Add GeneratedClassRowTypeConstraint

sdks/python/apache_beam/coders/row_coder.py

@@ -133,6 +133,8 @@ def __reduce__(self):
 
 
 typecoders.registry.register_coder(row_type.RowTypeConstraint, RowCoder)
+typecoders.registry.register_coder(
+    row_type.GeneratedClassRowTypeConstraint, RowCoder)
 
 
 def _coder_from_type(field_type):

sdks/python/apache_beam/transforms/core.py

@@ -2977,7 +2977,7 @@ def _key_type_hint(self, input_type):
       expr = self._key_fields[0][1]
       return trivial_inference.infer_return_type(expr, [input_type])
     else:
-      return row_type.RowTypeConstraint([
+      return row_type.RowTypeConstraint.from_fields([
           (name, trivial_inference.infer_return_type(expr, [input_type]))
           for (name, expr) in self._key_fields
       ])
@@ -3089,7 +3089,7 @@ def expand(self, pcoll):
                                 for name, expr in self._fields}))
 
   def infer_output_type(self, input_type):
-    return row_type.RowTypeConstraint([
+    return row_type.RowTypeConstraint.from_fields([
         (name, trivial_inference.infer_return_type(expr, [input_type]))
         for (name, expr) in self._fields
     ])

sdks/python/apache_beam/typehints/row_type.py

@@ -21,13 +21,13 @@
 
 from typing import Any
 from typing import Dict
-from typing import List
 from typing import Optional
 from typing import Sequence
 from typing import Tuple
 
 from apache_beam.typehints import typehints
 from apache_beam.typehints.native_type_compatibility import match_is_named_tuple
+from apache_beam.typehints.schema_registry import SchemaTypeRegistry
 
 # Name of the attribute added to user types (existing and generated) to store
 # the corresponding schema ID
@@ -37,10 +37,10 @@
 class RowTypeConstraint(typehints.TypeConstraint):
   def __init__(
       self,
-      fields: List[Tuple[str, type]],
-      user_type=None,
-      schema_options: Optional[List[Tuple[str, Any]]] = None,
-      field_options: Optional[Dict[str, List[Tuple[str, Any]]]] = None):
+      fields: Sequence[Tuple[str, type]],
+      user_type,
+      schema_options: Optional[Sequence[Tuple[str, Any]]] = None,
+      field_options: Optional[Dict[str, Sequence[Tuple[str, Any]]]] = None):
     """For internal use only, no backwards comatibility guaratees.  See
     https://beam.apache.org/documentation/programming-guide/#schemas-for-pl-types
     for guidance on creating PCollections with inferred schemas.
@@ -83,19 +83,16 @@ def __init__(
     # Note schema ID can be None if the schema is not registered yet.
     # Currently registration happens when converting to schema protos, in
     # apache_beam.typehints.schemas
-    if self._user_type is not None:
-      self._schema_id = getattr(self._user_type, _BEAM_SCHEMA_ID, None)
-    else:
-      self._schema_id = None
+    self._schema_id = getattr(self._user_type, _BEAM_SCHEMA_ID, None)
 
     self._schema_options = schema_options or []
     self._field_options = field_options or {}
 
   @staticmethod
   def from_user_type(
       user_type: type,
-      schema_options: Optional[List[Tuple[str, Any]]] = None,
-      field_options: Optional[Dict[str, List[Tuple[str, Any]]]] = None
+      schema_options: Optional[Sequence[Tuple[str, Any]]] = None,
+      field_options: Optional[Dict[str, Sequence[Tuple[str, Any]]]] = None
   ) -> Optional[RowTypeConstraint]:
     if match_is_named_tuple(user_type):
       fields = [(name, user_type.__annotations__[name])
@@ -112,8 +109,19 @@ def from_user_type(
     return None
 
   @staticmethod
-  def from_fields(fields: Sequence[Tuple[str, type]]) -> RowTypeConstraint:
-    return RowTypeConstraint(fields=fields, user_type=None)
+  def from_fields(
+      fields: Sequence[Tuple[str, type]],
+      schema_id: Optional[str] = None,
+      schema_options: Optional[Sequence[Tuple[str, Any]]] = None,
+      field_options: Optional[Dict[str, Sequence[Tuple[str, Any]]]] = None,
+      schema_registry: Optional[SchemaTypeRegistry] = None,
+  ) -> RowTypeConstraint:
+    return GeneratedClassRowTypeConstraint(
+        fields,
+        schema_id=schema_id,
+        schema_options=schema_options,
+        field_options=field_options,
+        schema_registry=schema_registry)
 
   @property
   def user_type(self):
@@ -160,3 +168,49 @@ def __repr__(self):
 
   def get_type_for(self, name):
     return dict(self._fields)[name]
+
+
+class GeneratedClassRowTypeConstraint(RowTypeConstraint):
+  """Specialization of RowTypeConstraint which relies on a generated user_type.
+
+  Since the generated user_type cannot be pickled, we supply a custom __reduce__
+  function that will regenerate the user_type.
+  """
+  def __init__(
+      self,
+      fields,
+      schema_id: Optional[str] = None,
+      schema_options: Optional[Sequence[Tuple[str, Any]]] = None,
+      field_options: Optional[Dict[str, Sequence[Tuple[str, Any]]]] = None,
+      schema_registry: Optional[SchemaTypeRegistry] = None,
+  ):
+    from apache_beam.typehints.schemas import named_fields_to_schema
+    from apache_beam.typehints.schemas import named_tuple_from_schema
+
+    kwargs = {'schema_registry': schema_registry} if schema_registry else {}
+
+    schema = named_fields_to_schema(
+        fields,
+        schema_id=schema_id,
+        schema_options=schema_options,
+        field_options=field_options,
+        **kwargs)
+    user_type = named_tuple_from_schema(schema, **kwargs)
+    setattr(user_type, _BEAM_SCHEMA_ID, schema_id)
+
+    super().__init__(
+        fields,
+        user_type,
+        schema_options=schema_options,
+        field_options=field_options)
+
+  def __reduce__(self):
+    return (
+        RowTypeConstraint.from_fields,
+        (
+            self._fields,
+            self._schema_id,
+            self._schema_options,
+            self._field_options,
+            None,
+        ))

sdks/python/apache_beam/typehints/schema_registry.py

@@ -0,0 +1,54 @@
+#
+# Licensed to the Apache Software Foundation (ASF) under one or more
+# contributor license agreements.  See the NOTICE file distributed with
+# this work for additional information regarding copyright ownership.
+# The ASF licenses this file to You 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.
+#
+
+"""This module is intended for internal use only. Nothing defined here provides
+any backwards-compatibility guarantee.
+"""
+
+from uuid import uuid4
+
+
+# Registry of typings for a schema by UUID
+class SchemaTypeRegistry(object):
+  def __init__(self):
+    self.by_id = {}
+    self.by_typing = {}
+
+  def generate_new_id(self):
+    for _ in range(100):
+      schema_id = str(uuid4())
+      if schema_id not in self.by_id:
+        return schema_id
+
+    raise AssertionError(
+        "Failed to generate a unique UUID for schema after "
+        f"100 tries! Registry contains {len(self.by_id)} "
+        "schemas.")
+
+  def add(self, typing, schema):
+    self.by_id[schema.id] = (typing, schema)
+
+  def get_typing_by_id(self, unique_id):
+    result = self.by_id.get(unique_id, None)
+    return result[0] if result is not None else None
+
+  def get_schema_by_id(self, unique_id):
+    result = self.by_id.get(unique_id, None)
+    return result[1] if result is not None else None
+
+
+SCHEMA_REGISTRY = SchemaTypeRegistry()