def _get_transform_overrides():
# A list of PTransformOverride objects to be applied before running a pipeline
# using DirectRunner.
# Currently this only works for overrides where the input and output types do
# not change.
# For internal use only; no backwards-compatibility guarantees.
# Importing following locally to avoid a circular dependency.
from apache_beam.runners.sdf_common import SplittableParDoOverride
from apache_beam.runners.direct.sdf_direct_runner import ProcessKeyedElementsViaKeyedWorkItemsOverride
return [SplittableParDoOverride(),
ProcessKeyedElementsViaKeyedWorkItemsOverride()]
def _get_transform_overrides(pipeline_options):
# A list of PTransformOverride objects to be applied before running a pipeline
# using DirectRunner.
# Currently this only works for overrides where the input and output types do
# not change.
# For internal use only; no backwards-compatibility guarantees.
# Importing following locally to avoid a circular dependency.
from apache_beam.pipeline import PTransformOverride
from apache_beam.runners.sdf_common import SplittableParDoOverride
from apache_beam.runners.direct.helper_transforms import LiftedCombinePerKey
from apache_beam.runners.direct.sdf_direct_runner import ProcessKeyedElementsViaKeyedWorkItemsOverride
class CombinePerKeyOverride(PTransformOverride):
def matches(self, applied_ptransform):
if isinstance(applied_ptransform.transform, CombinePerKey):
return applied_ptransform.inputs[0].windowing.is_default()
def get_replacement_transform(self, transform):
# TODO: Move imports to top. Pipeline <-> Runner dependency cause problems
# with resolving imports when they are at top.
# pylint: disable=wrong-import-position
try:
return LiftedCombinePerKey(transform.fn, transform.args,
transform.kwargs)
except NotImplementedError:
return transform
class StreamingGroupByKeyOverride(PTransformOverride):
def matches(self, applied_ptransform):
# Note: we match the exact class, since we replace it with a subclass.
return applied_ptransform.transform.__class__ == _GroupByKeyOnly
def get_replacement_transform(self, transform):
# Use specialized streaming implementation.
transform = _StreamingGroupByKeyOnly()
return transform
class StreamingGroupAlsoByWindowOverride(PTransformOverride):
def matches(self, applied_ptransform):
# Note: we match the exact class, since we replace it with a subclass.
transform = applied_ptransform.transform
return (isinstance(applied_ptransform.transform, ParDo) and
isinstance(transform.dofn, _GroupAlsoByWindowDoFn) and
transform.__class__ != _StreamingGroupAlsoByWindow)
def get_replacement_transform(self, transform):
# Use specialized streaming implementation.
transform = _StreamingGroupAlsoByWindow(transform.dofn.windowing)
return transform
overrides = [SplittableParDoOverride(),
ProcessKeyedElementsViaKeyedWorkItemsOverride(),
CombinePerKeyOverride()]
# Add streaming overrides, if necessary.
if pipeline_options.view_as(StandardOptions).streaming:
overrides.append(StreamingGroupByKeyOverride())
overrides.append(StreamingGroupAlsoByWindowOverride())
# Add PubSub overrides, if PubSub is available.
try:
from apache_beam.io.gcp import pubsub as unused_pubsub
overrides += _get_pubsub_transform_overrides(pipeline_options)
except ImportError:
pass
return overrides
def _get_transform_overrides(pipeline_options):
# A list of PTransformOverride objects to be applied before running a pipeline
# using DirectRunner.
# Currently this only works for overrides where the input and output types do
# not change.
# For internal use only; no backwards-compatibility guarantees.
# Importing following locally to avoid a circular dependency.
from apache_beam.pipeline import PTransformOverride
from apache_beam.runners.direct.helper_transforms import LiftedCombinePerKey
from apache_beam.runners.direct.sdf_direct_runner import ProcessKeyedElementsViaKeyedWorkItemsOverride
from apache_beam.runners.direct.sdf_direct_runner import SplittableParDoOverride
class CombinePerKeyOverride(PTransformOverride):
def matches(self, applied_ptransform):
if isinstance(applied_ptransform.transform, CombinePerKey):
return applied_ptransform.inputs[0].windowing.is_default()
def get_replacement_transform_for_applied_ptransform(
self, applied_ptransform):
# TODO: Move imports to top. Pipeline <-> Runner dependency cause problems
# with resolving imports when they are at top.
# pylint: disable=wrong-import-position
try:
transform = applied_ptransform.transform
return LiftedCombinePerKey(transform.fn, transform.args,
transform.kwargs)
except NotImplementedError:
return transform
class StreamingGroupByKeyOverride(PTransformOverride):
def matches(self, applied_ptransform):
# Note: we match the exact class, since we replace it with a subclass.
return applied_ptransform.transform.__class__ == _GroupByKeyOnly
def get_replacement_transform_for_applied_ptransform(
self, applied_ptransform):
# Use specialized streaming implementation.
transform = _StreamingGroupByKeyOnly()
return transform
class StreamingGroupAlsoByWindowOverride(PTransformOverride):
def matches(self, applied_ptransform):
# Note: we match the exact class, since we replace it with a subclass.
transform = applied_ptransform.transform
return (isinstance(applied_ptransform.transform, ParDo)
and isinstance(transform.dofn, _GroupAlsoByWindowDoFn)
and transform.__class__ != _StreamingGroupAlsoByWindow)
def get_replacement_transform_for_applied_ptransform(
self, applied_ptransform):
# Use specialized streaming implementation.
transform = _StreamingGroupAlsoByWindow(
applied_ptransform.transform.dofn.windowing)
return transform
class TestStreamOverride(PTransformOverride):
def matches(self, applied_ptransform):
from apache_beam.testing.test_stream import TestStream
self.applied_ptransform = applied_ptransform
return isinstance(applied_ptransform.transform, TestStream)
def get_replacement_transform_for_applied_ptransform(
self, applied_ptransform):
from apache_beam.runners.direct.test_stream_impl import _ExpandableTestStream
return _ExpandableTestStream(applied_ptransform.transform)
class GroupByKeyPTransformOverride(PTransformOverride):
"""A ``PTransformOverride`` for ``GroupByKey``.
This replaces the Beam implementation as a primitive.
"""
def matches(self, applied_ptransform):
# Imported here to avoid circular dependencies.
# pylint: disable=wrong-import-order, wrong-import-position
from apache_beam.transforms.core import GroupByKey
return isinstance(applied_ptransform.transform, GroupByKey)
def get_replacement_transform_for_applied_ptransform(
self, applied_ptransform):
return _GroupByKey()
overrides = [
# This needs to be the first and the last override. Other overrides depend
# on the GroupByKey implementation to be composed of _GroupByKeyOnly and
# _GroupAlsoByWindow.
GroupByKeyPTransformOverride(),
SplittableParDoOverride(),
ProcessKeyedElementsViaKeyedWorkItemsOverride(),
CombinePerKeyOverride(),
TestStreamOverride(),
]
# Add streaming overrides, if necessary.
if pipeline_options.view_as(StandardOptions).streaming:
overrides.append(StreamingGroupByKeyOverride())
overrides.append(StreamingGroupAlsoByWindowOverride())
# Add PubSub overrides, if PubSub is available.
try:
from apache_beam.io.gcp import pubsub as unused_pubsub
overrides += _get_pubsub_transform_overrides(pipeline_options)
except ImportError:
pass
# This also needs to be last because other transforms apply GBKs which need to
# be translated into a DirectRunner-compatible transform.
overrides.append(GroupByKeyPTransformOverride())
return overrides
