PCollection
Interactive Syntax Reference
PCollectionApache Beam Cheatsheet: PCollection
Recommended reading: 3 minsCopy-paste ready Python code snippets
Core Architecture Overview
Understand the core data container, its properties, and state representations.
beam.Create()
returns: PCollectionPurpose & Description
Generates a PCollection from an in-memory iterable (lists, sets, dictionary lists).
Syntax Signature
beam.Create(iterable)Executable Example
import apache_beam as beam
with beam.Pipeline() as p:
elements = p | "Create Elements" >> beam.Create([10, 20, 30])
elements | beam.Map(print)Expected Stdout / Output
10
20
30Time Complexity
O(N) where N is the number of elements in the iterable
Used In
Testing, loading configurations, and quick sandbox runs.
Related Methods
ReadFromText(), ReadFromPubSub()
Pro Tip
Avoid creating very large PCollections using beam.Create since the entire list is held in driver memory.
PCollection Attributes
returns: Data RepresentationPurpose & Description
Understanding core immutability, distributed elements, and schemas.
Syntax Signature
PCollection Characteristics (Immutable, Distributed, Bounded/Unbounded)Executable Example
import apache_beam as beam
# PCollections are immutable; transforms return new collections
inputs = p | beam.Create([1, 2, 3, 4])
evens = inputs | "FilterEvens" >> beam.Filter(lambda x: x % 2 == 0)Used In
Architecting streaming or batch pipelines.
Common Pitfall
Attempting to modify elements in-place inside user code processes.
Pro Tip
PCollections do not support index lookups or random access. All access must flow through transforms.
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