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Advanced SQL Window Functions Questions

Mastery of Structured Query Language window functions and advanced aggregation techniques for analytical queries. Core function families include ranking functions such as ROW_NUMBER, RANK, DENSE_RANK, and NTILE; offset functions such as LAG and LEAD; value functions such as FIRST_VALUE, LAST_VALUE, and NTH_VALUE; and aggregate window expressions such as SUM OVER and AVG OVER. Candidates should understand the OVER clause with PARTITION BY and ORDER BY, frame specifications using ROWS BETWEEN and RANGE BETWEEN, tie handling, null behavior, and how frame definitions affect results. Common application patterns include top N per group, deduplication using row numbering, running totals and cumulative aggregates, moving averages, percent rank and distribution calculations, event sequencing and period over period comparisons, gap and island analysis, cohort and retention analysis, and trend and growth calculations. The topic also covers structuring complex queries with Common Table Expressions including recursive Common Table Expressions to break multi step analytical pipelines and to handle hierarchical or iterative problems, and choosing between window functions, GROUP BY, joins, and subqueries for correctness and readability. Performance and correctness considerations are essential, including join and sort costs, index usage, memory and sort spill behavior, execution planning and query optimization techniques, and trade offs across different database dialects and large data volumes. Interview assessments typically ask candidates to write and explain queries that use these functions, reason about frame semantics for edge cases such as ties, nulls, and partition boundaries, and to rewrite or optimize expensive queries.

MediumTechnical
67 practiced
You're ranking candidates by score within each region, but many candidates tie on score. Describe strategies to ensure deterministic ROW_NUMBER results for downstream de-duplication or joins, and show a sample ORDER BY clause that breaks ties deterministically.
MediumTechnical
121 practiced
Design a SQL query using CTEs and window functions to compute weekly retention for cohorts defined by user signup_week. Output columns: cohort_week, week_number (0,1,...), retained_users, cohort_size, retention_rate. Describe key steps and assumptions.
EasyTechnical
60 practiced
Explain the purpose and components of the SQL OVER clause when used with window functions. Describe how PARTITION BY and ORDER BY inside OVER change the result set, and provide a compact example using ROW_NUMBER() over partitions of country ordered by revenue to illustrate the differences.
HardTechnical
63 practiced
A slow analytics query computes several aggregates by joining the same aggregated subquery multiple times. Show how to rewrite the query using window functions to compute all aggregates in one pass, provide an example, and discuss trade-offs in readability and optimizer behavior.
EasyTechnical
72 practiced
Explain the difference between FIRST_VALUE and LAST_VALUE window functions, and describe a scenario where LAST_VALUE returns unexpected values due to default frame semantics. Show how to change the frame specification to get the intended 'last seen up to current row' behavior.

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