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PDE Ingesting and Processing the Data Practice Question

A data engineer needs to load a 10 GB CSV file from GCS into BigQuery. The file contains some malformed rows that should be skipped. Which approach is most efficient?

⚠ Common exam trap

Google often tests the misconception that complex ETL pipelines (Spark, Dataflow) are always required for data cleaning, when in fact BigQuery's native load options like `--max_bad_records` can handle common malformed row scenarios directly and more efficiently.

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 the bq command-line tool with the --max_bad_records flag

The `bq` command-line tool's `--max_bad_records` flag allows BigQuery's native CSV loader to skip malformed rows up to a specified limit during a load job. This is the most efficient approach for a one-time batch load of a 10 GB file, as it avoids the overhead of spinning up separate processing clusters (Dataproc, Dataflow) or streaming each row individually, leveraging BigQuery's optimized ingestion pipeline.

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 Dataproc to run a Spark job that cleans the data and writes to BigQuery

    Why it's wrong here

    Unnecessary complexity for a single file.

  • ✗

    Use the Storage Write API to stream each row, skipping bad ones in code

    Why it's wrong here

    Streaming is for real-time; batch load is better for a 10 GB file.

  • ✗

    Use a Dataflow pipeline to read CSV, filter bad rows, and write to BigQuery

    Why it's wrong here

    Overkill for a simple load; inefficient for a single file.

  • ✓

    Use the bq command-line tool with the --max_bad_records flag

    Why this is correct

    bq load with --max_bad_records skips malformed rows efficiently.

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This PDE practice question is part of Courseiva's free Google Cloud certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the PDE exam.