp in SQL, so we can't.
|
|
for period_start, period_end in base.iter_period(
|
|
sample_filter.start or res.tsmin,
|
|
sample_filter.end or res.tsmax,
|
|
period):
|
|
q = query.filter(models.Sample.timestamp >= period_start)
|
|
q = q.filter(models.Sample.timestamp < period_end)
|
|
for r in q.all():
|
|
if r.count:
|
|
yield self._stats_result_to_model(
|
|
result=r,
|
|
period=int(timeutils.delta_seconds(period_start,
|
|
period_end)),
|
|
period_start=period_start,
|
|
period_end=period_end,
|
|
groupby=groupby,
|
|
aggregate=aggregate
|
|
)
|
|
|
|
def _get_or_create_trait_type(self, trait_type, data_type, session=None):
|
|
"""Find if this trait already exists in the database.
|
|
|
|
If it does not, create a new entry in the trait type table.
|
|
"""
|
|
if session is None:
|
|
session = self._engine_facade.get_session()
|
|
with session.begin(subtransactions=True):
|
|
tt = session.query(models.TraitType).filter(
|
|
models.TraitType.desc == trait_type,
|
|
models.TraitType.data_type == data_type).first()
|
|
if not tt:
|
|
tt = models.TraitType(trait_type, data_type)
|
|
session.add(tt)
|
|
return tt
|
|
|
|
def _make_trait(self, trait_model, event, session=None):
|
|
"""Make a new Trait from a Trait model.
|
|
|
|
Doesn't flush or add to session.
|
|
"""
|
|
trait_type = self._get_or_create_trait_type(trait_model.name,
|
|
trait_model.dtype,
|
|
session)
|
|
value_map = models.Trait._value_map
|
|
values = {'t_string': None, 't_float': None,
|
|
't_int': None, 't_datetime': None}
|
|
value = trait_model.value
|
|
values[value_map[trait_model.dtype]] = value
|
|
return models.Trait(trait_type, event, **values)
|
|
|
|
def _get_or_create_event_type(self, event_type, session=None):
|
|
"""Check if an event type with the supplied name is already exists.
|
|
|
|
If not, we create it and return the record. This may result in a flush.
|
|
"""
|
|
if session is None:
|
|
session = self._engine_facade.get_session()
|
|
with session.begin(subtransactions=True):
|
|
et = session.query(models.EventType).filter(
|
|
models.EventType.desc == event_type).first()
|
|
if not et:
|
|
et = models.EventType(event_type)
|
|
session.add(et)
|
|
return et
|
|
|
|
def _record_event(self, session, event_model):
|
|
"""Store a single Event, including related Traits."""
|
|
with session.begin(subtransactions=True):
|
|
event_type = self._get_or_create_event_type(event_model.event_type,
|
|
session=session)
|
|
|
|
event = models.Event(event_model.message_id, event_type,
|
|
event_model.generated)
|
|
session.add(event)
|
|
|
|
new_traits = []
|
|
if event_model.traits:
|
|
for trait in event_model.traits:
|
|
t = self._make_trait(trait, event, session=session)
|
|
session.add(t)
|
|
new_traits.append(t)
|
|
|
|
# Note: we don't flush here, explicitly (unless a new trait or event
|
|
# does it). Otherwise, just wait until all the Events are staged.
|
|
return event, new_traits
|
|
|
|
def record_events(self, event_models):
|
|
"""Write the events to SQL database via sqlalchemy.
|
|
|
|
:param event_models: a list of model.Event objects.
|
|
|
|
Returns a list of events that could not be saved in a
|
|
(reason, event) tuple. Reasons are enumerated in
|
|
storage.model.Event
|
|
|
|
Flush when they're all added, unless new EventTypes or
|
|
TraitTypes are added along the way.
|
|
"""
|
|
session = self._engine_facade.get_session()
|
|
events = []
|
|
problem_events = []
|
|
for event_model in event_models:
|
|
event = None
|
|
try:
|
|
with session.begin():
|
|
event = self._record_event(session, event_model)
|
|
except dbexc.DBDuplicateEntry as e:
|
|
LOG.exception(_("Failed to record duplicated event: %s") % e)
|
|
problem_events.append((api_models.Event.DUPLICATE,
|
|
event_model))
|
|
except Exception as e:
|
|
LOG.exception(_('Failed to record event: %s') % e)
|
|
problem_events.append((api_models.Event.UNKNOWN_PROBLEM,
|
|
event_model))
|
|
events.append(event)
|
|
return problem_events
|
|
|
|
def get_events(self, event_filter):
|
|
"""Return an iterable of model.Event objects.
|
|
|
|
:param event_filter: EventFilter instance
|
|
"""
|
|
|
|
start = event_filter.start_time
|
|
end = event_filter.end_time
|
|
session = self._engine_facade.get_session()
|
|
LOG.debug(_("Getting events that match filter: %s") % event_filter)
|
|
with session.begin():
|
|
event_query = session.query(models.Event)
|
|
|
|
# Build up the join conditions
|
|
event_join_conditions = [models.EventType.id ==
|
|
models.Event.event_type_id]
|
|
|
|
if event_filter.event_type:
|
|
event_join_conditions.append(models.EventType.desc ==
|
|
event_filter.event_type)
|
|
|
|
event_query = event_query.join(models.EventType,
|
|
and_(*event_join_conditions))
|
|
|
|
# Build up the where conditions
|
|
event_filter_conditions = []
|
|
if event_filter.message_id:
|
|
event_filter_conditions.append(models.Event.message_id ==
|
|
event_filter.message_id)
|
|
if start:
|
|
event_filter_conditions.append(models.Event.generated >= start)
|
|
if end:
|
|
event_filter_conditions.append(models.Event.generated <= end)
|
|
|
|
if event_filter_conditions:
|
|
event_query = (event_query.
|
|
filter(and_(*event_filter_conditions)))
|
|
|
|
event_models_dict = {}
|
|
if event_filter.traits_filter:
|
|
for trait_filter in event_filter.traits_filter:
|
|
|
|
# Build a sub query that joins Trait to TraitType
|
|
# where the trait name matches
|
|
trait_name = trait_filter.pop('key')
|
|
op = trait_filter.pop('op', 'eq')
|
|
conditions = [models.Trait.trait_type_id ==
|
|
models.TraitType.id,
|
|
models.TraitType.desc == trait_name]
|
|
|
|
for key, value in six.iteritems(trait_filter):
|
|
sql_utils.trait_op_condition(conditions,
|
|
key, value, op)
|
|
|
|
trait_query = (session.query(models.Trait.event_id).
|
|
join(models.TraitType,
|
|
and_(*conditions)).subquery())
|
|
|
|
event_query = (event_query.
|
|
join(trait_query, models.Event.id ==
|
|
trait_query.c.event_id))
|
|
else:
|
|
# If there are no trait filters, grab the events from the db
|
|
query = (session.query(models.Event.id,
|
|
models.Event.generated,
|
|
models.Event.message_id,
|
|
models.EventType.desc).
|
|
join(models.EventType, and_(*event_join_conditions)))
|
|
if event_filter_conditions:
|
|
query = query.filter(and_(*event_filter_conditions))
|
|
for (id_, generated, message_id, desc_) in query.all():
|
|
event_models_dict[id_] = api_models.Event(message_id,
|
|
desc_,
|
|
generated,
|
|
[])
|
|
|
|
# Build event models for the events
|
|
event_query = event_query.subquery()
|
|
query = (session.query(models.Trait).
|
|
join(models.TraitType, models.Trait.trait_type_id ==
|
|
models.TraitType.id).
|
|
join(event_query, models.Trait.event_id ==
|
|
event_query.c.id))
|
|
|
|
# Now convert the sqlalchemy objects back into Models ...
|
|
for trait in query.all():
|
|
event = event_models_dict.get(trait.event_id)
|
|
if not event:
|
|
event = api_models.Event(
|
|
trait.event.message_id,
|
|
trait.event.event_type.desc,
|
|
trait.event.generated, [])
|
|
event_models_dict[trait.event_id] = event
|
|
trait_model = api_models.Trait(trait.trait_type.desc,
|
|
trait.trait_type.data_type,
|
|
trait.get_value())
|
|
event.append_trait(trait_model)
|
|
|
|
event_models = event_models_dict.values()
|
|
return sorted(event_models, key=operator.attrgetter('generated'))
|
|
|
|
def get_event_types(self):
|
|
"""Return all event types as an iterable of strings."""
|
|
|
|
session = self._engine_facade.get_session()
|
|
with session.begin():
|
|
query = (session.query(models.EventType.desc).
|
|
order_by(models.EventType.desc))
|
|
for name in query.all():
|
|
# The query returns a tuple with one element.
|
|
yield name[0]
|
|
|
|
def get_trait_types(self, event_type):
|
|
"""Return a dictionary containing the name and data type of the trait.
|
|
|
|
Only trait types for the provided event_type are returned.
|
|
:param event_type: the type of the Event
|
|
"""
|
|
session = self._engine_facade.get_session()
|
|
|
|
LOG.debug(_("Get traits for %s") % event_type)
|
|
with session.begin():
|
|
query = (session.query(models.TraitType.desc,
|
|
models.TraitType.data_type)
|
|
.join(models.Trait,
|
|
models.Trait.trait_type_id ==
|
|
models.TraitType.id)
|
|
.join(models.Event,
|
|
models.Event.id ==
|
|
models.Trait.event_id)
|
|
.join(models.EventType,
|
|
and_(models.EventType.id ==
|
|
models.Event.id,
|
|
models.EventType.desc ==
|
|
event_type))
|
|
.group_by(models.TraitType.desc,
|
|
models.TraitType.data_type)
|
|
.distinct())
|
|
|
|
for desc_, dtype in query.all():
|
|
yield {'name': desc_, 'data_type': dtype}
|
|
|
|
def get_traits(self, event_type, trait_type=None):
|
|
"""Return all trait instances associated with an event_type.
|
|
|
|
If trait_type is specified, only return instances of that trait type.
|
|
:param event_type: the type of the Event to filter by
|
|
:param trait_type: the name of the Trait to filter by
|
|
"""
|
|
|
|
session = self._engine_facade.get_session()
|
|
with session.begin():
|
|
trait_type_filters = [models.TraitType.id ==
|
|
models.Trait.trait_type_id]
|
|
if trait_type:
|
|
trait_type_filters.append(models.TraitType.desc == trait_type)
|
|
|
|
query = (session.query(models.Trait)
|
|
.join(models.TraitType, and_(*trait_type_filters))
|
|
.join(models.Event,
|
|
models.Event.id == models.Trait.event_id)
|
|
.join(models.EventType,
|
|
and_(models.EventType.id ==
|
|
models.Event.event_type_id,
|
|
models.EventType.desc == event_type)))
|
|
|
|
for trait in query.all():
|
|
type = trait.trait_type
|
|
yield api_models.Trait(name=type.desc,
|
|
dtype=type.data_type,
|
|
value=trait.get_value())
|