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Home/Questions/Cloud/Tools/Explain the key components of Apache Beam in the context of Google Dataflow.

Explain the key components of Apache Beam in the context of Google Dataflow.

Cloud/Toolsmedium0.2 min read

Reviewed by Aditya Kumar · Last reviewed 2026-03-24

Architectural components: PCollection (bounded/unbounded dataset), PTransform (Map, Filter, GroupByKey), Pipeline (graph), Runner (Dataflow). Side inputs for lookups; watermarks for event-time. Flow: ReadFromPubSub → Map → WindowInto → GroupByKey → WriteToBigQuery. Why Beam:...

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Asked at 1 company
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Key Concepts Tested
bigquerywindow
Expert Answer
48 words

Architectural components: PCollection (bounded/unbounded dataset), PTransform (Map, Filter, GroupByKey), Pipeline (graph), Runner (Dataflow). Side inputs for lookups; watermarks for event-time. Flow: ReadFromPubSub → Map → WindowInto → GroupByKey → WriteToBigQuery. Why Beam: Portable; batch and stream. Best practice: Structured data; design for parallelism; allowed lateness for late data.

⚡
Pro Tip

Red Flag: Ignoring late data handling in streaming. Pro-Move: 'We use allowedLateness=1h and side input for enrichment—backlog cleared, no late data loss.'

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