text: # -*- coding: utf-8 -*-
  # Copyright 2014-2016 OpenMarket Ltd
  # Copyright 2018 New Vector Ltd
  #
  # Licensed under the Apache License, Version 2.0 (the "License");
  # you may not use this file except in compliance with the License.
  # You may obtain a copy of the License at
  #
  #     http://www.apache.org/licenses/LICENSE-2.0
  #
  # Unless required by applicable law or agreed to in writing, software
  # distributed under the License is distributed on an "AS IS" BASIS,
  # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
  # See the License for the specific language governing permissions and
  # limitations under the License.
  import heapq
  import logging
  from collections import defaultdict, namedtuple
  from typing import (
      Any,
      Awaitable,
      Callable,
      DefaultDict,
      Dict,
      Iterable,
      List,
      Optional,
      Sequence,
      Set,
      Tuple,
      Union,
      overload,
  )
  
  import attr
  from frozendict import frozendict
  from prometheus_client import Counter, Histogram
  from typing_extensions import Literal
  
  from synapse.api.constants import EventTypes
  from synapse.api.room_versions import KNOWN_ROOM_VERSIONS, StateResolutionVersions
  from synapse.events import EventBase
  from synapse.events.snapshot import EventContext
  from synapse.logging.context import ContextResourceUsage
  from synapse.logging.utils import log_function
  from synapse.state import v1, v2
  from synapse.storage.databases.main.events_worker import EventRedactBehaviour
  from synapse.storage.roommember import ProfileInfo
  from synapse.types import Collection, StateMap
  from synapse.util.async_helpers import Linearizer
  from synapse.util.caches.expiringcache import ExpiringCache
  from synapse.util.metrics import Measure, measure_func
  
  logger = logging.getLogger(__name__)
  metrics_logger = logging.getLogger("synapse.state.metrics")
  
  # Metrics for number of state groups involved in a resolution.
  state_groups_histogram = Histogram(
      "synapse_state_number_state_groups_in_resolution",
      "Number of state groups used when performing a state resolution",
      buckets=(1, 2, 3, 5, 7, 10, 15, 20, 50, 100, 200, 500, "+Inf"),
  )
  
  
  KeyStateTuple = namedtuple("KeyStateTuple", ("context", "type", "state_key"))
  
  
  EVICTION_TIMEOUT_SECONDS = 60 * 60
  
  
  _NEXT_STATE_ID = 1
  
  POWER_KEY = (EventTypes.PowerLevels, "")
  
  
  def _gen_state_id():
      global _NEXT_STATE_ID
      s = "X%d" % (_NEXT_STATE_ID,)
      _NEXT_STATE_ID += 1
      return s
  
  
  class _StateCacheEntry:
      __slots__ = ["state", "state_group", "state_id", "prev_group", "delta_ids"]
  
      def __init__(
          self,
          state: StateMap[str],
          state_group: Optional[int],
          prev_group: Optional[int] = None,
          delta_ids: Optional[StateMap[str]] = None,
      ):
          # A map from (type, state_key) to event_id.
          self.state = frozendict(state)
  
          # the ID of a state group if one and only one is involved.
          # otherwise, None otherwise?
          self.state_group = state_group
  
          self.prev_group = prev_group
          self.delta_ids = frozendict(delta_ids) if delta_ids is not None else None
  
          # The `state_id` is a unique ID we generate that can be used as ID for
          # this collection of state. Usually this would be the same as the
          # state group, but on worker instances we can't generate a new state
          # group each time we resolve state, so we generate a separate one that
          # isn't persisted and is used solely for caches.
          # `state_id` is either a state_group (and so an int) or a string. This
          # ensures we don't accidentally persist a state_id as a stateg_group
          if state_group:
              self.state_id = state_group
          else:
              self.state_id = _gen_state_id()
  
      def __len__(self):
          return len(self.state)
  
  
  class StateHandler:
      """Fetches bits of state from the stores, and does state resolution
      where necessary
      """
  
      def __init__(self, hs):
          self.clock = hs.get_clock()
          self.store = hs.get_datastore()
          self.state_store = hs.get_storage().state
          self.hs = hs
          self._state_resolution_handler = hs.get_state_resolution_handler()
  
      @overload
      async def get_current_state(
          self,
          room_id: str,
          event_type: Literal[None] = None,
          state_key: str = "",
          latest_event_ids: Optional[List[str]] = None,
      ) -> StateMap[EventBase]:
          ...
  
      @overload
      async def get_current_state(
          self,
          room_id: str,
          event_type: str,
          state_key: str = "",
          latest_event_ids: Optional[List[str]] = None,
      ) -> Optional[EventBase]:
          ...
  
      async def get_current_state(
          self,
          room_id: str,
          event_type: Optional[str] = None,
          state_key: str = "",
          latest_event_ids: Optional[List[str]] = None,
      ) -> Union[Optional[EventBase], StateMap[EventBase]]:
          """Retrieves the current state for the room. This is done by
          calling `get_latest_events_in_room` to get the leading edges of the
          event graph and then resolving any of the state conflicts.
  
          This is equivalent to getting the state of an event that were to send
          next before receiving any new events.
  
          Returns:
              If `event_type` is specified, then the method returns only the one
              event (or None) with that `event_type` and `state_key`.
  
              Otherwise, a map from (type, state_key) to event.
          """
          if not latest_event_ids:
              latest_event_ids = await self.store.get_latest_event_ids_in_room(room_id)
          assert latest_event_ids is not None
  
          logger.debug("calling resolve_state_groups from get_current_state")
          ret = await self.resolve_state_groups_for_events(room_id, latest_event_ids)
          state = ret.state
  
          if event_type:
              event_id = state.get((event_type, state_key))
              event = None
              if event_id:
                  event = await self.store.get_event(event_id, allow_none=True)
              return event
  
          state_map = await self.store.get_events(
              list(state.values()), get_prev_content=False
          )
          return {
              key: state_map[e_id] for key, e_id in state.items() if e_id in state_map
          }
  
      async def get_current_state_ids(
          self, room_id: str, latest_event_ids: Optional[Iterable[str]] = None
      ) -> StateMap[str]:
          """Get the current state, or the state at a set of events, for a room
  
          Args:
              room_id:
              latest_event_ids: if given, the forward extremities to resolve. If
                  None, we look them up from the database (via a cache).
  
          Returns:
              the state dict, mapping from (event_type, state_key) -> event_id
          """
          if not latest_event_ids:
              latest_event_ids = await self.store.get_latest_event_ids_in_room(room_id)
          assert latest_event_ids is not None
  
          logger.debug("calling resolve_state_groups from get_current_state_ids")
          ret = await self.resolve_state_groups_for_events(room_id, latest_event_ids)
          return ret.state
  
      async def get_current_users_in_room(
          self, room_id: str, latest_event_ids: Optional[List[str]] = None
      ) -> Dict[str, ProfileInfo]:
          """
          Get the users who are currently in a room.
  
          Args:
              room_id: The ID of the room.
              latest_event_ids: Precomputed list of latest event IDs. Will be computed if None.
          Returns:
              Dictionary of user IDs to their profileinfo.
          """
          if not latest_event_ids:
              latest_event_ids = await self.store.get_latest_event_ids_in_room(room_id)
          assert latest_event_ids is not None
  
          logger.debug("calling resolve_state_groups from get_current_users_in_room")
          entry = await self.resolve_state_groups_for_events(room_id, latest_event_ids)
          return await self.store.get_joined_users_from_state(room_id, entry)
  
      async def get_current_hosts_in_room(self, room_id: str) -> Set[str]:
          event_ids = await self.store.get_latest_event_ids_in_room(room_id)
          return await self.get_hosts_in_room_at_events(room_id, event_ids)
  
      async def get_hosts_in_room_at_events(
          self, room_id: str, event_ids: List[str]
      ) -> Set[str]:
          """Get the hosts that were in a room at the given event ids
  
          Args:
              room_id:
              event_ids:
  
          Returns:
              The hosts in the room at the given events
          """
          entry = await self.resolve_state_groups_for_events(room_id, event_ids)
          return await self.store.get_joined_hosts(room_id, entry)
  
      async def compute_event_context(
          self, event: EventBase, old_state: Optional[Iterable[EventBase]] = None
      ) -> EventContext:
          """Build an EventContext structure for the event.
  
          This works out what the current state should be for the event, and
          generates a new state group if necessary.
  
          Args:
              event:
              old_state: The state at the event if it can't be
                  calculated from existing events. This is normally only specified
                  when receiving an event from federation where we don't have the
                  prev events for, e.g. when backfilling.
          Returns:
              The event context.
          """
  
          if event.internal_metadata.is_outlier():
              # If this is an outlier, then we know it shouldn't have any current
              # state. Certainly store.get_current_state won't return any, and
              # persisting the event won't store the state group.
  
              # FIXME: why do we populate current_state_ids? I thought the point was
              # that we weren't supposed to have any state for outliers?
              if old_state:
                  prev_state_ids = {(s.type, s.state_key): s.event_id for s in old_state}
                  if event.is_state():
                      current_state_ids = dict(prev_state_ids)
                      key = (event.type, event.state_key)
                      current_state_ids[key] = event.event_id
                  else:
                      current_state_ids = prev_state_ids
              else:
                  current_state_ids = {}
                  prev_state_ids = {}
  
              # We don't store state for outliers, so we don't generate a state
              # group for it.
              context = EventContext.with_state(
                  state_group=None,
                  state_group_before_event=None,
                  current_state_ids=current_state_ids,
                  prev_state_ids=prev_state_ids,
              )
  
              return context
  
          #
          # first of all, figure out the state before the event
          #
  
          if old_state:
              # if we're given the state before the event, then we use that
              state_ids_before_event = {
                  (s.type, s.state_key): s.event_id for s in old_state
              }  # type: StateMap[str]
              state_group_before_event = None
              state_group_before_event_prev_group = None
              deltas_to_state_group_before_event = None
              entry = None
  
          else:
              # otherwise, we'll need to resolve the state across the prev_events.
              logger.debug("calling resolve_state_groups from compute_event_context")
  
              entry = await self.resolve_state_groups_for_events(
                  event.room_id, event.prev_event_ids()
              )
  
              state_ids_before_event = entry.state
              state_group_before_event = entry.state_group
              state_group_before_event_prev_group = entry.prev_group
              deltas_to_state_group_before_event = entry.delta_ids
  
          #
          # make sure that we have a state group at that point. If it's not a state event,
          # that will be the state group for the new event. If it *is* a state event,
          # it might get rejected (in which case we'll need to persist it with the
          # previous state group)
          #
  
          if not state_group_before_event:
              state_group_before_event = await self.state_store.store_state_group(
                  event.event_id,
                  event.room_id,
                  prev_group=state_group_before_event_prev_group,
                  delta_ids=deltas_to_state_group_before_event,
                  current_state_ids=state_ids_before_event,
              )
  
              # Assign the new state group to the cached state entry.
              #
              # Note that this can race in that we could generate multiple state
              # groups for the same state entry, but that is just inefficient
              # rather than dangerous.
              if entry and entry.state_group is None:
                  entry.state_group = state_group_before_event
  
          #
          # now if it's not a state event, we're done
          #
  
          if not event.is_state():
              return EventContext.with_state(
                  state_group_before_event=state_group_before_event,
                  state_group=state_group_before_event,
                  current_state_ids=state_ids_before_event,
                  prev_state_ids=state_ids_before_event,
                  prev_group=state_group_before_event_prev_group,
                  delta_ids=deltas_to_state_group_before_event,
              )
  
          #
          # otherwise, we'll need to create a new state group for after the event
          #
  
          key = (event.type, event.state_key)
          if key in state_ids_before_event:
              replaces = state_ids_before_event[key]
              if replaces != event.event_id:
                  event.unsigned["replaces_state"] = replaces
  
          state_ids_after_event = dict(state_ids_before_event)
          state_ids_after_event[key] = event.event_id
          delta_ids = {key: event.event_id}
  
          state_group_after_event = await self.state_store.store_state_group(
              event.event_id,
              event.room_id,
              prev_group=state_group_before_event,
              delta_ids=delta_ids,
              current_state_ids=state_ids_after_event,
          )
  
          return EventContext.with_state(
              state_group=state_group_after_event,
              state_group_before_event=state_group_before_event,
              current_state_ids=state_ids_after_event,
              prev_state_ids=state_ids_before_event,
              prev_group=state_group_before_event,
              delta_ids=delta_ids,
          )
  
      @measure_func()
      async def resolve_state_groups_for_events(
          self, room_id: str, event_ids: Iterable[str]
      ) -> _StateCacheEntry:
          """ Given a list of event_ids this method fetches the state at each
          event, resolves conflicts between them and returns them.
  
          Args:
              room_id
              event_ids
  
          Returns:
              The resolved state
          """
          logger.debug("resolve_state_groups event_ids %s", event_ids)
  
          # map from state group id to the state in that state group (where
          # 'state' is a map from state key to event id)
          # dict[int, dict[(str, str), str]]
          state_groups_ids = await self.state_store.get_state_groups_ids(
              room_id, event_ids
          )
  
          if len(state_groups_ids) == 0:
              return _StateCacheEntry(state={}, state_group=None)
          elif len(state_groups_ids) == 1:
              name, state_list = list(state_groups_ids.items()).pop()
  
              prev_group, delta_ids = await self.state_store.get_state_group_delta(name)
  
              return _StateCacheEntry(
                  state=state_list,
                  state_group=name,
                  prev_group=prev_group,
                  delta_ids=delta_ids,
              )
  
          room_version = await self.store.get_room_version_id(room_id)
  
          result = await self._state_resolution_handler.resolve_state_groups(
              room_id,
              room_version,
              state_groups_ids,
              None,
              state_res_store=StateResolutionStore(self.store),
          )
          return result
  
      async def resolve_events(
          self,
          room_version: str,
          state_sets: Collection[Iterable[EventBase]],
          event: EventBase,
      ) -> StateMap[EventBase]:
          logger.info(
              "Resolving state for %s with %d groups", event.room_id, len(state_sets)
          )
          state_set_ids = [
              {(ev.type, ev.state_key): ev.event_id for ev in st} for st in state_sets
          ]
  
          state_map = {ev.event_id: ev for st in state_sets for ev in st}
  
          new_state = await self._state_resolution_handler.resolve_events_with_store(
              event.room_id,
              room_version,
              state_set_ids,
              event_map=state_map,
              state_res_store=StateResolutionStore(self.store),
          )
  
          return {key: state_map[ev_id] for key, ev_id in new_state.items()}
  
  
  @attr.s(slots=True)
  class _StateResMetrics:
      """Keeps track of some usage metrics about state res."""
  
      # System and User CPU time, in seconds
      cpu_time = attr.ib(type=float, default=0.0)
  
      # time spent on database transactions (excluding scheduling time). This roughly
      # corresponds to the amount of work done on the db server, excluding event fetches.
      db_time = attr.ib(type=float, default=0.0)
  
      # number of events fetched from the db.
      db_events = attr.ib(type=int, default=0)
  
  
  _biggest_room_by_cpu_counter = Counter(
      "synapse_state_res_cpu_for_biggest_room_seconds",
      "CPU time spent performing state resolution for the single most expensive "
      "room for state resolution",
  )
  _biggest_room_by_db_counter = Counter(
      "synapse_state_res_db_for_biggest_room_seconds",
      "Database time spent performing state resolution for the single most "
      "expensive room for state resolution",
  )
  
  
  class StateResolutionHandler:
      """Responsible for doing state conflict resolution.
  
      Note that the storage layer depends on this handler, so all functions must
      be storage-independent.
      """
  
      def __init__(self, hs):
          self.clock = hs.get_clock()
  
          self.resolve_linearizer = Linearizer(name="state_resolve_lock")
  
          # dict of set of event_ids -> _StateCacheEntry.
          self._state_cache = ExpiringCache(
              cache_name="state_cache",
              clock=self.clock,
              max_len=100000,
              expiry_ms=EVICTION_TIMEOUT_SECONDS * 1000,
              iterable=True,
              reset_expiry_on_get=True,
          )
  
          #
          # stuff for tracking time spent on state-res by room
          #
  
          # tracks the amount of work done on state res per room
          self._state_res_metrics = defaultdict(
              _StateResMetrics
          )  # type: DefaultDict[str, _StateResMetrics]
  
          self.clock.looping_call(self._report_metrics, 120 * 1000)
  
      @log_function
      async def resolve_state_groups(
          self,
          room_id: str,
          room_version: str,
          state_groups_ids: Dict[int, StateMap[str]],
          event_map: Optional[Dict[str, EventBase]],
          state_res_store: "StateResolutionStore",
      ):
          """Resolves conflicts between a set of state groups
  
          Always generates a new state group (unless we hit the cache), so should
          not be called for a single state group
  
          Args:
              room_id: room we are resolving for (used for logging and sanity checks)
              room_version: version of the room
              state_groups_ids:
                  A map from state group id to the state in that state group
                  (where 'state' is a map from state key to event id)
  
              event_map:
                  a dict from event_id to event, for any events that we happen to
                  have in flight (eg, those currently being persisted). This will be
                  used as a starting point for finding the state we need; any missing
                  events will be requested via state_res_store.
  
                  If None, all events will be fetched via state_res_store.
  
              state_res_store
  
          Returns:
              The resolved state
          """
          group_names = frozenset(state_groups_ids.keys())
  
          with (await self.resolve_linearizer.queue(group_names)):
              cache = self._state_cache.get(group_names, None)
              if cache:
                  return cache
  
              logger.info(
                  "Resolving state for %s with groups %s", room_id, list(group_names),
              )
  
              state_groups_histogram.observe(len(state_groups_ids))
  
              new_state = await self.resolve_events_with_store(
                  room_id,
                  room_version,
                  list(state_groups_ids.values()),
                  event_map=event_map,
                  state_res_store=state_res_store,
              )
  
              # if the new state matches any of the input state groups, we can
              # use that state group again. Otherwise we will generate a state_id
              # which will be used as a cache key for future resolutions, but
              # not get persisted.
  
              with Measure(self.clock, "state.create_group_ids"):
                  cache = _make_state_cache_entry(new_state, state_groups_ids)
  
              self._state_cache[group_names] = cache
  
              return cache
  
      async def resolve_events_with_store(
          self,
          room_id: str,
          room_version: str,
          state_sets: Sequence[StateMap[str]],
          event_map: Optional[Dict[str, EventBase]],
          state_res_store: "StateResolutionStore",
      ) -> StateMap[str]:
          """
          Args:
              room_id: the room we are working in
  
              room_version: Version of the room
  
              state_sets: List of dicts of (type, state_key) -> event_id,
                  which are the different state groups to resolve.
  
              event_map:
                  a dict from event_id to event, for any events that we happen to
                  have in flight (eg, those currently being persisted). This will be
                  used as a starting point fof finding the state we need; any missing
                  events will be requested via state_map_factory.
  
                  If None, all events will be fetched via state_res_store.
  
              state_res_store: a place to fetch events from
  
          Returns:
              a map from (type, state_key) to event_id.
          """
          try:
              with Measure(self.clock, "state._resolve_events") as m:
                  v = KNOWN_ROOM_VERSIONS[room_version]
                  if v.state_res == StateResolutionVersions.V1:
                      return await v1.resolve_events_with_store(
                          room_id, state_sets, event_map, state_res_store.get_events
                      )
                  else:
                      return await v2.resolve_events_with_store(
                          self.clock,
                          room_id,
                          room_version,
                          state_sets,
                          event_map,
                          state_res_store,
                      )
          finally:
              self._record_state_res_metrics(room_id, m.get_resource_usage())
  
      def _record_state_res_metrics(self, room_id: str, rusage: ContextResourceUsage):
          room_metrics = self._state_res_metrics[room_id]
          room_metrics.cpu_time += rusage.ru_utime + rusage.ru_stime
          room_metrics.db_time += rusage.db_txn_duration_sec
          room_metrics.db_events += rusage.evt_db_fetch_count
  
      def _report_metrics(self):
          if not self._state_res_metrics:
              # no state res has happened since the last iteration: don't bother logging.
              return
  
          self._report_biggest(
              lambda i: i.cpu_time, "CPU time", _biggest_room_by_cpu_counter,
          )
  
          self._report_biggest(
              lambda i: i.db_time, "DB time", _biggest_room_by_db_counter,
          )
  
          self._state_res_metrics.clear()
  
      def _report_biggest(
          self,
          extract_key: Callable[[_StateResMetrics], Any],
          metric_name: str,
          prometheus_counter_metric: Counter,
      ) -> None:
          """Report metrics on the biggest rooms for state res
  
          Args:
              extract_key: a callable which, given a _StateResMetrics, extracts a single
                  metric to sort by.
              metric_name: the name of the metric we have extracted, for the log line
              prometheus_counter_metric: a prometheus metric recording the sum of the
                  the extracted metric
          """
          n_to_log = 10
          if not metrics_logger.isEnabledFor(logging.DEBUG):
              # only need the most expensive if we don't have debug logging, which
              # allows nlargest() to degrade to max()
              n_to_log = 1
  
          items = self._state_res_metrics.items()
  
          # log the N biggest rooms
          biggest = heapq.nlargest(
              n_to_log, items, key=lambda i: extract_key(i[1])
          )  # type: List[Tuple[str, _StateResMetrics]]
          metrics_logger.debug(
              "%i biggest rooms for state-res by %s: %s",
              len(biggest),
              metric_name,
              ["%s (%gs)" % (r, extract_key(m)) for (r, m) in biggest],
          )
  
          # report info on the single biggest to prometheus
          _, biggest_metrics = biggest[0]
          prometheus_counter_metric.inc(extract_key(biggest_metrics))
  
  
  def _make_state_cache_entry(
      new_state: StateMap[str], state_groups_ids: Dict[int, StateMap[str]]
  ) -> _StateCacheEntry:
      """Given a resolved state, and a set of input state groups, pick one to base
      a new state group on (if any), and return an appropriately-constructed
      _StateCacheEntry.
  
      Args:
          new_state: resolved state map (mapping from (type, state_key) to event_id)
  
          state_groups_ids:
              map from state group id to the state in that state group (where
              'state' is a map from state key to event id)
  
      Returns:
          The cache entry.
      """
      # if the new state matches any of the input state groups, we can
      # use that state group again. Otherwise we will generate a state_id
      # which will be used as a cache key for future resolutions, but
      # not get persisted.
  
      # first look for exact matches
      new_state_event_ids = set(new_state.values())
      for sg, state in state_groups_ids.items():
          if len(new_state_event_ids) != len(state):
              continue
  
          old_state_event_ids = set(state.values())
          if new_state_event_ids == old_state_event_ids:
              # got an exact match.
              return _StateCacheEntry(state=new_state, state_group=sg)
  
      # TODO: We want to create a state group for this set of events, to
      # increase cache hits, but we need to make sure that it doesn't
      # end up as a prev_group without being added to the database
  
      # failing that, look for the closest match.
      prev_group = None
      delta_ids = None  # type: Optional[StateMap[str]]
  
      for old_group, old_state in state_groups_ids.items():
          n_delta_ids = {k: v for k, v in new_state.items() if old_state.get(k) != v}
          if not delta_ids or len(n_delta_ids) < len(delta_ids):
              prev_group = old_group
              delta_ids = n_delta_ids
  
      return _StateCacheEntry(
          state=new_state, state_group=None, prev_group=prev_group, delta_ids=delta_ids
      )
  
  
  @attr.s(slots=True)
  class StateResolutionStore:
      """Interface that allows state resolution algorithms to access the database
      in well defined way.
  
      Args:
          store (DataStore)
      """
  
      store = attr.ib()
  
      def get_events(
          self, event_ids: Iterable[str], allow_rejected: bool = False
      ) -> Awaitable[Dict[str, EventBase]]:
          """Get events from the database
  
          Args:
              event_ids: The event_ids of the events to fetch
              allow_rejected: If True return rejected events.
  
          Returns:
              An awaitable which resolves to a dict from event_id to event.
          """
  
          return self.store.get_events(
              event_ids,
              redact_behaviour=EventRedactBehaviour.AS_IS,
              get_prev_content=False,
              allow_rejected=allow_rejected,
          )
  
      def get_auth_chain_difference(
          self, room_id: str, state_sets: List[Set[str]]
      ) -> Awaitable[Set[str]]:
          """Given sets of state events figure out the auth chain difference (as
          per state res v2 algorithm).
  
          This 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.
  
          Returns:
              An awaitable that resolves to a set of event IDs.
          """
  
          return self.store.get_auth_chain_difference(room_id, state_sets)
  