Reviewed by Aditya Kumar · Last reviewed 2026-03-24
UNNEST converts an array into a set of rows. In BigQuery: SELECT id, item FROM my_table, UNNEST(items_array) AS item. Example: WITH data AS (SELECT 1 id, [1,2,3] arr) SELECT id, x FROM data, UNNEST(arr) AS x; -- returns 3 rows. Use for: exploding arrays for analysis, joining...
This medium-level SQL question appears frequently in data engineering interviews at companies like EY. While less common, it tests deeper understanding that distinguishes strong candidates. Mastering the underlying concepts (bigquery, join, sql) 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.
UNNEST converts an array into a set of rows. In BigQuery: SELECT id, item FROM my_table, UNNEST(items_array) AS item. Example: WITH data AS (SELECT 1 id, [1,2,3] arr) SELECT id, x FROM data, UNNEST(arr) AS x; -- returns 3 rows. Use for: exploding arrays for analysis, joining array elements. In PostgreSQL: unnest(arr). Best practice: Use with CROSS JOIN or comma for 1:1; LATERAL for correlated. Handle NULL arrays—use COALESCE or IFNULL to provide empty array. Why it matters: Design choices compound at scale—wrong approach can cause 100× overhead. Scalability trade-offs: Profile before optimizing; validate on sample then full. Cost implications: Suboptimal choices multiply at billion-row scale.
Red Flag: Generic textbook answers. Pro-Move: 'At scale we measured X, implemented Y, achieved Z%—validated and iterated.'
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According to DataEngPrep.tech, this is one of the most frequently asked SQL interview questions, reported at 1 company. DataEngPrep.tech maintains an editor-reviewed database of 1,863 data engineering interview questions across 7 categories.