877 lines
30 KiB
Python
877 lines
30 KiB
Python
# -*- coding: utf-8 -*-
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# Copyright 2018, 2019 New Vector Ltd
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# Copyright 2019 The Matrix.org Foundation C.I.C.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain 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,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import logging
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from itertools import chain
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from twisted.internet import defer
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from twisted.internet.defer import DeferredLock
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from synapse.api.constants import EventTypes, Membership
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from synapse.storage import PostgresEngine
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from synapse.storage.state_deltas import StateDeltasStore
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from synapse.util.caches.descriptors import cached
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logger = logging.getLogger(__name__)
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# these fields track absolutes (e.g. total number of rooms on the server)
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# You can think of these as Prometheus Gauges.
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# You can draw these stats on a line graph.
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# Example: number of users in a room
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ABSOLUTE_STATS_FIELDS = {
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"room": (
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"current_state_events",
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"joined_members",
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"invited_members",
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"left_members",
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"banned_members",
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"local_users_in_room",
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),
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"user": ("joined_rooms",),
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}
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# these fields are per-timeslice and so should be reset to 0 upon a new slice
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# You can draw these stats on a histogram.
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# Example: number of events sent locally during a time slice
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PER_SLICE_FIELDS = {
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"room": ("total_events", "total_event_bytes"),
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"user": ("invites_sent", "rooms_created", "total_events", "total_event_bytes"),
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}
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TYPE_TO_TABLE = {"room": ("room_stats", "room_id"), "user": ("user_stats", "user_id")}
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# these are the tables (& ID columns) which contain our actual subjects
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TYPE_TO_ORIGIN_TABLE = {"room": ("rooms", "room_id"), "user": ("users", "name")}
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class StatsStore(StateDeltasStore):
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def __init__(self, db_conn, hs):
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super(StatsStore, self).__init__(db_conn, hs)
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self.server_name = hs.hostname
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self.clock = self.hs.get_clock()
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self.stats_enabled = hs.config.stats_enabled
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self.stats_bucket_size = hs.config.stats_bucket_size
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self.stats_delta_processing_lock = DeferredLock()
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self.register_background_update_handler(
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"populate_stats_process_rooms", self._populate_stats_process_rooms
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)
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self.register_background_update_handler(
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"populate_stats_process_users", self._populate_stats_process_users
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)
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# we no longer need to perform clean-up, but we will give ourselves
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# the potential to reintroduce it in the future – so documentation
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# will still encourage the use of this no-op handler.
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self.register_noop_background_update("populate_stats_cleanup")
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self.register_noop_background_update("populate_stats_prepare")
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def quantise_stats_time(self, ts):
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"""
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Quantises a timestamp to be a multiple of the bucket size.
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Args:
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ts (int): the timestamp to quantise, in milliseconds since the Unix
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Epoch
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Returns:
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int: a timestamp which
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- is divisible by the bucket size;
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- is no later than `ts`; and
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- is the largest such timestamp.
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"""
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return (ts // self.stats_bucket_size) * self.stats_bucket_size
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@defer.inlineCallbacks
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def _populate_stats_process_users(self, progress, batch_size):
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"""
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This is a background update which regenerates statistics for users.
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"""
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if not self.stats_enabled:
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yield self._end_background_update("populate_stats_process_users")
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return 1
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last_user_id = progress.get("last_user_id", "")
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def _get_next_batch(txn):
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sql = """
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SELECT DISTINCT name FROM users
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WHERE name > ?
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ORDER BY name ASC
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LIMIT ?
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"""
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txn.execute(sql, (last_user_id, batch_size))
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return [r for r, in txn]
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users_to_work_on = yield self.runInteraction(
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"_populate_stats_process_users", _get_next_batch
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)
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# No more rooms -- complete the transaction.
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if not users_to_work_on:
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yield self._end_background_update("populate_stats_process_users")
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return 1
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for user_id in users_to_work_on:
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yield self._calculate_and_set_initial_state_for_user(user_id)
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progress["last_user_id"] = user_id
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yield self.runInteraction(
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"populate_stats_process_users",
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self._background_update_progress_txn,
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"populate_stats_process_users",
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progress,
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)
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return len(users_to_work_on)
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@defer.inlineCallbacks
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def _populate_stats_process_rooms(self, progress, batch_size):
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"""
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This is a background update which regenerates statistics for rooms.
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"""
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if not self.stats_enabled:
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yield self._end_background_update("populate_stats_process_rooms")
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return 1
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last_room_id = progress.get("last_room_id", "")
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def _get_next_batch(txn):
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sql = """
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SELECT DISTINCT room_id FROM current_state_events
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WHERE room_id > ?
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ORDER BY room_id ASC
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LIMIT ?
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"""
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txn.execute(sql, (last_room_id, batch_size))
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return [r for r, in txn]
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rooms_to_work_on = yield self.runInteraction(
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"populate_stats_rooms_get_batch", _get_next_batch
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)
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# No more rooms -- complete the transaction.
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if not rooms_to_work_on:
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yield self._end_background_update("populate_stats_process_rooms")
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return 1
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for room_id in rooms_to_work_on:
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yield self._calculate_and_set_initial_state_for_room(room_id)
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progress["last_room_id"] = room_id
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yield self.runInteraction(
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"_populate_stats_process_rooms",
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self._background_update_progress_txn,
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"populate_stats_process_rooms",
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progress,
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)
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return len(rooms_to_work_on)
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def get_stats_positions(self):
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"""
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Returns the stats processor positions.
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"""
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return self._simple_select_one_onecol(
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table="stats_incremental_position",
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keyvalues={},
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retcol="stream_id",
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desc="stats_incremental_position",
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)
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def update_room_state(self, room_id, fields):
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"""
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Args:
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room_id (str)
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fields (dict[str:Any])
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"""
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# For whatever reason some of the fields may contain null bytes, which
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# postgres isn't a fan of, so we replace those fields with null.
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for col in (
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"join_rules",
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"history_visibility",
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"encryption",
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"name",
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"topic",
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"avatar",
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"canonical_alias",
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):
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field = fields.get(col)
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if field and "\0" in field:
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fields[col] = None
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return self._simple_upsert(
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table="room_stats_state",
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keyvalues={"room_id": room_id},
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values=fields,
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desc="update_room_state",
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)
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def get_statistics_for_subject(self, stats_type, stats_id, start, size=100):
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"""
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Get statistics for a given subject.
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Args:
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stats_type (str): The type of subject
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stats_id (str): The ID of the subject (e.g. room_id or user_id)
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start (int): Pagination start. Number of entries, not timestamp.
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size (int): How many entries to return.
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Returns:
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Deferred[list[dict]], where the dict has the keys of
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ABSOLUTE_STATS_FIELDS[stats_type], and "bucket_size" and "end_ts".
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"""
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return self.runInteraction(
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"get_statistics_for_subject",
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self._get_statistics_for_subject_txn,
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stats_type,
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stats_id,
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start,
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size,
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)
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def _get_statistics_for_subject_txn(
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self, txn, stats_type, stats_id, start, size=100
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):
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"""
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Transaction-bound version of L{get_statistics_for_subject}.
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"""
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table, id_col = TYPE_TO_TABLE[stats_type]
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selected_columns = list(
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ABSOLUTE_STATS_FIELDS[stats_type] + PER_SLICE_FIELDS[stats_type]
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)
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slice_list = self._simple_select_list_paginate_txn(
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txn,
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table + "_historical",
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{id_col: stats_id},
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"end_ts",
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start,
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size,
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retcols=selected_columns + ["bucket_size", "end_ts"],
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order_direction="DESC",
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)
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return slice_list
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def get_room_stats_state(self, room_id):
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"""
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Returns the current room_stats_state for a room.
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Args:
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room_id (str): The ID of the room to return state for.
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Returns (dict):
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Dictionary containing these keys:
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"name", "topic", "canonical_alias", "avatar", "join_rules",
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"history_visibility"
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"""
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return self._simple_select_one(
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"room_stats_state",
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{"room_id": room_id},
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retcols=(
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"name",
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"topic",
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"canonical_alias",
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"avatar",
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"join_rules",
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"history_visibility",
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),
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)
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@cached()
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def get_earliest_token_for_stats(self, stats_type, id):
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"""
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Fetch the "earliest token". This is used by the room stats delta
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processor to ignore deltas that have been processed between the
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start of the background task and any particular room's stats
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being calculated.
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Returns:
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Deferred[int]
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"""
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table, id_col = TYPE_TO_TABLE[stats_type]
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return self._simple_select_one_onecol(
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"%s_current" % (table,),
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keyvalues={id_col: id},
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retcol="completed_delta_stream_id",
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allow_none=True,
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)
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def bulk_update_stats_delta(self, ts, updates, stream_id):
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"""Bulk update stats tables for a given stream_id and updates the stats
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incremental position.
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Args:
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ts (int): Current timestamp in ms
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updates(dict[str, dict[str, dict[str, Counter]]]): The updates to
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commit as a mapping stats_type -> stats_id -> field -> delta.
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stream_id (int): Current position.
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Returns:
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Deferred
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"""
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def _bulk_update_stats_delta_txn(txn):
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for stats_type, stats_updates in updates.items():
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for stats_id, fields in stats_updates.items():
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self._update_stats_delta_txn(
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txn,
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ts=ts,
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stats_type=stats_type,
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stats_id=stats_id,
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fields=fields,
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complete_with_stream_id=stream_id,
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)
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self._simple_update_one_txn(
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txn,
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table="stats_incremental_position",
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keyvalues={},
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updatevalues={"stream_id": stream_id},
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)
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return self.runInteraction(
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"bulk_update_stats_delta", _bulk_update_stats_delta_txn
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)
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def update_stats_delta(
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self,
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ts,
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stats_type,
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stats_id,
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fields,
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complete_with_stream_id,
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absolute_field_overrides=None,
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):
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"""
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Updates the statistics for a subject, with a delta (difference/relative
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change).
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Args:
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ts (int): timestamp of the change
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stats_type (str): "room" or "user" – the kind of subject
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stats_id (str): the subject's ID (room ID or user ID)
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fields (dict[str, int]): Deltas of stats values.
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complete_with_stream_id (int, optional):
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If supplied, converts an incomplete row into a complete row,
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with the supplied stream_id marked as the stream_id where the
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row was completed.
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absolute_field_overrides (dict[str, int]): Current stats values
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(i.e. not deltas) of absolute fields.
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Does not work with per-slice fields.
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"""
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return self.runInteraction(
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"update_stats_delta",
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self._update_stats_delta_txn,
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ts,
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stats_type,
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stats_id,
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fields,
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complete_with_stream_id=complete_with_stream_id,
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absolute_field_overrides=absolute_field_overrides,
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)
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def _update_stats_delta_txn(
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self,
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txn,
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ts,
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stats_type,
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stats_id,
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fields,
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complete_with_stream_id,
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absolute_field_overrides=None,
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):
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if absolute_field_overrides is None:
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absolute_field_overrides = {}
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table, id_col = TYPE_TO_TABLE[stats_type]
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quantised_ts = self.quantise_stats_time(int(ts))
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end_ts = quantised_ts + self.stats_bucket_size
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# Lets be paranoid and check that all the given field names are known
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abs_field_names = ABSOLUTE_STATS_FIELDS[stats_type]
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slice_field_names = PER_SLICE_FIELDS[stats_type]
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for field in chain(fields.keys(), absolute_field_overrides.keys()):
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if field not in abs_field_names and field not in slice_field_names:
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# guard against potential SQL injection dodginess
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raise ValueError(
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"%s is not a recognised field"
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" for stats type %s" % (field, stats_type)
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)
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# Per slice fields do not get added to the _current table
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# This calculates the deltas (`field = field + ?` values)
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# for absolute fields,
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# * defaulting to 0 if not specified
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# (required for the INSERT part of upserting to work)
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# * omitting overrides specified in `absolute_field_overrides`
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deltas_of_absolute_fields = {
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key: fields.get(key, 0)
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for key in abs_field_names
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if key not in absolute_field_overrides
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}
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# Keep the delta stream ID field up to date
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absolute_field_overrides = absolute_field_overrides.copy()
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absolute_field_overrides["completed_delta_stream_id"] = complete_with_stream_id
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# first upsert the `_current` table
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self._upsert_with_additive_relatives_txn(
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txn=txn,
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table=table + "_current",
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keyvalues={id_col: stats_id},
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absolutes=absolute_field_overrides,
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additive_relatives=deltas_of_absolute_fields,
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)
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per_slice_additive_relatives = {
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key: fields.get(key, 0) for key in slice_field_names
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}
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self._upsert_copy_from_table_with_additive_relatives_txn(
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txn=txn,
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into_table=table + "_historical",
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keyvalues={id_col: stats_id},
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extra_dst_insvalues={"bucket_size": self.stats_bucket_size},
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extra_dst_keyvalues={"end_ts": end_ts},
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additive_relatives=per_slice_additive_relatives,
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src_table=table + "_current",
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copy_columns=abs_field_names,
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)
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def _upsert_with_additive_relatives_txn(
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self, txn, table, keyvalues, absolutes, additive_relatives
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):
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"""Used to update values in the stats tables.
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This is basically a slightly convoluted upsert that *adds* to any
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existing rows.
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Args:
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txn
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table (str): Table name
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keyvalues (dict[str, any]): Row-identifying key values
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absolutes (dict[str, any]): Absolute (set) fields
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additive_relatives (dict[str, int]): Fields that will be added onto
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if existing row present.
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"""
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if self.database_engine.can_native_upsert:
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absolute_updates = [
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"%(field)s = EXCLUDED.%(field)s" % {"field": field}
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for field in absolutes.keys()
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]
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relative_updates = [
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"%(field)s = EXCLUDED.%(field)s + %(table)s.%(field)s"
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% {"table": table, "field": field}
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for field in additive_relatives.keys()
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]
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insert_cols = []
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qargs = []
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for (key, val) in chain(
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keyvalues.items(), absolutes.items(), additive_relatives.items()
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):
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insert_cols.append(key)
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qargs.append(val)
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sql = """
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INSERT INTO %(table)s (%(insert_cols_cs)s)
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VALUES (%(insert_vals_qs)s)
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ON CONFLICT (%(key_columns)s) DO UPDATE SET %(updates)s
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""" % {
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"table": table,
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"insert_cols_cs": ", ".join(insert_cols),
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"insert_vals_qs": ", ".join(
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["?"] * (len(keyvalues) + len(absolutes) + len(additive_relatives))
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),
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"key_columns": ", ".join(keyvalues),
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"updates": ", ".join(chain(absolute_updates, relative_updates)),
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}
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txn.execute(sql, qargs)
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else:
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self.database_engine.lock_table(txn, table)
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retcols = list(chain(absolutes.keys(), additive_relatives.keys()))
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current_row = self._simple_select_one_txn(
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txn, table, keyvalues, retcols, allow_none=True
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)
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if current_row is None:
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merged_dict = {**keyvalues, **absolutes, **additive_relatives}
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self._simple_insert_txn(txn, table, merged_dict)
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else:
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for (key, val) in additive_relatives.items():
|
||
current_row[key] += val
|
||
current_row.update(absolutes)
|
||
self._simple_update_one_txn(txn, table, keyvalues, current_row)
|
||
|
||
def _upsert_copy_from_table_with_additive_relatives_txn(
|
||
self,
|
||
txn,
|
||
into_table,
|
||
keyvalues,
|
||
extra_dst_keyvalues,
|
||
extra_dst_insvalues,
|
||
additive_relatives,
|
||
src_table,
|
||
copy_columns,
|
||
):
|
||
"""Updates the historic stats table with latest updates.
|
||
|
||
This involves copying "absolute" fields from the `_current` table, and
|
||
adding relative fields to any existing values.
|
||
|
||
Args:
|
||
txn: Transaction
|
||
into_table (str): The destination table to UPSERT the row into
|
||
keyvalues (dict[str, any]): Row-identifying key values
|
||
extra_dst_keyvalues (dict[str, any]): Additional keyvalues
|
||
for `into_table`.
|
||
extra_dst_insvalues (dict[str, any]): Additional values to insert
|
||
on new row creation for `into_table`.
|
||
additive_relatives (dict[str, any]): Fields that will be added onto
|
||
if existing row present. (Must be disjoint from copy_columns.)
|
||
src_table (str): The source table to copy from
|
||
copy_columns (iterable[str]): The list of columns to copy
|
||
"""
|
||
if self.database_engine.can_native_upsert:
|
||
ins_columns = chain(
|
||
keyvalues,
|
||
copy_columns,
|
||
additive_relatives,
|
||
extra_dst_keyvalues,
|
||
extra_dst_insvalues,
|
||
)
|
||
sel_exprs = chain(
|
||
keyvalues,
|
||
copy_columns,
|
||
(
|
||
"?"
|
||
for _ in chain(
|
||
additive_relatives, extra_dst_keyvalues, extra_dst_insvalues
|
||
)
|
||
),
|
||
)
|
||
keyvalues_where = ("%s = ?" % f for f in keyvalues)
|
||
|
||
sets_cc = ("%s = EXCLUDED.%s" % (f, f) for f in copy_columns)
|
||
sets_ar = (
|
||
"%s = EXCLUDED.%s + %s.%s" % (f, f, into_table, f)
|
||
for f in additive_relatives
|
||
)
|
||
|
||
sql = """
|
||
INSERT INTO %(into_table)s (%(ins_columns)s)
|
||
SELECT %(sel_exprs)s
|
||
FROM %(src_table)s
|
||
WHERE %(keyvalues_where)s
|
||
ON CONFLICT (%(keyvalues)s)
|
||
DO UPDATE SET %(sets)s
|
||
""" % {
|
||
"into_table": into_table,
|
||
"ins_columns": ", ".join(ins_columns),
|
||
"sel_exprs": ", ".join(sel_exprs),
|
||
"keyvalues_where": " AND ".join(keyvalues_where),
|
||
"src_table": src_table,
|
||
"keyvalues": ", ".join(
|
||
chain(keyvalues.keys(), extra_dst_keyvalues.keys())
|
||
),
|
||
"sets": ", ".join(chain(sets_cc, sets_ar)),
|
||
}
|
||
|
||
qargs = list(
|
||
chain(
|
||
additive_relatives.values(),
|
||
extra_dst_keyvalues.values(),
|
||
extra_dst_insvalues.values(),
|
||
keyvalues.values(),
|
||
)
|
||
)
|
||
txn.execute(sql, qargs)
|
||
else:
|
||
self.database_engine.lock_table(txn, into_table)
|
||
src_row = self._simple_select_one_txn(
|
||
txn, src_table, keyvalues, copy_columns
|
||
)
|
||
all_dest_keyvalues = {**keyvalues, **extra_dst_keyvalues}
|
||
dest_current_row = self._simple_select_one_txn(
|
||
txn,
|
||
into_table,
|
||
keyvalues=all_dest_keyvalues,
|
||
retcols=list(chain(additive_relatives.keys(), copy_columns)),
|
||
allow_none=True,
|
||
)
|
||
|
||
if dest_current_row is None:
|
||
merged_dict = {
|
||
**keyvalues,
|
||
**extra_dst_keyvalues,
|
||
**extra_dst_insvalues,
|
||
**src_row,
|
||
**additive_relatives,
|
||
}
|
||
self._simple_insert_txn(txn, into_table, merged_dict)
|
||
else:
|
||
for (key, val) in additive_relatives.items():
|
||
src_row[key] = dest_current_row[key] + val
|
||
self._simple_update_txn(txn, into_table, all_dest_keyvalues, src_row)
|
||
|
||
def get_changes_room_total_events_and_bytes(self, min_pos, max_pos):
|
||
"""Fetches the counts of events in the given range of stream IDs.
|
||
|
||
Args:
|
||
min_pos (int)
|
||
max_pos (int)
|
||
|
||
Returns:
|
||
Deferred[dict[str, dict[str, int]]]: Mapping of room ID to field
|
||
changes.
|
||
"""
|
||
|
||
return self.runInteraction(
|
||
"stats_incremental_total_events_and_bytes",
|
||
self.get_changes_room_total_events_and_bytes_txn,
|
||
min_pos,
|
||
max_pos,
|
||
)
|
||
|
||
def get_changes_room_total_events_and_bytes_txn(self, txn, low_pos, high_pos):
|
||
"""Gets the total_events and total_event_bytes counts for rooms and
|
||
senders, in a range of stream_orderings (including backfilled events).
|
||
|
||
Args:
|
||
txn
|
||
low_pos (int): Low stream ordering
|
||
high_pos (int): High stream ordering
|
||
|
||
Returns:
|
||
tuple[dict[str, dict[str, int]], dict[str, dict[str, int]]]: The
|
||
room and user deltas for total_events/total_event_bytes in the
|
||
format of `stats_id` -> fields
|
||
"""
|
||
|
||
if low_pos >= high_pos:
|
||
# nothing to do here.
|
||
return {}, {}
|
||
|
||
if isinstance(self.database_engine, PostgresEngine):
|
||
new_bytes_expression = "OCTET_LENGTH(json)"
|
||
else:
|
||
new_bytes_expression = "LENGTH(CAST(json AS BLOB))"
|
||
|
||
sql = """
|
||
SELECT events.room_id, COUNT(*) AS new_events, SUM(%s) AS new_bytes
|
||
FROM events INNER JOIN event_json USING (event_id)
|
||
WHERE (? < stream_ordering AND stream_ordering <= ?)
|
||
OR (? <= stream_ordering AND stream_ordering <= ?)
|
||
GROUP BY events.room_id
|
||
""" % (
|
||
new_bytes_expression,
|
||
)
|
||
|
||
txn.execute(sql, (low_pos, high_pos, -high_pos, -low_pos))
|
||
|
||
room_deltas = {
|
||
room_id: {"total_events": new_events, "total_event_bytes": new_bytes}
|
||
for room_id, new_events, new_bytes in txn
|
||
}
|
||
|
||
sql = """
|
||
SELECT events.sender, COUNT(*) AS new_events, SUM(%s) AS new_bytes
|
||
FROM events INNER JOIN event_json USING (event_id)
|
||
WHERE (? < stream_ordering AND stream_ordering <= ?)
|
||
OR (? <= stream_ordering AND stream_ordering <= ?)
|
||
GROUP BY events.sender
|
||
""" % (
|
||
new_bytes_expression,
|
||
)
|
||
|
||
txn.execute(sql, (low_pos, high_pos, -high_pos, -low_pos))
|
||
|
||
user_deltas = {
|
||
user_id: {"total_events": new_events, "total_event_bytes": new_bytes}
|
||
for user_id, new_events, new_bytes in txn
|
||
if self.hs.is_mine_id(user_id)
|
||
}
|
||
|
||
return room_deltas, user_deltas
|
||
|
||
@defer.inlineCallbacks
|
||
def _calculate_and_set_initial_state_for_room(self, room_id):
|
||
"""Calculate and insert an entry into room_stats_current.
|
||
|
||
Args:
|
||
room_id (str)
|
||
|
||
Returns:
|
||
Deferred[tuple[dict, dict, int]]: A tuple of room state, membership
|
||
counts and stream position.
|
||
"""
|
||
|
||
def _fetch_current_state_stats(txn):
|
||
pos = self.get_room_max_stream_ordering()
|
||
|
||
rows = self._simple_select_many_txn(
|
||
txn,
|
||
table="current_state_events",
|
||
column="type",
|
||
iterable=[
|
||
EventTypes.Create,
|
||
EventTypes.JoinRules,
|
||
EventTypes.RoomHistoryVisibility,
|
||
EventTypes.Encryption,
|
||
EventTypes.Name,
|
||
EventTypes.Topic,
|
||
EventTypes.RoomAvatar,
|
||
EventTypes.CanonicalAlias,
|
||
],
|
||
keyvalues={"room_id": room_id, "state_key": ""},
|
||
retcols=["event_id"],
|
||
)
|
||
|
||
event_ids = [row["event_id"] for row in rows]
|
||
|
||
txn.execute(
|
||
"""
|
||
SELECT membership, count(*) FROM current_state_events
|
||
WHERE room_id = ? AND type = 'm.room.member'
|
||
GROUP BY membership
|
||
""",
|
||
(room_id,),
|
||
)
|
||
membership_counts = {membership: cnt for membership, cnt in txn}
|
||
|
||
txn.execute(
|
||
"""
|
||
SELECT COALESCE(count(*), 0) FROM current_state_events
|
||
WHERE room_id = ?
|
||
""",
|
||
(room_id,),
|
||
)
|
||
|
||
current_state_events_count, = txn.fetchone()
|
||
|
||
users_in_room = self.get_users_in_room_txn(txn, room_id)
|
||
|
||
return (
|
||
event_ids,
|
||
membership_counts,
|
||
current_state_events_count,
|
||
users_in_room,
|
||
pos,
|
||
)
|
||
|
||
(
|
||
event_ids,
|
||
membership_counts,
|
||
current_state_events_count,
|
||
users_in_room,
|
||
pos,
|
||
) = yield self.runInteraction(
|
||
"get_initial_state_for_room", _fetch_current_state_stats
|
||
)
|
||
|
||
state_event_map = yield self.get_events(event_ids, get_prev_content=False)
|
||
|
||
room_state = {
|
||
"join_rules": None,
|
||
"history_visibility": None,
|
||
"encryption": None,
|
||
"name": None,
|
||
"topic": None,
|
||
"avatar": None,
|
||
"canonical_alias": None,
|
||
"is_federatable": True,
|
||
}
|
||
|
||
for event in state_event_map.values():
|
||
if event.type == EventTypes.JoinRules:
|
||
room_state["join_rules"] = event.content.get("join_rule")
|
||
elif event.type == EventTypes.RoomHistoryVisibility:
|
||
room_state["history_visibility"] = event.content.get(
|
||
"history_visibility"
|
||
)
|
||
elif event.type == EventTypes.Encryption:
|
||
room_state["encryption"] = event.content.get("algorithm")
|
||
elif event.type == EventTypes.Name:
|
||
room_state["name"] = event.content.get("name")
|
||
elif event.type == EventTypes.Topic:
|
||
room_state["topic"] = event.content.get("topic")
|
||
elif event.type == EventTypes.RoomAvatar:
|
||
room_state["avatar"] = event.content.get("url")
|
||
elif event.type == EventTypes.CanonicalAlias:
|
||
room_state["canonical_alias"] = event.content.get("alias")
|
||
elif event.type == EventTypes.Create:
|
||
room_state["is_federatable"] = event.content.get("m.federate", True)
|
||
|
||
yield self.update_room_state(room_id, room_state)
|
||
|
||
local_users_in_room = [u for u in users_in_room if self.hs.is_mine_id(u)]
|
||
|
||
yield self.update_stats_delta(
|
||
ts=self.clock.time_msec(),
|
||
stats_type="room",
|
||
stats_id=room_id,
|
||
fields={},
|
||
complete_with_stream_id=pos,
|
||
absolute_field_overrides={
|
||
"current_state_events": current_state_events_count,
|
||
"joined_members": membership_counts.get(Membership.JOIN, 0),
|
||
"invited_members": membership_counts.get(Membership.INVITE, 0),
|
||
"left_members": membership_counts.get(Membership.LEAVE, 0),
|
||
"banned_members": membership_counts.get(Membership.BAN, 0),
|
||
"local_users_in_room": len(local_users_in_room),
|
||
},
|
||
)
|
||
|
||
@defer.inlineCallbacks
|
||
def _calculate_and_set_initial_state_for_user(self, user_id):
|
||
def _calculate_and_set_initial_state_for_user_txn(txn):
|
||
pos = self._get_max_stream_id_in_current_state_deltas_txn(txn)
|
||
|
||
txn.execute(
|
||
"""
|
||
SELECT COUNT(distinct room_id) FROM current_state_events
|
||
WHERE type = 'm.room.member' AND state_key = ?
|
||
AND membership = 'join'
|
||
""",
|
||
(user_id,),
|
||
)
|
||
count, = txn.fetchone()
|
||
return count, pos
|
||
|
||
joined_rooms, pos = yield self.runInteraction(
|
||
"calculate_and_set_initial_state_for_user",
|
||
_calculate_and_set_initial_state_for_user_txn,
|
||
)
|
||
|
||
yield self.update_stats_delta(
|
||
ts=self.clock.time_msec(),
|
||
stats_type="user",
|
||
stats_id=user_id,
|
||
fields={},
|
||
complete_with_stream_id=pos,
|
||
absolute_field_overrides={"joined_rooms": joined_rooms},
|
||
)
|