Source code for apache_beam.runners.direct.consumer_tracking_pipeline_visitor

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"""ConsumerTrackingPipelineVisitor, a PipelineVisitor object."""

# pytype: skip-file

from __future__ import absolute_import

from typing import TYPE_CHECKING
from typing import Dict
from typing import Set

from apache_beam import pvalue
from apache_beam.pipeline import PipelineVisitor

if TYPE_CHECKING:
  from apache_beam.pipeline import AppliedPTransform


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 = {
    }  # type: Dict[pvalue.PValue, Set[AppliedPTransform]]
    self.root_transforms = set()  # type: Set[AppliedPTransform]
    self.step_names = {}  # type: Dict[AppliedPTransform, str]

    self._num_transforms = 0
    self._views = set()

  @property
  def views(self):
    """Returns a list of side intputs extracted from the graph.

    Returns:
      A list of pvalue.AsSideInput.
    """
    return list(self._views)

  def visit_transform(self, applied_ptransform):
    # type: (AppliedPTransform) -> None
    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] = set()
        self.value_to_consumers[input_value].add(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.add(side_input)