7b45f7536b
Synced from commit 5fb343faee1442921e2d610b1a5222e67418c4cd. Due to changes in oslo.db API, this sync requires a bit more work on Neutron side. Sync includes the following commits: 5b7e61c Dispose db connections pool on disconnect d1988b9 Set sql_mode callback on connect instead of checkout a1a8280 Fix excessive logging from db.sqlalchemy.session 9933bdd Get mysql_sql_mode parameter from config 96a2217 Prevent incorrect usage of _wrap_db_error() 20a7510 Add from_config() method to EngineFacade fea119e Drop special case for MySQL traditional mode, update unit tests dda24eb Introduce mysql_sql_mode option, remove old warning 0b5af67 Introduce a method to set any MySQL session SQL mode 8dccc7b Handle ibm_db_sa DBDuplicateEntry integrity errors 5b9e9f4 Fix doc build errors in db.sqlalchemy ac84a40 Update log translation domains 86707cd Remove None for dict.get() 0545121 Fix duplicating of SQL queries in logs fcf517d Update oslo log messages with translation domains 630d395 Don't use cfg.CONF in oslo.db ce69e7f Don't store engine instances in oslo.db Change-Id: I0e1d86878d3eb924b01e04dced0f90b4e57757d8
648 lines
24 KiB
Python
648 lines
24 KiB
Python
# Copyright 2010 United States Government as represented by the
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# Administrator of the National Aeronautics and Space Administration.
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# Copyright 2010-2011 OpenStack Foundation.
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# Copyright 2012 Justin Santa Barbara
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# All Rights Reserved.
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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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import logging
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import re
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import sqlalchemy
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from sqlalchemy import Boolean
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from sqlalchemy import CheckConstraint
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from sqlalchemy import Column
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from sqlalchemy.engine import reflection
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from sqlalchemy.ext.compiler import compiles
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from sqlalchemy import func
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from sqlalchemy import Index
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from sqlalchemy import Integer
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from sqlalchemy import MetaData
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from sqlalchemy import or_
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from sqlalchemy.sql.expression import literal_column
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from sqlalchemy.sql.expression import UpdateBase
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from sqlalchemy import String
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from sqlalchemy import Table
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from sqlalchemy.types import NullType
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from neutron.openstack.common import context as request_context
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from neutron.openstack.common.db.sqlalchemy import models
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from neutron.openstack.common.gettextutils import _, _LI, _LW
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from neutron.openstack.common import timeutils
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LOG = logging.getLogger(__name__)
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_DBURL_REGEX = re.compile(r"[^:]+://([^:]+):([^@]+)@.+")
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def sanitize_db_url(url):
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match = _DBURL_REGEX.match(url)
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if match:
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return '%s****:****%s' % (url[:match.start(1)], url[match.end(2):])
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return url
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class InvalidSortKey(Exception):
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message = _("Sort key supplied was not valid.")
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# copy from glance/db/sqlalchemy/api.py
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def paginate_query(query, model, limit, sort_keys, marker=None,
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sort_dir=None, sort_dirs=None):
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"""Returns a query with sorting / pagination criteria added.
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Pagination works by requiring a unique sort_key, specified by sort_keys.
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(If sort_keys is not unique, then we risk looping through values.)
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We use the last row in the previous page as the 'marker' for pagination.
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So we must return values that follow the passed marker in the order.
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With a single-valued sort_key, this would be easy: sort_key > X.
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With a compound-values sort_key, (k1, k2, k3) we must do this to repeat
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the lexicographical ordering:
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(k1 > X1) or (k1 == X1 && k2 > X2) or (k1 == X1 && k2 == X2 && k3 > X3)
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We also have to cope with different sort_directions.
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Typically, the id of the last row is used as the client-facing pagination
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marker, then the actual marker object must be fetched from the db and
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passed in to us as marker.
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:param query: the query object to which we should add paging/sorting
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:param model: the ORM model class
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:param limit: maximum number of items to return
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:param sort_keys: array of attributes by which results should be sorted
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:param marker: the last item of the previous page; we returns the next
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results after this value.
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:param sort_dir: direction in which results should be sorted (asc, desc)
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:param sort_dirs: per-column array of sort_dirs, corresponding to sort_keys
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:rtype: sqlalchemy.orm.query.Query
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:return: The query with sorting/pagination added.
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"""
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if 'id' not in sort_keys:
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# TODO(justinsb): If this ever gives a false-positive, check
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# the actual primary key, rather than assuming its id
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LOG.warning(_LW('Id not in sort_keys; is sort_keys unique?'))
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assert(not (sort_dir and sort_dirs))
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# Default the sort direction to ascending
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if sort_dirs is None and sort_dir is None:
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sort_dir = 'asc'
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# Ensure a per-column sort direction
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if sort_dirs is None:
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sort_dirs = [sort_dir for _sort_key in sort_keys]
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assert(len(sort_dirs) == len(sort_keys))
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# Add sorting
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for current_sort_key, current_sort_dir in zip(sort_keys, sort_dirs):
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try:
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sort_dir_func = {
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'asc': sqlalchemy.asc,
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'desc': sqlalchemy.desc,
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}[current_sort_dir]
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except KeyError:
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raise ValueError(_("Unknown sort direction, "
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"must be 'desc' or 'asc'"))
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try:
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sort_key_attr = getattr(model, current_sort_key)
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except AttributeError:
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raise InvalidSortKey()
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query = query.order_by(sort_dir_func(sort_key_attr))
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# Add pagination
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if marker is not None:
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marker_values = []
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for sort_key in sort_keys:
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v = getattr(marker, sort_key)
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marker_values.append(v)
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# Build up an array of sort criteria as in the docstring
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criteria_list = []
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for i in range(len(sort_keys)):
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crit_attrs = []
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for j in range(i):
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model_attr = getattr(model, sort_keys[j])
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crit_attrs.append((model_attr == marker_values[j]))
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model_attr = getattr(model, sort_keys[i])
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if sort_dirs[i] == 'desc':
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crit_attrs.append((model_attr < marker_values[i]))
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else:
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crit_attrs.append((model_attr > marker_values[i]))
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criteria = sqlalchemy.sql.and_(*crit_attrs)
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criteria_list.append(criteria)
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f = sqlalchemy.sql.or_(*criteria_list)
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query = query.filter(f)
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if limit is not None:
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query = query.limit(limit)
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return query
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def _read_deleted_filter(query, db_model, read_deleted):
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if 'deleted' not in db_model.__table__.columns:
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raise ValueError(_("There is no `deleted` column in `%s` table. "
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"Project doesn't use soft-deleted feature.")
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% db_model.__name__)
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default_deleted_value = db_model.__table__.c.deleted.default.arg
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if read_deleted == 'no':
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query = query.filter(db_model.deleted == default_deleted_value)
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elif read_deleted == 'yes':
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pass # omit the filter to include deleted and active
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elif read_deleted == 'only':
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query = query.filter(db_model.deleted != default_deleted_value)
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else:
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raise ValueError(_("Unrecognized read_deleted value '%s'")
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% read_deleted)
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return query
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def _project_filter(query, db_model, context, project_only):
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if project_only and 'project_id' not in db_model.__table__.columns:
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raise ValueError(_("There is no `project_id` column in `%s` table.")
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% db_model.__name__)
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if request_context.is_user_context(context) and project_only:
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if project_only == 'allow_none':
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is_none = None
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query = query.filter(or_(db_model.project_id == context.project_id,
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db_model.project_id == is_none))
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else:
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query = query.filter(db_model.project_id == context.project_id)
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return query
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def model_query(context, model, session, args=None, project_only=False,
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read_deleted=None):
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"""Query helper that accounts for context's `read_deleted` field.
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:param context: context to query under
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:param model: Model to query. Must be a subclass of ModelBase.
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:type model: models.ModelBase
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:param session: The session to use.
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:type session: sqlalchemy.orm.session.Session
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:param args: Arguments to query. If None - model is used.
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:type args: tuple
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:param project_only: If present and context is user-type, then restrict
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query to match the context's project_id. If set to
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'allow_none', restriction includes project_id = None.
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:type project_only: bool
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:param read_deleted: If present, overrides context's read_deleted field.
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:type read_deleted: bool
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Usage:
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..code:: python
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result = (utils.model_query(context, models.Instance, session=session)
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.filter_by(uuid=instance_uuid)
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.all())
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query = utils.model_query(
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context, Node,
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session=session,
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args=(func.count(Node.id), func.sum(Node.ram))
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).filter_by(project_id=project_id)
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"""
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if not read_deleted:
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if hasattr(context, 'read_deleted'):
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# NOTE(viktors): some projects use `read_deleted` attribute in
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# their contexts instead of `show_deleted`.
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read_deleted = context.read_deleted
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else:
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read_deleted = context.show_deleted
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if not issubclass(model, models.ModelBase):
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raise TypeError(_("model should be a subclass of ModelBase"))
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query = session.query(model) if not args else session.query(*args)
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query = _read_deleted_filter(query, model, read_deleted)
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query = _project_filter(query, model, context, project_only)
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return query
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def get_table(engine, name):
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"""Returns an sqlalchemy table dynamically from db.
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Needed because the models don't work for us in migrations
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as models will be far out of sync with the current data.
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"""
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metadata = MetaData()
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metadata.bind = engine
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return Table(name, metadata, autoload=True)
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class InsertFromSelect(UpdateBase):
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"""Form the base for `INSERT INTO table (SELECT ... )` statement."""
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def __init__(self, table, select):
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self.table = table
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self.select = select
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@compiles(InsertFromSelect)
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def visit_insert_from_select(element, compiler, **kw):
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"""Form the `INSERT INTO table (SELECT ... )` statement."""
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return "INSERT INTO %s %s" % (
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compiler.process(element.table, asfrom=True),
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compiler.process(element.select))
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class ColumnError(Exception):
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"""Error raised when no column or an invalid column is found."""
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def _get_not_supported_column(col_name_col_instance, column_name):
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try:
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column = col_name_col_instance[column_name]
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except KeyError:
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msg = _("Please specify column %s in col_name_col_instance "
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"param. It is required because column has unsupported "
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"type by sqlite).")
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raise ColumnError(msg % column_name)
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if not isinstance(column, Column):
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msg = _("col_name_col_instance param has wrong type of "
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"column instance for column %s It should be instance "
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"of sqlalchemy.Column.")
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raise ColumnError(msg % column_name)
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return column
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def drop_unique_constraint(migrate_engine, table_name, uc_name, *columns,
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**col_name_col_instance):
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"""Drop unique constraint from table.
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DEPRECATED: this function is deprecated and will be removed from neutron.db
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in a few releases. Please use UniqueConstraint.drop() method directly for
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sqlalchemy-migrate migration scripts.
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This method drops UC from table and works for mysql, postgresql and sqlite.
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In mysql and postgresql we are able to use "alter table" construction.
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Sqlalchemy doesn't support some sqlite column types and replaces their
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type with NullType in metadata. We process these columns and replace
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NullType with the correct column type.
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:param migrate_engine: sqlalchemy engine
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:param table_name: name of table that contains uniq constraint.
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:param uc_name: name of uniq constraint that will be dropped.
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:param columns: columns that are in uniq constraint.
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:param col_name_col_instance: contains pair column_name=column_instance.
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column_instance is instance of Column. These params
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are required only for columns that have unsupported
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types by sqlite. For example BigInteger.
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"""
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from migrate.changeset import UniqueConstraint
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meta = MetaData()
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meta.bind = migrate_engine
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t = Table(table_name, meta, autoload=True)
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if migrate_engine.name == "sqlite":
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override_cols = [
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_get_not_supported_column(col_name_col_instance, col.name)
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for col in t.columns
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if isinstance(col.type, NullType)
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]
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for col in override_cols:
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t.columns.replace(col)
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uc = UniqueConstraint(*columns, table=t, name=uc_name)
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uc.drop()
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def drop_old_duplicate_entries_from_table(migrate_engine, table_name,
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use_soft_delete, *uc_column_names):
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"""Drop all old rows having the same values for columns in uc_columns.
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This method drop (or mark ad `deleted` if use_soft_delete is True) old
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duplicate rows form table with name `table_name`.
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:param migrate_engine: Sqlalchemy engine
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:param table_name: Table with duplicates
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:param use_soft_delete: If True - values will be marked as `deleted`,
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if False - values will be removed from table
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:param uc_column_names: Unique constraint columns
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"""
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meta = MetaData()
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meta.bind = migrate_engine
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table = Table(table_name, meta, autoload=True)
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columns_for_group_by = [table.c[name] for name in uc_column_names]
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columns_for_select = [func.max(table.c.id)]
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columns_for_select.extend(columns_for_group_by)
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duplicated_rows_select = sqlalchemy.sql.select(
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columns_for_select, group_by=columns_for_group_by,
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having=func.count(table.c.id) > 1)
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for row in migrate_engine.execute(duplicated_rows_select):
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# NOTE(boris-42): Do not remove row that has the biggest ID.
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delete_condition = table.c.id != row[0]
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is_none = None # workaround for pyflakes
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delete_condition &= table.c.deleted_at == is_none
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for name in uc_column_names:
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delete_condition &= table.c[name] == row[name]
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rows_to_delete_select = sqlalchemy.sql.select(
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[table.c.id]).where(delete_condition)
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for row in migrate_engine.execute(rows_to_delete_select).fetchall():
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LOG.info(_LI("Deleting duplicated row with id: %(id)s from table: "
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"%(table)s") % dict(id=row[0], table=table_name))
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if use_soft_delete:
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delete_statement = table.update().\
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where(delete_condition).\
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values({
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'deleted': literal_column('id'),
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'updated_at': literal_column('updated_at'),
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'deleted_at': timeutils.utcnow()
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})
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else:
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delete_statement = table.delete().where(delete_condition)
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migrate_engine.execute(delete_statement)
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def _get_default_deleted_value(table):
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if isinstance(table.c.id.type, Integer):
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return 0
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if isinstance(table.c.id.type, String):
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return ""
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raise ColumnError(_("Unsupported id columns type"))
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def _restore_indexes_on_deleted_columns(migrate_engine, table_name, indexes):
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table = get_table(migrate_engine, table_name)
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insp = reflection.Inspector.from_engine(migrate_engine)
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real_indexes = insp.get_indexes(table_name)
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existing_index_names = dict(
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[(index['name'], index['column_names']) for index in real_indexes])
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# NOTE(boris-42): Restore indexes on `deleted` column
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for index in indexes:
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if 'deleted' not in index['column_names']:
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continue
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name = index['name']
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if name in existing_index_names:
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column_names = [table.c[c] for c in existing_index_names[name]]
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old_index = Index(name, *column_names, unique=index["unique"])
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old_index.drop(migrate_engine)
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column_names = [table.c[c] for c in index['column_names']]
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new_index = Index(index["name"], *column_names, unique=index["unique"])
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new_index.create(migrate_engine)
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def change_deleted_column_type_to_boolean(migrate_engine, table_name,
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**col_name_col_instance):
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if migrate_engine.name == "sqlite":
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return _change_deleted_column_type_to_boolean_sqlite(
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migrate_engine, table_name, **col_name_col_instance)
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insp = reflection.Inspector.from_engine(migrate_engine)
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indexes = insp.get_indexes(table_name)
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table = get_table(migrate_engine, table_name)
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old_deleted = Column('old_deleted', Boolean, default=False)
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old_deleted.create(table, populate_default=False)
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table.update().\
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where(table.c.deleted == table.c.id).\
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values(old_deleted=True).\
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execute()
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table.c.deleted.drop()
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table.c.old_deleted.alter(name="deleted")
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_restore_indexes_on_deleted_columns(migrate_engine, table_name, indexes)
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def _change_deleted_column_type_to_boolean_sqlite(migrate_engine, table_name,
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**col_name_col_instance):
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insp = reflection.Inspector.from_engine(migrate_engine)
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table = get_table(migrate_engine, table_name)
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columns = []
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for column in table.columns:
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column_copy = None
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if column.name != "deleted":
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if isinstance(column.type, NullType):
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column_copy = _get_not_supported_column(col_name_col_instance,
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column.name)
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else:
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column_copy = column.copy()
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else:
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column_copy = Column('deleted', Boolean, default=0)
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columns.append(column_copy)
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constraints = [constraint.copy() for constraint in table.constraints]
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meta = table.metadata
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new_table = Table(table_name + "__tmp__", meta,
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*(columns + constraints))
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new_table.create()
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indexes = []
|
|
for index in insp.get_indexes(table_name):
|
|
column_names = [new_table.c[c] for c in index['column_names']]
|
|
indexes.append(Index(index["name"], *column_names,
|
|
unique=index["unique"]))
|
|
|
|
c_select = []
|
|
for c in table.c:
|
|
if c.name != "deleted":
|
|
c_select.append(c)
|
|
else:
|
|
c_select.append(table.c.deleted == table.c.id)
|
|
|
|
ins = InsertFromSelect(new_table, sqlalchemy.sql.select(c_select))
|
|
migrate_engine.execute(ins)
|
|
|
|
table.drop()
|
|
[index.create(migrate_engine) for index in indexes]
|
|
|
|
new_table.rename(table_name)
|
|
new_table.update().\
|
|
where(new_table.c.deleted == new_table.c.id).\
|
|
values(deleted=True).\
|
|
execute()
|
|
|
|
|
|
def change_deleted_column_type_to_id_type(migrate_engine, table_name,
|
|
**col_name_col_instance):
|
|
if migrate_engine.name == "sqlite":
|
|
return _change_deleted_column_type_to_id_type_sqlite(
|
|
migrate_engine, table_name, **col_name_col_instance)
|
|
insp = reflection.Inspector.from_engine(migrate_engine)
|
|
indexes = insp.get_indexes(table_name)
|
|
|
|
table = get_table(migrate_engine, table_name)
|
|
|
|
new_deleted = Column('new_deleted', table.c.id.type,
|
|
default=_get_default_deleted_value(table))
|
|
new_deleted.create(table, populate_default=True)
|
|
|
|
deleted = True # workaround for pyflakes
|
|
table.update().\
|
|
where(table.c.deleted == deleted).\
|
|
values(new_deleted=table.c.id).\
|
|
execute()
|
|
table.c.deleted.drop()
|
|
table.c.new_deleted.alter(name="deleted")
|
|
|
|
_restore_indexes_on_deleted_columns(migrate_engine, table_name, indexes)
|
|
|
|
|
|
def _change_deleted_column_type_to_id_type_sqlite(migrate_engine, table_name,
|
|
**col_name_col_instance):
|
|
# NOTE(boris-42): sqlaclhemy-migrate can't drop column with check
|
|
# constraints in sqlite DB and our `deleted` column has
|
|
# 2 check constraints. So there is only one way to remove
|
|
# these constraints:
|
|
# 1) Create new table with the same columns, constraints
|
|
# and indexes. (except deleted column).
|
|
# 2) Copy all data from old to new table.
|
|
# 3) Drop old table.
|
|
# 4) Rename new table to old table name.
|
|
insp = reflection.Inspector.from_engine(migrate_engine)
|
|
meta = MetaData(bind=migrate_engine)
|
|
table = Table(table_name, meta, autoload=True)
|
|
default_deleted_value = _get_default_deleted_value(table)
|
|
|
|
columns = []
|
|
for column in table.columns:
|
|
column_copy = None
|
|
if column.name != "deleted":
|
|
if isinstance(column.type, NullType):
|
|
column_copy = _get_not_supported_column(col_name_col_instance,
|
|
column.name)
|
|
else:
|
|
column_copy = column.copy()
|
|
else:
|
|
column_copy = Column('deleted', table.c.id.type,
|
|
default=default_deleted_value)
|
|
columns.append(column_copy)
|
|
|
|
def is_deleted_column_constraint(constraint):
|
|
# NOTE(boris-42): There is no other way to check is CheckConstraint
|
|
# associated with deleted column.
|
|
if not isinstance(constraint, CheckConstraint):
|
|
return False
|
|
sqltext = str(constraint.sqltext)
|
|
return (sqltext.endswith("deleted in (0, 1)") or
|
|
sqltext.endswith("deleted IN (:deleted_1, :deleted_2)"))
|
|
|
|
constraints = []
|
|
for constraint in table.constraints:
|
|
if not is_deleted_column_constraint(constraint):
|
|
constraints.append(constraint.copy())
|
|
|
|
new_table = Table(table_name + "__tmp__", meta,
|
|
*(columns + constraints))
|
|
new_table.create()
|
|
|
|
indexes = []
|
|
for index in insp.get_indexes(table_name):
|
|
column_names = [new_table.c[c] for c in index['column_names']]
|
|
indexes.append(Index(index["name"], *column_names,
|
|
unique=index["unique"]))
|
|
|
|
ins = InsertFromSelect(new_table, table.select())
|
|
migrate_engine.execute(ins)
|
|
|
|
table.drop()
|
|
[index.create(migrate_engine) for index in indexes]
|
|
|
|
new_table.rename(table_name)
|
|
deleted = True # workaround for pyflakes
|
|
new_table.update().\
|
|
where(new_table.c.deleted == deleted).\
|
|
values(deleted=new_table.c.id).\
|
|
execute()
|
|
|
|
# NOTE(boris-42): Fix value of deleted column: False -> "" or 0.
|
|
deleted = False # workaround for pyflakes
|
|
new_table.update().\
|
|
where(new_table.c.deleted == deleted).\
|
|
values(deleted=default_deleted_value).\
|
|
execute()
|
|
|
|
|
|
def get_connect_string(backend, database, user=None, passwd=None):
|
|
"""Get database connection
|
|
|
|
Try to get a connection with a very specific set of values, if we get
|
|
these then we'll run the tests, otherwise they are skipped
|
|
"""
|
|
args = {'backend': backend,
|
|
'user': user,
|
|
'passwd': passwd,
|
|
'database': database}
|
|
if backend == 'sqlite':
|
|
template = '%(backend)s:///%(database)s'
|
|
else:
|
|
template = "%(backend)s://%(user)s:%(passwd)s@localhost/%(database)s"
|
|
return template % args
|
|
|
|
|
|
def is_backend_avail(backend, database, user=None, passwd=None):
|
|
try:
|
|
connect_uri = get_connect_string(backend=backend,
|
|
database=database,
|
|
user=user,
|
|
passwd=passwd)
|
|
engine = sqlalchemy.create_engine(connect_uri)
|
|
connection = engine.connect()
|
|
except Exception:
|
|
# intentionally catch all to handle exceptions even if we don't
|
|
# have any backend code loaded.
|
|
return False
|
|
else:
|
|
connection.close()
|
|
engine.dispose()
|
|
return True
|
|
|
|
|
|
def get_db_connection_info(conn_pieces):
|
|
database = conn_pieces.path.strip('/')
|
|
loc_pieces = conn_pieces.netloc.split('@')
|
|
host = loc_pieces[1]
|
|
|
|
auth_pieces = loc_pieces[0].split(':')
|
|
user = auth_pieces[0]
|
|
password = ""
|
|
if len(auth_pieces) > 1:
|
|
password = auth_pieces[1].strip()
|
|
|
|
return (user, password, database, host)
|