DM-48288: Do not cache collection summaries by default in queries

python/lsst/daf/butler/_query_all_datasets.py

@@ -113,30 +113,33 @@
         raise InvalidQueryError("Can not use wildcards in collections when find_first=True")
 
     dataset_type_query = list(ensure_iterable(args.name))
-    dataset_type_collections = _filter_collections_and_dataset_types(
-        butler, args.collections, dataset_type_query
-    )
 
-    limit = args.limit
-    for dt, filtered_collections in sorted(dataset_type_collections.items()):
-        _LOG.debug("Querying dataset type %s", dt)
-        results = (
-            query.datasets(dt, filtered_collections, find_first=args.find_first)
-            .where(args.data_id, args.where, args.kwargs, bind=args.bind)
-            .limit(limit)
+    with butler.registry.caching_context():
+        dataset_type_collections = _filter_collections_and_dataset_types(
+            butler, args.collections, dataset_type_query
         )
-        if args.with_dimension_records:
-            results = results.with_dimension_records()
-
-        for page in results._iter_pages():
-            if limit is not None:
-                # Track how much of the limit has been used up by each query.
-                limit -= len(page)
-
-            yield DatasetsPage(dataset_type=dt, data=page)
 
-        if limit is not None and limit <= 0:
-            break
+        limit = args.limit
+        for dt, filtered_collections in sorted(dataset_type_collections.items()):
+            _LOG.debug("Querying dataset type %s", dt)
+            results = (
+                query.datasets(dt, filtered_collections, find_first=args.find_first)
+                .where(args.data_id, args.where, args.kwargs, bind=args.bind)
+                .limit(limit)
+            )
+            if args.with_dimension_records:
+                results = results.with_dimension_records()
+
+            for page in results._iter_pages():
+                if limit is not None:
+                    # Track how much of the limit has been used up by each
+                    # query.
+                    limit -= len(page)
+
+                yield DatasetsPage(dataset_type=dt, data=page)
+
+            if limit is not None and limit <= 0:
+                break
 
 
 def _filter_collections_and_dataset_types(

python/lsst/daf/butler/direct_butler/_direct_butler.py

@@ -1426,18 +1426,19 @@
         names = list(names)
         refs: list[DatasetRef] = []
         all_dataset_types = [dt.name for dt in self._registry.queryDatasetTypes(...)]
-        for name in names:
-            collectionType = self._registry.getCollectionType(name)
-            if collectionType is not CollectionType.RUN:
-                raise TypeError(f"The collection type of '{name}' is {collectionType.name}, not RUN.")
-            with self.query() as query:
-                # Work out the dataset types that are relevant.
-                collections_info = self.collections.query_info(name, include_summary=True)
-                filtered_dataset_types = self.collections._filter_dataset_types(
-                    all_dataset_types, collections_info
-                )
-                for dt in filtered_dataset_types:
-                    refs.extend(query.datasets(dt, collections=name))
+        with self._caching_context():
+            for name in names:
+                collectionType = self._registry.getCollectionType(name)
+                if collectionType is not CollectionType.RUN:
+                    raise TypeError(f"The collection type of '{name}' is {collectionType.name}, not RUN.")
+                with self.query() as query:
+                    # Work out the dataset types that are relevant.
+                    collections_info = self.collections.query_info(name, include_summary=True)
+                    filtered_dataset_types = self.collections._filter_dataset_types(
+                        all_dataset_types, collections_info
+                    )
+                    for dt in filtered_dataset_types:
+                        refs.extend(query.datasets(dt, collections=name))
         with self._datastore.transaction(), self._registry.transaction():
             if unstore:
                 self._datastore.trash(refs)

python/lsst/daf/butler/registry/_caching_context.py

@@ -27,6 +27,10 @@
 
 from __future__ import annotations
 
+from collections.abc import Callable, Iterator
+from contextlib import AbstractContextManager, contextmanager
+from typing import Generic, TypeVar
+
 __all__ = ["CachingContext"]
 
 from ._collection_record_cache import CollectionRecordCache
@@ -48,46 +52,70 @@ class is passed to the relevant managers that can use it to query or
     """
 
     def __init__(self) -> None:
-        self._collection_records: CollectionRecordCache | None = None
-        self._collection_summaries: CollectionSummaryCache | None = None
-        self._depth = 0
+        self._collection_records = _CacheToggle(CollectionRecordCache)
+        self._collection_summaries = _CacheToggle(CollectionSummaryCache)
 
-    @property
-    def is_enabled(self) -> bool:
-        return self._collection_records is not None
+    def enable_collection_record_cache(self) -> AbstractContextManager[None]:
+        """Enable the collection record cache.
 
-    def _enable(self) -> None:
-        """Enable caches.
-
-        For use only by RegistryManagerInstances, which is the single point
-        of entry for enabling and disabling the caches.
+        Notes
+        -----
+        When this cache is enabled, any changes made by other processes to
+        collections in the database may not be visible.
         """
-        if self._depth == 0:
-            self._collection_records = CollectionRecordCache()
-            self._collection_summaries = CollectionSummaryCache()
-        self._depth += 1
+        return self._collection_records.enable()
 
-    def _disable(self) -> None:
-        """Disable caches.
+    def enable_collection_summary_cache(self) -> AbstractContextManager[None]:
+        """Enable the collection summary cache.
 
-        For use only by RegistryManagerInstances, which is the single point
-        of entry for enabling and disabling the caches.
+        Notes
+        -----
+        When this cache is enabled, changes made by other processes to
+        collections in the database may not be visible.
+
+        When the collection summary cache is enabled, the performance of
+        database lookups for summaries changes.  Summaries will be aggressively
+        fetched for all dataset types in the collections, which can cause
+        significantly more rows to be returned than when the cache is disabled.
+        This should only be enabled when you know that you will be doing many
+        summary lookups for the same collections.
         """
-        if self._depth == 1:
-            self._collection_records = None
-            self._collection_summaries = None
-            self._depth = 0
-        elif self._depth > 1:
-            self._depth -= 1
-        else:
-            raise AssertionError("Bad caching context management detected.")
+        return self._collection_summaries.enable()
 
     @property
     def collection_records(self) -> CollectionRecordCache | None:
         """Cache for collection records (`CollectionRecordCache`)."""
-        return self._collection_records
+        return self._collection_records.cache
 
     @property
     def collection_summaries(self) -> CollectionSummaryCache | None:
         """Cache for collection summary records (`CollectionSummaryCache`)."""
-        return self._collection_summaries
+        return self._collection_summaries.cache
+
+
+_T = TypeVar("_T")
+
+
+class _CacheToggle(Generic[_T]):
+    """Utility class to track nested enable/disable calls for a cache."""
+
+    def __init__(self, enable_function: Callable[[], _T]):
+        self.cache: _T | None = None
+        self._enable_function = enable_function
+        self._depth = 0
+
+    @contextmanager
+    def enable(self) -> Iterator[None]:
+        """Context manager to enable the cache.  This context may be nested any
+        number of times, and the cache will only be disabled once all callers
+        have exited the context manager.
+        """
+        self._depth += 1
+        try:
+            if self._depth == 1:
+                self.cache = self._enable_function()
+            yield
+        finally:
+            self._depth -= 1
+            if self._depth == 0:
+                self.cache = None

python/lsst/daf/butler/registry/collections/_base.py

@@ -581,7 +581,7 @@ def _modify_collection_chain(
         skip_caching_check: bool = False,
         skip_cycle_check: bool = False,
     ) -> Iterator[_CollectionChainModificationContext[K]]:
-        if (not skip_caching_check) and self._caching_context.is_enabled:
+        if (not skip_caching_check) and self._caching_context.collection_records is not None:
             # Avoid having cache-maintenance code around that is unlikely to
             # ever be used.
             raise RuntimeError("Chained collection modification not permitted with active caching context.")

python/lsst/daf/butler/registry/managers.py

@@ -362,11 +362,11 @@ def caching_context_manager(self) -> Iterator[None]:
         may even be closed out of order, with only the context manager entered
         and the last context manager exited having any effect.
         """
-        self.caching_context._enable()
-        try:
+        with (
+            self.caching_context.enable_collection_record_cache(),
+            self.caching_context.enable_collection_summary_cache(),
+        ):
             yield
-        finally:
-            self.caching_context._disable()
 
     @classmethod
     def initialize(

python/lsst/daf/butler/registry/queries/_sql_query_backend.py

@@ -86,7 +86,7 @@ def context(self) -> SqlQueryContext:
 
     def get_collection_name(self, key: Any) -> str:
         assert (
-            self._managers.caching_context.is_enabled
+            self._managers.caching_context.collection_records is not None
         ), "Collection-record caching should already been enabled any time this is called."
         return self._managers.collections[key].name
 

python/lsst/daf/butler/registry/sql_registry.py

@@ -2332,7 +2332,9 @@ def _query_driver(
         default_data_id: DataCoordinate,
     ) -> Iterator[DirectQueryDriver]:
         """Set up a `QueryDriver` instance for query execution."""
-        with self.caching_context():
+        # Query internals do repeated lookups of the same collections, so it
+        # benefits from the collection record cache.
+        with self._managers.caching_context.enable_collection_record_cache():
             driver = DirectQueryDriver(
                 self._db,
                 self.dimensions,

python/lsst/daf/butler/script/removeRuns.py

@@ -86,29 +86,34 @@ def _getCollectionInfo(
         The dataset types and and how many will be removed.
     """
     butler = Butler.from_config(repo)
-    try:
-        collections = butler.collections.query_info(
-            collection, CollectionType.RUN, include_chains=False, include_parents=True, include_summary=True
-        )
-    except MissingCollectionError:
-        # Act as if no collections matched.
-        collections = []
-    dataset_types = [dt.name for dt in butler.registry.queryDatasetTypes(...)]
-    dataset_types = list(butler.collections._filter_dataset_types(dataset_types, collections))
-
-    runs = []
-    datasets: dict[str, int] = defaultdict(int)
-    for collection_info in collections:
-        assert collection_info.type == CollectionType.RUN and collection_info.parents is not None
-        runs.append(RemoveRun(collection_info.name, list(collection_info.parents)))
-        with butler.query() as query:
-            for dt in dataset_types:
-                results = query.datasets(dt, collections=collection_info.name)
-                count = results.count(exact=False)
-                if count:
-                    datasets[dt] += count
-
-    return runs, {k: datasets[k] for k in sorted(datasets.keys())}
+    with butler.registry.caching_context():
+        try:
+            collections = butler.collections.query_info(
+                collection,
+                CollectionType.RUN,
+                include_chains=False,
+                include_parents=True,
+                include_summary=True,
+            )
+        except MissingCollectionError:
+            # Act as if no collections matched.
+            collections = []
+        dataset_types = [dt.name for dt in butler.registry.queryDatasetTypes(...)]
+        dataset_types = list(butler.collections._filter_dataset_types(dataset_types, collections))
+
+        runs = []
+        datasets: dict[str, int] = defaultdict(int)
+        for collection_info in collections:
+            assert collection_info.type == CollectionType.RUN and collection_info.parents is not None
+            runs.append(RemoveRun(collection_info.name, list(collection_info.parents)))
+            with butler.query() as query:
+                for dt in dataset_types:
+                    results = query.datasets(dt, collections=collection_info.name)
+                    count = results.count(exact=False)
+                    if count:
+                        datasets[dt] += count
+
+        return runs, {k: datasets[k] for k in sorted(datasets.keys())}
 
 
 def removeRuns(