CombinePerKey

Pydoc Pydoc




Combines all elements for each key in a collection.

See more information in the Beam Programming Guide.

Examples

In the following examples, we create a pipeline with a PCollection of produce. Then, we apply CombinePerKey in multiple ways to combine all the elements in the PCollection.

CombinePerKey accepts a function that takes a list of values as an input, and combines them for each key.

Example 1: Combining with a predefined function

We use the function sum which takes an iterable of numbers and adds them together.

import apache_beam as beam

with beam.Pipeline() as pipeline:
  total = (
      pipeline
      | 'Create plant counts' >> beam.Create([
          ('🥕', 3),
          ('🥕', 2),
          ('🍆', 1),
          ('🍅', 4),
          ('🍅', 5),
          ('🍅', 3),
      ])
      | 'Sum' >> beam.CombinePerKey(sum)
      | beam.Map(print))

Output:

('🥕', 5)
('🍆', 1)
('🍅', 12)

Example 2: Combining with a function

We define a function saturated_sum which takes an iterable of numbers and adds them together, up to a predefined maximum number.

import apache_beam as beam

def saturated_sum(values):
  max_value = 8
  return min(sum(values), max_value)

with beam.Pipeline() as pipeline:
  saturated_total = (
      pipeline
      | 'Create plant counts' >> beam.Create([
          ('🥕', 3),
          ('🥕', 2),
          ('🍆', 1),
          ('🍅', 4),
          ('🍅', 5),
          ('🍅', 3),
      ])
      | 'Saturated sum' >> beam.CombinePerKey(saturated_sum)
      | beam.Map(print))

Output:

('🥕', 5)
('🍆', 1)
('🍅', 8)

Example 3: Combining with a lambda function

We can also use lambda functions to simplify Example 2.

import apache_beam as beam

with beam.Pipeline() as pipeline:
  saturated_total = (
      pipeline
      | 'Create plant counts' >> beam.Create([
          ('🥕', 3),
          ('🥕', 2),
          ('🍆', 1),
          ('🍅', 4),
          ('🍅', 5),
          ('🍅', 3),
      ])
      | 'Saturated sum' >>
      beam.CombinePerKey(lambda values: min(sum(values), 8))
      | beam.Map(print))

Output:

('🥕', 5)
('🍆', 1)
('🍅', 8)

Example 4: Combining with multiple arguments

You can pass functions with multiple arguments to CombinePerKey. They are passed as additional positional arguments or keyword arguments to the function.

In this example, the lambda function takes values and max_value as arguments.

import apache_beam as beam

with beam.Pipeline() as pipeline:
  saturated_total = (
      pipeline
      | 'Create plant counts' >> beam.Create([
          ('🥕', 3),
          ('🥕', 2),
          ('🍆', 1),
          ('🍅', 4),
          ('🍅', 5),
          ('🍅', 3),
      ])
      | 'Saturated sum' >> beam.CombinePerKey(
          lambda values, max_value: min(sum(values), max_value), max_value=8)
      | beam.Map(print))

Output:

('🥕', 5)
('🍆', 1)
('🍅', 8)

Example 5: Combining with a CombineFn

The more general way to combine elements, and the most flexible, is with a class that inherits from CombineFn.

import apache_beam as beam

class AverageFn(beam.CombineFn):
  def create_accumulator(self):
    sum = 0.0
    count = 0
    accumulator = sum, count
    return accumulator

  def add_input(self, accumulator, input):
    sum, count = accumulator
    return sum + input, count + 1

  def merge_accumulators(self, accumulators):
    # accumulators = [(sum1, count1), (sum2, count2), (sum3, count3), ...]
    sums, counts = zip(*accumulators)
    # sums = [sum1, sum2, sum3, ...]
    # counts = [count1, count2, count3, ...]
    return sum(sums), sum(counts)

  def extract_output(self, accumulator):
    sum, count = accumulator
    if count == 0:
      return float('NaN')
    return sum / count

with beam.Pipeline() as pipeline:
  average = (
      pipeline
      | 'Create plant counts' >> beam.Create([
          ('🥕', 3),
          ('🥕', 2),
          ('🍆', 1),
          ('🍅', 4),
          ('🍅', 5),
          ('🍅', 3),
      ])
      | 'Average' >> beam.CombinePerKey(AverageFn())
      | beam.Map(print))

Output:

('🥕', 2.5)
('🍆', 1.0)
('🍅', 4.0)

You can use the following combiner transforms:

See also GroupBy which allows you to combine more than one field at once.

Pydoc Pydoc