415 lines
17 KiB
Python
415 lines
17 KiB
Python
#
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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 datetime
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import operator
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import time
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from oslo_log import log
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from oslo_utils import timeutils
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import ceilometer
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from ceilometer.i18n import _
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from ceilometer.storage import base
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from ceilometer.storage.hbase import base as hbase_base
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from ceilometer.storage.hbase import migration as hbase_migration
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from ceilometer.storage.hbase import utils as hbase_utils
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from ceilometer.storage import models
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from ceilometer import utils
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LOG = log.getLogger(__name__)
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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': {'query': {'simple': True,
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'metadata': True}},
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'statistics': {'query': {'simple': True,
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'metadata': True},
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'aggregation': {'standard': 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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class Connection(hbase_base.Connection, base.Connection):
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"""Put the metering data into a HBase database
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Collections:
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- meter (describes sample actually):
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- row-key: consists of reversed timestamp, meter and a message uuid
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for purposes of uniqueness
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- Column Families:
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f: contains the following qualifiers:
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- counter_name: <name of counter>
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- counter_type: <type of counter>
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- counter_unit: <unit of counter>
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- counter_volume: <volume of counter>
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- message: <raw incoming data>
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- message_id: <id of message>
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- message_signature: <signature of message>
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- resource_metadata: raw metadata for corresponding resource
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of the meter
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- project_id: <id of project>
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- resource_id: <id of resource>
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- user_id: <id of user>
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- recorded_at: <datetime when sample has been recorded (utc.now)>
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- flattened metadata with prefix r_metadata. e.g.::
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f:r_metadata.display_name or f:r_metadata.tag
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- rts: <reversed timestamp of entry>
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- timestamp: <meter's timestamp (came from message)>
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- source for meter with prefix 's'
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- resource:
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- row_key: uuid of resource
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- Column Families:
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f: contains the following qualifiers:
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- resource_metadata: raw metadata for corresponding resource
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- project_id: <id of project>
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- resource_id: <id of resource>
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- user_id: <id of user>
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- flattened metadata with prefix r_metadata. e.g.::
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f:r_metadata.display_name or f:r_metadata.tag
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- sources for all corresponding meters with prefix 's'
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- all meters with prefix 'm' for this resource in format:
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.. code-block:: python
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"%s:%s:%s:%s:%s" % (rts, source, counter_name, counter_type,
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counter_unit)
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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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_memory_instance = None
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RESOURCE_TABLE = "resource"
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METER_TABLE = "meter"
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def __init__(self, url):
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super(Connection, self).__init__(url)
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def upgrade(self):
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tables = [self.RESOURCE_TABLE, self.METER_TABLE]
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column_families = {'f': dict(max_versions=1)}
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with self.conn_pool.connection() as conn:
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hbase_utils.create_tables(conn, tables, column_families)
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hbase_migration.migrate_tables(conn, tables)
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def clear(self):
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LOG.debug(_('Dropping HBase schema...'))
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with self.conn_pool.connection() as conn:
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for table in [self.RESOURCE_TABLE,
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self.METER_TABLE]:
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try:
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conn.disable_table(table)
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except Exception:
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LOG.debug(_('Cannot disable table but ignoring error'))
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try:
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conn.delete_table(table)
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except Exception:
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LOG.debug(_('Cannot delete table but ignoring error'))
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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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with self.conn_pool.connection() as conn:
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resource_table = conn.table(self.RESOURCE_TABLE)
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meter_table = conn.table(self.METER_TABLE)
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resource_metadata = data.get('resource_metadata', {})
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# Determine the name of new meter
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rts = hbase_utils.timestamp(data['timestamp'])
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new_meter = hbase_utils.prepare_key(
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rts, data['source'], data['counter_name'],
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data['counter_type'], data['counter_unit'])
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# TODO(nprivalova): try not to store resource_id
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resource = hbase_utils.serialize_entry(**{
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'source': data['source'],
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'meter': {new_meter: data['timestamp']},
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'resource_metadata': resource_metadata,
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'resource_id': data['resource_id'],
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'project_id': data['project_id'], 'user_id': data['user_id']})
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# Here we put entry in HBase with our own timestamp. This is needed
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# when samples arrive out-of-order
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# If we use timestamp=data['timestamp'] the newest data will be
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# automatically 'on the top'. It is needed to keep metadata
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# up-to-date: metadata from newest samples is considered as actual.
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ts = int(time.mktime(data['timestamp'].timetuple()) * 1000)
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resource_table.put(hbase_utils.encode_unicode(data['resource_id']),
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resource, ts)
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# Rowkey consists of reversed timestamp, meter and a
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# message uuid for purposes of uniqueness
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row = hbase_utils.prepare_key(data['counter_name'], rts,
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data['message_id'])
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record = hbase_utils.serialize_entry(
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data, **{'source': data['source'], 'rts': rts,
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'message': data, 'recorded_at': timeutils.utcnow()})
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meter_table.put(row, record)
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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):
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"""Return an iterable of 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 ge, gt.
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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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"""
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q = hbase_utils.make_query(metaquery=metaquery, user_id=user,
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project_id=project,
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resource_id=resource, source=source)
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q = hbase_utils.make_meter_query_for_resource(start_timestamp,
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start_timestamp_op,
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end_timestamp,
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end_timestamp_op,
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source, q)
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with self.conn_pool.connection() as conn:
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resource_table = conn.table(self.RESOURCE_TABLE)
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LOG.debug(_("Query Resource table: %s") % q)
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for resource_id, data in resource_table.scan(filter=q):
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f_res, sources, meters, md = hbase_utils.deserialize_entry(
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data)
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resource_id = hbase_utils.encode_unicode(resource_id)
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# Unfortunately happybase doesn't keep ordered result from
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# HBase. So that's why it's needed to find min and max
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# manually
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first_ts = min(meters, key=operator.itemgetter(1))[1]
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last_ts = max(meters, key=operator.itemgetter(1))[1]
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source = meters[0][0][1]
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# If we use QualifierFilter then HBase returnes only
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# qualifiers filtered by. It will not return the whole entry.
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# That's why if we need to ask additional qualifiers manually.
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if 'project_id' not in f_res and 'user_id' not in f_res:
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row = resource_table.row(
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resource_id, columns=['f:project_id', 'f:user_id',
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'f:resource_metadata'])
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f_res, _s, _m, md = hbase_utils.deserialize_entry(row)
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yield models.Resource(
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resource_id=resource_id,
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first_sample_timestamp=first_ts,
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last_sample_timestamp=last_ts,
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project_id=f_res['project_id'],
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source=source,
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user_id=f_res['user_id'],
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metadata=md)
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def get_meters(self, user=None, project=None, resource=None, source=None,
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metaquery=None):
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"""Return an iterable of 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 resource filter.
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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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"""
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metaquery = metaquery or {}
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with self.conn_pool.connection() as conn:
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resource_table = conn.table(self.RESOURCE_TABLE)
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q = hbase_utils.make_query(metaquery=metaquery, user_id=user,
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project_id=project,
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resource_id=resource,
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source=source)
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LOG.debug(_("Query Resource table: %s") % q)
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gen = resource_table.scan(filter=q)
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# We need result set to be sure that user doesn't receive several
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# same meters. Please see bug
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# https://bugs.launchpad.net/ceilometer/+bug/1301371
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result = set()
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for ignored, data in gen:
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flatten_result, s, meters, md = hbase_utils.deserialize_entry(
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data)
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for m in meters:
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_m_rts, m_source, name, m_type, unit = m[0]
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meter_dict = {'name': name,
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'type': m_type,
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'unit': unit,
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'resource_id': flatten_result['resource_id'],
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'project_id': flatten_result['project_id'],
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'user_id': flatten_result['user_id']}
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frozen_meter = frozenset(meter_dict.items())
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if frozen_meter in result:
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continue
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result.add(frozen_meter)
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meter_dict.update({'source': m_source
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if m_source else None})
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yield models.Meter(**meter_dict)
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def get_samples(self, sample_filter, limit=None):
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"""Return an iterable of models.Sample instances.
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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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with self.conn_pool.connection() as conn:
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meter_table = conn.table(self.METER_TABLE)
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q, start, stop, columns = (hbase_utils.
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make_sample_query_from_filter
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(sample_filter, require_meter=False))
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LOG.debug(_("Query Meter Table: %s") % q)
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gen = meter_table.scan(filter=q, row_start=start, row_stop=stop,
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limit=limit, columns=columns)
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for ignored, meter in gen:
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d_meter = hbase_utils.deserialize_entry(meter)[0]
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d_meter['message']['recorded_at'] = d_meter['recorded_at']
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yield models.Sample(**d_meter['message'])
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@staticmethod
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def _update_meter_stats(stat, meter):
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"""Do the stats calculation on a requested time bucket in stats dict
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:param stats: dict where aggregated stats are kept
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:param index: time bucket index in stats
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:param meter: meter record as returned from HBase
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:param start_time: query start time
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:param period: length of the time bucket
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"""
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vol = meter['counter_volume']
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ts = meter['timestamp']
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stat.unit = meter['counter_unit']
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stat.min = min(vol, stat.min or vol)
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stat.max = max(vol, stat.max)
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stat.sum = vol + (stat.sum or 0)
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stat.count += 1
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stat.avg = (stat.sum / float(stat.count))
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stat.duration_start = min(ts, stat.duration_start or ts)
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stat.duration_end = max(ts, stat.duration_end or ts)
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stat.duration = (timeutils.delta_seconds(stat.duration_start,
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stat.duration_end))
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def get_meter_statistics(self, sample_filter, period=None, groupby=None,
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aggregate=None):
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"""Return an iterable of models.Statistics instances.
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Items are containing meter statistics described by the query
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parameters. The filter must have a meter value set.
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.. note::
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Due to HBase limitations the aggregations are implemented
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in the driver itself, therefore this method will be quite slow
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because of all the Thrift traffic it is going to create.
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"""
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if groupby:
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raise ceilometer.NotImplementedError("Group by not implemented.")
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if aggregate:
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raise ceilometer.NotImplementedError(
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'Selectable aggregates not implemented')
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with self.conn_pool.connection() as conn:
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meter_table = conn.table(self.METER_TABLE)
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q, start, stop, columns = (hbase_utils.
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make_sample_query_from_filter
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(sample_filter))
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# These fields are used in statistics' calculating
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columns.extend(['f:timestamp', 'f:counter_volume',
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'f:counter_unit'])
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meters = map(hbase_utils.deserialize_entry,
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list(meter for (ignored, meter) in
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meter_table.scan(
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filter=q, row_start=start,
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row_stop=stop, columns=columns)))
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if sample_filter.start_timestamp:
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start_time = sample_filter.start_timestamp
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elif meters:
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start_time = meters[-1][0]['timestamp']
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else:
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start_time = None
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if sample_filter.end_timestamp:
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end_time = sample_filter.end_timestamp
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elif meters:
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end_time = meters[0][0]['timestamp']
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else:
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end_time = None
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results = []
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if not period:
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period = 0
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period_start = start_time
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period_end = end_time
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# As our HBase meters are stored as newest-first, we need to iterate
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# in the reverse order
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for meter in meters[::-1]:
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ts = meter[0]['timestamp']
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if period:
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offset = int(timeutils.delta_seconds(
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start_time, ts) / period) * period
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period_start = start_time + datetime.timedelta(0, offset)
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if not results or not results[-1].period_start == period_start:
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if period:
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period_end = period_start + datetime.timedelta(
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0, period)
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results.append(
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models.Statistics(unit='',
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count=0,
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min=0,
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max=0,
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avg=0,
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sum=0,
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period=period,
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period_start=period_start,
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period_end=period_end,
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duration=None,
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duration_start=None,
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duration_end=None,
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groupby=None)
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)
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self._update_meter_stats(results[-1], meter[0])
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return results
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