Your question is Handling Deadlocks in Concurrent Transactions. Take a moment with it on the right.
Talk me through your thinking if you like. When you're confident, submit your answer and I'll grade it like a real screen (7/10 or better passes).
In high-concurrency data systems, deadlocks can cause transaction failures, retries, and throughput drops. This matters in operational pipelines and transactional workloads where many sessions update overlapping rows.
Explain how you would handle deadlocks in a high-concurrency PostgreSQL environment. Your answer should cover how deadlocks happen, how PostgreSQL detects and resolves them, how you would investigate them in production, and what query or schema design changes reduce their frequency. You should also explain what an application should do when a transaction is aborted due to a deadlock.
The interviewer is looking for a practical database answer, not just a definition. You should speak to transaction ordering, lock scope, indexing, short transactions, retry strategy, and the trade-off between correctness and throughput, ideally using examples from operational tables such as incident, alert, or case-processing workloads.