diff --git a/changelog.d/10078.misc b/changelog.d/10078.misc new file mode 100644 index 0000000000..a4b089d0fd --- /dev/null +++ b/changelog.d/10078.misc @@ -0,0 +1 @@ +Fix up `BatchingQueue` implementation. diff --git a/synapse/util/batching_queue.py b/synapse/util/batching_queue.py index 44bbb7b1a8..8fd5bfb69b 100644 --- a/synapse/util/batching_queue.py +++ b/synapse/util/batching_queue.py @@ -25,10 +25,11 @@ from typing import ( TypeVar, ) +from prometheus_client import Gauge + from twisted.internet import defer from synapse.logging.context import PreserveLoggingContext, make_deferred_yieldable -from synapse.metrics import LaterGauge from synapse.metrics.background_process_metrics import run_as_background_process from synapse.util import Clock @@ -38,6 +39,24 @@ logger = logging.getLogger(__name__) V = TypeVar("V") R = TypeVar("R") +number_queued = Gauge( + "synapse_util_batching_queue_number_queued", + "The number of items waiting in the queue across all keys", + labelnames=("name",), +) + +number_in_flight = Gauge( + "synapse_util_batching_queue_number_pending", + "The number of items across all keys either being processed or waiting in a queue", + labelnames=("name",), +) + +number_of_keys = Gauge( + "synapse_util_batching_queue_number_of_keys", + "The number of distinct keys that have items queued", + labelnames=("name",), +) + class BatchingQueue(Generic[V, R]): """A queue that batches up work, calling the provided processing function @@ -48,10 +67,20 @@ class BatchingQueue(Generic[V, R]): called, and will keep being called until the queue has been drained (for the given key). + If the processing function raises an exception then the exception is proxied + through to the callers waiting on that batch of work. + Note that the return value of `add_to_queue` will be the return value of the processing function that processed the given item. This means that the returned value will likely include data for other items that were in the batch. + + Args: + name: A name for the queue, used for logging contexts and metrics. + This must be unique, otherwise the metrics will be wrong. + clock: The clock to use to schedule work. + process_batch_callback: The callback to to be run to process a batch of + work. """ def __init__( @@ -73,19 +102,15 @@ class BatchingQueue(Generic[V, R]): # The function to call with batches of values. self._process_batch_callback = process_batch_callback - LaterGauge( - "synapse_util_batching_queue_number_queued", - "The number of items waiting in the queue across all keys", - labels=("name",), - caller=lambda: sum(len(v) for v in self._next_values.values()), + number_queued.labels(self._name).set_function( + lambda: sum(len(q) for q in self._next_values.values()) ) - LaterGauge( - "synapse_util_batching_queue_number_of_keys", - "The number of distinct keys that have items queued", - labels=("name",), - caller=lambda: len(self._next_values), - ) + number_of_keys.labels(self._name).set_function(lambda: len(self._next_values)) + + self._number_in_flight_metric = number_in_flight.labels( + self._name + ) # type: Gauge async def add_to_queue(self, value: V, key: Hashable = ()) -> R: """Adds the value to the queue with the given key, returning the result @@ -107,17 +132,18 @@ class BatchingQueue(Generic[V, R]): if key not in self._processing_keys: run_as_background_process(self._name, self._process_queue, key) - return await make_deferred_yieldable(d) + with self._number_in_flight_metric.track_inprogress(): + return await make_deferred_yieldable(d) async def _process_queue(self, key: Hashable) -> None: """A background task to repeatedly pull things off the queue for the given key and call the `self._process_batch_callback` with the values. """ - try: - if key in self._processing_keys: - return + if key in self._processing_keys: + return + try: self._processing_keys.add(key) while True: @@ -137,16 +163,16 @@ class BatchingQueue(Generic[V, R]): values = [value for value, _ in next_values] results = await self._process_batch_callback(values) - for _, deferred in next_values: - with PreserveLoggingContext(): + with PreserveLoggingContext(): + for _, deferred in next_values: deferred.callback(results) except Exception as e: - for _, deferred in next_values: - if deferred.called: - continue + with PreserveLoggingContext(): + for _, deferred in next_values: + if deferred.called: + continue - with PreserveLoggingContext(): deferred.errback(e) finally: diff --git a/tests/util/test_batching_queue.py b/tests/util/test_batching_queue.py index 5def1e56c9..edf29e5b96 100644 --- a/tests/util/test_batching_queue.py +++ b/tests/util/test_batching_queue.py @@ -14,7 +14,12 @@ from twisted.internet import defer from synapse.logging.context import make_deferred_yieldable -from synapse.util.batching_queue import BatchingQueue +from synapse.util.batching_queue import ( + BatchingQueue, + number_in_flight, + number_of_keys, + number_queued, +) from tests.server import get_clock from tests.unittest import TestCase @@ -24,6 +29,14 @@ class BatchingQueueTestCase(TestCase): def setUp(self): self.clock, hs_clock = get_clock() + # We ensure that we remove any existing metrics for "test_queue". + try: + number_queued.remove("test_queue") + number_of_keys.remove("test_queue") + number_in_flight.remove("test_queue") + except KeyError: + pass + self._pending_calls = [] self.queue = BatchingQueue("test_queue", hs_clock, self._process_queue) @@ -32,6 +45,41 @@ class BatchingQueueTestCase(TestCase): self._pending_calls.append((values, d)) return await make_deferred_yieldable(d) + def _assert_metrics(self, queued, keys, in_flight): + """Assert that the metrics are correct""" + + self.assertEqual(len(number_queued.collect()), 1) + self.assertEqual(len(number_queued.collect()[0].samples), 1) + self.assertEqual( + number_queued.collect()[0].samples[0].labels, + {"name": self.queue._name}, + ) + self.assertEqual( + number_queued.collect()[0].samples[0].value, + queued, + "number_queued", + ) + + self.assertEqual(len(number_of_keys.collect()), 1) + self.assertEqual(len(number_of_keys.collect()[0].samples), 1) + self.assertEqual( + number_queued.collect()[0].samples[0].labels, {"name": self.queue._name} + ) + self.assertEqual( + number_of_keys.collect()[0].samples[0].value, keys, "number_of_keys" + ) + + self.assertEqual(len(number_in_flight.collect()), 1) + self.assertEqual(len(number_in_flight.collect()[0].samples), 1) + self.assertEqual( + number_queued.collect()[0].samples[0].labels, {"name": self.queue._name} + ) + self.assertEqual( + number_in_flight.collect()[0].samples[0].value, + in_flight, + "number_in_flight", + ) + def test_simple(self): """Tests the basic case of calling `add_to_queue` once and having `_process_queue` return. @@ -41,6 +89,8 @@ class BatchingQueueTestCase(TestCase): queue_d = defer.ensureDeferred(self.queue.add_to_queue("foo")) + self._assert_metrics(queued=1, keys=1, in_flight=1) + # The queue should wait a reactor tick before calling the processing # function. self.assertFalse(self._pending_calls) @@ -52,12 +102,15 @@ class BatchingQueueTestCase(TestCase): self.assertEqual(len(self._pending_calls), 1) self.assertEqual(self._pending_calls[0][0], ["foo"]) self.assertFalse(queue_d.called) + self._assert_metrics(queued=0, keys=0, in_flight=1) # Return value of the `_process_queue` should be propagated back. self._pending_calls.pop()[1].callback("bar") self.assertEqual(self.successResultOf(queue_d), "bar") + self._assert_metrics(queued=0, keys=0, in_flight=0) + def test_batching(self): """Test that multiple calls at the same time get batched up into one call to `_process_queue`. @@ -68,6 +121,8 @@ class BatchingQueueTestCase(TestCase): queue_d1 = defer.ensureDeferred(self.queue.add_to_queue("foo1")) queue_d2 = defer.ensureDeferred(self.queue.add_to_queue("foo2")) + self._assert_metrics(queued=2, keys=1, in_flight=2) + self.clock.pump([0]) # We should see only *one* call to `_process_queue` @@ -75,12 +130,14 @@ class BatchingQueueTestCase(TestCase): self.assertEqual(self._pending_calls[0][0], ["foo1", "foo2"]) self.assertFalse(queue_d1.called) self.assertFalse(queue_d2.called) + self._assert_metrics(queued=0, keys=0, in_flight=2) # Return value of the `_process_queue` should be propagated back to both. self._pending_calls.pop()[1].callback("bar") self.assertEqual(self.successResultOf(queue_d1), "bar") self.assertEqual(self.successResultOf(queue_d2), "bar") + self._assert_metrics(queued=0, keys=0, in_flight=0) def test_queuing(self): """Test that we queue up requests while a `_process_queue` is being @@ -92,13 +149,20 @@ class BatchingQueueTestCase(TestCase): queue_d1 = defer.ensureDeferred(self.queue.add_to_queue("foo1")) self.clock.pump([0]) + self.assertEqual(len(self._pending_calls), 1) + + # We queue up work after the process function has been called, testing + # that they get correctly queued up. queue_d2 = defer.ensureDeferred(self.queue.add_to_queue("foo2")) + queue_d3 = defer.ensureDeferred(self.queue.add_to_queue("foo3")) # We should see only *one* call to `_process_queue` self.assertEqual(len(self._pending_calls), 1) self.assertEqual(self._pending_calls[0][0], ["foo1"]) self.assertFalse(queue_d1.called) self.assertFalse(queue_d2.called) + self.assertFalse(queue_d3.called) + self._assert_metrics(queued=2, keys=1, in_flight=3) # Return value of the `_process_queue` should be propagated back to the # first. @@ -106,18 +170,24 @@ class BatchingQueueTestCase(TestCase): self.assertEqual(self.successResultOf(queue_d1), "bar1") self.assertFalse(queue_d2.called) + self.assertFalse(queue_d3.called) + self._assert_metrics(queued=2, keys=1, in_flight=2) # We should now see a second call to `_process_queue` self.clock.pump([0]) self.assertEqual(len(self._pending_calls), 1) - self.assertEqual(self._pending_calls[0][0], ["foo2"]) + self.assertEqual(self._pending_calls[0][0], ["foo2", "foo3"]) self.assertFalse(queue_d2.called) + self.assertFalse(queue_d3.called) + self._assert_metrics(queued=0, keys=0, in_flight=2) # Return value of the `_process_queue` should be propagated back to the # second. self._pending_calls.pop()[1].callback("bar2") self.assertEqual(self.successResultOf(queue_d2), "bar2") + self.assertEqual(self.successResultOf(queue_d3), "bar2") + self._assert_metrics(queued=0, keys=0, in_flight=0) def test_different_keys(self): """Test that calls to different keys get processed in parallel.""" @@ -140,6 +210,7 @@ class BatchingQueueTestCase(TestCase): self.assertFalse(queue_d1.called) self.assertFalse(queue_d2.called) self.assertFalse(queue_d3.called) + self._assert_metrics(queued=1, keys=1, in_flight=3) # Return value of the `_process_queue` should be propagated back to the # first. @@ -148,6 +219,7 @@ class BatchingQueueTestCase(TestCase): self.assertEqual(self.successResultOf(queue_d1), "bar1") self.assertFalse(queue_d2.called) self.assertFalse(queue_d3.called) + self._assert_metrics(queued=1, keys=1, in_flight=2) # Return value of the `_process_queue` should be propagated back to the # second. @@ -161,9 +233,11 @@ class BatchingQueueTestCase(TestCase): self.assertEqual(len(self._pending_calls), 1) self.assertEqual(self._pending_calls[0][0], ["foo3"]) self.assertFalse(queue_d3.called) + self._assert_metrics(queued=0, keys=0, in_flight=1) # Return value of the `_process_queue` should be propagated back to the # third deferred. self._pending_calls.pop()[1].callback("bar4") self.assertEqual(self.successResultOf(queue_d3), "bar4") + self._assert_metrics(queued=0, keys=0, in_flight=0)