path: root/synapse/storage/client_ips.py

# -*- coding: utf-8 -*-
# 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 six import iteritems

from twisted.internet import defer

from synapse.metrics.background_process_metrics import run_as_background_process
from synapse.util.caches import CACHE_SIZE_FACTOR

from . import background_updates
from ._base import Cache

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 ClientIpStore(background_updates.BackgroundUpdateStore):
    def __init__(self, db_conn, hs):

        self.client_ip_last_seen = Cache(
            name="client_ip_last_seen", keylen=4, max_entries=50000 * CACHE_SIZE_FACTOR
        )

        super(ClientIpStore, self).__init__(db_conn, hs)

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

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

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

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

        # Register a unique index
        self.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.register_background_update_handler(
            "user_ips_drop_nonunique_index", self._remove_user_ip_nonunique
        )

        # (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
        )

    @defer.inlineCallbacks
    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()

        yield self.runWithConnection(f)
        yield self._end_background_update("user_ips_drop_nonunique_index")
        defer.returnValue(1)

    @defer.inlineCallbacks
    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")

        yield self.runInteraction("user_ips_analyze", user_ips_analyze)

        yield self._end_background_update("user_ips_analyze")

        defer.returnValue(1)

    @defer.inlineCallbacks
    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 = yield self.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._background_update_progress_txn(
                txn, "user_ips_remove_dupes", {"last_seen": end_last_seen}
            )

        yield self.runInteraction("user_ips_dups_remove", remove)

        if last:
            yield self._end_background_update("user_ips_remove_dupes")

        defer.returnValue(batch_size)

    @defer.inlineCallbacks
    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
        yield 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.prefill(key, now)

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

    def _update_client_ips_batch(self):

        # If the DB pool has already terminated, don't try updating
        if not self.hs.get_db_pool().running:
            return

        def update():
            to_update = self._batch_row_update
            self._batch_row_update = {}
            return self.runInteraction(
                "_update_client_ips_batch", self._update_client_ips_batch_txn, to_update
            )

        return run_as_background_process("update_client_ips", update)

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

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

            try:
                self._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,
                )
            except Exception as e:
                # Failed to upsert, log and continue
                logger.error("Failed to insert client IP %r: %r", entry, e)

    @defer.inlineCallbacks
    def get_last_client_ip_by_device(self, user_id, device_id):
        """For each device_id listed, give the user_ip it was last seen on

        Args:
            user_id (str)
            device_id (str): If None fetches all devices for the user

        Returns:
            defer.Deferred: resolves to a dict, where the keys
            are (user_id, device_id) tuples. The values are also dicts, with
            keys giving the column names
        """

        res = yield self.runInteraction(
            "get_last_client_ip_by_device",
            self._get_last_client_ip_by_device_txn,
            user_id,
            device_id,
            retcols=(
                "user_id",
                "access_token",
                "ip",
                "user_agent",
                "device_id",
                "last_seen",
            ),
        )

        ret = {(d["user_id"], d["device_id"]): d for d in res}
        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,
                    }
        defer.returnValue(ret)

    @classmethod
    def _get_last_client_ip_by_device_txn(cls, txn, user_id, device_id, retcols):
        where_clauses = []
        bindings = []
        if device_id is None:
            where_clauses.append("user_id = ?")
            bindings.extend((user_id,))
        else:
            where_clauses.append("(user_id = ? AND device_id = ?)")
            bindings.extend((user_id, device_id))

        if not where_clauses:
            return []

        inner_select = (
            "SELECT MAX(last_seen) mls, user_id, device_id FROM user_ips "
            "WHERE %(where)s "
            "GROUP BY user_id, device_id"
        ) % {"where": " OR ".join(where_clauses)}

        sql = (
            "SELECT %(retcols)s FROM user_ips "
            "JOIN (%(inner_select)s) ips ON"
            "    user_ips.last_seen = ips.mls AND"
            "    user_ips.user_id = ips.user_id AND"
            "    (user_ips.device_id = ips.device_id OR"
            "         (user_ips.device_id IS NULL AND ips.device_id IS NULL)"
            "    )"
        ) % {
            "retcols": ",".join("user_ips." + c for c in retcols),
            "inner_select": inner_select,
        }

        txn.execute(sql, bindings)
        return cls.cursor_to_dict(txn)

    @defer.inlineCallbacks
    def get_user_ip_and_agents(self, user):
        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 = yield self._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
        )
        defer.returnValue(
            list(
                {
                    "access_token": access_token,
                    "ip": ip,
                    "user_agent": user_agent,
                    "last_seen": last_seen,
                }
                for (access_token, ip), (user_agent, last_seen) in iteritems(results)
            )
        )