Common Table Expressions and Subqueries Questions

Covers writing and structuring complex SQL queries using Common Table Expressions and subqueries, including when to prefer one approach over another for readability, maintainability, and performance. Candidates should be able to author WITH clauses to break multi step logic into clear stages, implement recursive CTEs for hierarchical data, and use subqueries in SELECT, FROM, and WHERE clauses. This topic also includes understanding correlated versus non correlated subqueries, how subqueries interact with joins and window functions, and practical guidance on choosing CTEs, subqueries, or joins based on clarity and execution characteristics. Interviewers may probe syntax, typical pitfalls, refactoring nested queries into CTEs, testing and validating each step of a CTE pipeline, and trade offs that affect execution plans and index usage.

HardTechnical

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Discuss how CTEs and subqueries interact with security and SQL-injection concerns when generating complex SQL from data science notebooks or applications. Provide best practices for parameterizing both values and identifiers in dynamic queries that include WITH clauses and nested selects.

EasyTechnical

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Explain the differences between a Common Table Expression (WITH clause) and an inline subquery (derived table or subquery in WHERE/SELECT). For a data scientist writing analytic SQL, when would you prefer a CTE over a subquery for readability, maintainability, and testing?

HardTechnical

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You're given an EXPLAIN ANALYZE snippet that shows a CTE Scan on cte1 followed by a Nested Loop Join to a large table and high actual time for the nested loop. How would you interpret this plan and what concrete steps would you try to optimize the query? Mention indexing, CTE materialization, rewrite strategies and statistics improvements.

MediumTechnical

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Given sales(order_id INT, user_id INT, amount NUMERIC, sale_date DATE), produce a query that uses a CTE and a window function to compute each user's running month-to-date revenue and then select users with the highest MTD increase compared to previous month. Describe the CTE stages.

HardTechnical

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Describe how you would implement 'top N per group' analytics: find top 3 orders by amount per customer. Window functions cannot be used in WHERE; show how to use a CTE to compute ROW_NUMBER() OVER (PARTITION BY customer_id ORDER BY amount DESC) and then filter to top 3 per customer. Provide example SQL and discuss scalability.

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