Join back: SQL STRING_AGG(value, ',') or array_to_string(array_agg(col), ','). Python ','.join(list). Spark: groupBy.agg(collect_list).alias('vals').withColumn('restored', concat_ws(',','vals')). Preserve order: array_agg with ORDER BY. Handle nulls....
This medium-level General/Other question appears frequently in data engineering interviews at companies like Pubmatic. While less common, it tests deeper understanding that distinguishes strong candidates. Mastering the underlying concepts (etl, join, python) will help you answer variations of this question confidently.
Break this problem into components. Identify the core trade-offs involved, then walk the interviewer through your reasoning step by step. Demonstrate awareness of edge cases and production considerations - this is what separates good answers from great ones.
Join back: SQL STRING_AGG(value, ',') or array_to_string(array_agg(col), ','). Python ','.join(list). Spark: groupBy.agg(collect_list).alias('vals').withColumn('restored', concat_ws(',','vals')). Preserve order: array_agg with ORDER BY. Handle nulls. WHY: Explode/implode symmetry for ETL; order matters for reproducibility.
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Analyze My Answer β FreeAccording to DataEngPrep.tech, this is one of the most frequently asked General/Other interview questions, reported at 1 company. DataEngPrep.tech maintains a curated database of 1,863+ real data engineering interview questions across 7 categories, verified by industry professionals.