Java Backend Interview Experience: Spring, Nacos, Redis, SQL Optimization and More

This article presents a developer's detailed interview recap after about two years of experience, offering insights and advice for future candidates.

It starts with a reminder to prepare a concise self‑introduction, as a shaky opening can hurt the interview.

The candidate lists the frameworks used in past projects—Spring, Spring MVC, Spring Boot, MyBatis, and the Spring Cloud suite—stating they can build and run applications independently but have limited deep knowledge of underlying principles.

For microservice service registration and discovery, the team chose Nacos over Eureka because Nacos provides a built‑in configuration center, supports grouping by business or environment, and offers more advanced features.

The interviewee could not explain Nacos's internal implementation and was directed to an external article for further study.

When asked about the differences between SpringBoot and Spring, the answer highlighted SpringBoot's auto‑configuration, embedded container, and zero‑configuration approach. The startup process relies on the @SpringBootApplication annotation, which includes @ComponentScan to scan and register beans in the Spring context.

Design patterns mentioned include the Factory pattern (used in BeanFactory and ApplicationContext), Proxy pattern (JDK dynamic proxy in AOP), and Singleton pattern (default bean scope).

The candidate affirmed familiarity with Linux, listing common commands such as vim, find, mkdir, rm, kill, cp, as well as network‑related commands like ping ip and service network restart.

Redis experience is described as regular usage, with examples of commands like info, shutdown, get, setnx, and lindex. The interview also touched on cache issues such as penetration, avalanche, and breakdown, though detailed solutions were not provided.

For Excel import/export, the candidate used Apache POI and noted that exporting very large datasets can cause memory overflow.

SQL optimization strategies discussed include replacing subqueries with JOINs, adding indexes on WHERE and ORDER BY columns, using EXISTS instead of IN, avoiding functions on indexed columns, limiting the number of JOINs, and recognizing that more indexes are not always better, especially on low‑cardinality columns or frequently modified tables.

Additional topics covered brief mentions of red‑black trees, a transaction annotation pitfall that caused data issues, and other project‑specific questions.

The article concludes with links to further interview resources and a call to follow the author's public account for more content.