Report state res metrics to Prometheus and log

synapse/state/__init__.py

@@ -13,42 +13,46 @@
 # 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 namedtuple
+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 Histogram
+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 import Clock
 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(
@@ -459,6 +463,33 @@ class StateHandler:
         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.
 
@@ -481,6 +512,17 @@ class StateResolutionHandler:
             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,
@@ -578,7 +620,8 @@ class StateResolutionHandler:
         Returns:
             a map from (type, state_key) to event_id.
         """
-        with Measure(self.clock, "state._resolve_events"):
+        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(
@@ -593,6 +636,67 @@ class StateResolutionHandler:
                         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(