805 lines
30 KiB
Python
805 lines
30 KiB
Python
# Copyright 2016 OpenMarket Ltd
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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 typing import TYPE_CHECKING, Dict, List, Mapping, Optional, Tuple, Union, cast
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import attr
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from typing_extensions import TypedDict
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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 (
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DatabasePool,
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LoggingDatabaseConnection,
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LoggingTransaction,
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make_tuple_comparison_clause,
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)
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from synapse.storage.databases.main.monthly_active_users import (
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MonthlyActiveUsersWorkerStore,
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)
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from synapse.types import JsonDict, UserID
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from synapse.util.caches.lrucache import LruCache
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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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# Number of msec of granularity to store the user IP 'last seen' time. Smaller
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# times give more inserts into the database even for readonly API hits
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# 120 seconds == 2 minutes
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LAST_SEEN_GRANULARITY = 120 * 1000
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@attr.s(slots=True, frozen=True, auto_attribs=True)
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class DeviceLastConnectionInfo:
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"""Metadata for the last connection seen for a user and device combination"""
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# These types must match the columns in the `devices` table
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user_id: str
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device_id: str
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ip: Optional[str]
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user_agent: Optional[str]
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last_seen: Optional[int]
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class LastConnectionInfo(TypedDict):
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"""Metadata for the last connection seen for an access token and IP combination"""
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# These types must match the columns in the `user_ips` table
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access_token: str
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ip: str
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user_agent: str
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last_seen: int
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class ClientIpBackgroundUpdateStore(SQLBaseStore):
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def __init__(
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self,
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database: DatabasePool,
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db_conn: LoggingDatabaseConnection,
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hs: "HomeServer",
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):
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super().__init__(database, db_conn, hs)
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self.db_pool.updates.register_background_index_update(
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"user_ips_device_index",
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index_name="user_ips_device_id",
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table="user_ips",
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columns=["user_id", "device_id", "last_seen"],
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)
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self.db_pool.updates.register_background_index_update(
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"user_ips_last_seen_index",
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index_name="user_ips_last_seen",
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table="user_ips",
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columns=["user_id", "last_seen"],
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)
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self.db_pool.updates.register_background_index_update(
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"user_ips_last_seen_only_index",
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index_name="user_ips_last_seen_only",
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table="user_ips",
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columns=["last_seen"],
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)
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self.db_pool.updates.register_background_update_handler(
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"user_ips_analyze", self._analyze_user_ip
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)
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self.db_pool.updates.register_background_update_handler(
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"user_ips_remove_dupes", self._remove_user_ip_dupes
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)
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# Register a unique index
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self.db_pool.updates.register_background_index_update(
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"user_ips_device_unique_index",
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index_name="user_ips_user_token_ip_unique_index",
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table="user_ips",
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columns=["user_id", "access_token", "ip"],
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unique=True,
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)
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# Drop the old non-unique index
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self.db_pool.updates.register_background_update_handler(
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"user_ips_drop_nonunique_index", self._remove_user_ip_nonunique
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)
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# Update the last seen info in devices.
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self.db_pool.updates.register_background_update_handler(
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"devices_last_seen", self._devices_last_seen_update
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)
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async def _remove_user_ip_nonunique(
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self, progress: JsonDict, batch_size: int
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) -> int:
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def f(conn: LoggingDatabaseConnection) -> None:
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txn = conn.cursor()
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txn.execute("DROP INDEX IF EXISTS user_ips_user_ip")
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txn.close()
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await self.db_pool.runWithConnection(f)
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await self.db_pool.updates._end_background_update(
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"user_ips_drop_nonunique_index"
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)
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return 1
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async def _analyze_user_ip(self, progress: JsonDict, batch_size: int) -> int:
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# Background update to analyze user_ips table before we run the
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# deduplication background update. The table may not have been analyzed
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# for ages due to the table locks.
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#
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# This will lock out the naive upserts to user_ips while it happens, but
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# the analyze should be quick (28GB table takes ~10s)
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def user_ips_analyze(txn: LoggingTransaction) -> None:
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txn.execute("ANALYZE user_ips")
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await self.db_pool.runInteraction("user_ips_analyze", user_ips_analyze)
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await self.db_pool.updates._end_background_update("user_ips_analyze")
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return 1
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async def _remove_user_ip_dupes(self, progress: JsonDict, batch_size: int) -> int:
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# This works function works by scanning the user_ips table in batches
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# based on `last_seen`. For each row in a batch it searches the rest of
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# the table to see if there are any duplicates, if there are then they
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# are removed and replaced with a suitable row.
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# Fetch the start of the batch
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begin_last_seen: int = progress.get("last_seen", 0)
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def get_last_seen(txn: LoggingTransaction) -> Optional[int]:
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txn.execute(
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"""
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SELECT last_seen FROM user_ips
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WHERE last_seen > ?
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ORDER BY last_seen
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LIMIT 1
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OFFSET ?
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""",
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(begin_last_seen, batch_size),
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)
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row = cast(Optional[Tuple[int]], txn.fetchone())
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if row:
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return row[0]
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else:
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return None
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# Get a last seen that has roughly `batch_size` since `begin_last_seen`
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end_last_seen = await self.db_pool.runInteraction(
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"user_ips_dups_get_last_seen", get_last_seen
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)
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# If it returns None, then we're processing the last batch
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last = end_last_seen is None
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logger.info(
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"Scanning for duplicate 'user_ips' rows in range: %s <= last_seen < %s",
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begin_last_seen,
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end_last_seen,
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)
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def remove(txn: LoggingTransaction) -> None:
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# This works by looking at all entries in the given time span, and
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# then for each (user_id, access_token, ip) tuple in that range
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# checking for any duplicates in the rest of the table (via a join).
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# It then only returns entries which have duplicates, and the max
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# last_seen across all duplicates, which can the be used to delete
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# all other duplicates.
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# It is efficient due to the existence of (user_id, access_token,
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# ip) and (last_seen) indices.
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# Define the search space, which requires handling the last batch in
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# a different way
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args: Tuple[int, ...]
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if last:
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clause = "? <= last_seen"
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args = (begin_last_seen,)
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else:
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assert end_last_seen is not None
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clause = "? <= last_seen AND last_seen < ?"
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args = (begin_last_seen, end_last_seen)
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# (Note: The DISTINCT in the inner query is important to ensure that
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# the COUNT(*) is accurate, otherwise double counting may happen due
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# to the join effectively being a cross product)
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txn.execute(
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"""
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SELECT user_id, access_token, ip,
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MAX(device_id), MAX(user_agent), MAX(last_seen),
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COUNT(*)
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FROM (
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SELECT DISTINCT user_id, access_token, ip
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FROM user_ips
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WHERE {}
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) c
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INNER JOIN user_ips USING (user_id, access_token, ip)
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GROUP BY user_id, access_token, ip
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HAVING count(*) > 1
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""".format(
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clause
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),
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args,
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)
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res = cast(
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List[Tuple[str, str, str, Optional[str], str, int, int]], txn.fetchall()
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)
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# We've got some duplicates
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for i in res:
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user_id, access_token, ip, device_id, user_agent, last_seen, count = i
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# We want to delete the duplicates so we end up with only a
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# single row.
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#
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# The naive way of doing this would be just to delete all rows
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# and reinsert a constructed row. However, if there are a lot of
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# duplicate rows this can cause the table to grow a lot, which
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# can be problematic in two ways:
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# 1. If user_ips is already large then this can cause the
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# table to rapidly grow, potentially filling the disk.
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# 2. Reinserting a lot of rows can confuse the table
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# statistics for postgres, causing it to not use the
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# correct indices for the query above, resulting in a full
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# table scan. This is incredibly slow for large tables and
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# can kill database performance. (This seems to mainly
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# happen for the last query where the clause is simply `? <
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# last_seen`)
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#
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# So instead we want to delete all but *one* of the duplicate
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# rows. That is hard to do reliably, so we cheat and do a two
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# step process:
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# 1. Delete all rows with a last_seen strictly less than the
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# max last_seen. This hopefully results in deleting all but
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# one row the majority of the time, but there may be
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# duplicate last_seen
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# 2. If multiple rows remain, we fall back to the naive method
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# and simply delete all rows and reinsert.
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#
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# Note that this relies on no new duplicate rows being inserted,
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# but if that is happening then this entire process is futile
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# anyway.
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# Do step 1:
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txn.execute(
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"""
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DELETE FROM user_ips
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WHERE user_id = ? AND access_token = ? AND ip = ? AND last_seen < ?
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""",
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(user_id, access_token, ip, last_seen),
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)
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if txn.rowcount == count - 1:
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# We deleted all but one of the duplicate rows, i.e. there
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# is exactly one remaining and so there is nothing left to
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# do.
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continue
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elif txn.rowcount >= count:
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raise Exception(
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"We deleted more duplicate rows from 'user_ips' than expected"
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)
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# The previous step didn't delete enough rows, so we fallback to
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# step 2:
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# Drop all the duplicates
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txn.execute(
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"""
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DELETE FROM user_ips
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WHERE user_id = ? AND access_token = ? AND ip = ?
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""",
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(user_id, access_token, ip),
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)
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# Add in one to be the last_seen
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txn.execute(
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"""
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INSERT INTO user_ips
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(user_id, access_token, ip, device_id, user_agent, last_seen)
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VALUES (?, ?, ?, ?, ?, ?)
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""",
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(user_id, access_token, ip, device_id, user_agent, last_seen),
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)
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self.db_pool.updates._background_update_progress_txn(
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txn, "user_ips_remove_dupes", {"last_seen": end_last_seen}
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)
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await self.db_pool.runInteraction("user_ips_dups_remove", remove)
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if last:
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await self.db_pool.updates._end_background_update("user_ips_remove_dupes")
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return batch_size
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async def _devices_last_seen_update(
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self, progress: JsonDict, batch_size: int
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) -> int:
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"""Background update to insert last seen info into devices table"""
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last_user_id: str = progress.get("last_user_id", "")
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last_device_id: str = progress.get("last_device_id", "")
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def _devices_last_seen_update_txn(txn: LoggingTransaction) -> int:
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# This consists of two queries:
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#
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# 1. The sub-query searches for the next N devices and joins
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# against user_ips to find the max last_seen associated with
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# that device.
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# 2. The outer query then joins again against user_ips on
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# user/device/last_seen. This *should* hopefully only
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# return one row, but if it does return more than one then
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# we'll just end up updating the same device row multiple
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# times, which is fine.
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where_args: List[Union[str, int]]
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where_clause, where_args = make_tuple_comparison_clause(
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[("user_id", last_user_id), ("device_id", last_device_id)],
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)
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sql = """
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SELECT
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last_seen, ip, user_agent, user_id, device_id
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FROM (
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SELECT
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user_id, device_id, MAX(u.last_seen) AS last_seen
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FROM devices
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INNER JOIN user_ips AS u USING (user_id, device_id)
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WHERE %(where_clause)s
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GROUP BY user_id, device_id
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ORDER BY user_id ASC, device_id ASC
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LIMIT ?
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) c
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INNER JOIN user_ips AS u USING (user_id, device_id, last_seen)
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""" % {
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"where_clause": where_clause
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}
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txn.execute(sql, where_args + [batch_size])
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rows = cast(List[Tuple[int, str, str, str, str]], txn.fetchall())
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if not rows:
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return 0
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sql = """
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UPDATE devices
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SET last_seen = ?, ip = ?, user_agent = ?
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WHERE user_id = ? AND device_id = ?
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"""
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txn.execute_batch(sql, rows)
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_, _, _, user_id, device_id = rows[-1]
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self.db_pool.updates._background_update_progress_txn(
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txn,
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"devices_last_seen",
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{"last_user_id": user_id, "last_device_id": device_id},
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)
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return len(rows)
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updated = await self.db_pool.runInteraction(
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"_devices_last_seen_update", _devices_last_seen_update_txn
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)
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if not updated:
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await self.db_pool.updates._end_background_update("devices_last_seen")
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return updated
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class ClientIpWorkerStore(ClientIpBackgroundUpdateStore, MonthlyActiveUsersWorkerStore):
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def __init__(
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self,
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database: DatabasePool,
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db_conn: LoggingDatabaseConnection,
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hs: "HomeServer",
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):
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super().__init__(database, db_conn, hs)
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if hs.config.redis.redis_enabled:
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# If we're using Redis, we can shift this update process off to
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# the background worker
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self._update_on_this_worker = hs.config.worker.run_background_tasks
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else:
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# If we're NOT using Redis, this must be handled by the master
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self._update_on_this_worker = hs.get_instance_name() == "master"
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self.user_ips_max_age = hs.config.server.user_ips_max_age
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# (user_id, access_token, ip,) -> last_seen
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self.client_ip_last_seen = LruCache[Tuple[str, str, str], int](
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cache_name="client_ip_last_seen", max_size=50000
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)
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if hs.config.worker.run_background_tasks and self.user_ips_max_age:
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self._clock.looping_call(self._prune_old_user_ips, 5 * 1000)
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if self._update_on_this_worker:
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# This is the designated worker that can write to the client IP
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# tables.
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# (user_id, access_token, ip,) -> (user_agent, device_id, last_seen)
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self._batch_row_update: Dict[
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Tuple[str, str, str], Tuple[str, Optional[str], int]
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] = {}
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self._client_ip_looper = self._clock.looping_call(
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self._update_client_ips_batch, 5 * 1000
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)
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self.hs.get_reactor().addSystemEventTrigger(
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"before", "shutdown", self._update_client_ips_batch
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)
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@wrap_as_background_process("prune_old_user_ips")
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async def _prune_old_user_ips(self) -> None:
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"""Removes entries in user IPs older than the configured period."""
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if self.user_ips_max_age is None:
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# Nothing to do
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return
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if not await self.db_pool.updates.has_completed_background_update(
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"devices_last_seen"
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):
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# Only start pruning if we have finished populating the devices
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# last seen info.
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return
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# We do a slightly funky SQL delete to ensure we don't try and delete
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# too much at once (as the table may be very large from before we
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# started pruning).
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#
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# This works by finding the max last_seen that is less than the given
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# time, but has no more than N rows before it, deleting all rows with
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# a lesser last_seen time. (We use an `IN` clause to force postgres to
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# use the index, otherwise it tends to do a seq scan).
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sql = """
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DELETE FROM user_ips
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WHERE last_seen IN (
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SELECT last_seen FROM user_ips
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WHERE last_seen <= ?
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ORDER BY last_seen ASC
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LIMIT 5000
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)
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"""
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timestamp = self._clock.time_msec() - self.user_ips_max_age
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def _prune_old_user_ips_txn(txn: LoggingTransaction) -> None:
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txn.execute(sql, (timestamp,))
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await self.db_pool.runInteraction(
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"_prune_old_user_ips", _prune_old_user_ips_txn
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)
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async def _get_last_client_ip_by_device_from_database(
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self, user_id: str, device_id: Optional[str]
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) -> Dict[Tuple[str, str], DeviceLastConnectionInfo]:
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"""For each device_id listed, give the user_ip it was last seen on.
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The result might be slightly out of date as client IPs are inserted in batches.
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Args:
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user_id: The user to fetch devices for.
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device_id: If None fetches all devices for the user
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Returns:
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A dictionary mapping a tuple of (user_id, device_id) to DeviceLastConnectionInfo.
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"""
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keyvalues = {"user_id": user_id}
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if device_id is not None:
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keyvalues["device_id"] = device_id
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|
|
res = cast(
|
|
List[Tuple[str, Optional[str], Optional[str], str, Optional[int]]],
|
|
await self.db_pool.simple_select_list(
|
|
table="devices",
|
|
keyvalues=keyvalues,
|
|
retcols=("user_id", "ip", "user_agent", "device_id", "last_seen"),
|
|
),
|
|
)
|
|
|
|
return {
|
|
(user_id, device_id): DeviceLastConnectionInfo(
|
|
user_id=user_id,
|
|
device_id=device_id,
|
|
ip=ip,
|
|
user_agent=user_agent,
|
|
last_seen=last_seen,
|
|
)
|
|
for user_id, ip, user_agent, device_id, last_seen in res
|
|
}
|
|
|
|
async def _get_user_ip_and_agents_from_database(
|
|
self, user: UserID, since_ts: int = 0
|
|
) -> List[LastConnectionInfo]:
|
|
"""Fetch the IPs and user agents for a user since the given timestamp.
|
|
|
|
The result might be slightly out of date as client IPs are inserted in batches.
|
|
|
|
Args:
|
|
user: The user for which to fetch IP addresses and user agents.
|
|
since_ts: The timestamp after which to fetch IP addresses and user agents,
|
|
in milliseconds.
|
|
|
|
Returns:
|
|
A list of dictionaries, each containing:
|
|
* `access_token`: The access token used.
|
|
* `ip`: The IP address used.
|
|
* `user_agent`: The last user agent seen for this access token and IP
|
|
address combination.
|
|
* `last_seen`: The timestamp at which this access token and IP address
|
|
combination was last seen, in milliseconds.
|
|
|
|
Only the latest user agent for each access token and IP address combination
|
|
is available.
|
|
"""
|
|
user_id = user.to_string()
|
|
|
|
def get_recent(txn: LoggingTransaction) -> List[Tuple[str, str, str, int]]:
|
|
txn.execute(
|
|
"""
|
|
SELECT access_token, ip, user_agent, last_seen FROM user_ips
|
|
WHERE last_seen >= ? AND user_id = ?
|
|
ORDER BY last_seen
|
|
DESC
|
|
""",
|
|
(since_ts, user_id),
|
|
)
|
|
return cast(List[Tuple[str, str, str, int]], txn.fetchall())
|
|
|
|
rows = await self.db_pool.runInteraction(
|
|
desc="get_user_ip_and_agents", func=get_recent
|
|
)
|
|
|
|
return [
|
|
{
|
|
"access_token": access_token,
|
|
"ip": ip,
|
|
"user_agent": user_agent,
|
|
"last_seen": last_seen,
|
|
}
|
|
for access_token, ip, user_agent, last_seen in rows
|
|
]
|
|
|
|
async def insert_client_ip(
|
|
self,
|
|
user_id: str,
|
|
access_token: str,
|
|
ip: str,
|
|
user_agent: str,
|
|
device_id: Optional[str],
|
|
now: Optional[int] = None,
|
|
) -> None:
|
|
"""Record that `user_id` used `access_token` from this `ip` address.
|
|
|
|
This method does two things.
|
|
|
|
1. It queues up a row to be upserted into the `client_ips` table. These happen
|
|
periodically; see _update_client_ips_batch.
|
|
2. It immediately records this user as having taken action for the purposes of
|
|
MAU tracking.
|
|
|
|
Any DB writes take place on the background tasks worker, falling back to the
|
|
main process. If we're not that worker, this method emits a replication payload
|
|
to run this logic on that worker.
|
|
|
|
Two caveats to note:
|
|
|
|
- We only take action once per LAST_SEEN_GRANULARITY, to avoid spamming the
|
|
DB with writes.
|
|
- Requests using the sliding-sync proxy's user agent are excluded, as its
|
|
requests are not directly driven by end-users. This is a hack and we're not
|
|
very proud of it.
|
|
"""
|
|
# The sync proxy continuously triggers /sync even if the user is not
|
|
# present so should be excluded from user_ips entries.
|
|
if user_agent == "sync-v3-proxy-":
|
|
return
|
|
|
|
if not now:
|
|
now = int(self._clock.time_msec())
|
|
key = (user_id, access_token, ip)
|
|
|
|
try:
|
|
last_seen = self.client_ip_last_seen.get(key)
|
|
except KeyError:
|
|
last_seen = None
|
|
|
|
# Rate-limited inserts
|
|
if last_seen is not None and (now - last_seen) < LAST_SEEN_GRANULARITY:
|
|
return
|
|
|
|
self.client_ip_last_seen.set(key, now)
|
|
|
|
if self._update_on_this_worker:
|
|
await self.populate_monthly_active_users(user_id)
|
|
self._batch_row_update[key] = (user_agent, device_id, now)
|
|
else:
|
|
# We are not the designated writer-worker, so stream over replication
|
|
self.hs.get_replication_command_handler().send_user_ip(
|
|
user_id, access_token, ip, user_agent, device_id, now
|
|
)
|
|
|
|
@wrap_as_background_process("update_client_ips")
|
|
async def _update_client_ips_batch(self) -> None:
|
|
assert (
|
|
self._update_on_this_worker
|
|
), "This worker is not designated to update client IPs"
|
|
|
|
# If the DB pool has already terminated, don't try updating
|
|
if not self.db_pool.is_running():
|
|
return
|
|
|
|
to_update = self._batch_row_update
|
|
self._batch_row_update = {}
|
|
|
|
if to_update:
|
|
await self.db_pool.runInteraction(
|
|
"_update_client_ips_batch", self._update_client_ips_batch_txn, to_update
|
|
)
|
|
|
|
def _update_client_ips_batch_txn(
|
|
self,
|
|
txn: LoggingTransaction,
|
|
to_update: Mapping[Tuple[str, str, str], Tuple[str, Optional[str], int]],
|
|
) -> None:
|
|
assert (
|
|
self._update_on_this_worker
|
|
), "This worker is not designated to update client IPs"
|
|
|
|
# Keys and values for the `user_ips` upsert.
|
|
user_ips_keys = []
|
|
user_ips_values = []
|
|
|
|
# Keys and values for the `devices` update.
|
|
devices_keys = []
|
|
devices_values = []
|
|
|
|
for entry in to_update.items():
|
|
(user_id, access_token, ip), (user_agent, device_id, last_seen) = entry
|
|
user_ips_keys.append((user_id, access_token, ip))
|
|
user_ips_values.append((user_agent, device_id, last_seen))
|
|
|
|
# Technically an access token might not be associated with
|
|
# a device so we need to check.
|
|
if device_id:
|
|
devices_keys.append((user_id, device_id))
|
|
devices_values.append((user_agent, last_seen, ip))
|
|
|
|
self.db_pool.simple_upsert_many_txn(
|
|
txn,
|
|
table="user_ips",
|
|
key_names=("user_id", "access_token", "ip"),
|
|
key_values=user_ips_keys,
|
|
value_names=("user_agent", "device_id", "last_seen"),
|
|
value_values=user_ips_values,
|
|
)
|
|
|
|
if devices_values:
|
|
self.db_pool.simple_update_many_txn(
|
|
txn,
|
|
table="devices",
|
|
key_names=("user_id", "device_id"),
|
|
key_values=devices_keys,
|
|
value_names=("user_agent", "last_seen", "ip"),
|
|
value_values=devices_values,
|
|
)
|
|
|
|
async def get_last_client_ip_by_device(
|
|
self, user_id: str, device_id: Optional[str]
|
|
) -> Dict[Tuple[str, str], DeviceLastConnectionInfo]:
|
|
"""For each device_id listed, give the user_ip it was last seen on
|
|
|
|
Args:
|
|
user_id: The user to fetch devices for.
|
|
device_id: If None fetches all devices for the user
|
|
|
|
Returns:
|
|
A dictionary mapping a tuple of (user_id, device_id) to DeviceLastConnectionInfo.
|
|
"""
|
|
ret = await self._get_last_client_ip_by_device_from_database(user_id, device_id)
|
|
|
|
if not self._update_on_this_worker:
|
|
# Only the writing-worker has additional in-memory data to enhance
|
|
# the result
|
|
return ret
|
|
|
|
# Update what is retrieved from the database with data which is pending
|
|
# insertion, as if it has already been stored in the database.
|
|
for key in self._batch_row_update:
|
|
uid, _access_token, ip = key
|
|
if uid == user_id:
|
|
user_agent, did, last_seen = self._batch_row_update[key]
|
|
|
|
if did is None:
|
|
# These updates don't make it to the `devices` table
|
|
continue
|
|
|
|
if not device_id or did == device_id:
|
|
ret[(user_id, did)] = DeviceLastConnectionInfo(
|
|
user_id=user_id,
|
|
ip=ip,
|
|
user_agent=user_agent,
|
|
device_id=did,
|
|
last_seen=last_seen,
|
|
)
|
|
return ret
|
|
|
|
async def get_user_ip_and_agents(
|
|
self, user: UserID, since_ts: int = 0
|
|
) -> List[LastConnectionInfo]:
|
|
"""Fetch the IPs and user agents for a user since the given timestamp.
|
|
|
|
Args:
|
|
user: The user for which to fetch IP addresses and user agents.
|
|
since_ts: The timestamp after which to fetch IP addresses and user agents,
|
|
in milliseconds.
|
|
|
|
Returns:
|
|
A list of dictionaries, each containing:
|
|
* `access_token`: The access token used.
|
|
* `ip`: The IP address used.
|
|
* `user_agent`: The last user agent seen for this access token and IP
|
|
address combination.
|
|
* `last_seen`: The timestamp at which this access token and IP address
|
|
combination was last seen, in milliseconds.
|
|
|
|
Only the latest user agent for each access token and IP address combination
|
|
is available.
|
|
"""
|
|
rows_from_db = await self._get_user_ip_and_agents_from_database(user, since_ts)
|
|
|
|
if not self._update_on_this_worker:
|
|
# Only the writing-worker has additional in-memory data to enhance
|
|
# the result
|
|
return rows_from_db
|
|
|
|
results: Dict[Tuple[str, str], LastConnectionInfo] = {
|
|
(connection["access_token"], connection["ip"]): connection
|
|
for connection in rows_from_db
|
|
}
|
|
|
|
# Overlay data that is pending insertion on top of the results from the
|
|
# database.
|
|
user_id = user.to_string()
|
|
for key in self._batch_row_update:
|
|
uid, access_token, ip = key
|
|
if uid == user_id:
|
|
user_agent, _, last_seen = self._batch_row_update[key]
|
|
if last_seen >= since_ts:
|
|
results[(access_token, ip)] = {
|
|
"access_token": access_token,
|
|
"ip": ip,
|
|
"user_agent": user_agent,
|
|
"last_seen": last_seen,
|
|
}
|
|
|
|
return list(results.values())
|
|
|
|
async def get_last_seen_for_user_id(self, user_id: str) -> Optional[int]:
|
|
"""Get the last seen timestamp for a user, if we have it."""
|
|
|
|
return await self.db_pool.simple_select_one_onecol(
|
|
table="user_ips",
|
|
keyvalues={"user_id": user_id},
|
|
retcol="MAX(last_seen)",
|
|
allow_none=True,
|
|
desc="get_last_seen_for_user_id",
|
|
)
|