InterviewStack.io LogoInterviewStack.io

Advanced Querying with Structured Query Language Questions

Covers authoring correct, maintainable, and high quality Structured Query Language statements for analytical and transactional problems. Candidates should demonstrate writing Select Insert Update and Delete statements and using filtering grouping ordering and aggregation correctly. Emphasis is on complex query constructs and patterns such as multi table joins and join condition logic self joins for hierarchical data nested and correlated subqueries common table expressions including recursive common table expressions window functions such as row number rank dense rank lag and lead set operations like union and union all and techniques for calculating running totals moving averages cohort metrics and consecutive event detection. Candidates should be able to break down and refactor complex requirements into composable queries for readability and maintainability while reasoning about performance implications on large data sets. Senior expectations may include mentoring on best practices for query composition and understanding how schema and configuration choices influence query performance.

HardTechnical
0 practiced
Your team uses BigQuery and charges are dominated by bytes scanned. Propose query refactor strategies and table design choices to reduce query costs for repeated ML experiments: include partitioning, clustering, materialized views, column selection, and data format choices. Provide small SQL examples that illustrate cost-saving techniques.
MediumTechnical
0 practiced
Given a production features table and new incoming records in staging, write a standard SQL MERGE statement to perform an upsert: update existing rows and insert new rows, updating a last_updated column. Discuss concurrency considerations and how to make the operation idempotent for retries.
HardTechnical
0 practiced
Write an optimized SQL query (Postgres or Spark SQL) that computes session boundaries for each user given events(user_id, event_time) where a new session begins if gap > 30 minutes. For each user, return the longest session duration and the top 3 sessions by duration. Also explain indexes and partitioning that make this fast on millions of users.
MediumTechnical
0 practiced
Given a feature_updates table(feature_id, entity_id, value, valid_from timestamp, valid_to timestamp null means current), write SQL to produce the latest valid feature value for all entities as of a given timestamp 'as_of_ts'. Show an efficient filter-based approach and discuss indexing strategy for fast lookups when as_of_ts varies per query.
HardTechnical
0 practiced
Show how to detect cardinality estimation errors in PostgreSQL using EXPLAIN ANALYZE by comparing estimated rows to actual rows. Explain how creating multi-column statistics or increasing statistics target can help, and provide SQL commands to create extended statistics.

Unlock Full Question Bank

Get access to hundreds of Advanced Querying with Structured Query Language interview questions and detailed answers.

Sign in to Continue

Join thousands of developers preparing for their dream job.