Sample Answer
On a customer-orders microservice (PostgreSQL, ~5M rows across tables), I used Spring Data JPA. Our main entity was `Order` with a one-to-many to `OrderItem` and a many-to-one to `Customer`. Entities were lean: JPA annotations, validation, and minimal business logic. We used `@EntityGraph` and DTO projections to avoid over-fetching. Repositories extended `JpaRepository<Order, Long>` with a few query methods like `findByCustomerIdAndStatus`. Anything complex went into custom repository implementations using `@Query` with JPQL. The service layer was annotated with `@Transactional`, and we defaulted to read-only transactions for queries to reduce overhead. Lazy loading was a big issue at first; we hit N+1 problems and `LazyInitializationException` in REST controllers. To fix it, we used explicit fetch joins in queries, `@EntityGraph` for common read paths, and mapped to DTOs inside the transaction boundary. That cut some endpoints from 200+ queries down to under 10 and improved response times by ~35%.
Keywords
In your civil engineering studies, what specific design coursework or project work did you complete related to irrigation channels or canals (e.g., design of lined/unlined canals, distributaries, minors)? Describe one such design in detail, including how you determined discharge, permissible velocity, section dimensions, and lining choice for Gujarat-type soil and climate conditions.
Based on your hydrology and irrigation engineering background, explain how you would estimate the irrigation water requirement for a kharif crop in a semi-arid region of Gujarat. Walk me through each step: from reference evapotranspiration estimation, crop coefficient selection, effective rainfall calculation, to arriving at canal discharge for a given command area.
On your resume you mention working on a cross-functional project (e.g., involving multiple teams or stakeholders). Describe a situation from that project where priorities conflicted—how did you navigate the trade-offs and what was the final outcome?
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