Archive: Respect filter_size in query for existing nodes

The `QueryParams` dataclass defines the `filter_size` attribute which is
used in all queries to limit the number of parameters used in a query.
This is necessary because without it, large archives would result in
queries with a lot of parameters which can cause exceptions in database
backends, such as SQLite, which define a limit of 1000 by default.

The `aiida.tools.archive._import_nodes` function was not respecting this
setting when determining the set of nodes from the archive that already
exist in the target storage. This would result in an exception when
trying to import a large archive into a storage using SQLite. The
problem is fixed by using the `batch_iter` utility to retrieve the
existing UUIDs in batches of size `filter_size`.

src/aiida/tools/archive/imports.py

@@ -460,12 +460,17 @@ def _import_nodes(
 
     # get matching uuids from the backend
     backend_uuid_id: Dict[str, int] = {}
+    input_id_uuid_uuids = list(input_id_uuid.values())
+
     if input_id_uuid:
-        backend_uuid_id = dict(
-            orm.QueryBuilder(backend=backend_to)
-            .append(orm.Node, filters={'uuid': {'in': list(input_id_uuid.values())}}, project=['uuid', 'id'])
-            .all(batch_size=query_params.batch_size)
-        )
+        for _, batch in batch_iter(input_id_uuid_uuids, query_params.filter_size):
+            backend_uuid_id.update(
+                dict(
+                    orm.QueryBuilder(backend=backend_to)
+                    .append(orm.Node, filters={'uuid': {'in': batch}}, project=['uuid', 'id'])
+                    .all(batch_size=query_params.batch_size)
+                )
+            )
 
     new_nodes = len(input_id_uuid) - len(backend_uuid_id)