Cache data da costaffi a samarwa, an karanta sau-sau, kuma ba kasua ba — wato ne gida da caching an bugi. TTL (lokacin rayu) canja tsakanin shiryewa (menene kwatancen data) da sulkewar gida (menene zafin ajiya da yawancin lokaci).
Cache data da costaffi a samarwa, an karanta sau-sau, kuma ba kasua ba — wato ne gida da caching an bugi. TTL (lokacin rayu) canja tsakanin shiryewa (menene kwatancen data) da sulkewar gida (menene zafin ajiya da yawancin lokaci).
Candidate mai kyau don cache yana kan manyan gaba gaida:
Ka cache abin dan samuwa, rubuta-mai nauyi, ko sirrin mai aiki-gida data cewa ka bugi yiyuwa daidai (misali, akwatin dala a lokacin kasuwa).
Staleness tolerance → TTL:
config / static reference data → long (hours to days)
product listings, article body → medium (minutes)
prices, stock, leaderboards → short (seconds)
must always be exact → don't cache, or use explicit invalidation
Don daidai akai data da ke canja ba alama, haɗa TTL da fallaci gaskiya: rubuta-ta gida ko rubuta-on-rubuta yadda cache ya fadi tashe a maimakon jiran sakewa.
on update(record):
db.save(record)
cache.delete(key(record)) // invalidate now, don't serve stale until TTL
hit ratio = hits / (hits + misses)
high (>90%) → cache is doing its job
low → TTL too short, keys too granular, or data not cacheable
Kalli cache hit ratio don tune TTLs: rauni kaɗan yana nufin ba ka caching ba; rauni mai girma tare da daidai-daidai yana nufin TTLs suna da tsayi.
Samun menene za ka cache da TTL daidai ne ainihin caching maidowa. Cache abubuwa mara kyau da kuma ka ƙara hadaddiya ba tare da anfani ba; sai da TTLs da tsayi kuma ka ba da tsoffin data; gida mai laushi da kuma ba ka taba anfani. Amfani da sulkewar gida don zabing TTLs, sai da fallaci gaskiya don daidai, da kalli rauni ya ba ka hanya da ma'anar samu, asusuwa na cache.