mirror of
https://git.anonymousland.org/anonymousland/synapse.git
synced 2024-10-01 11:49:51 -04:00
01c88a09cd
Instead of proxying through the magic getter of the RootConfig object. This should be more performant (and is more explicit).
521 lines
20 KiB
Python
521 lines
20 KiB
Python
# Copyright 2020 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 calendar
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import logging
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import time
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from typing import Dict
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from synapse.metrics import GaugeBucketCollector
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from synapse.metrics.background_process_metrics import wrap_as_background_process
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from synapse.storage._base import SQLBaseStore
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from synapse.storage.database import DatabasePool
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from synapse.storage.databases.main.event_push_actions import (
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EventPushActionsWorkerStore,
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)
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logger = logging.getLogger(__name__)
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# Collect metrics on the number of forward extremities that exist.
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_extremities_collecter = GaugeBucketCollector(
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"synapse_forward_extremities",
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"Number of rooms on the server with the given number of forward extremities"
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" or fewer",
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buckets=[1, 2, 3, 5, 7, 10, 15, 20, 50, 100, 200, 500],
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)
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# we also expose metrics on the "number of excess extremity events", which is
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# (E-1)*N, where E is the number of extremities and N is the number of state
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# events in the room. This is an approximation to the number of state events
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# we could remove from state resolution by reducing the graph to a single
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# forward extremity.
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_excess_state_events_collecter = GaugeBucketCollector(
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"synapse_excess_extremity_events",
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"Number of rooms on the server with the given number of excess extremity "
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"events, or fewer",
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buckets=[0] + [1 << n for n in range(12)],
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)
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class ServerMetricsStore(EventPushActionsWorkerStore, SQLBaseStore):
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"""Functions to pull various metrics from the DB, for e.g. phone home
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stats and prometheus metrics.
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"""
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def __init__(self, database: DatabasePool, db_conn, hs):
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super().__init__(database, db_conn, hs)
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# Read the extrems every 60 minutes
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if hs.config.worker.run_background_tasks:
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self._clock.looping_call(self._read_forward_extremities, 60 * 60 * 1000)
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# Used in _generate_user_daily_visits to keep track of progress
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self._last_user_visit_update = self._get_start_of_day()
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@wrap_as_background_process("read_forward_extremities")
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async def _read_forward_extremities(self):
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def fetch(txn):
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txn.execute(
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"""
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SELECT t1.c, t2.c
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FROM (
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SELECT room_id, COUNT(*) c FROM event_forward_extremities
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GROUP BY room_id
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) t1 LEFT JOIN (
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SELECT room_id, COUNT(*) c FROM current_state_events
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GROUP BY room_id
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) t2 ON t1.room_id = t2.room_id
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"""
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)
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return txn.fetchall()
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res = await self.db_pool.runInteraction("read_forward_extremities", fetch)
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_extremities_collecter.update_data(x[0] for x in res)
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_excess_state_events_collecter.update_data(
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(x[0] - 1) * x[1] for x in res if x[1]
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)
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async def count_daily_e2ee_messages(self):
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"""
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Returns an estimate of the number of messages sent in the last day.
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If it has been significantly less or more than one day since the last
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call to this function, it will return None.
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"""
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def _count_messages(txn):
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sql = """
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SELECT COALESCE(COUNT(*), 0) FROM events
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WHERE type = 'm.room.encrypted'
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AND stream_ordering > ?
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"""
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txn.execute(sql, (self.stream_ordering_day_ago,))
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(count,) = txn.fetchone()
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return count
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return await self.db_pool.runInteraction("count_e2ee_messages", _count_messages)
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async def count_daily_sent_e2ee_messages(self):
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def _count_messages(txn):
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# This is good enough as if you have silly characters in your own
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# hostname then that's your own fault.
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like_clause = "%:" + self.hs.hostname
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sql = """
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SELECT COALESCE(COUNT(*), 0) FROM events
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WHERE type = 'm.room.encrypted'
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AND sender LIKE ?
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AND stream_ordering > ?
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"""
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txn.execute(sql, (like_clause, self.stream_ordering_day_ago))
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(count,) = txn.fetchone()
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return count
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return await self.db_pool.runInteraction(
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"count_daily_sent_e2ee_messages", _count_messages
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)
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async def count_daily_active_e2ee_rooms(self):
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def _count(txn):
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sql = """
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SELECT COALESCE(COUNT(DISTINCT room_id), 0) FROM events
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WHERE type = 'm.room.encrypted'
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AND stream_ordering > ?
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"""
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txn.execute(sql, (self.stream_ordering_day_ago,))
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(count,) = txn.fetchone()
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return count
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return await self.db_pool.runInteraction(
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"count_daily_active_e2ee_rooms", _count
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)
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async def count_daily_messages(self):
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"""
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Returns an estimate of the number of messages sent in the last day.
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If it has been significantly less or more than one day since the last
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call to this function, it will return None.
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"""
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def _count_messages(txn):
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sql = """
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SELECT COALESCE(COUNT(*), 0) FROM events
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WHERE type = 'm.room.message'
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AND stream_ordering > ?
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"""
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txn.execute(sql, (self.stream_ordering_day_ago,))
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(count,) = txn.fetchone()
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return count
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return await self.db_pool.runInteraction("count_messages", _count_messages)
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async def count_daily_sent_messages(self):
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def _count_messages(txn):
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# This is good enough as if you have silly characters in your own
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# hostname then that's your own fault.
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like_clause = "%:" + self.hs.hostname
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sql = """
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SELECT COALESCE(COUNT(*), 0) FROM events
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WHERE type = 'm.room.message'
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AND sender LIKE ?
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AND stream_ordering > ?
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"""
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txn.execute(sql, (like_clause, self.stream_ordering_day_ago))
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(count,) = txn.fetchone()
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return count
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return await self.db_pool.runInteraction(
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"count_daily_sent_messages", _count_messages
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)
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async def count_daily_active_rooms(self):
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def _count(txn):
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sql = """
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SELECT COALESCE(COUNT(DISTINCT room_id), 0) FROM events
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WHERE type = 'm.room.message'
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AND stream_ordering > ?
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"""
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txn.execute(sql, (self.stream_ordering_day_ago,))
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(count,) = txn.fetchone()
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return count
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return await self.db_pool.runInteraction("count_daily_active_rooms", _count)
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async def count_daily_users(self) -> int:
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"""
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Counts the number of users who used this homeserver in the last 24 hours.
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"""
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yesterday = int(self._clock.time_msec()) - (1000 * 60 * 60 * 24)
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return await self.db_pool.runInteraction(
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"count_daily_users", self._count_users, yesterday
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)
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async def count_monthly_users(self) -> int:
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"""
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Counts the number of users who used this homeserver in the last 30 days.
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Note this method is intended for phonehome metrics only and is different
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from the mau figure in synapse.storage.monthly_active_users which,
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amongst other things, includes a 3 day grace period before a user counts.
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"""
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thirty_days_ago = int(self._clock.time_msec()) - (1000 * 60 * 60 * 24 * 30)
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return await self.db_pool.runInteraction(
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"count_monthly_users", self._count_users, thirty_days_ago
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)
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def _count_users(self, txn, time_from):
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"""
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Returns number of users seen in the past time_from period
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"""
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sql = """
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SELECT COALESCE(count(*), 0) FROM (
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SELECT user_id FROM user_ips
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WHERE last_seen > ?
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GROUP BY user_id
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) u
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"""
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txn.execute(sql, (time_from,))
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(count,) = txn.fetchone()
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return count
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async def count_r30_users(self) -> Dict[str, int]:
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"""
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Counts the number of 30 day retained users, defined as:-
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* Users who have created their accounts more than 30 days ago
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* Where last seen at most 30 days ago
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* Where account creation and last_seen are > 30 days apart
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Returns:
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A mapping of counts globally as well as broken out by platform.
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"""
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def _count_r30_users(txn):
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thirty_days_in_secs = 86400 * 30
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now = int(self._clock.time())
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thirty_days_ago_in_secs = now - thirty_days_in_secs
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sql = """
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SELECT platform, COALESCE(count(*), 0) FROM (
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SELECT
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users.name, platform, users.creation_ts * 1000,
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MAX(uip.last_seen)
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FROM users
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INNER JOIN (
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SELECT
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user_id,
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last_seen,
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CASE
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WHEN user_agent LIKE '%%Android%%' THEN 'android'
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WHEN user_agent LIKE '%%iOS%%' THEN 'ios'
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WHEN user_agent LIKE '%%Electron%%' THEN 'electron'
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WHEN user_agent LIKE '%%Mozilla%%' THEN 'web'
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WHEN user_agent LIKE '%%Gecko%%' THEN 'web'
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ELSE 'unknown'
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END
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AS platform
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FROM user_ips
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) uip
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ON users.name = uip.user_id
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AND users.appservice_id is NULL
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AND users.creation_ts < ?
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AND uip.last_seen/1000 > ?
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AND (uip.last_seen/1000) - users.creation_ts > 86400 * 30
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GROUP BY users.name, platform, users.creation_ts
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) u GROUP BY platform
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"""
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results = {}
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txn.execute(sql, (thirty_days_ago_in_secs, thirty_days_ago_in_secs))
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for row in txn:
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if row[0] == "unknown":
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pass
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results[row[0]] = row[1]
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sql = """
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SELECT COALESCE(count(*), 0) FROM (
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SELECT users.name, users.creation_ts * 1000,
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MAX(uip.last_seen)
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FROM users
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INNER JOIN (
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SELECT
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user_id,
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last_seen
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FROM user_ips
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) uip
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ON users.name = uip.user_id
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AND appservice_id is NULL
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AND users.creation_ts < ?
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AND uip.last_seen/1000 > ?
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AND (uip.last_seen/1000) - users.creation_ts > 86400 * 30
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GROUP BY users.name, users.creation_ts
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) u
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"""
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txn.execute(sql, (thirty_days_ago_in_secs, thirty_days_ago_in_secs))
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(count,) = txn.fetchone()
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results["all"] = count
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return results
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return await self.db_pool.runInteraction("count_r30_users", _count_r30_users)
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async def count_r30v2_users(self) -> Dict[str, int]:
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"""
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Counts the number of 30 day retained users, defined as users that:
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- Appear more than once in the past 60 days
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- Have more than 30 days between the most and least recent appearances that
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occurred in the past 60 days.
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(This is the second version of this metric, hence R30'v2')
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Returns:
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A mapping from client type to the number of 30-day retained users for that client.
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The dict keys are:
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- "all" (a combined number of users across any and all clients)
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- "android" (Element Android)
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- "ios" (Element iOS)
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- "electron" (Element Desktop)
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- "web" (any web application -- it's not possible to distinguish Element Web here)
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"""
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def _count_r30v2_users(txn):
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thirty_days_in_secs = 86400 * 30
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now = int(self._clock.time())
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sixty_days_ago_in_secs = now - 2 * thirty_days_in_secs
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one_day_from_now_in_secs = now + 86400
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# This is the 'per-platform' count.
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sql = """
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SELECT
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client_type,
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count(client_type)
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FROM
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(
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SELECT
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user_id,
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CASE
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WHEN
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LOWER(user_agent) LIKE '%%riot%%' OR
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LOWER(user_agent) LIKE '%%element%%'
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THEN CASE
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WHEN
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LOWER(user_agent) LIKE '%%electron%%'
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THEN 'electron'
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WHEN
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LOWER(user_agent) LIKE '%%android%%'
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THEN 'android'
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WHEN
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LOWER(user_agent) LIKE '%%ios%%'
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THEN 'ios'
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ELSE 'unknown'
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END
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WHEN
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LOWER(user_agent) LIKE '%%mozilla%%' OR
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LOWER(user_agent) LIKE '%%gecko%%'
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THEN 'web'
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ELSE 'unknown'
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END as client_type
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FROM
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user_daily_visits
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WHERE
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timestamp > ?
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AND
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timestamp < ?
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GROUP BY
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user_id,
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client_type
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HAVING
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max(timestamp) - min(timestamp) > ?
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) AS temp
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GROUP BY
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client_type
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;
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"""
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# We initialise all the client types to zero, so we get an explicit
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# zero if they don't appear in the query results
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results = {"ios": 0, "android": 0, "web": 0, "electron": 0}
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txn.execute(
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sql,
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(
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sixty_days_ago_in_secs * 1000,
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one_day_from_now_in_secs * 1000,
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thirty_days_in_secs * 1000,
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),
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)
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for row in txn:
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if row[0] == "unknown":
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continue
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results[row[0]] = row[1]
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# This is the 'all users' count.
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sql = """
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SELECT COUNT(*) FROM (
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SELECT
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1
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FROM
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user_daily_visits
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WHERE
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timestamp > ?
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AND
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timestamp < ?
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GROUP BY
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user_id
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HAVING
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max(timestamp) - min(timestamp) > ?
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) AS r30_users
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"""
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txn.execute(
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sql,
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(
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sixty_days_ago_in_secs * 1000,
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one_day_from_now_in_secs * 1000,
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thirty_days_in_secs * 1000,
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),
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)
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row = txn.fetchone()
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if row is None:
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results["all"] = 0
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else:
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results["all"] = row[0]
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return results
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return await self.db_pool.runInteraction(
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"count_r30v2_users", _count_r30v2_users
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)
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def _get_start_of_day(self):
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"""
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Returns millisecond unixtime for start of UTC day.
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"""
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now = time.gmtime(self._clock.time())
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today_start = calendar.timegm((now.tm_year, now.tm_mon, now.tm_mday, 0, 0, 0))
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return today_start * 1000
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@wrap_as_background_process("generate_user_daily_visits")
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async def generate_user_daily_visits(self) -> None:
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"""
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Generates daily visit data for use in cohort/ retention analysis
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"""
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def _generate_user_daily_visits(txn):
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logger.info("Calling _generate_user_daily_visits")
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today_start = self._get_start_of_day()
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a_day_in_milliseconds = 24 * 60 * 60 * 1000
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now = self._clock.time_msec()
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# A note on user_agent. Technically a given device can have multiple
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# user agents, so we need to decide which one to pick. We could have
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# handled this in number of ways, but given that we don't care
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# _that_ much we have gone for MAX(). For more details of the other
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# options considered see
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# https://github.com/matrix-org/synapse/pull/8503#discussion_r502306111
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sql = """
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INSERT INTO user_daily_visits (user_id, device_id, timestamp, user_agent)
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SELECT u.user_id, u.device_id, ?, MAX(u.user_agent)
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FROM user_ips AS u
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LEFT JOIN (
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SELECT user_id, device_id, timestamp FROM user_daily_visits
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WHERE timestamp = ?
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) udv
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ON u.user_id = udv.user_id AND u.device_id=udv.device_id
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INNER JOIN users ON users.name=u.user_id
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WHERE ? <= last_seen AND last_seen < ?
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AND udv.timestamp IS NULL AND users.is_guest=0
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AND users.appservice_id IS NULL
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GROUP BY u.user_id, u.device_id
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"""
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# This means that the day has rolled over but there could still
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# be entries from the previous day. There is an edge case
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# where if the user logs in at 23:59 and overwrites their
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# last_seen at 00:01 then they will not be counted in the
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# previous day's stats - it is important that the query is run
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# often to minimise this case.
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if today_start > self._last_user_visit_update:
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yesterday_start = today_start - a_day_in_milliseconds
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txn.execute(
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sql,
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(
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yesterday_start,
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yesterday_start,
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self._last_user_visit_update,
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today_start,
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),
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)
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self._last_user_visit_update = today_start
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txn.execute(
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sql, (today_start, today_start, self._last_user_visit_update, now)
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)
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# Update _last_user_visit_update to now. The reason to do this
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# rather just clamping to the beginning of the day is to limit
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# the size of the join - meaning that the query can be run more
|
|
# frequently
|
|
self._last_user_visit_update = now
|
|
|
|
await self.db_pool.runInteraction(
|
|
"generate_user_daily_visits", _generate_user_daily_visits
|
|
)
|