Complex Data Integration and Joins Questions
Handling intricate join scenarios: multi-condition joins, conditional joins with complex logic, joining on date ranges or overlapping time periods, complex left joins with multiple filtering conditions, self-joins for hierarchical or relationship data, handling non-standard relationships between tables. Understanding implications of different join types on row counts, NULL values, and duplicate handling. Designing queries that correctly integrate data from multiple sources while maintaining data integrity and avoiding duplicate counting or missing data.
HardTechnical
0 practiced
Write a SQL query that assigns each transaction (transactions(tx_id, tx_time, amount)) to the allocation with the highest priority in allocations(alloc_id, start_time, end_time, priority). Allocations may overlap; ensure transactions get at most one allocation (the highest-priority one that contains tx_time). Use window functions or lateral joins in Postgres and explain performance considerations.
MediumTechnical
0 practiced
You have students, courses, enrollments(student_id, course_id), and grades(student_id, course_id, grade). When computing average grade per course, naive joins can produce duplicates due to multiple enrollment rows or grade rollback audits. Describe a SQL approach that ensures accurate per-course averages and implement it in SQL.
MediumTechnical
0 practiced
Discuss the trade-offs of performing complex joins inside the data warehouse during query time vs performing the same joins during an ETL batch job to produce denormalized tables. Consider cost, query performance, data freshness, and operational complexity for a data engineering team.
HardTechnical
0 practiced
Explain a scalable approach in Apache Spark to join orders to promotions (time ranges) while minimizing shuffle and avoiding cartesian explosion. Describe code-level choices in Spark 3.x (broadcast, repartition, map-side join), partitioning strategy, and fallbacks when promotions are not small.
EasyTechnical
0 practiced
Explain the differences between inner, left, right, full outer, semi, and anti joins and how each affects output row counts, NULL handling, and duplicate rows in typical relational engines. Provide one short example scenario that shows when a LEFT JOIN returns the same number of rows as an INNER JOIN.
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