| # |
| # 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. |
| # |
| |
| from __future__ import absolute_import |
| |
| import collections |
| import itertools |
| |
| import apache_beam as beam |
| from apache_beam import typehints |
| from apache_beam.internal.util import ArgumentPlaceholder |
| from apache_beam.transforms.combiners import _CurriedFn |
| from apache_beam.utils.windowed_value import WindowedValue |
| |
| |
| class LiftedCombinePerKey(beam.PTransform): |
| """An implementation of CombinePerKey that does mapper-side pre-combining. |
| """ |
| def __init__(self, combine_fn, args, kwargs): |
| args_to_check = itertools.chain(args, kwargs.values()) |
| if isinstance(combine_fn, _CurriedFn): |
| args_to_check = itertools.chain(args_to_check, |
| combine_fn.args, |
| combine_fn.kwargs.values()) |
| if any(isinstance(arg, ArgumentPlaceholder) |
| for arg in args_to_check): |
| # This isn't implemented in dataflow either... |
| raise NotImplementedError('Deferred CombineFn side inputs.') |
| self._combine_fn = beam.transforms.combiners.curry_combine_fn( |
| combine_fn, args, kwargs) |
| |
| def expand(self, pcoll): |
| return ( |
| pcoll |
| | beam.ParDo(PartialGroupByKeyCombiningValues(self._combine_fn)) |
| | beam.GroupByKey() |
| | beam.ParDo(FinishCombine(self._combine_fn))) |
| |
| |
| class PartialGroupByKeyCombiningValues(beam.DoFn): |
| """Aggregates values into a per-key-window cache. |
| |
| As bundles are in-memory-sized, we don't bother flushing until the very end. |
| """ |
| def __init__(self, combine_fn): |
| self._combine_fn = combine_fn |
| |
| def start_bundle(self): |
| self._cache = collections.defaultdict(self._combine_fn.create_accumulator) |
| |
| def process(self, element, window=beam.DoFn.WindowParam): |
| k, vi = element |
| self._cache[k, window] = self._combine_fn.add_input(self._cache[k, window], |
| vi) |
| |
| def finish_bundle(self): |
| for (k, w), va in self._cache.items(): |
| # We compact the accumulator since a GBK (which necessitates encoding) |
| # will follow. |
| yield WindowedValue((k, self._combine_fn.compact(va)), w.end, (w,)) |
| |
| def default_type_hints(self): |
| hints = self._combine_fn.get_type_hints().copy() |
| K = typehints.TypeVariable('K') |
| if hints.input_types: |
| args, kwargs = hints.input_types |
| args = (typehints.Tuple[K, args[0]],) + args[1:] |
| hints.set_input_types(*args, **kwargs) |
| else: |
| hints.set_input_types(typehints.Tuple[K, typehints.Any]) |
| hints.set_output_types(typehints.Tuple[K, typehints.Any]) |
| return hints |
| |
| |
| class FinishCombine(beam.DoFn): |
| """Merges partially combined results. |
| """ |
| def __init__(self, combine_fn): |
| self._combine_fn = combine_fn |
| |
| def process(self, element): |
| k, vs = element |
| return [( |
| k, |
| self._combine_fn.extract_output( |
| self._combine_fn.merge_accumulators(vs)))] |
| |
| def default_type_hints(self): |
| hints = self._combine_fn.get_type_hints().copy() |
| K = typehints.TypeVariable('K') |
| hints.set_input_types(typehints.Tuple[K, typehints.Any]) |
| if hints.output_types: |
| main_output_type = hints.simple_output_type('') |
| hints.set_output_types(typehints.Tuple[K, main_output_type]) |
| return hints |