Tune aiki a Spring Boot galibi game da iyakar database ne: connection pooling, caching, da kashe matsalar tambaya ta N+1. Auna tukuna (Micrometer + Actuator metrics), sannan ka kai hari kan tsada mafi girma.
Lazy associations suna harba tambaya guda kowane parent, sannan ƙarin guda kowace samun child:
List<Order> orders = orderRepo.findAll();
(Order o : orders) {
o.getItems().size();
}
Gyara shi ta ɗauko association a cikin join guda:
@Query("SELECT o FROM Order o JOIN FETCH o.items") // one query, items eagerly loaded
List<Order> findAllWithItems();
// Or @EntityGraph(attributePaths = "items") on the repository method.
HikariCP shi ne pool na tsoho. Girma ba ya fi kyau — connections da yawa suna murƙushe DB. Fasali na kowa yana farawa kusa da cores * 2:
spring:
datasource:
hikari:
maximum-pool-size: 10 # match DB capacity, not thread count
connection-timeout: 3000 # fail fast instead of piling up requests
@Cacheable(value = "products", key = "#id") // serve from cache after first load
public Product findById(Long id) { return repo.findById(id).orElseThrow(); }
@CacheEvict(value = "products", key = "#p.id") // invalidate on write
public Product update(Product p) { return repo.save(p); }
Goya shi da Redis (spring-boot-starter-data-redis) don cache da aka raba a tsakanin misalai.
Hira ta senior tana gwada ko kana bincike kafin ka ingiza. Ƙarfafan amsoshi suna ambaton kayan aikin da ke tabbatar da cinkoso (kunna spring.jpa.show-sql ko datasource-proxy don ƙidaya tambayoyi, karanta p99 latency daga Actuator), suna bayyana dalilin da ya sa pool mai girma ke cutarwa, kuma suna ɗaukar caching a matsayin matsalar daidaito — tsofin bayanai da invalidation — ba kawai maɓallin gudu ba.
Ɗakin karatu na tambayoyin hira na IT tare da amsoshi cikakke — daga Junior zuwa Senior.
Ba da Gudummawa