Uboreshaji wa performance katika Spring Boot mara nyingi unahusu mpaka wa database: connection pooling, caching, na kuua tatizo la N+1 query. Pima kwanza (Micrometer + Actuator metrics), kisha shambulia gharama kubwa zaidi.
Lazy associations hutoa query moja kwa kila parent, kisha moja zaidi kwa kila ufikiaji wa child:
List<Order> orders = orderRepo.findAll();
(Order o : orders) {
o.getItems().size();
}
Irekebishe kwa kupata association katika join moja:
@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 ndio pool ya chaguo-msingi. Kubwa zaidi si bora zaidi — connections nyingi mno hupiga vita database. Fomula ya kawaida huanza karibu na 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); }
Iunge mkono na Redis (spring-boot-starter-data-redis) kwa cache inayoshirikiwa kuvuka instances.
Mahojiano ya senior hupima kama unatambua (diagnose) kabla ya kuboresha. Majibu imara zaidi hutaja chombo kinachothibitisha kizuizi (washa spring.jpa.show-sql au datasource-proxy kuhesabu queries, soma p99 latency kutoka Actuator), hueleza kwa nini pool kubwa mno huumiza, na huchukulia caching kama tatizo la usahihi — data iliyopitwa na wakati na invalidation — si tu kifundo cha kasi.
Maktaba ya maswali ya mahojiano ya IT yenye majibu ya kina — kutoka Junior hadi Senior.
Changia