PDE Ingesting and Processing the Data Practice Question

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 the 'skip_leading_rows' option.

  Why it's wrong here

  'skip_leading_rows' merely omits header lines at the start of each file; it performs no validation of subsequent records, so malformed rows still cause the job to fail. It is the right setting when CSV files carry a header row that must not be loaded as data.

• ✗

  Use the 'ignore_unknown_values' option.

  Why it's wrong here

  The 'ignore_unknown_values' option discards values in columns absent from the schema, not malformed rows; rows with wrong field counts still fail the load. It is intended for extra trailing fields in otherwise well-formed data, so it would be correct when surplus columns appear, not when rows are structurally broken.

• ✓

  Use the 'max_bad_records' option set to a value like 10.

  Why this is correct

  Setting max_bad_records to 10 lets the load job tolerate up to ten malformed rows per file, skipping them while importing the valid data. Without it, any single bad row aborts the entire 10 GB load.

• ✗

  Use the 'allow_jagged_rows' option.

  Why it's wrong here

  'allow_jagged_rows' permits rows with fewer columns than the schema by padding missing trailing fields with nulls; it does not skip rows that are malformed in other ways. It is correct when short rows should be retained rather than rejected.