Reviewed by Aditya Kumar · Last reviewed 2026-03-24
Choose model based on read/write patterns and depth. WHY: Hierarchy queries (ancestors, descendants, paths) vary in cost across models. OPTIONS: (1) Adjacency list (parent_id)—simple, recursive CTEs; expensive for deep trees. (2) Path enumeration (/1/2/5/)—fast reads, costly...
This hard-level General/Other question appears frequently in data engineering interviews at companies like Goldman Sachs. While less common, it tests deeper understanding that distinguishes strong candidates. Mastering the underlying concepts (etl, sql) will help you answer variations of this question confidently.
This is a senior-level question that tests architectural thinking. Lead with the high-level design, then drill into specifics. Discuss trade-offs explicitly - there is rarely one correct answer. Show awareness of scale, fault tolerance, and operational complexity.
Choose model based on read/write patterns and depth. WHY: Hierarchy queries (ancestors, descendants, paths) vary in cost across models. OPTIONS: (1) Adjacency list (parent_id)—simple, recursive CTEs; expensive for deep trees. (2) Path enumeration (/1/2/5/)—fast reads, costly updates. (3) Closure table (ancestor, descendant, depth)—excellent read-heavy; extra storage. (4) Nested sets—complex updates. ARCHITECTURE (Adjacency + Recursive CTE):
[Applications]
|
v
[Query Layer]
/ | \
v v v
[Adj] [Path] [Closure]
| | |
v v v
[PostgreSQL] with indexes
SCALABILITY: Closure table scales reads but grows O(n*depth) in rows. COST: Adjacency is cheapest to maintain; closure adds ETL cost for sync.
Red Flag: Only mentioning adjacency list. Pro-Move: 'For org charts we use adjacency; for category trees with heavy reads we materialized a closure table—reduced query time from 800ms to 50ms.'
Some links below are affiliate links. If you buy through them we may earn a small commission at no extra cost to you — it helps keep DataEngPrep free.
According to DataEngPrep.tech, this is one of the most frequently asked General/Other interview questions, reported at 1 company. DataEngPrep.tech maintains an editor-reviewed database of 1,863 data engineering interview questions across 7 categories.