Reviewed by Aditya Kumar · Last reviewed 2026-03-24
Implementation: WITH RECURSIVE emp_tree AS (SELECT id, name, manager_id, 1 AS level FROM employees WHERE manager_id IS NULL UNION ALL SELECT e.id, e.name, e.manager_id, t.level + 1 FROM employees e JOIN emp_tree t ON e.manager_id = t.id) SELECT * FROM emp_tree. Why it works:...
This medium-level SQL question appears frequently in data engineering interviews at companies like American Express. While less common, it tests deeper understanding that distinguishes strong candidates. Mastering the underlying concepts (join, spark) 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.
Implementation: WITH RECURSIVE emp_tree AS (SELECT id, name, manager_id, 1 AS level FROM employees WHERE manager_id IS NULL UNION ALL SELECT e.id, e.name, e.manager_id, t.level + 1 FROM employees e JOIN emp_tree t ON e.manager_id = t.id) SELECT * FROM emp_tree. Why it works: Base case = roots; recursive case = join to prior level. Termination: Ensured by acyclic graph; cycles require cycle detection or LIMIT. Scalability: Recursive CTEs materialize each level; deep hierarchies (10+ levels) can explode intermediate rows. In Spark: No native recursive CTE; use GraphFrames, iterative DataFrame joins, or export to graph DB. Cost: Iterations = network shuffles; deep graphs = expensive. Best practice: Index parent key; validate acyclicity; for graph-scale, use GraphFrames or Neo4j.
Red Flag: Running recursive CTE on unbounded hierarchy without depth limit—risk of runaway execution. Pro-Move: Add MAX_RECURSION or level cap; for large orgs, precompute closure table or use graph engine.
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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.