#
# This file is licensed under the Affero General Public License (AGPL) version 3.
#
# Copyright 2014-2016 OpenMarket Ltd
# Copyright (C) 2023 New Vector, Ltd
#
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU Affero General Public License as
# published by the Free Software Foundation, either version 3 of the
# License, or (at your option) any later version.
#
# See the GNU Affero General Public License for more details:
# <https://www.gnu.org/licenses/agpl-3.0.html>.
#
# Originally licensed under the Apache License, Version 2.0:
# <http://www.apache.org/licenses/LICENSE-2.0>.
#
# [This file includes modifications made by New Vector Limited]
#
#
import datetime
import itertools
import logging
from queue import Empty, PriorityQueue
from typing import (
    TYPE_CHECKING,
    Collection,
    Generator,
    Iterable,
    Sequence,
    cast,
)

import attr
from prometheus_client import Counter, Gauge

from synapse.api.constants import MAX_DEPTH
from synapse.api.errors import StoreError
from synapse.api.room_versions import EventFormatVersions, RoomVersion
from synapse.events import EventBase, make_event_from_dict
from synapse.logging.opentracing import tag_args, trace
from synapse.metrics import SERVER_NAME_LABEL
from synapse.metrics.background_process_metrics import wrap_as_background_process
from synapse.storage._base import db_to_json, make_in_list_sql_clause
from synapse.storage.background_updates import ForeignKeyConstraint
from synapse.storage.database import (
    DatabasePool,
    LoggingDatabaseConnection,
    LoggingTransaction,
)
from synapse.storage.databases.main.cache import CacheInvalidationWorkerStore
from synapse.storage.databases.main.events_worker import EventsWorkerStore
from synapse.storage.databases.main.signatures import SignatureWorkerStore
from synapse.storage.engines import PostgresEngine, Sqlite3Engine
from synapse.types import JsonDict, StrCollection
from synapse.util.caches.descriptors import cached
from synapse.util.caches.lrucache import LruCache
from synapse.util.cancellation import cancellable
from synapse.util.duration import Duration
from synapse.util.iterutils import batch_iter
from synapse.util.json import json_encoder

if TYPE_CHECKING:
    from synapse.server import HomeServer

oldest_pdu_in_federation_staging = Gauge(
    "synapse_federation_server_oldest_inbound_pdu_in_staging",
    "The age in seconds since we received the oldest pdu in the federation staging area",
    labelnames=[SERVER_NAME_LABEL],
)

number_pdus_in_federation_queue = Gauge(
    "synapse_federation_server_number_inbound_pdu_in_staging",
    "The total number of events in the inbound federation staging",
    labelnames=[SERVER_NAME_LABEL],
)

pdus_pruned_from_federation_queue = Counter(
    "synapse_federation_server_number_inbound_pdu_pruned",
    "The number of events in the inbound federation staging that have been "
    "pruned due to the queue getting too long",
    labelnames=[SERVER_NAME_LABEL],
)

logger = logging.getLogger(__name__)

# Parameters controlling exponential backoff between backfill failures.
# After the first failure to backfill, we wait 2 hours before trying again. If the
# second attempt fails, we wait 4 hours before trying again. If the third attempt fails,
# we wait 8 hours before trying again, ... and so on.
#
# Each successive backoff period is twice as long as the last. However we cap this
# period at a maximum of 2^8 = 256 hours: a little over 10 days. (This is the smallest
# power of 2 which yields a maximum backoff period of at least 7 days---which was the
# original maximum backoff period.) Even when we hit this cap, we will continue to
# make backfill attempts once every 10 days.
BACKFILL_EVENT_EXPONENTIAL_BACKOFF_MAXIMUM_DOUBLING_STEPS = 8
BACKFILL_EVENT_EXPONENTIAL_BACKOFF_STEP_MILLISECONDS = int(
    datetime.timedelta(hours=1).total_seconds() * 1000
)

# We need a cap on the power of 2 or else the backoff period
#   2^N * (milliseconds per hour)
# will overflow when calcuated within the database. We ensure overflow does not occur
# by checking that the largest backoff period fits in a 32-bit signed integer.
_LONGEST_BACKOFF_PERIOD_MILLISECONDS = (
    2**BACKFILL_EVENT_EXPONENTIAL_BACKOFF_MAXIMUM_DOUBLING_STEPS
) * BACKFILL_EVENT_EXPONENTIAL_BACKOFF_STEP_MILLISECONDS
assert 0 < _LONGEST_BACKOFF_PERIOD_MILLISECONDS <= ((2**31) - 1)


# We use 2^53-1 as a "very large number", it has no particular
# importance other than knowing synapse can support it (given canonical json
# requires it).
MAX_CHAIN_LENGTH = (2**53) - 1


# All the info we need while iterating the DAG while backfilling
@attr.s(frozen=True, slots=True, auto_attribs=True)
class BackfillQueueNavigationItem:
    depth: int
    stream_ordering: int
    event_id: str
    type: str


@attr.s(frozen=True, slots=True, auto_attribs=True)
class StateDifference:
    # The event IDs in the auth difference.
    auth_difference: set[str]
    # The event IDs in the conflicted state subgraph. Used in v2.1 only.
    conflicted_subgraph: set[str] | None


class _NoChainCoverIndex(Exception):
    def __init__(self, room_id: str):
        super().__init__("Unexpectedly no chain cover for events in %s" % (room_id,))


class EventFederationWorkerStore(
    SignatureWorkerStore, EventsWorkerStore, CacheInvalidationWorkerStore
):
    # TODO: this attribute comes from EventPushActionWorkerStore. Should we inherit from
    # that store so that mypy can deduce this for itself?
    stream_ordering_month_ago: int | None

    def __init__(
        self,
        database: DatabasePool,
        db_conn: LoggingDatabaseConnection,
        hs: "HomeServer",
    ):
        super().__init__(database, db_conn, hs)

        self.hs = hs

        if hs.config.worker.run_background_tasks:
            hs.get_clock().looping_call(
                self._delete_old_forward_extrem_cache, Duration(hours=1)
            )

        # Cache of event ID to list of auth event IDs and their depths.
        self._event_auth_cache: LruCache[str, list[tuple[str, int]]] = LruCache(
            max_size=500000,
            clock=self.hs.get_clock(),
            server_name=self.server_name,
            cache_name="_event_auth_cache",
            size_callback=len,
        )

        # Flag used by unit tests to disable fallback when there is no chain cover
        # index.
        self.tests_allow_no_chain_cover_index = True

        self.clock.looping_call(
            self._get_stats_for_federation_staging, Duration(seconds=30)
        )

        if isinstance(self.database_engine, PostgresEngine):
            self.db_pool.updates.register_background_validate_constraint_and_delete_rows(
                update_name="event_forward_extremities_event_id_foreign_key_constraint_update",
                table="event_forward_extremities",
                constraint_name="event_forward_extremities_event_id",
                constraint=ForeignKeyConstraint(
                    "events", [("event_id", "event_id")], deferred=True
                ),
                unique_columns=("event_id", "room_id"),
            )

        self.db_pool.updates.register_background_index_update(
            update_name="event_auth_chain_links_origin_index",
            index_name="event_auth_chain_links_origin_index",
            table="event_auth_chain_links",
            columns=("origin_chain_id", "origin_sequence_number"),
        )

    async def get_auth_chain(
        self, room_id: str, event_ids: Collection[str], include_given: bool = False
    ) -> list[EventBase]:
        """Get auth events for given event_ids. The events *must* be state events.

        Args:
            room_id: The room the event is in.
            event_ids: state events
            include_given: include the given events in result

        Returns:
            list of events
        """
        event_ids = await self.get_auth_chain_ids(
            room_id, event_ids, include_given=include_given
        )
        return await self.get_events_as_list(event_ids)

    @trace
    @tag_args
    async def get_auth_chain_ids(
        self,
        room_id: str,
        event_ids: Collection[str],
        include_given: bool = False,
    ) -> set[str]:
        """Get auth events for given event_ids. The events *must* be state events.

        Args:
            room_id: The room the event is in.
            event_ids: state events
            include_given: include the given events in result

        Returns:
            set of event_ids
        """

        # Check if we have indexed the room so we can use the chain cover
        # algorithm.
        room = await self.get_room(room_id)  # type: ignore[attr-defined]
        # If the room has an auth chain index.
        if room[1]:
            try:
                return await self.db_pool.runInteraction(
                    "get_auth_chain_ids_chains",
                    self._get_auth_chain_ids_using_cover_index_txn,
                    room_id,
                    event_ids,
                    include_given,
                )
            except _NoChainCoverIndex:
                # For whatever reason we don't actually have a chain cover index
                # for the events in question, so we fall back to the old method
                # (except in tests)
                if not self.tests_allow_no_chain_cover_index:
                    raise

        return await self.db_pool.runInteraction(
            "get_auth_chain_ids",
            self._get_auth_chain_ids_txn,
            event_ids,
            include_given,
        )

    def _get_auth_chain_ids_using_cover_index_txn(
        self,
        txn: LoggingTransaction,
        room_id: str,
        event_ids: Collection[str],
        include_given: bool,
    ) -> set[str]:
        """Calculates the auth chain IDs using the chain index."""

        # First we look up the chain ID/sequence numbers for the given events.

        initial_events = set(event_ids)

        # All the events that we've found that are reachable from the events.
        seen_events: set[str] = set()

        # A map from chain ID to max sequence number of the given events.
        event_chains: dict[int, int] = {}

        sql = """
            SELECT event_id, chain_id, sequence_number
            FROM event_auth_chains
            WHERE %s
        """
        for batch in batch_iter(initial_events, 1000):
            clause, args = make_in_list_sql_clause(
                txn.database_engine, "event_id", batch
            )
            txn.execute(sql % (clause,), args)

            for event_id, chain_id, sequence_number in txn:
                seen_events.add(event_id)
                event_chains[chain_id] = max(
                    sequence_number, event_chains.get(chain_id, 0)
                )

        # Check that we actually have a chain ID for all the events.
        events_missing_chain_info = initial_events.difference(seen_events)
        if events_missing_chain_info:
            # This can happen due to e.g. downgrade/upgrade of the server. We
            # raise an exception and fall back to the previous algorithm.
            logger.error(
                "Unexpectedly found that events don't have chain IDs in room %s: %s",
                room_id,
                events_missing_chain_info,
            )
            raise _NoChainCoverIndex(room_id)

        # Now we look up all links for the chains we have, adding chains that
        # are reachable from any event.

        # A map from chain ID to max sequence number *reachable* from any event ID.
        chains: dict[int, int] = {}
        for links in self._get_chain_links(txn, set(event_chains.keys())):
            for chain_id in links:
                if chain_id not in event_chains:
                    continue

                _materialize(chain_id, event_chains[chain_id], links, chains)

        # Add the initial set of chains, excluding the sequence corresponding to
        # initial event.
        for chain_id, seq_no in event_chains.items():
            # Check if the initial event is the first item in the chain. If so, then
            # there is nothing new to add from this chain.
            if seq_no == 1:
                continue

            chains[chain_id] = max(seq_no - 1, chains.get(chain_id, 0))

        # Now for each chain we figure out the maximum sequence number reachable
        # from *any* event ID. Events with a sequence less than that are in the
        # auth chain.
        if include_given:
            results = initial_events
        else:
            results = set()

        if isinstance(self.database_engine, PostgresEngine):
            # We can use `execute_values` to efficiently fetch the gaps when
            # using postgres.
            sql = """
                SELECT event_id
                FROM event_auth_chains AS c, (VALUES ?) AS l(chain_id, max_seq)
                WHERE
                    c.chain_id = l.chain_id
                    AND sequence_number <= max_seq
            """

            rows = txn.execute_values(sql, chains.items())
            results.update(r for (r,) in rows)
        else:
            # For SQLite we just fall back to doing a noddy for loop.
            sql = """
                SELECT event_id FROM event_auth_chains
                WHERE chain_id = ? AND sequence_number <= ?
            """
            for chain_id, max_no in chains.items():
                txn.execute(sql, (chain_id, max_no))
                results.update(r for (r,) in txn)

        return results

    @classmethod
    def _get_chain_links(
        cls, txn: LoggingTransaction, chains_to_fetch: set[int]
    ) -> Generator[dict[int, list[tuple[int, int, int]]], None, None]:
        """Fetch all auth chain links from the given set of chains, and all
        links from those chains, recursively.

        Note: This may return links that are not reachable from the given
        chains.

        Returns a generator that produces dicts from origin chain ID to 3-tuple
        of origin sequence number, target chain ID and target sequence number.
        """

        # This query is structured to first get all chain IDs reachable, and
        # then pull out all links from those chains. This does pull out more
        # rows than is strictly necessary, however there isn't a way of
        # structuring the recursive part of query to pull out the links without
        # also returning large quantities of redundant data (which can make it a
        # lot slower).
        sql = """
            WITH RECURSIVE links(chain_id) AS (
                SELECT
                    DISTINCT origin_chain_id
                FROM event_auth_chain_links WHERE %s
                UNION
                SELECT
                    target_chain_id
                FROM event_auth_chain_links
                INNER JOIN links ON (chain_id = origin_chain_id)
            )
            SELECT
                origin_chain_id, origin_sequence_number,
                target_chain_id, target_sequence_number
            FROM links
            INNER JOIN event_auth_chain_links ON (chain_id = origin_chain_id)
        """

        while chains_to_fetch:
            batch2 = tuple(itertools.islice(chains_to_fetch, 1000))
            chains_to_fetch.difference_update(batch2)
            clause, args = make_in_list_sql_clause(
                txn.database_engine, "origin_chain_id", batch2
            )
            txn.execute(sql % (clause,), args)

            links: dict[int, list[tuple[int, int, int]]] = {}

            for (
                origin_chain_id,
                origin_sequence_number,
                target_chain_id,
                target_sequence_number,
            ) in txn:
                links.setdefault(origin_chain_id, []).append(
                    (origin_sequence_number, target_chain_id, target_sequence_number)
                )

            chains_to_fetch.difference_update(links)

            yield links

    def _get_auth_chain_ids_txn(
        self, txn: LoggingTransaction, event_ids: Collection[str], include_given: bool
    ) -> set[str]:
        """Calculates the auth chain IDs.

        This is used when we don't have a cover index for the room.
        """
        if include_given:
            results = set(event_ids)
        else:
            results = set()

        # We pull out the depth simply so that we can populate the
        # `_event_auth_cache` cache.
        base_sql = """
            SELECT a.event_id, auth_id, depth
            FROM event_auth AS a
            INNER JOIN events AS e ON (e.event_id = a.auth_id)
            WHERE
        """

        front = set(event_ids)
        while front:
            new_front: set[str] = set()
            for chunk in batch_iter(front, 100):
                # Pull the auth events either from the cache or DB.
                to_fetch: list[str] = []  # Event IDs to fetch from DB
                for event_id in chunk:
                    res = self._event_auth_cache.get(event_id)
                    if res is None:
                        to_fetch.append(event_id)
                    else:
                        new_front.update(auth_id for auth_id, depth in res)

                if to_fetch:
                    clause, args = make_in_list_sql_clause(
                        txn.database_engine, "a.event_id", to_fetch
                    )
                    txn.execute(base_sql + clause, args)

                    # Note we need to batch up the results by event ID before
                    # adding to the cache.
                    to_cache: dict[str, list[tuple[str, int]]] = {}
                    for event_id, auth_event_id, auth_event_depth in txn:
                        to_cache.setdefault(event_id, []).append(
                            (auth_event_id, auth_event_depth)
                        )
                        new_front.add(auth_event_id)

                    for event_id, auth_events in to_cache.items():
                        self._event_auth_cache.set(event_id, auth_events)

            new_front -= results

            front = new_front
            results.update(front)

        return results

    async def get_auth_chain_difference(
        self,
        room_id: str,
        state_sets: list[set[str]],
    ) -> set[str]:
        state_diff = await self.get_auth_chain_difference_extended(
            room_id, state_sets, None, None
        )
        return state_diff.auth_difference

    async def get_auth_chain_difference_extended(
        self,
        room_id: str,
        state_sets: list[set[str]],
        conflicted_set: set[str] | None,
        additional_backwards_reachable_conflicted_events: set[str] | None,
    ) -> StateDifference:
        """ "Given sets of state events figure out the auth chain difference (as
        per state res v2 algorithm).

        This is equivalent to fetching the full auth chain for each set of state
        and returning the events that don't appear in each and every auth
        chain.

        If conflicted_set is not None, calculate and return the conflicted sub-graph as per
        state res v2.1. The event IDs in the conflicted set MUST be a subset of the event IDs in
        state_sets.

        If additional_backwards_reachable_conflicted_events is set, the provided events are included
        when calculating the conflicted subgraph. This is primarily useful for calculating the
        subgraph across a combination of persisted and unpersisted events. The event IDs in this set
        MUST be a subset of the event IDs in state_sets.

        Returns:
            information on the auth chain difference, and also the conflicted subgraph if
            conflicted_set is not None
        """

        # Check if we have indexed the room so we can use the chain cover
        # algorithm.
        room = await self.get_room(room_id)  # type: ignore[attr-defined]
        # If the room has an auth chain index.
        if room[1]:
            try:
                return await self.db_pool.runInteraction(
                    "get_auth_chain_difference_chains",
                    self._get_auth_chain_difference_using_cover_index_txn,
                    room_id,
                    state_sets,
                    conflicted_set,
                    additional_backwards_reachable_conflicted_events,
                )
            except _NoChainCoverIndex:
                # For whatever reason we don't actually have a chain cover index
                # for the events in question, so we fall back to the old method
                # (except in tests)
                if not self.tests_allow_no_chain_cover_index:
                    raise

        # It's been 4 years since we added chain cover, so we expect all rooms to have it.
        # If they don't, we will error out when trying to do state res v2.1
        if conflicted_set is not None:
            raise _NoChainCoverIndex(room_id)

        auth_diff = await self.db_pool.runInteraction(
            "get_auth_chain_difference",
            self._get_auth_chain_difference_txn,
            state_sets,
        )
        return StateDifference(auth_difference=auth_diff, conflicted_subgraph=None)

    def _get_auth_chain_difference_using_cover_index_txn(
        self,
        txn: LoggingTransaction,
        room_id: str,
        state_sets: list[set[str]],
        conflicted_set: set[str] | None = None,
        additional_backwards_reachable_conflicted_events: set[str] | None = None,
    ) -> StateDifference:
        """Calculates the auth chain difference using the chain index.

        See docs/auth_chain_difference_algorithm.md for details
        """
        is_state_res_v21 = conflicted_set is not None

        # First we look up the chain ID/sequence numbers for all the events, and
        # work out the chain/sequence numbers reachable from each state set.

        initial_events = set(state_sets[0]).union(*state_sets[1:])

        if is_state_res_v21:
            # Sanity check v2.1 fields
            assert conflicted_set is not None
            assert conflicted_set.issubset(initial_events)
            # It's possible for the conflicted_set to be empty if all the conflicts are in
            # unpersisted events, so we don't assert that conflicted_set has len > 0
            if additional_backwards_reachable_conflicted_events:
                assert additional_backwards_reachable_conflicted_events.issubset(
                    initial_events
                )

        # Map from event_id -> (chain ID, seq no)
        chain_info: dict[str, tuple[int, int]] = {}

        # Map from chain ID -> seq no -> event Id
        chain_to_event: dict[int, dict[int, str]] = {}

        # All the chains that we've found that are reachable from the state
        # sets.
        seen_chains: set[int] = set()

        # Fetch the chain cover index for the initial set of events we're
        # considering.
        def fetch_chain_info(events_to_fetch: Collection[str]) -> None:
            sql = """
                SELECT event_id, chain_id, sequence_number
                FROM event_auth_chains
                WHERE %s
            """
            for batch in batch_iter(events_to_fetch, 1000):
                clause, args = make_in_list_sql_clause(
                    txn.database_engine, "event_id", batch
                )
                txn.execute(sql % (clause,), args)

                for event_id, chain_id, sequence_number in txn:
                    chain_info[event_id] = (chain_id, sequence_number)
                    seen_chains.add(chain_id)
                    chain_to_event.setdefault(chain_id, {})[sequence_number] = event_id

        fetch_chain_info(initial_events)

        # Check that we actually have a chain ID for all the events.
        events_missing_chain_info = initial_events.difference(chain_info)

        # The result set to return, i.e. the auth chain difference.
        auth_difference_result: set[str] = set()

        if events_missing_chain_info:
            # For some reason we have events we haven't calculated the chain
            # index for, so we need to handle those separately. This should only
            # happen for older rooms where the server doesn't have all the auth
            # events.
            auth_difference_result = self._fixup_auth_chain_difference_sets(
                txn,
                room_id,
                state_sets=state_sets,
                events_missing_chain_info=events_missing_chain_info,
                events_that_have_chain_index=chain_info,
            )

            # We now need to refetch any events that we have added to the state
            # sets.
            new_events_to_fetch = {
                event_id
                for state_set in state_sets
                for event_id in state_set
                if event_id not in initial_events
            }

            fetch_chain_info(new_events_to_fetch)

        # State Res v2.1 needs extra data structures to calculate the conflicted subgraph which
        # are outlined below.

        # A subset of chain_info for conflicted events only, as we need to
        # loop all conflicted chain positions. Map from event_id -> (chain ID, seq no)
        conflicted_chain_positions: dict[str, tuple[int, int]] = {}
        # For each chain, remember the positions where conflicted events are.
        # We need this for calculating the forward reachable events.
        conflicted_chain_to_seq: dict[int, set[int]] = {}  # chain_id => {seq_num}
        #  A subset of chain_info for additional backwards reachable events only, as we need to
        # loop all additional backwards reachable events for calculating backwards reachable events.
        additional_backwards_reachable_positions: dict[
            str, tuple[int, int]
        ] = {}  # event_id => (chain_id, seq_num)
        # These next two fields are critical as the intersection of them is the conflicted subgraph.
        # We'll populate them when we walk the chain links.
        # chain_id => max(seq_num) backwards reachable (e.g 4 means 1,2,3,4 are backwards reachable)
        conflicted_backwards_reachable: dict[int, int] = {}
        # chain_id => min(seq_num) forwards reachable (e.g 4 means 4,5,6..n are forwards reachable)
        conflicted_forwards_reachable: dict[int, int] = {}

        # populate the v2.1 data structures
        if is_state_res_v21:
            assert conflicted_set is not None
            # provide chain positions for each conflicted event
            for conflicted_event_id in conflicted_set:
                (chain_id, seq_num) = chain_info[conflicted_event_id]
                conflicted_chain_positions[conflicted_event_id] = (chain_id, seq_num)
                conflicted_chain_to_seq.setdefault(chain_id, set()).add(seq_num)
            if additional_backwards_reachable_conflicted_events:
                for (
                    additional_event_id
                ) in additional_backwards_reachable_conflicted_events:
                    (chain_id, seq_num) = chain_info[additional_event_id]
                    additional_backwards_reachable_positions[additional_event_id] = (
                        chain_id,
                        seq_num,
                    )

        # Corresponds to `state_sets`, except as a map from chain ID to max
        # sequence number reachable from the state set.
        set_to_chain: list[dict[int, int]] = []
        for state_set in state_sets:
            chains: dict[int, int] = {}
            set_to_chain.append(chains)

            for state_id in state_set:
                chain_id, seq_no = chain_info[state_id]

                chains[chain_id] = max(seq_no, chains.get(chain_id, 0))

        # Now we look up all links for the chains we have, adding chains that
        # are reachable from any event.

        # (We need to take a copy of `seen_chains` as the function mutates it)
        for links in self._get_chain_links(txn, set(seen_chains)):
            # `links` encodes the backwards reachable events _from a single chain_ all the way to
            # the root of the graph.
            for chains in set_to_chain:
                for chain_id in links:
                    if chain_id not in chains:
                        continue

                    _materialize(chain_id, chains[chain_id], links, chains)

                seen_chains.update(chains)
            if is_state_res_v21:
                # Apply v2.1 conflicted event reachability checks.
                #
                #  A <-- B <-- C <-- D <-- E
                #
                # Backwards reachable from C = {A,B}
                # Forwards reachable from C = {D,E}

                # this handles calculating forwards reachable information and updates
                # conflicted_forwards_reachable.
                accumulate_forwards_reachable_events(
                    conflicted_forwards_reachable,
                    links,
                    conflicted_chain_positions,
                )

                # handle backwards reachable information
                for (
                    conflicted_chain_id,
                    conflicted_chain_seq,
                ) in conflicted_chain_positions.values():
                    if conflicted_chain_id not in links:
                        # This conflicted event does not lie on the path to the root.
                        continue

                    # The conflicted chain position itself encodes reachability information
                    # _within_ the chain. Set it now before walking to other links.
                    conflicted_backwards_reachable[conflicted_chain_id] = max(
                        conflicted_chain_seq,
                        conflicted_backwards_reachable.get(conflicted_chain_id, 0),
                    )

                    # Build backwards reachability paths. This is the same as what the auth difference
                    # code does. We find which chain the conflicted event
                    # belongs to then walk it backwards to the root. We store reachability info
                    # for all conflicted events in the same map 'conflicted_backwards_reachable'
                    # as we don't care about the paths themselves.
                    _materialize(
                        conflicted_chain_id,
                        conflicted_chain_seq,
                        links,
                        conflicted_backwards_reachable,
                    )
                # Mark some extra events as backwards reachable. This is used when we have some
                # unpersisted events and want to know the subgraph across the persisted/unpersisted
                # boundary:
                #                  |
                #  A <-- B <-- C <-|- D <-- E <-- F
                #     persisted    |   unpersisted
                #
                # Assume {B,E} are conflicted, we want to return {B,C,D,E}
                #
                # The unpersisted code ensures it passes C as an additional backwards reachable
                # event. C is NOT a conflicted event, but we do need to consider it as part of
                # the backwards reachable set. When we then calculate the forwards reachable set
                # from B, C will be in both the backwards and forwards reachable sets and hence
                # will be included in the conflicted subgraph.
                for (
                    additional_chain_id,
                    additional_chain_seq,
                ) in additional_backwards_reachable_positions.values():
                    if additional_chain_id not in links:
                        # The additional backwards reachable event does not lie on the path to the root.
                        continue

                    # the additional event chain position itself encodes reachability information.
                    # It means that position and all positions earlier in that chain are backwards reachable
                    # by some unpersisted conflicted event.
                    conflicted_backwards_reachable[additional_chain_id] = max(
                        additional_chain_seq,
                        conflicted_backwards_reachable.get(additional_chain_id, 0),
                    )

                    # Now walk the chains back, marking backwards reachable events.
                    # This is the same thing we do for auth difference / conflicted events.
                    _materialize(
                        additional_chain_id,  # walk all links back, marking them as backwards reachable
                        additional_chain_seq,
                        links,
                        conflicted_backwards_reachable,
                    )

        # Now for each chain we figure out the maximum sequence number reachable
        # from *any* state set and the minimum sequence number reachable from
        # *all* state sets. Events in that range are in the auth chain
        # difference.

        # Mapping from chain ID to the range of sequence numbers that should be
        # pulled from the database.
        auth_diff_chain_to_gap: dict[int, tuple[int, int]] = {}

        for chain_id in seen_chains:
            min_seq_no = min(chains.get(chain_id, 0) for chains in set_to_chain)
            max_seq_no = max(chains.get(chain_id, 0) for chains in set_to_chain)

            if min_seq_no < max_seq_no:
                # We have a non empty gap, try and fill it from the events that
                # we have, otherwise add them to the list of gaps to pull out
                # from the DB.
                for seq_no in range(min_seq_no + 1, max_seq_no + 1):
                    event_id = chain_to_event.get(chain_id, {}).get(seq_no)
                    if event_id:
                        auth_difference_result.add(event_id)
                    else:
                        auth_diff_chain_to_gap[chain_id] = (min_seq_no, max_seq_no)
                        break

        conflicted_subgraph_result: set[str] = set()
        # Mapping from chain ID to the range of sequence numbers that should be
        # pulled from the database.
        conflicted_subgraph_chain_to_gap: dict[int, tuple[int, int]] = {}
        if is_state_res_v21:
            # also include the conflicted subgraph using backward/forward reachability info from all
            # the conflicted events. To calculate this, we want to extract the intersection between
            # the backwards and forwards reachability sets, e.g:
            #     A <- B <- C <- D <- E
            #    Assume B and D are conflicted so we want {C} as the conflicted subgraph.
            #    B_backwards={A}, B_forwards={C,D,E}
            #    D_backwards={A,B,C} D_forwards={E}
            #    ALL_backwards={A,B,C} ALL_forwards={C,D,E}
            #    Intersection(ALL_backwards, ALL_forwards) = {C}
            #
            # It's worth noting that once we have the ALL_ sets, we no longer care about the paths.
            # We're dealing with chains and not singular events, but we've already got the ALL_ sets.
            # As such, we can inspect each chain in isolation and check for overlapping sequence
            # numbers:
            #             1,2,3,4,5 Seq Num
            #    Chain N [A,B,C,D,E]
            #
            # if (N,4) is in the backwards set and (N,2) is in the forwards set, then the
            # intersection is events between 2 < 4. We will include the conflicted events themselves
            # in the subgraph, but they will already be, hence the full set of events is {B,C,D}.
            for chain_id, backwards_seq_num in conflicted_backwards_reachable.items():
                forwards_seq_num = conflicted_forwards_reachable.get(chain_id)
                if forwards_seq_num is None:
                    continue  # this chain isn't in both sets so can't intersect
                if forwards_seq_num > backwards_seq_num:
                    continue  # this chain is in both sets but they don't overap
                for seq_no in range(
                    forwards_seq_num, backwards_seq_num + 1
                ):  # inclusive of both
                    event_id = chain_to_event.get(chain_id, {}).get(seq_no)
                    if event_id:
                        conflicted_subgraph_result.add(event_id)
                    else:
                        conflicted_subgraph_chain_to_gap[chain_id] = (
                            # _fetch_event_ids_from_chains_txn is exclusive of the min value
                            forwards_seq_num - 1,
                            backwards_seq_num,
                        )
                        break

        if auth_diff_chain_to_gap:
            auth_difference_result.update(
                self._fetch_event_ids_from_chains_txn(txn, auth_diff_chain_to_gap)
            )
        if conflicted_subgraph_chain_to_gap:
            conflicted_subgraph_result.update(
                self._fetch_event_ids_from_chains_txn(
                    txn, conflicted_subgraph_chain_to_gap
                )
            )

        return StateDifference(
            auth_difference=auth_difference_result,
            conflicted_subgraph=conflicted_subgraph_result,
        )

    def _fetch_event_ids_from_chains_txn(
        self, txn: LoggingTransaction, chains: dict[int, tuple[int, int]]
    ) -> set[str]:
        result: set[str] = set()
        if isinstance(self.database_engine, PostgresEngine):
            # We can use `execute_values` to efficiently fetch the gaps when
            # using postgres.
            sql = """
                SELECT event_id
                FROM event_auth_chains AS c, (VALUES ?) AS l(chain_id, min_seq, max_seq)
                WHERE
                    c.chain_id = l.chain_id
                    AND min_seq < sequence_number AND sequence_number <= max_seq
            """

            args = [
                (chain_id, min_no, max_no)
                for chain_id, (min_no, max_no) in chains.items()
            ]

            rows = txn.execute_values(sql, args)
            result.update(r for (r,) in rows)
        else:
            # For SQLite we just fall back to doing a noddy for loop.
            sql = """
                SELECT event_id FROM event_auth_chains
                WHERE chain_id = ? AND ? < sequence_number AND sequence_number <= ?
            """
            for chain_id, (min_no, max_no) in chains.items():
                txn.execute(sql, (chain_id, min_no, max_no))
                result.update(r for (r,) in txn)
        return result

    def _fixup_auth_chain_difference_sets(
        self,
        txn: LoggingTransaction,
        room_id: str,
        state_sets: list[set[str]],
        events_missing_chain_info: set[str],
        events_that_have_chain_index: Collection[str],
    ) -> set[str]:
        """Helper for `_get_auth_chain_difference_using_cover_index_txn` to
        handle the case where we haven't calculated the chain cover index for
        all events.

        This modifies `state_sets` so that they only include events that have a
        chain cover index, and returns a set of event IDs that are part of the
        auth difference.
        """

        # This works similarly to the handling of unpersisted events in
        # `synapse.state.v2_get_auth_chain_difference`. We uses the observation
        # that if you can split the set of events into two classes X and Y,
        # where no events in Y have events in X in their auth chain, then we can
        # calculate the auth difference by considering X and Y separately.
        #
        # We do this in three steps:
        #   1. Compute the set of events without chain cover index belonging to
        #      the auth difference.
        #   2. Replacing the un-indexed events in the state_sets with their auth
        #      events, recursively, until the state_sets contain only indexed
        #      events. We can then calculate the auth difference of those state
        #      sets using the chain cover index.
        #   3. Add the results of 1 and 2 together.

        # By construction we know that all events that we haven't persisted the
        # chain cover index for are contained in
        # `event_auth_chain_to_calculate`, so we pull out the events from those
        # rather than doing recursive queries to walk the auth chain.
        #
        # We pull out those events with their auth events, which gives us enough
        # information to construct the auth chain of an event up to auth events
        # that have the chain cover index.
        sql = """
            SELECT tc.event_id, ea.auth_id, eac.chain_id IS NOT NULL
            FROM event_auth_chain_to_calculate AS tc
            LEFT JOIN event_auth AS ea USING (event_id)
            LEFT JOIN event_auth_chains AS eac ON (ea.auth_id = eac.event_id)
            WHERE tc.room_id = ?
        """
        txn.execute(sql, (room_id,))
        event_to_auth_ids: dict[str, set[str]] = {}
        events_that_have_chain_index = set(events_that_have_chain_index)
        for event_id, auth_id, auth_id_has_chain in txn:
            s = event_to_auth_ids.setdefault(event_id, set())
            if auth_id is not None:
                s.add(auth_id)
                if auth_id_has_chain:
                    events_that_have_chain_index.add(auth_id)

        if events_missing_chain_info - event_to_auth_ids.keys():
            # Uh oh, we somehow haven't correctly done the chain cover index,
            # bail and fall back to the old method.
            logger.error(
                "Unexpectedly found that events don't have chain IDs in room %s: %s",
                room_id,
                events_missing_chain_info - event_to_auth_ids.keys(),
            )
            raise _NoChainCoverIndex(room_id)

        # Create a map from event IDs we care about to their partial auth chain.
        event_id_to_partial_auth_chain: dict[str, set[str]] = {}
        for event_id, auth_ids in event_to_auth_ids.items():
            if not any(event_id in state_set for state_set in state_sets):
                continue

            processing = set(auth_ids)
            to_add = set()
            while processing:
                auth_id = processing.pop()
                to_add.add(auth_id)

                sub_auth_ids = event_to_auth_ids.get(auth_id)
                if sub_auth_ids is None:
                    continue

                processing.update(sub_auth_ids - to_add)

            event_id_to_partial_auth_chain[event_id] = to_add

        # Now we do two things:
        #   1. Update the state sets to only include indexed events; and
        #   2. Create a new list containing the auth chains of the un-indexed
        #      events
        unindexed_state_sets: list[set[str]] = []
        for state_set in state_sets:
            unindexed_state_set = set()
            for event_id, auth_chain in event_id_to_partial_auth_chain.items():
                if event_id not in state_set:
                    continue

                unindexed_state_set.add(event_id)

                state_set.discard(event_id)
                state_set.difference_update(auth_chain)
                for auth_id in auth_chain:
                    if auth_id in events_that_have_chain_index:
                        state_set.add(auth_id)
                    else:
                        unindexed_state_set.add(auth_id)

            unindexed_state_sets.append(unindexed_state_set)

        # Calculate and return the auth difference of the un-indexed events.
        union = unindexed_state_sets[0].union(*unindexed_state_sets[1:])
        intersection = unindexed_state_sets[0].intersection(*unindexed_state_sets[1:])

        return union - intersection

    def _get_auth_chain_difference_txn(
        self, txn: LoggingTransaction, state_sets: list[set[str]]
    ) -> set[str]:
        """Calculates the auth chain difference using a breadth first search.

        This is used when we don't have a cover index for the room.
        """

        # Algorithm Description
        # ~~~~~~~~~~~~~~~~~~~~~
        #
        # The idea here is to basically walk the auth graph of each state set in
        # tandem, keeping track of which auth events are reachable by each state
        # set. If we reach an auth event we've already visited (via a different
        # state set) then we mark that auth event and all ancestors as reachable
        # by the state set. This requires that we keep track of the auth chains
        # in memory.
        #
        # Doing it in a such a way means that we can stop early if all auth
        # events we're currently walking are reachable by all state sets.
        #
        # *Note*: We can't stop walking an event's auth chain if it is reachable
        # by all state sets. This is because other auth chains we're walking
        # might be reachable only via the original auth chain. For example,
        # given the following auth chain:
        #
        #       A -> C -> D -> E
        #           /         /
        #       B -´---------´
        #
        # and state sets {A} and {B} then walking the auth chains of A and B
        # would immediately show that C is reachable by both. However, if we
        # stopped at C then we'd only reach E via the auth chain of B and so E
        # would erroneously get included in the returned difference.
        #
        # The other thing that we do is limit the number of auth chains we walk
        # at once, due to practical limits (i.e. we can only query the database
        # with a limited set of parameters). We pick the auth chains we walk
        # each iteration based on their depth, in the hope that events with a
        # lower depth are likely reachable by those with higher depths.
        #
        # We could use any ordering that we believe would give a rough
        # topological ordering, e.g. origin server timestamp. If the ordering
        # chosen is not topological then the algorithm still produces the right
        # result, but perhaps a bit more inefficiently. This is why it is safe
        # to use "depth" here.

        initial_events = set(state_sets[0]).union(*state_sets[1:])

        # Dict from events in auth chains to which sets *cannot* reach them.
        # I.e. if the set is empty then all sets can reach the event.
        event_to_missing_sets = {
            event_id: {i for i, a in enumerate(state_sets) if event_id not in a}
            for event_id in initial_events
        }

        # The sorted list of events whose auth chains we should walk.
        search: list[tuple[int, str]] = []

        # We need to get the depth of the initial events for sorting purposes.
        sql = """
            SELECT depth, event_id FROM events
            WHERE %s
        """
        # the list can be huge, so let's avoid looking them all up in one massive
        # query.
        for batch in batch_iter(initial_events, 1000):
            clause, args = make_in_list_sql_clause(
                txn.database_engine, "event_id", batch
            )
            txn.execute(sql % (clause,), args)

            # I think building a temporary list with fetchall is more efficient than
            # just `search.extend(txn)`, but this is unconfirmed
            search.extend(cast(list[tuple[int, str]], txn.fetchall()))

        # sort by depth
        search.sort()

        # Map from event to its auth events
        event_to_auth_events: dict[str, set[str]] = {}

        base_sql = """
            SELECT a.event_id, auth_id, depth
            FROM event_auth AS a
            INNER JOIN events AS e ON (e.event_id = a.auth_id)
            WHERE
        """

        while search:
            # Check whether all our current walks are reachable by all state
            # sets. If so we can bail.
            if all(not event_to_missing_sets[eid] for _, eid in search):
                break

            # Fetch the auth events and their depths of the N last events we're
            # currently walking, either from cache or DB.
            search, chunk = search[:-100], search[-100:]

            found: list[tuple[str, str, int]] = []  # Results found
            to_fetch: list[str] = []  # Event IDs to fetch from DB
            for _, event_id in chunk:
                res = self._event_auth_cache.get(event_id)
                if res is None:
                    to_fetch.append(event_id)
                else:
                    found.extend((event_id, auth_id, depth) for auth_id, depth in res)

            if to_fetch:
                clause, args = make_in_list_sql_clause(
                    txn.database_engine, "a.event_id", to_fetch
                )
                txn.execute(base_sql + clause, args)

                # We parse the results and add the to the `found` set and the
                # cache (note we need to batch up the results by event ID before
                # adding to the cache).
                to_cache: dict[str, list[tuple[str, int]]] = {}
                for event_id, auth_event_id, auth_event_depth in txn:
                    to_cache.setdefault(event_id, []).append(
                        (auth_event_id, auth_event_depth)
                    )
                    found.append((event_id, auth_event_id, auth_event_depth))

                for event_id, auth_events in to_cache.items():
                    self._event_auth_cache.set(event_id, auth_events)

            for event_id, auth_event_id, auth_event_depth in found:
                event_to_auth_events.setdefault(event_id, set()).add(auth_event_id)

                sets = event_to_missing_sets.get(auth_event_id)
                if sets is None:
                    # First time we're seeing this event, so we add it to the
                    # queue of things to fetch.
                    search.append((auth_event_depth, auth_event_id))

                    # Assume that this event is unreachable from any of the
                    # state sets until proven otherwise
                    sets = event_to_missing_sets[auth_event_id] = set(
                        range(len(state_sets))
                    )
                else:
                    # We've previously seen this event, so look up its auth
                    # events and recursively mark all ancestors as reachable
                    # by the current event's state set.
                    a_ids = event_to_auth_events.get(auth_event_id)
                    while a_ids:
                        new_aids = set()
                        for a_id in a_ids:
                            event_to_missing_sets[a_id].intersection_update(
                                event_to_missing_sets[event_id]
                            )

                            b = event_to_auth_events.get(a_id)
                            if b:
                                new_aids.update(b)

                        a_ids = new_aids

                # Mark that the auth event is reachable by the appropriate sets.
                sets.intersection_update(event_to_missing_sets[event_id])

            search.sort()

        # Return all events where not all sets can reach them.
        return {eid for eid, n in event_to_missing_sets.items() if n}

    @trace
    @tag_args
    async def get_backfill_points_in_room(
        self,
        room_id: str,
        current_depth: int,
        limit: int,
    ) -> list[tuple[str, int]]:
        """
        Get the backward extremities to backfill from in the room along with the
        approximate depth.

        Only returns events that are at a depth lower than or
        equal to the `current_depth`. Sorted by depth, highest to lowest (descending)
        so the closest events to the `current_depth` are first in the list.

        We ignore extremities that are newer than the user's current scroll position
        (ie, those with depth greater than `current_depth`) as:
            1. we don't really care about getting events that have happened
               after our current position; and
            2. by the nature of paginating and scrolling back, we have likely
               previously tried and failed to backfill from that extremity, so
               to avoid getting "stuck" requesting the same backfill repeatedly
               we drop those extremities.

        Args:
            room_id: Room where we want to find the oldest events
            current_depth: The depth at the user's current scrollback position
            limit: The max number of backfill points to return

        Returns:
            List of (event_id, depth) tuples. Sorted by depth, highest to lowest
            (descending) so the closest events to the `current_depth` are first
            in the list.
        """

        def get_backfill_points_in_room_txn(
            txn: LoggingTransaction, room_id: str
        ) -> list[tuple[str, int]]:
            # Assemble a tuple lookup of event_id -> depth for the oldest events
            # we know of in the room. Backwards extremeties are the oldest
            # events we know of in the room but we only know of them because
            # some other event referenced them by prev_event and aren't
            # persisted in our database yet (meaning we don't know their depth
            # specifically). So we need to look for the approximate depth from
            # the events connected to the current backwards extremeties.

            if isinstance(self.database_engine, PostgresEngine):
                least_function = "LEAST"
            elif isinstance(self.database_engine, Sqlite3Engine):
                least_function = "MIN"
            else:
                raise RuntimeError("Unknown database engine")

            sql = f"""
                SELECT backward_extrem.event_id, event.depth FROM events AS event
                /**
                 * Get the edge connections from the event_edges table
                 * so we can see whether this event's prev_events points
                 * to a backward extremity in the next join.
                 */
                INNER JOIN event_edges AS edge
                ON edge.event_id = event.event_id
                /**
                 * We find the "oldest" events in the room by looking for
                 * events connected to backwards extremeties (oldest events
                 * in the room that we know of so far).
                 */
                INNER JOIN event_backward_extremities AS backward_extrem
                ON edge.prev_event_id = backward_extrem.event_id
                /**
                 * We use this info to make sure we don't retry to use a backfill point
                 * if we've already attempted to backfill from it recently.
                 */
                LEFT JOIN event_failed_pull_attempts AS failed_backfill_attempt_info
                ON
                    failed_backfill_attempt_info.room_id = backward_extrem.room_id
                    AND failed_backfill_attempt_info.event_id = backward_extrem.event_id
                WHERE
                    backward_extrem.room_id = ?
                    /* We only care about non-state edges because we used to use
                     * `event_edges` for two different sorts of "edges" (the current
                     * event DAG, but also a link to the previous state, for state
                     * events). These legacy state event edges can be distinguished by
                     * `is_state` and are removed from the codebase and schema but
                     * because the schema change is in a background update, it's not
                     * necessarily safe to assume that it will have been completed.
                     */
                    AND edge.is_state is FALSE
                    /**
                     * We only want backwards extremities that are older than or at
                     * the same position of the given `current_depth` (where older
                     * means less than the given depth) because we're looking backwards
                     * from the `current_depth` when backfilling.
                     *
                     *                         current_depth (ignore events that come after this, ignore 2-4)
                     *                         |
                     *                         ▼
                     * <oldest-in-time> [0]<--[1]<--[2]<--[3]<--[4] <newest-in-time>
                     */
                    AND event.depth <= ? /* current_depth */
                    /**
                     * Exponential back-off (up to the upper bound) so we don't retry the
                     * same backfill point over and over. ex. 2hr, 4hr, 8hr, 16hr, etc.
                     *
                     * We use `1 << n` as a power of 2 equivalent for compatibility
                     * with older SQLites. The left shift equivalent only works with
                     * powers of 2 because left shift is a binary operation (base-2).
                     * Otherwise, we would use `power(2, n)` or the power operator, `2^n`.
                     */
                    AND (
                        failed_backfill_attempt_info.event_id IS NULL
                        OR ? /* current_time */ >= failed_backfill_attempt_info.last_attempt_ts + (
                            (1 << {least_function}(failed_backfill_attempt_info.num_attempts, ? /* max doubling steps */))
                            * ? /* step */
                        )
                    )
                /**
                 * Sort from highest (closest to the `current_depth`) to the lowest depth
                 * because the closest are most relevant to backfill from first.
                 * Then tie-break on alphabetical order of the event_ids so we get a
                 * consistent ordering which is nice when asserting things in tests.
                 */
                ORDER BY event.depth DESC, backward_extrem.event_id DESC
                LIMIT ?
            """

            txn.execute(
                sql,
                (
                    room_id,
                    current_depth,
                    self.clock.time_msec(),
                    BACKFILL_EVENT_EXPONENTIAL_BACKOFF_MAXIMUM_DOUBLING_STEPS,
                    BACKFILL_EVENT_EXPONENTIAL_BACKOFF_STEP_MILLISECONDS,
                    limit,
                ),
            )

            return cast(list[tuple[str, int]], txn.fetchall())

        return await self.db_pool.runInteraction(
            "get_backfill_points_in_room",
            get_backfill_points_in_room_txn,
            room_id,
        )

    async def get_max_depth_of(
        self, event_ids: Collection[str]
    ) -> tuple[str | None, int]:
        """Returns the event ID and depth for the event that has the max depth from a set of event IDs

        Args:
            event_ids: The event IDs to calculate the max depth of.
        """
        rows = cast(
            list[tuple[str, int]],
            await self.db_pool.simple_select_many_batch(
                table="events",
                column="event_id",
                iterable=event_ids,
                retcols=(
                    "event_id",
                    "depth",
                ),
                desc="get_max_depth_of",
            ),
        )

        if not rows:
            return None, 0
        else:
            max_depth_event_id = ""
            current_max_depth = 0
            for event_id, depth in rows:
                if depth > current_max_depth:
                    max_depth_event_id = event_id
                    current_max_depth = depth

            return max_depth_event_id, current_max_depth

    async def get_min_depth_of(self, event_ids: list[str]) -> tuple[str | None, int]:
        """Returns the event ID and depth for the event that has the min depth from a set of event IDs

        Args:
            event_ids: The event IDs to calculate the max depth of.
        """
        rows = cast(
            list[tuple[str, int]],
            await self.db_pool.simple_select_many_batch(
                table="events",
                column="event_id",
                iterable=event_ids,
                retcols=(
                    "event_id",
                    "depth",
                ),
                desc="get_min_depth_of",
            ),
        )

        if not rows:
            return None, 0
        else:
            min_depth_event_id = ""
            current_min_depth = MAX_DEPTH
            for event_id, depth in rows:
                if depth < current_min_depth:
                    min_depth_event_id = event_id
                    current_min_depth = depth

            return min_depth_event_id, current_min_depth

    async def get_prev_events_for_room(self, room_id: str) -> list[str]:
        """
        Gets a subset of the current forward extremities in the given room.

        Limits the result to 10 extremities, so that we can avoid creating
        events which refer to hundreds of prev_events.

        Args:
            room_id: room_id

        Returns:
            The event ids of the forward extremities.

        """

        return await self.db_pool.runInteraction(
            "get_prev_events_for_room", self._get_prev_events_for_room_txn, room_id
        )

    def _get_prev_events_for_room_txn(
        self, txn: LoggingTransaction, room_id: str
    ) -> list[str]:
        # we just use the 10 newest events. Older events will become
        # prev_events of future events.

        sql = """
            SELECT e.event_id FROM event_forward_extremities AS f
            INNER JOIN events AS e USING (event_id)
            WHERE f.room_id = ?
            ORDER BY e.depth DESC
            LIMIT 10
        """

        txn.execute(sql, (room_id,))

        return [row[0] for row in txn]

    async def get_rooms_with_many_extremities(
        self, min_count: int, limit: int, room_id_filter: Iterable[str]
    ) -> list[str]:
        """Get the top rooms with at least N extremities.

        Args:
            min_count: The minimum number of extremities
            limit: The maximum number of rooms to return.
            room_id_filter: room_ids to exclude from the results

        Returns:
            At most `limit` room IDs that have at least `min_count` extremities,
            sorted by extremity count.
        """

        def _get_rooms_with_many_extremities_txn(txn: LoggingTransaction) -> list[str]:
            where_clause = "1=1"
            if room_id_filter:
                where_clause = "room_id NOT IN (%s)" % (
                    ",".join("?" for _ in room_id_filter),
                )

            sql = """
                SELECT room_id FROM event_forward_extremities
                WHERE %s
                GROUP BY room_id
                HAVING count(*) > ?
                ORDER BY count(*) DESC
                LIMIT ?
            """ % (where_clause,)

            query_args = list(itertools.chain(room_id_filter, [min_count, limit]))
            txn.execute(sql, query_args)
            return [room_id for (room_id,) in txn]

        return await self.db_pool.runInteraction(
            "get_rooms_with_many_extremities", _get_rooms_with_many_extremities_txn
        )

    @cached(max_entries=5000, iterable=True)
    async def get_latest_event_ids_in_room(self, room_id: str) -> frozenset[str]:
        event_ids = await self.db_pool.simple_select_onecol(
            table="event_forward_extremities",
            keyvalues={"room_id": room_id},
            retcol="event_id",
            desc="get_latest_event_ids_in_room",
        )
        return frozenset(event_ids)

    async def get_state_dag_extremities(self, room_id: str) -> frozenset[str]:
        event_ids = await self.db_pool.simple_select_onecol(
            table="msc4242_state_dag_forward_extremities",
            keyvalues={"room_id": room_id},
            retcol="event_id",
            desc="get_state_dag_extremities",
        )
        return frozenset(event_ids)

    async def get_min_depth(self, room_id: str) -> int | None:
        """For the given room, get the minimum depth we have seen for it."""
        return await self.db_pool.runInteraction(
            "get_min_depth", self._get_min_depth_interaction, room_id
        )

    def _get_min_depth_interaction(
        self, txn: LoggingTransaction, room_id: str
    ) -> int | None:
        min_depth = self.db_pool.simple_select_one_onecol_txn(
            txn,
            table="room_depth",
            keyvalues={"room_id": room_id},
            retcol="min_depth",
            allow_none=True,
        )

        return int(min_depth) if min_depth is not None else None

    async def have_room_forward_extremities_changed_since(
        self,
        room_id: str,
        stream_ordering: int,
    ) -> bool:
        """Check if the forward extremities in a room have changed since the
        given stream ordering

        Throws a StoreError if we have since purged the index for
        stream_orderings from that point.
        """
        assert self.stream_ordering_month_ago is not None
        if stream_ordering <= self.stream_ordering_month_ago:
            raise StoreError(400, f"stream_ordering too old {stream_ordering}")

        sql = """
            SELECT 1 FROM stream_ordering_to_exterm
            WHERE stream_ordering > ? AND room_id = ?
            LIMIT 1
        """

        def have_room_forward_extremities_changed_since_txn(
            txn: LoggingTransaction,
        ) -> bool:
            txn.execute(sql, (stream_ordering, room_id))
            return txn.fetchone() is not None

        return await self.db_pool.runInteraction(
            "have_room_forward_extremities_changed_since",
            have_room_forward_extremities_changed_since_txn,
        )

    @cancellable
    async def get_forward_extremities_for_room_at_stream_ordering(
        self, room_id: str, stream_ordering: int
    ) -> Sequence[str]:
        """For a given room_id and stream_ordering, return the forward
        extremeties of the room at that point in "time".

        Throws a StoreError if we have since purged the index for
        stream_orderings from that point.

        Args:
            room_id:
            stream_ordering:

        Returns:
            A list of event_ids
        """
        # We want to make the cache more effective, so we clamp to the last
        # change before the given ordering.
        last_change = self._events_stream_cache.get_max_pos_of_last_change(room_id)  # type: ignore[attr-defined]
        if last_change is None:
            # If the room isn't in the cache we know that the last change was
            # somewhere before the earliest known position of the cache, so we
            # can clamp to that.
            last_change = self._events_stream_cache.get_earliest_known_position()  # type: ignore[attr-defined]

        # We don't always have a full stream_to_exterm_id table, e.g. after
        # the upgrade that introduced it, so we make sure we never ask for a
        # stream_ordering from before a restart
        last_change = max(self._stream_order_on_start, last_change)  # type: ignore[attr-defined]

        # provided the last_change is recent enough, we now clamp the requested
        # stream_ordering to it.
        assert self.stream_ordering_month_ago is not None
        if last_change > self.stream_ordering_month_ago:
            stream_ordering = min(last_change, stream_ordering)

        return await self._get_forward_extremeties_for_room(room_id, stream_ordering)

    @cached(max_entries=5000, num_args=2)
    async def _get_forward_extremeties_for_room(
        self, room_id: str, stream_ordering: int
    ) -> Sequence[str]:
        """For a given room_id and stream_ordering, return the forward
        extremeties of the room at that point in "time".

        Throws a StoreError if we have since purged the index for
        stream_orderings from that point.
        """
        assert self.stream_ordering_month_ago is not None
        if stream_ordering <= self.stream_ordering_month_ago:
            raise StoreError(400, "stream_ordering too old %s" % (stream_ordering,))

        sql = """
                SELECT event_id FROM stream_ordering_to_exterm
                INNER JOIN (
                    SELECT room_id, MAX(stream_ordering) AS stream_ordering
                    FROM stream_ordering_to_exterm
                    WHERE stream_ordering <= ? GROUP BY room_id
                ) AS rms USING (room_id, stream_ordering)
                WHERE room_id = ?
        """

        def get_forward_extremeties_for_room_txn(txn: LoggingTransaction) -> list[str]:
            txn.execute(sql, (stream_ordering, room_id))
            return [event_id for (event_id,) in txn]

        event_ids = await self.db_pool.runInteraction(
            "get_forward_extremeties_for_room", get_forward_extremeties_for_room_txn
        )

        # If we didn't find any IDs, then we must have cleared out the
        # associated `stream_ordering_to_exterm`.
        if not event_ids:
            raise StoreError(400, "stream_ordering too old %s" % (stream_ordering,))

        return event_ids

    def _get_connected_prev_event_backfill_results_txn(
        self, txn: LoggingTransaction, event_id: str, limit: int
    ) -> list[BackfillQueueNavigationItem]:
        """
        Find any events connected by prev_event the specified event_id.

        Args:
            txn: The database transaction to use
            event_id: The event ID to navigate from
            limit: Max number of event ID's to query for and return

        Returns:
            List of prev events that the backfill queue can process
        """
        # Look for the prev_event_id connected to the given event_id
        connected_prev_event_query = """
            SELECT depth, stream_ordering, prev_event_id, events.type FROM event_edges
            /* Get the depth and stream_ordering of the prev_event_id from the events table */
            INNER JOIN events
            ON prev_event_id = events.event_id

            /* exclude outliers from the results (we don't have the state, so cannot
             * verify if the requesting server can see them).
             */
            WHERE NOT events.outlier

            /* Look for an edge which matches the given event_id */
            AND event_edges.event_id = ? AND NOT event_edges.is_state

            /* Because we can have many events at the same depth,
            * we want to also tie-break and sort on stream_ordering */
            ORDER BY depth DESC, stream_ordering DESC
            LIMIT ?
        """

        txn.execute(
            connected_prev_event_query,
            (event_id, limit),
        )
        return [
            BackfillQueueNavigationItem(
                depth=row[0],
                stream_ordering=row[1],
                event_id=row[2],
                type=row[3],
            )
            for row in txn
        ]

    async def get_backfill_events(
        self, room_id: str, seed_event_id_list: list[str], limit: int
    ) -> list[EventBase]:
        """Get a list of Events for a given topic that occurred before (and
        including) the events in seed_event_id_list. Return a list of max size `limit`

        Args:
            room_id
            seed_event_id_list
            limit
        """
        event_ids = await self.db_pool.runInteraction(
            "get_backfill_events",
            self._get_backfill_events,
            room_id,
            seed_event_id_list,
            limit,
        )
        events = await self.get_events_as_list(event_ids)
        return sorted(
            # type-ignore: mypy doesn't like negating the int | None stream_ordering.
            # But it's never None, because these events were previously persisted to the DB.
            events,
            key=lambda e: (-e.depth, -e.internal_metadata.stream_ordering),  # type: ignore[operator]
        )

    def _get_backfill_events(
        self,
        txn: LoggingTransaction,
        room_id: str,
        seed_event_id_list: list[str],
        limit: int,
    ) -> set[str]:
        """
        We want to make sure that we do a breadth-first, "depth" ordered search.
        We also handle navigating historical branches of history connected by
        insertion and batch events.
        """
        logger.debug(
            "_get_backfill_events(room_id=%s): seeding backfill with seed_event_id_list=%s limit=%s",
            room_id,
            seed_event_id_list,
            limit,
        )

        event_id_results: set[str] = set()

        # In a PriorityQueue, the lowest valued entries are retrieved first.
        # We're using depth as the priority in the queue and tie-break based on
        # stream_ordering. Depth is lowest at the oldest-in-time message and
        # highest and newest-in-time message. We add events to the queue with a
        # negative depth so that we process the newest-in-time messages first
        # going backwards in time. stream_ordering follows the same pattern.
        queue: "PriorityQueue[tuple[int, int, str, str]]" = PriorityQueue()

        for seed_event_id in seed_event_id_list:
            event_lookup_result = self.db_pool.simple_select_one_txn(
                txn,
                table="events",
                keyvalues={"event_id": seed_event_id, "room_id": room_id},
                retcols=(
                    "type",
                    "depth",
                    "stream_ordering",
                ),
                allow_none=True,
            )

            if event_lookup_result is not None:
                event_type, depth, stream_ordering = event_lookup_result
                logger.debug(
                    "_get_backfill_events(room_id=%s): seed_event_id=%s depth=%s stream_ordering=%s type=%s",
                    room_id,
                    seed_event_id,
                    depth,
                    stream_ordering,
                    event_type,
                )

                if depth:
                    queue.put((-depth, -stream_ordering, seed_event_id, event_type))

        while not queue.empty() and len(event_id_results) < limit:
            try:
                _, _, event_id, event_type = queue.get_nowait()
            except Empty:
                break

            if event_id in event_id_results:
                continue

            event_id_results.add(event_id)

            # Now we just look up the DAG by prev_events as normal
            connected_prev_event_backfill_results = (
                self._get_connected_prev_event_backfill_results_txn(
                    txn, event_id, limit - len(event_id_results)
                )
            )
            logger.debug(
                "_get_backfill_events(room_id=%s): connected_prev_event_backfill_results=%s",
                room_id,
                connected_prev_event_backfill_results,
            )
            for (
                connected_prev_event_backfill_item
            ) in connected_prev_event_backfill_results:
                if connected_prev_event_backfill_item.event_id not in event_id_results:
                    queue.put(
                        (
                            -connected_prev_event_backfill_item.depth,
                            -connected_prev_event_backfill_item.stream_ordering,
                            connected_prev_event_backfill_item.event_id,
                            connected_prev_event_backfill_item.type,
                        )
                    )

        return event_id_results

    @trace
    async def record_event_failed_pull_attempt(
        self, room_id: str, event_id: str, cause: str
    ) -> None:
        """
        Record when we fail to pull an event over federation.

        This information allows us to be more intelligent when we decide to
        retry (we don't need to fail over and over) and we can process that
        event in the background so we don't block on it each time.

        Args:
            room_id: The room where the event failed to pull from
            event_id: The event that failed to be fetched or processed
            cause: The error message or reason that we failed to pull the event
        """
        logger.debug(
            "record_event_failed_pull_attempt room_id=%s, event_id=%s, cause=%s",
            room_id,
            event_id,
            cause,
        )
        await self.db_pool.runInteraction(
            "record_event_failed_pull_attempt",
            self._record_event_failed_pull_attempt_upsert_txn,
            room_id,
            event_id,
            cause,
            db_autocommit=True,  # Safe as it's a single upsert
        )

    def _record_event_failed_pull_attempt_upsert_txn(
        self,
        txn: LoggingTransaction,
        room_id: str,
        event_id: str,
        cause: str,
    ) -> None:
        sql = """
            INSERT INTO event_failed_pull_attempts (
                room_id, event_id, num_attempts, last_attempt_ts, last_cause
            )
                VALUES (?, ?, ?, ?, ?)
            ON CONFLICT (room_id, event_id) DO UPDATE SET
                num_attempts=event_failed_pull_attempts.num_attempts + 1,
                last_attempt_ts=EXCLUDED.last_attempt_ts,
                last_cause=EXCLUDED.last_cause;
        """

        txn.execute(sql, (room_id, event_id, 1, self.clock.time_msec(), cause))

    @trace
    async def get_event_ids_with_failed_pull_attempts(
        self, event_ids: StrCollection
    ) -> set[str]:
        """
        Filter the given list of `event_ids` and return events which have any failed
        pull attempts.

        Args:
            event_ids: A list of events to filter down.

        Returns:
            A filtered down list of `event_ids` that have previous failed pull attempts.
        """

        rows = cast(
            list[tuple[str]],
            await self.db_pool.simple_select_many_batch(
                table="event_failed_pull_attempts",
                column="event_id",
                iterable=event_ids,
                keyvalues={},
                retcols=("event_id",),
                desc="get_event_ids_with_failed_pull_attempts",
            ),
        )
        return {row[0] for row in rows}

    @trace
    async def get_event_ids_to_not_pull_from_backoff(
        self,
        room_id: str,
        event_ids: Collection[str],
    ) -> dict[str, int]:
        """
        Filter down the events to ones that we've failed to pull before recently. Uses
        exponential backoff.

        Args:
            room_id: The room that the events belong to
            event_ids: A list of events to filter down

        Returns:
            A dictionary of event_ids that should not be attempted to be pulled and the
            next timestamp at which we may try pulling them again.
        """
        event_failed_pull_attempts = cast(
            list[tuple[str, int, int]],
            await self.db_pool.simple_select_many_batch(
                table="event_failed_pull_attempts",
                column="event_id",
                iterable=event_ids,
                keyvalues={},
                retcols=(
                    "event_id",
                    "last_attempt_ts",
                    "num_attempts",
                ),
                desc="get_event_ids_to_not_pull_from_backoff",
            ),
        )

        current_time = self.clock.time_msec()

        event_ids_with_backoff = {}
        for event_id, last_attempt_ts, num_attempts in event_failed_pull_attempts:
            # Exponential back-off (up to the upper bound) so we don't try to
            # pull the same event over and over. ex. 2hr, 4hr, 8hr, 16hr, etc.
            backoff_end_time = (
                last_attempt_ts
                + (
                    2
                    ** min(
                        num_attempts,
                        BACKFILL_EVENT_EXPONENTIAL_BACKOFF_MAXIMUM_DOUBLING_STEPS,
                    )
                )
                * BACKFILL_EVENT_EXPONENTIAL_BACKOFF_STEP_MILLISECONDS
            )

            if current_time < backoff_end_time:  # `backoff_end_time` is exclusive
                event_ids_with_backoff[event_id] = backoff_end_time

        return event_ids_with_backoff

    async def get_missing_events(
        self,
        room_id: str,
        earliest_events: list[str],
        latest_events: list[str],
        limit: int,
    ) -> list[EventBase]:
        ids = await self.db_pool.runInteraction(
            "get_missing_events",
            self._get_missing_events,
            room_id,
            earliest_events,
            latest_events,
            limit,
        )
        return await self.get_events_as_list(ids)

    def _get_missing_events(
        self,
        txn: LoggingTransaction,
        room_id: str,
        earliest_events: list[str],
        latest_events: list[str],
        limit: int,
    ) -> list[str]:
        seen_events = set(earliest_events)
        front = set(latest_events) - seen_events
        event_results: list[str] = []

        query = (
            "SELECT prev_event_id FROM event_edges "
            "WHERE event_id = ? AND NOT is_state "
            "LIMIT ?"
        )

        while front and len(event_results) < limit:
            new_front = set()
            for event_id in front:
                txn.execute(query, (event_id, limit - len(event_results)))
                new_results = {t[0] for t in txn} - seen_events

                new_front |= new_results
                seen_events |= new_results
                event_results.extend(new_results)

            front = new_front

        # we built the list working backwards from latest_events; we now need to
        # reverse it so that the events are approximately chronological.
        event_results.reverse()
        return event_results

    @trace
    @tag_args
    async def get_successor_events(self, event_id: str) -> list[str]:
        """Fetch all events that have the given event as a prev event

        Args:
            event_id: The event to search for as a prev_event.
        """
        return await self.db_pool.simple_select_onecol(
            table="event_edges",
            keyvalues={"prev_event_id": event_id},
            retcol="event_id",
            desc="get_successor_events",
        )

    @wrap_as_background_process("delete_old_forward_extrem_cache")
    async def _delete_old_forward_extrem_cache(self) -> None:
        def _delete_old_forward_extrem_cache_txn(txn: LoggingTransaction) -> None:
            sql = """
                DELETE FROM stream_ordering_to_exterm
                WHERE stream_ordering < ?
            """
            txn.execute(sql, (self.stream_ordering_month_ago,))

        await self.db_pool.runInteraction(
            "_delete_old_forward_extrem_cache",
            _delete_old_forward_extrem_cache_txn,
        )

    async def insert_received_event_to_staging(
        self, origin: str, event: EventBase
    ) -> None:
        """Insert a newly received event from federation into the staging area."""

        # We use an upsert here to handle the case where we see the same event
        # from the same server multiple times.
        await self.db_pool.simple_upsert(
            table="federation_inbound_events_staging",
            keyvalues={
                "origin": origin,
                "event_id": event.event_id,
            },
            values={},
            insertion_values={
                "room_id": event.room_id,
                "received_ts": self.clock.time_msec(),
                "event_json": json_encoder.encode(event.get_dict()),
                "internal_metadata": json_encoder.encode(
                    event.internal_metadata.get_dict()
                ),
            },
            desc="insert_received_event_to_staging",
        )

    async def remove_received_event_from_staging(
        self,
        origin: str,
        event_id: str,
    ) -> int | None:
        """Remove the given event from the staging area.

        Returns:
            The received_ts of the row that was deleted, if any.
        """

        def _remove_received_event_from_staging_txn(
            txn: LoggingTransaction,
        ) -> int | None:
            sql = """
                DELETE FROM federation_inbound_events_staging
                WHERE origin = ? AND event_id = ?
                RETURNING received_ts
            """

            txn.execute(sql, (origin, event_id))
            row = cast(tuple[int] | None, txn.fetchone())

            if row is None:
                return None

            return row[0]

        return await self.db_pool.runInteraction(
            "remove_received_event_from_staging",
            _remove_received_event_from_staging_txn,
            db_autocommit=True,
        )

    async def get_next_staged_event_id_for_room(
        self,
        room_id: str,
    ) -> tuple[str, str] | None:
        """
        Get the next event ID in the staging area for the given room.

        Returns:
            Tuple of the `origin` and `event_id`
        """

        def _get_next_staged_event_id_for_room_txn(
            txn: LoggingTransaction,
        ) -> tuple[str, str] | None:
            sql = """
                SELECT origin, event_id
                FROM federation_inbound_events_staging
                WHERE room_id = ?
                ORDER BY received_ts ASC
                LIMIT 1
            """

            txn.execute(sql, (room_id,))

            return cast(tuple[str, str] | None, txn.fetchone())

        return await self.db_pool.runInteraction(
            "get_next_staged_event_id_for_room", _get_next_staged_event_id_for_room_txn
        )

    async def get_next_staged_event_for_room(
        self,
        room_id: str,
        room_version: RoomVersion,
    ) -> tuple[str, EventBase] | None:
        """Get the next event in the staging area for the given room."""

        def _get_next_staged_event_for_room_txn(
            txn: LoggingTransaction,
        ) -> tuple[str, str, str] | None:
            sql = """
                SELECT event_json, internal_metadata, origin
                FROM federation_inbound_events_staging
                WHERE room_id = ?
                ORDER BY received_ts ASC
                LIMIT 1
            """
            txn.execute(sql, (room_id,))

            return cast(tuple[str, str, str] | None, txn.fetchone())

        row = await self.db_pool.runInteraction(
            "get_next_staged_event_for_room", _get_next_staged_event_for_room_txn
        )

        if not row:
            return None

        event_d = db_to_json(row[0])
        internal_metadata_d = db_to_json(row[1])
        origin = row[2]

        event = make_event_from_dict(
            event_dict=event_d,
            room_version=room_version,
            internal_metadata_dict=internal_metadata_d,
        )

        return origin, event

    async def prune_staged_events_in_room(
        self,
        room_id: str,
        room_version: RoomVersion,
    ) -> bool:
        """Checks if there are lots of staged events for the room, and if so
        prune them down.

        Returns:
            Whether any events were pruned
        """

        # First check the size of the queue.
        count = await self.db_pool.simple_select_one_onecol(
            table="federation_inbound_events_staging",
            keyvalues={"room_id": room_id},
            retcol="COUNT(*)",
            desc="prune_staged_events_in_room_count",
        )

        if count < 100:
            return False

        # If the queue is too large, then we want clear the entire queue,
        # keeping only the forward extremities (i.e. the events not referenced
        # by other events in the queue). We do this so that we can always
        # backpaginate in all the events we have dropped.
        rows = cast(
            list[tuple[str, str]],
            await self.db_pool.simple_select_list(
                table="federation_inbound_events_staging",
                keyvalues={"room_id": room_id},
                retcols=("event_id", "event_json"),
                desc="prune_staged_events_in_room_fetch",
            ),
        )

        # Find the set of events referenced by those in the queue, as well as
        # collecting all the event IDs in the queue.
        referenced_events: set[str] = set()
        seen_events: set[str] = set()
        for event_id, event_json in rows:
            seen_events.add(event_id)
            event_d = db_to_json(event_json)

            # We don't bother parsing the dicts into full blown event objects,
            # as that is needlessly expensive.

            # We haven't checked that the `prev_events` have the right format
            # yet, so we check as we go.
            prev_events = event_d.get("prev_events", [])
            if not isinstance(prev_events, list):
                logger.info("Invalid prev_events for %s", event_id)
                continue

            if room_version.event_format == EventFormatVersions.ROOM_V1_V2:
                for prev_event_tuple in prev_events:
                    if (
                        not isinstance(prev_event_tuple, list)
                        or len(prev_event_tuple) != 2
                    ):
                        logger.info("Invalid prev_events for %s", event_id)
                        break

                    prev_event_id = prev_event_tuple[0]
                    if not isinstance(prev_event_id, str):
                        logger.info("Invalid prev_events for %s", event_id)
                        break

                    referenced_events.add(prev_event_id)
            else:
                for prev_event_id in prev_events:
                    if not isinstance(prev_event_id, str):
                        logger.info("Invalid prev_events for %s", event_id)
                        break

                    referenced_events.add(prev_event_id)

        to_delete = referenced_events & seen_events
        if not to_delete:
            return False

        pdus_pruned_from_federation_queue.labels(
            **{SERVER_NAME_LABEL: self.server_name}
        ).inc(len(to_delete))
        logger.info(
            "Pruning %d events in room %s from federation queue",
            len(to_delete),
            room_id,
        )

        await self.db_pool.simple_delete_many(
            table="federation_inbound_events_staging",
            keyvalues={"room_id": room_id},
            iterable=to_delete,
            column="event_id",
            desc="prune_staged_events_in_room_delete",
        )

        return True

    async def get_all_rooms_with_staged_incoming_events(self) -> list[str]:
        """Get the room IDs of all events currently staged."""
        return await self.db_pool.simple_select_onecol(
            table="federation_inbound_events_staging",
            keyvalues={},
            retcol="DISTINCT room_id",
            desc="get_all_rooms_with_staged_incoming_events",
        )

    @wrap_as_background_process("_get_stats_for_federation_staging")
    async def _get_stats_for_federation_staging(self) -> None:
        """Update the prometheus metrics for the inbound federation staging area."""

        def _get_stats_for_federation_staging_txn(
            txn: LoggingTransaction,
        ) -> tuple[int, int]:
            txn.execute("SELECT count(*) FROM federation_inbound_events_staging")
            (count,) = cast(tuple[int], txn.fetchone())

            txn.execute(
                "SELECT min(received_ts) FROM federation_inbound_events_staging"
            )

            (received_ts,) = cast(tuple[int | None], txn.fetchone())

            # If there is nothing in the staging area default it to 0.
            age = 0
            if received_ts is not None:
                age = self.clock.time_msec() - received_ts

            return count, age

        count, age = await self.db_pool.runInteraction(
            "_get_stats_for_federation_staging", _get_stats_for_federation_staging_txn
        )

        number_pdus_in_federation_queue.labels(
            **{SERVER_NAME_LABEL: self.server_name}
        ).set(count)
        oldest_pdu_in_federation_staging.labels(
            **{SERVER_NAME_LABEL: self.server_name}
        ).set(age)

    async def clean_room_for_join(self, room_id: str) -> None:
        await self.db_pool.runInteraction(
            "clean_room_for_join", self._clean_room_for_join_txn, room_id
        )

    def _clean_room_for_join_txn(self, txn: LoggingTransaction, room_id: str) -> None:
        query = "DELETE FROM event_forward_extremities WHERE room_id = ?"

        txn.execute(query, (room_id,))
        self._invalidate_cache_and_stream(
            txn, self.get_latest_event_ids_in_room, (room_id,)
        )


class EventFederationStore(EventFederationWorkerStore):
    """Responsible for storing and serving up the various graphs associated
    with an event. Including the main event graph and the auth chains for an
    event.

    Also has methods for getting the front (latest) and back (oldest) edges
    of the event graphs. These are used to generate the parents for new events
    and backfilling from another server respectively.
    """

    EVENT_AUTH_STATE_ONLY = "event_auth_state_only"

    def __init__(
        self,
        database: DatabasePool,
        db_conn: LoggingDatabaseConnection,
        hs: "HomeServer",
    ):
        super().__init__(database, db_conn, hs)

        self.db_pool.updates.register_background_update_handler(
            self.EVENT_AUTH_STATE_ONLY, self._background_delete_non_state_event_auth
        )

    async def _background_delete_non_state_event_auth(
        self, progress: JsonDict, batch_size: int
    ) -> int:
        def delete_event_auth(txn: LoggingTransaction) -> bool:
            target_min_stream_id = progress.get("target_min_stream_id_inclusive")
            max_stream_id = progress.get("max_stream_id_exclusive")

            if not target_min_stream_id or not max_stream_id:
                txn.execute("SELECT COALESCE(MIN(stream_ordering), 0) FROM events")
                rows = txn.fetchall()
                target_min_stream_id = rows[0][0]

                txn.execute("SELECT COALESCE(MAX(stream_ordering), 0) FROM events")
                rows = txn.fetchall()
                max_stream_id = rows[0][0]

            min_stream_id = max_stream_id - batch_size

            sql = """
                DELETE FROM event_auth
                WHERE event_id IN (
                    SELECT event_id FROM events
                    LEFT JOIN state_events AS se USING (room_id, event_id)
                    WHERE ? <= stream_ordering AND stream_ordering < ?
                        AND se.state_key IS null
                )
            """

            txn.execute(sql, (min_stream_id, max_stream_id))

            new_progress = {
                "target_min_stream_id_inclusive": target_min_stream_id,
                "max_stream_id_exclusive": min_stream_id,
            }

            self.db_pool.updates._background_update_progress_txn(
                txn, self.EVENT_AUTH_STATE_ONLY, new_progress
            )

            return min_stream_id >= target_min_stream_id

        result = await self.db_pool.runInteraction(
            self.EVENT_AUTH_STATE_ONLY, delete_event_auth
        )

        if not result:
            await self.db_pool.updates._end_background_update(
                self.EVENT_AUTH_STATE_ONLY
            )

        return batch_size


def _materialize(
    origin_chain_id: int,
    origin_sequence_number: int,
    links: dict[int, list[tuple[int, int, int]]],
    materialized: dict[int, int],
    backwards: bool = True,
) -> None:
    """Helper function for fetching auth chain links. For a given origin chain
    ID / sequence number and a dictionary of links, updates the materialized
    dict with the reachable chains.

    To get a dict of all chains reachable from a set of chains this function can
    be called in a loop, once per origin chain with the same links and
    materialized args. The materialized dict will the result.

    Args:
        origin_chain_id, origin_sequence_number
        links: map of the links between chains as a dict from origin chain ID
            to list of 3-tuples of origin sequence number, target chain ID and
            target sequence number.
        materialized: dict to update with new reachability information, as a
            map from chain ID to max sequence number reachable.
        backwards: If True, walks backwards down the chains. If False, walks forwards from the chains.
    """

    # Do a standard graph traversal.
    stack = [(origin_chain_id, origin_sequence_number)]

    while stack:
        c, s = stack.pop()

        chain_links = links.get(c, [])
        for (
            sequence_number,
            target_chain_id,
            target_sequence_number,
        ) in chain_links:
            if backwards:
                # Ignore any links that are higher up the chain
                if sequence_number > s:
                    continue

                # Check if we have already visited the target chain before, if so we
                # can skip it.
                if materialized.get(target_chain_id, 0) < target_sequence_number:
                    stack.append((target_chain_id, target_sequence_number))
                    materialized[target_chain_id] = target_sequence_number
            else:
                # Ignore any links that are lower down the chain.
                if sequence_number < s:
                    continue
                # Check if we have already visited the target chain before, if so we
                # can skip it.
                if (
                    materialized.get(target_chain_id, MAX_CHAIN_LENGTH)
                    > target_sequence_number
                ):
                    stack.append((target_chain_id, target_sequence_number))
                    materialized[target_chain_id] = target_sequence_number


def _generate_forward_links(
    links: dict[int, list[tuple[int, int, int]]],
) -> dict[int, list[tuple[int, int, int]]]:
    """Reverse the input links from the given backwards links"""
    new_links: dict[int, list[tuple[int, int, int]]] = {}
    for origin_chain_id, chain_links in links.items():
        for origin_seq_num, target_chain_id, target_seq_num in chain_links:
            new_links.setdefault(target_chain_id, []).append(
                (target_seq_num, origin_chain_id, origin_seq_num)
            )
    return new_links


def accumulate_forwards_reachable_events(
    conflicted_forwards_reachable: dict[int, int],
    back_links: dict[int, list[tuple[int, int, int]]],
    conflicted_chain_positions: dict[str, tuple[int, int]],
) -> None:
    """Accumulate new forwards reachable events using the back_links provided.

    Accumulating forwards reachable information is quite different from backwards reachable information
    because _get_chain_links returns the entire linkage information for backwards reachable events,
    but not _forwards_ reachable events. We are only interested in the forwards reachable information
    that is encoded in the backwards reachable links, so we can just invert all the operations we do
    for backwards reachable events to calculate a subset of forwards reachable information. The
    caveat with this approach is that it is a _subset_. This means new back_links may encode new
    forwards reachable information which we also need. Consider this scenario:

    A <-- B <-- C <--- D <-- E <-- F         Chain 1
                |
                `----- G <-- H <-- I         Chain 2
                             |
                             `---- J <-- K   Chain 3

    Now consider what happens when B is a conflicted event. _get_chain_links returns the conflicted
    chain and ALL links heading towards the root of the graph. This means we will know the
    Chain 1 to Chain 2 link via C (as all links for the chain are returned, not strictly ones with
    a lower sequence number), but we will NOT know the Chain 2 to Chain 3 link via H. We can be
    blissfully unaware of Chain 3 entirely, if and only if there isn't some other conflicted event
    on that chain. Consider what happens when K is /also/ conflicted. _get_chain_links will generate
    two iterations: one for B and one for K. It's important that we re-evaluate the forwards reachable
    information for B to include Chain 3 when we process the K iteration, hence we are "accumulating"
    forwards reachability information.

    NB: We don't consider 'additional backwards reachable events' here because they have no effect
    on forwards reachability calculations, only backwards.

    Args:
      conflicted_forwards_reachable: The materialised dict of forwards reachable information.
      The output to this function are stored here.
      back_links: One iteration of _get_chain_links which encodes backwards reachable information.
      conflicted_chain_positions: The conflicted events.
    """
    # links go backwards but we want them to go forwards as well for v2.1
    fwd_links = _generate_forward_links(back_links)

    # for each conflicted event, accumulate forwards reachability information
    for (
        conflicted_chain_id,
        conflicted_chain_seq,
    ) in conflicted_chain_positions.values():
        # the conflicted event itself encodes reachability information
        # e.g if D was conflicted, it encodes E,F as forwards reachable.
        conflicted_forwards_reachable[conflicted_chain_id] = min(
            conflicted_chain_seq,
            conflicted_forwards_reachable.get(conflicted_chain_id, MAX_CHAIN_LENGTH),
        )
        # Walk from the conflicted event forwards to explore the links.
        # This function checks if we've visited the chain before and skips reprocessing, so this
        # does not repeatedly traverse the graph.
        _materialize(
            conflicted_chain_id,
            conflicted_chain_seq,
            fwd_links,
            conflicted_forwards_reachable,
            backwards=False,
        )
