2023-04-26 12:00:11 -04:00
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#
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2023-11-21 15:29:58 -05:00
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# This file is licensed under the Affero General Public License (AGPL) version 3.
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#
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2024-01-23 06:26:48 -05:00
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# Copyright 2023 The Matrix.org Foundation C.I.C.
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2023-11-21 15:29:58 -05:00
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# Copyright (C) 2023 New Vector, Ltd
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#
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# This program is free software: you can redistribute it and/or modify
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# it under the terms of the GNU Affero General Public License as
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# published by the Free Software Foundation, either version 3 of the
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# License, or (at your option) any later version.
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#
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# See the GNU Affero General Public License for more details:
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# <https://www.gnu.org/licenses/agpl-3.0.html>.
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#
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# Originally licensed under the Apache License, Version 2.0:
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# <http://www.apache.org/licenses/LICENSE-2.0>.
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#
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# [This file includes modifications made by New Vector Limited]
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2023-04-26 12:00:11 -04:00
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#
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#
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import logging
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2023-05-16 13:19:46 -04:00
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from typing import TYPE_CHECKING, Collection, Counter, List, Tuple
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2023-04-26 12:00:11 -04:00
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from synapse.api.errors import SynapseError
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from synapse.storage.database import LoggingTransaction
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from synapse.storage.databases import Databases
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from synapse.storage.engines import PostgresEngine
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if TYPE_CHECKING:
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from synapse.server import HomeServer
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logger = logging.getLogger(__name__)
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class StatsController:
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"""High level interface for getting statistics."""
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def __init__(self, hs: "HomeServer", stores: Databases):
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self.stores = stores
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async def get_room_db_size_estimate(self) -> List[Tuple[str, int]]:
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"""Get an estimate of the largest rooms and how much database space they
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use, in bytes.
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Only works against PostgreSQL.
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Note: this uses the postgres statistics so is a very rough estimate.
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"""
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# Note: We look at both tables on the main and state databases.
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if not isinstance(self.stores.main.database_engine, PostgresEngine):
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raise SynapseError(400, "Endpoint requires using PostgreSQL")
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if not isinstance(self.stores.state.database_engine, PostgresEngine):
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raise SynapseError(400, "Endpoint requires using PostgreSQL")
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# For each "large" table, we go through and get the largest rooms
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# and an estimate of how much space they take. We can then sum the
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# results and return the top 10.
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#
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# This isn't the most accurate, but given all of these are estimates
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# anyway its good enough.
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room_estimates: Counter[str] = Counter()
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# Return size of the table on disk, including indexes and TOAST.
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table_sql = """
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SELECT pg_total_relation_size(?)
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"""
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# Get an estimate for the largest rooms and their frequency.
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#
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# Note: the cast here is a hack to cast from `anyarray` to an actual
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# type. This ensures that psycopg2 passes us a back a a Python list.
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column_sql = """
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SELECT
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most_common_vals::TEXT::TEXT[], most_common_freqs::TEXT::NUMERIC[]
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FROM pg_stats
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WHERE tablename = ? and attname = 'room_id'
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"""
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def get_room_db_size_estimate_txn(
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txn: LoggingTransaction,
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tables: Collection[str],
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) -> None:
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for table in tables:
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txn.execute(table_sql, (table,))
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row = txn.fetchone()
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assert row is not None
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(table_size,) = row
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txn.execute(column_sql, (table,))
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row = txn.fetchone()
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assert row is not None
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vals, freqs = row
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for room_id, freq in zip(vals, freqs):
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room_estimates[room_id] += int(freq * table_size)
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await self.stores.main.db_pool.runInteraction(
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"get_room_db_size_estimate_main",
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get_room_db_size_estimate_txn,
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(
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"event_json",
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"events",
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"event_search",
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"event_edges",
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"event_push_actions",
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"stream_ordering_to_exterm",
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),
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)
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await self.stores.state.db_pool.runInteraction(
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"get_room_db_size_estimate_state",
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get_room_db_size_estimate_txn,
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("state_groups_state",),
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)
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return room_estimates.most_common(10)
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