Vault 2016

A storage cache must implement an index to quickly locate the objects it holds. The index’s design is impacted by the storage medium. For example, a memory cache’s requirements differ from a cache built using storage tiers. In the former, an in-memory hash table or balanced tree may suffice. But in the later, those structures may stumble. The metadata required to track such a large number of objects won’t fit in memory. In such cases, the challenge is to find an index that scales. A further consideration is wether to track elements in LRU order, in which case a sorting mechanism is called for. This talk contrasts 3 cache tiering implementations in Linux that have tackled this problem from GlusterFS, Ceph, and DMcache. Solutions vary from bloom filters to sqlite databases. We will explore their relative pros and cons along the dimensions of performance, overhead, complexity, and more.