#
# 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.
#
"""Utility class for serializing pipelines via the runner API.
For internal use only; no backwards-compatibility guarantees.
"""
from __future__ import absolute_import
from builtins import object
from apache_beam import coders
from apache_beam import pipeline
from apache_beam import pvalue
from apache_beam.internal import pickler
from apache_beam.portability.api import beam_fn_api_pb2
from apache_beam.portability.api import beam_runner_api_pb2
from apache_beam.transforms import core
from apache_beam.typehints import native_type_compatibility
[docs]class Environment(object):
"""A wrapper around the environment proto.
Provides consistency with how the other componentes are accessed.
"""
def __init__(self, proto):
self._proto = proto
[docs] def to_runner_api(self, context):
return self._proto
[docs] @staticmethod
def from_runner_api(proto, context):
return Environment(proto)
class _PipelineContextMap(object):
"""This is a bi-directional map between objects and ids.
Under the hood it encodes and decodes these objects into runner API
representations.
"""
def __init__(self, context, obj_type, namespace, proto_map=None):
self._pipeline_context = context
self._obj_type = obj_type
self._namespace = namespace
self._obj_to_id = {}
self._id_to_obj = {}
self._id_to_proto = dict(proto_map) if proto_map else {}
self._counter = 0
def _unique_ref(self, obj=None, label=None):
self._counter += 1
return "%s_%s_%s_%d" % (
self._namespace,
self._obj_type.__name__,
label or type(obj).__name__,
self._counter)
def populate_map(self, proto_map):
for id, proto in self._id_to_proto.items():
proto_map[id].CopyFrom(proto)
def get_id(self, obj, label=None):
if obj not in self._obj_to_id:
id = self._unique_ref(obj, label)
self._id_to_obj[id] = obj
self._obj_to_id[obj] = id
self._id_to_proto[id] = obj.to_runner_api(self._pipeline_context)
return self._obj_to_id[obj]
def get_proto(self, obj, label=None):
return self._id_to_proto[self.get_id(obj, label)]
def get_by_id(self, id):
if id not in self._id_to_obj:
self._id_to_obj[id] = self._obj_type.from_runner_api(
self._id_to_proto[id], self._pipeline_context)
return self._id_to_obj[id]
def get_by_proto(self, maybe_new_proto, label=None, deduplicate=False):
if deduplicate:
for id, proto in self._id_to_proto.items():
if proto == maybe_new_proto:
return id
return self.put_proto(self._unique_ref(label), maybe_new_proto)
def get_id_to_proto_map(self):
return self._id_to_proto
def put_proto(self, id, proto):
if id in self._id_to_proto:
raise ValueError("Id '%s' is already taken." % id)
self._id_to_proto[id] = proto
return id
def __getitem__(self, id):
return self.get_by_id(id)
def __contains__(self, id):
return id in self._id_to_proto
[docs]class PipelineContext(object):
"""For internal use only; no backwards-compatibility guarantees.
Used for accessing and constructing the referenced objects of a Pipeline.
"""
_COMPONENT_TYPES = {
'transforms': pipeline.AppliedPTransform,
'pcollections': pvalue.PCollection,
'coders': coders.Coder,
'windowing_strategies': core.Windowing,
'environments': Environment,
}
def __init__(
self, proto=None, default_environment=None, use_fake_coders=False,
iterable_state_read=None, iterable_state_write=None,
namespace='ref', allow_proto_holders=False):
if isinstance(proto, beam_fn_api_pb2.ProcessBundleDescriptor):
proto = beam_runner_api_pb2.Components(
coders=dict(proto.coders.items()),
windowing_strategies=dict(proto.windowing_strategies.items()),
environments=dict(proto.environments.items()))
for name, cls in self._COMPONENT_TYPES.items():
setattr(
self, name, _PipelineContextMap(
self, cls, namespace, getattr(proto, name, None)))
if default_environment:
self._default_environment_id = self.environments.get_id(
Environment(default_environment), label='default_environment')
else:
self._default_environment_id = None
self.use_fake_coders = use_fake_coders
self.iterable_state_read = iterable_state_read
self.iterable_state_write = iterable_state_write
self.allow_proto_holders = allow_proto_holders
# If fake coders are requested, return a pickled version of the element type
# rather than an actual coder. The element type is required for some runners,
# as well as performing a round-trip through protos.
# TODO(BEAM-2717): Remove once this is no longer needed.
[docs] def coder_id_from_element_type(self, element_type):
if self.use_fake_coders:
return pickler.dumps(element_type)
else:
return self.coders.get_id(coders.registry.get_coder(element_type))
[docs] def element_type_from_coder_id(self, coder_id):
if self.use_fake_coders or coder_id not in self.coders:
return pickler.loads(coder_id)
else:
return native_type_compatibility.convert_to_beam_type(
self.coders[coder_id].to_type_hint())
[docs] @staticmethod
def from_runner_api(proto):
return PipelineContext(proto)
[docs] def to_runner_api(self):
context_proto = beam_runner_api_pb2.Components()
for name in self._COMPONENT_TYPES:
getattr(self, name).populate_map(getattr(context_proto, name))
return context_proto
[docs] def default_environment_id(self):
return self._default_environment_id