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Run a significantly smaller Dask Graph. #33806

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Jan 30, 2025
Merged

Run a significantly smaller Dask Graph. #33806

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2fd9a6e
Run a significantly smaller Dask Graph.
alxmrs Jan 29, 2025
5952e74
Fixing all run_pylint.sh issues.
alxmrs Jan 29, 2025
dfa2813
*shakes fist at `isort`*.
alxmrs Jan 30, 2025
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11 changes: 8 additions & 3 deletions sdks/python/apache_beam/runners/dask/dask_runner.py
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Original file line number Diff line number Diff line change
Expand Up @@ -22,6 +22,7 @@
scheduler.
"""
import argparse
import collections
import dataclasses
import typing as t

Expand Down Expand Up @@ -143,8 +144,8 @@ def to_dask_bag_visitor() -> PipelineVisitor:

@dataclasses.dataclass
class DaskBagVisitor(PipelineVisitor):
bags: t.Dict[AppliedPTransform,
db.Bag] = dataclasses.field(default_factory=dict)
bags: t.Dict[AppliedPTransform, db.Bag] = dataclasses.field(
default_factory=collections.OrderedDict)

def visit_transform(self, transform_node: AppliedPTransform) -> None:
op_class = TRANSLATIONS.get(transform_node.transform.__class__, NoOp)
Expand Down Expand Up @@ -212,6 +213,10 @@ def run_pipeline(self, pipeline, options):

dask_visitor = self.to_dask_bag_visitor()
pipeline.visit(dask_visitor)
opt_graph = dask.optimize(*list(dask_visitor.bags.values()))
# The dictionary in this visitor keeps a mapping of every Beam
# PTransform to the equivalent Bag operation. This is highly
# redundant. Thus, we can get away with computing just the last
# value, which should be connected to the full Bag Task Graph.
opt_graph = dask.optimize(list(dask_visitor.bags.values())[-1])
futures = client.compute(opt_graph)
return DaskRunnerResult(client, futures)
2 changes: 0 additions & 2 deletions sdks/python/apache_beam/runners/dask/transform_evaluator.py
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Expand Up @@ -19,8 +19,6 @@

A minimum set of operation substitutions, to adap Beam's PTransform model
to Dask Bag functions.

TODO(alxr): Translate ops from https://docs.dask.org/en/latest/bag-api.html.
"""
import abc
import dataclasses
Expand Down
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