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Ingesting and Processing the Data →hardMultiple ChoiceObjective-mapped

PDE Ingesting and Processing the Data Practice Question

A data pipeline uses Pub/Sub to ingest events, a Dataflow streaming pipeline to process them, and writes results to BigQuery. The pipeline must handle occasional duplicate events without causing duplicate rows in BigQuery. What is the best approach?

Answer choices

Why each option matters

Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.

Correct answer & explanation

✓

Use BigQuery legacy streaming inserts with insertId for deduplication

BigQuery does not enforce primary keys; deduplication must be handled in the pipeline using idempotent writes or a dedup step.

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

  • ✓

    Use BigQuery legacy streaming inserts with insertId for deduplication

    Why this is correct

    Legacy streaming inserts use insertId to deduplicate within a short window.

  • ✗

    Use the Storage Write API with the committed stream

    Why it's wrong here

    Committed stream does not deduplicate; duplicates may still occur.

  • ✗

    Set a unique constraint on the BigQuery table

    Why it's wrong here

    BigQuery does not support unique constraints.

  • ✗

    Enable exactly-once processing in Pub/Sub

    Why it's wrong here

    Pub/Sub offers at-least-once delivery; no exactly-once guarantee.

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