path: root/synapse/storage/databases/main/client_ips.py

# Copyright 2016 OpenMarket Ltd
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

import logging
from typing import Dict, List, Optional, Tuple, Union

from synapse.metrics.background_process_metrics import wrap_as_background_process
from synapse.storage._base import SQLBaseStore
from synapse.storage.database import DatabasePool, make_tuple_comparison_clause
from synapse.types import UserID
from synapse.util.caches.lrucache import LruCache

logger = logging.getLogger(__name__)

# Number of msec of granularity to store the user IP 'last seen' time. Smaller
# times give more inserts into the database even for readonly API hits
# 120 seconds == 2 minutes
LAST_SEEN_GRANULARITY = 120 * 1000


class ClientIpBackgroundUpdateStore(SQLBaseStore):
    def __init__(self, database: DatabasePool, db_conn, hs):
        super().__init__(database, db_conn, hs)

        self.db_pool.updates.register_background_index_update(
            "user_ips_device_index",
            index_name="user_ips_device_id",
            table="user_ips",
            columns=["user_id", "device_id", "last_seen"],
        )

        self.db_pool.updates.register_background_index_update(
            "user_ips_last_seen_index",
            index_name="user_ips_last_seen",
            table="user_ips",
            columns=["user_id", "last_seen"],
        )

        self.db_pool.updates.register_background_index_update(
            "user_ips_last_seen_only_index",
            index_name="user_ips_last_seen_only",
            table="user_ips",
            columns=["last_seen"],
        )

        self.db_pool.updates.register_background_update_handler(
            "user_ips_analyze", self._analyze_user_ip
        )

        self.db_pool.updates.register_background_update_handler(
            "user_ips_remove_dupes", self._remove_user_ip_dupes
        )

        # Register a unique index
        self.db_pool.updates.register_background_index_update(
            "user_ips_device_unique_index",
            index_name="user_ips_user_token_ip_unique_index",
            table="user_ips",
            columns=["user_id", "access_token", "ip"],
            unique=True,
        )

        # Drop the old non-unique index
        self.db_pool.updates.register_background_update_handler(
            "user_ips_drop_nonunique_index", self._remove_user_ip_nonunique
        )

        # Update the last seen info in devices.
        self.db_pool.updates.register_background_update_handler(
            "devices_last_seen", self._devices_last_seen_update
        )

    async def _remove_user_ip_nonunique(self, progress, batch_size):
        def f(conn):
            txn = conn.cursor()
            txn.execute("DROP INDEX IF EXISTS user_ips_user_ip")
            txn.close()

        await self.db_pool.runWithConnection(f)
        await self.db_pool.updates._end_background_update(
            "user_ips_drop_nonunique_index"
        )
        return 1

    async def _analyze_user_ip(self, progress, batch_size):
        # Background update to analyze user_ips table before we run the
        # deduplication background update. The table may not have been analyzed
        # for ages due to the table locks.
        #
        # This will lock out the naive upserts to user_ips while it happens, but
        # the analyze should be quick (28GB table takes ~10s)
        def user_ips_analyze(txn):
            txn.execute("ANALYZE user_ips")

        await self.db_pool.runInteraction("user_ips_analyze", user_ips_analyze)

        await self.db_pool.updates._end_background_update("user_ips_analyze")

        return 1

    async def _remove_user_ip_dupes(self, progress, batch_size):
        # This works function works by scanning the user_ips table in batches
        # based on `last_seen`. For each row in a batch it searches the rest of
        # the table to see if there are any duplicates, if there are then they
        # are removed and replaced with a suitable row.

        # Fetch the start of the batch
        begin_last_seen = progress.get("last_seen", 0)

        def get_last_seen(txn):
            txn.execute(
                """
                SELECT last_seen FROM user_ips
                WHERE last_seen > ?
                ORDER BY last_seen
                LIMIT 1
                OFFSET ?
                """,
                (begin_last_seen, batch_size),
            )
            row = txn.fetchone()
            if row:
                return row[0]
            else:
                return None

        # Get a last seen that has roughly `batch_size` since `begin_last_seen`
        end_last_seen = await self.db_pool.runInteraction(
            "user_ips_dups_get_last_seen", get_last_seen
        )

        # If it returns None, then we're processing the last batch
        last = end_last_seen is None

        logger.info(
            "Scanning for duplicate 'user_ips' rows in range: %s <= last_seen < %s",
            begin_last_seen,
            end_last_seen,
        )

        def remove(txn):
            # This works by looking at all entries in the given time span, and
            # then for each (user_id, access_token, ip) tuple in that range
            # checking for any duplicates in the rest of the table (via a join).
            # It then only returns entries which have duplicates, and the max
            # last_seen across all duplicates, which can the be used to delete
            # all other duplicates.
            # It is efficient due to the existence of (user_id, access_token,
            # ip) and (last_seen) indices.

            # Define the search space, which requires handling the last batch in
            # a different way
            if last:
                clause = "? <= last_seen"
                args = (begin_last_seen,)
            else:
                clause = "? <= last_seen AND last_seen < ?"
                args = (begin_last_seen, end_last_seen)

            # (Note: The DISTINCT in the inner query is important to ensure that
            # the COUNT(*) is accurate, otherwise double counting may happen due
            # to the join effectively being a cross product)
            txn.execute(
                """
                SELECT user_id, access_token, ip,
                       MAX(device_id), MAX(user_agent), MAX(last_seen),
                       COUNT(*)
                FROM (
                    SELECT DISTINCT user_id, access_token, ip
                    FROM user_ips
                    WHERE {}
                ) c
                INNER JOIN user_ips USING (user_id, access_token, ip)
                GROUP BY user_id, access_token, ip
                HAVING count(*) > 1
                """.format(
                    clause
                ),
                args,
            )
            res = txn.fetchall()

            # We've got some duplicates
            for i in res:
                user_id, access_token, ip, device_id, user_agent, last_seen, count = i

                # We want to delete the duplicates so we end up with only a
                # single row.
                #
                # The naive way of doing this would be just to delete all rows
                # and reinsert a constructed row. However, if there are a lot of
                # duplicate rows this can cause the table to grow a lot, which
                # can be problematic in two ways:
                #   1. If user_ips is already large then this can cause the
                #      table to rapidly grow, potentially filling the disk.
                #   2. Reinserting a lot of rows can confuse the table
                #      statistics for postgres, causing it to not use the
                #      correct indices for the query above, resulting in a full
                #      table scan. This is incredibly slow for large tables and
                #      can kill database performance. (This seems to mainly
                #      happen for the last query where the clause is simply `? <
                #      last_seen`)
                #
                # So instead we want to delete all but *one* of the duplicate
                # rows. That is hard to do reliably, so we cheat and do a two
                # step process:
                #   1. Delete all rows with a last_seen strictly less than the
                #      max last_seen. This hopefully results in deleting all but
                #      one row the majority of the time, but there may be
                #      duplicate last_seen
                #   2. If multiple rows remain, we fall back to the naive method
                #      and simply delete all rows and reinsert.
                #
                # Note that this relies on no new duplicate rows being inserted,
                # but if that is happening then this entire process is futile
                # anyway.

                # Do step 1:

                txn.execute(
                    """
                    DELETE FROM user_ips
                    WHERE user_id = ? AND access_token = ? AND ip = ? AND last_seen < ?
                    """,
                    (user_id, access_token, ip, last_seen),
                )
                if txn.rowcount == count - 1:
                    # We deleted all but one of the duplicate rows, i.e. there
                    # is exactly one remaining and so there is nothing left to
                    # do.
                    continue
                elif txn.rowcount >= count:
                    raise Exception(
                        "We deleted more duplicate rows from 'user_ips' than expected"
                    )

                # The previous step didn't delete enough rows, so we fallback to
                # step 2:

                # Drop all the duplicates
                txn.execute(
                    """
                    DELETE FROM user_ips
                    WHERE user_id = ? AND access_token = ? AND ip = ?
                    """,
                    (user_id, access_token, ip),
                )

                # Add in one to be the last_seen
                txn.execute(
                    """
                    INSERT INTO user_ips
                    (user_id, access_token, ip, device_id, user_agent, last_seen)
                    VALUES (?, ?, ?, ?, ?, ?)
                    """,
                    (user_id, access_token, ip, device_id, user_agent, last_seen),
                )

            self.db_pool.updates._background_update_progress_txn(
                txn, "user_ips_remove_dupes", {"last_seen": end_last_seen}
            )

        await self.db_pool.runInteraction("user_ips_dups_remove", remove)

        if last:
            await self.db_pool.updates._end_background_update("user_ips_remove_dupes")

        return batch_size

    async def _devices_last_seen_update(self, progress, batch_size):
        """Background update to insert last seen info into devices table"""

        last_user_id = progress.get("last_user_id", "")
        last_device_id = progress.get("last_device_id", "")

        def _devices_last_seen_update_txn(txn):
            # This consists of two queries:
            #
            #   1. The sub-query searches for the next N devices and joins
            #      against user_ips to find the max last_seen associated with
            #      that device.
            #   2. The outer query then joins again against user_ips on
            #      user/device/last_seen. This *should* hopefully only
            #      return one row, but if it does return more than one then
            #      we'll just end up updating the same device row multiple
            #      times, which is fine.

            where_clause, where_args = make_tuple_comparison_clause(
                [("user_id", last_user_id), ("device_id", last_device_id)],
            )

            sql = """
                SELECT
                    last_seen, ip, user_agent, user_id, device_id
                FROM (
                    SELECT
                        user_id, device_id, MAX(u.last_seen) AS last_seen
                    FROM devices
                    INNER JOIN user_ips AS u USING (user_id, device_id)
                    WHERE %(where_clause)s
                    GROUP BY user_id, device_id
                    ORDER BY user_id ASC, device_id ASC
                    LIMIT ?
                ) c
                INNER JOIN user_ips AS u USING (user_id, device_id, last_seen)
            """ % {
                "where_clause": where_clause
            }
            txn.execute(sql, where_args + [batch_size])

            rows = txn.fetchall()
            if not rows:
                return 0

            sql = """
                UPDATE devices
                SET last_seen = ?, ip = ?, user_agent = ?
                WHERE user_id = ? AND device_id = ?
            """
            txn.execute_batch(sql, rows)

            _, _, _, user_id, device_id = rows[-1]
            self.db_pool.updates._background_update_progress_txn(
                txn,
                "devices_last_seen",
                {"last_user_id": user_id, "last_device_id": device_id},
            )

            return len(rows)

        updated = await self.db_pool.runInteraction(
            "_devices_last_seen_update", _devices_last_seen_update_txn
        )

        if not updated:
            await self.db_pool.updates._end_background_update("devices_last_seen")

        return updated


class ClientIpWorkerStore(ClientIpBackgroundUpdateStore):
    def __init__(self, database: DatabasePool, db_conn, hs):
        super().__init__(database, db_conn, hs)

        self.user_ips_max_age = hs.config.user_ips_max_age

        if hs.config.run_background_tasks and self.user_ips_max_age:
            self._clock.looping_call(self._prune_old_user_ips, 5 * 1000)

    @wrap_as_background_process("prune_old_user_ips")
    async def _prune_old_user_ips(self):
        """Removes entries in user IPs older than the configured period."""

        if self.user_ips_max_age is None:
            # Nothing to do
            return

        if not await self.db_pool.updates.has_completed_background_update(
            "devices_last_seen"
        ):
            # Only start pruning if we have finished populating the devices
            # last seen info.
            return

        # We do a slightly funky SQL delete to ensure we don't try and delete
        # too much at once (as the table may be very large from before we
        # started pruning).
        #
        # This works by finding the max last_seen that is less than the given
        # time, but has no more than N rows before it, deleting all rows with
        # a lesser last_seen time. (We COALESCE so that the sub-SELECT always
        # returns exactly one row).
        sql = """
            DELETE FROM user_ips
            WHERE last_seen <= (
                SELECT COALESCE(MAX(last_seen), -1)
                FROM (
                    SELECT last_seen FROM user_ips
                    WHERE last_seen <= ?
                    ORDER BY last_seen ASC
                    LIMIT 5000
                ) AS u
            )
        """

        timestamp = self.clock.time_msec() - self.user_ips_max_age

        def _prune_old_user_ips_txn(txn):
            txn.execute(sql, (timestamp,))

        await self.db_pool.runInteraction(
            "_prune_old_user_ips", _prune_old_user_ips_txn
        )

    async def get_last_client_ip_by_device(
        self, user_id: str, device_id: Optional[str]
    ) -> Dict[Tuple[str, str], dict]:
        """For each device_id listed, give the user_ip it was last seen on.

        The result might be slightly out of date as client IPs are inserted in batches.

        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 dicts, with
            keys giving the column names from the devices table.
        """

        keyvalues = {"user_id": user_id}
        if device_id is not None:
            keyvalues["device_id"] = device_id

        res = await self.db_pool.simple_select_list(
            table="devices",
            keyvalues=keyvalues,
            retcols=("user_id", "ip", "user_agent", "device_id", "last_seen"),
        )

        return {(d["user_id"], d["device_id"]): d for d in res}


class ClientIpStore(ClientIpWorkerStore):
    def __init__(self, database: DatabasePool, db_conn, hs):

        self.client_ip_last_seen = LruCache(
            cache_name="client_ip_last_seen", keylen=4, max_size=50000
        )

        super().__init__(database, db_conn, hs)

        # (user_id, access_token, ip,) -> (user_agent, device_id, last_seen)
        self._batch_row_update = {}

        self._client_ip_looper = self._clock.looping_call(
            self._update_client_ips_batch, 5 * 1000
        )
        self.hs.get_reactor().addSystemEventTrigger(
            "before", "shutdown", self._update_client_ips_batch
        )

    async def insert_client_ip(
        self, user_id, access_token, ip, user_agent, device_id, now=None
    ):
        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
        await self.populate_monthly_active_users(user_id)
        # 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)

        self._batch_row_update[key] = (user_agent, device_id, now)

    @wrap_as_background_process("update_client_ips")
    async def _update_client_ips_batch(self) -> None:

        # 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 = {}

        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, to_update):
        if "user_ips" in self.db_pool._unsafe_to_upsert_tables or (
            not self.database_engine.can_native_upsert
        ):
            self.database_engine.lock_table(txn, "user_ips")

        for entry in to_update.items():
            (user_id, access_token, ip), (user_agent, device_id, last_seen) = entry

            self.db_pool.simple_upsert_txn(
                txn,
                table="user_ips",
                keyvalues={"user_id": user_id, "access_token": access_token, "ip": ip},
                values={
                    "user_agent": user_agent,
                    "device_id": device_id,
                    "last_seen": last_seen,
                },
                lock=False,
            )

            # Technically an access token might not be associated with
            # a device so we need to check.
            if device_id:
                # this is always an update rather than an upsert: the row should
                # already exist, and if it doesn't, that may be because it has been
                # deleted, and we don't want to re-create it.
                self.db_pool.simple_update_txn(
                    txn,
                    table="devices",
                    keyvalues={"user_id": user_id, "device_id": device_id},
                    updatevalues={
                        "user_agent": user_agent,
                        "last_seen": last_seen,
                        "ip": ip,
                    },
                )

    async def get_last_client_ip_by_device(
        self, user_id: str, device_id: Optional[str]
    ) -> Dict[Tuple[str, str], dict]:
        """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 dicts, with
            keys giving the column names from the devices table.
        """
        ret = await super().get_last_client_ip_by_device(user_id, device_id)

        # Update what is retrieved from the database with data which is pending insertion.
        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 not device_id or did == device_id:
                    ret[(user_id, device_id)] = {
                        "user_id": user_id,
                        "access_token": access_token,
                        "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
    ) -> List[Dict[str, Union[str, int]]]:
        user_id = user.to_string()
        results = {}

        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]
                results[(access_token, ip)] = (user_agent, last_seen)

        rows = await self.db_pool.simple_select_list(
            table="user_ips",
            keyvalues={"user_id": user_id},
            retcols=["access_token", "ip", "user_agent", "last_seen"],
            desc="get_user_ip_and_agents",
        )

        results.update(
            ((row["access_token"], row["ip"]), (row["user_agent"], row["last_seen"]))
            for row in rows
        )
        return [
            {
                "access_token": access_token,
                "ip": ip,
                "user_agent": user_agent,
                "last_seen": last_seen,
            }
            for (access_token, ip), (user_agent, last_seen) in results.items()
        ]