| # |
| # 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. |
| # |
| |
| """ConsumerTrackingPipelineVisitor, a PipelineVisitor object.""" |
| |
| from __future__ import absolute_import |
| |
| from apache_beam import pvalue |
| from apache_beam.pipeline import PipelineVisitor |
| |
| |
| class ConsumerTrackingPipelineVisitor(PipelineVisitor): |
| """For internal use only; no backwards-compatibility guarantees. |
| |
| Visitor for extracting value-consumer relations from the graph. |
| |
| Tracks the AppliedPTransforms that consume each PValue in the Pipeline. This |
| is used to schedule consuming PTransforms to consume input after the upstream |
| transform has produced and committed output. |
| """ |
| |
| def __init__(self): |
| self.value_to_consumers = {} # Map from PValue to [AppliedPTransform]. |
| self.root_transforms = set() # set of (root) AppliedPTransforms. |
| self.views = [] # list of side inputs. |
| self.step_names = {} # Map from AppliedPTransform to String. |
| |
| self._num_transforms = 0 |
| |
| def visit_transform(self, applied_ptransform): |
| inputs = list(applied_ptransform.inputs) |
| if inputs: |
| for input_value in inputs: |
| if isinstance(input_value, pvalue.PBegin): |
| self.root_transforms.add(applied_ptransform) |
| if input_value not in self.value_to_consumers: |
| self.value_to_consumers[input_value] = [] |
| self.value_to_consumers[input_value].append(applied_ptransform) |
| else: |
| self.root_transforms.add(applied_ptransform) |
| self.step_names[applied_ptransform] = 's%d' % (self._num_transforms) |
| self._num_transforms += 1 |
| for side_input in applied_ptransform.side_inputs: |
| self.views.append(side_input) |