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Currently, Moka cache uses TinyLFU as the admission/eviction policies (with a small buffer in front of the LFU filter). While it works well for many workloads like database, search, and analytics, it will not work well for recency-biased workloads, like job queues and event streams.
To provide better hit rate for such workloads, do the followings:
Upgrade the cache admission/eviction policy from TinyLFU to Window-TinyLFU (W-TinyLFU).
Implement hill climbing to auto-tune the size of the LRU window for current workload.
Currently, Moka cache uses TinyLFU as the admission/eviction policies (with a small buffer in front of the LFU filter). While it works well for many workloads like database, search, and analytics, it will not work well for recency-biased workloads, like job queues and event streams.
To provide better hit rate for such workloads, do the followings:
For more details, see the "Eviction Policy" chapter of an article about Java Caffeine cache:
http://highscalability.com/blog/2019/2/25/design-of-a-modern-cachepart-deux.html
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