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Design a Ranked Cache

System Design

Problem

Design a Ranked Cache.

Self-assessment rubric

0/20

Requirements & Scope

Clarified what "rank" means (recency, frequency, external score, or hybrid) before designing
Established whether scores are static or dynamically updated post-insertion
Defined scale targets (QPS, item count) and latency budget (P99 < ~5ms)
Explicitly scoped out exact global top-K/ranking in favor of approximate per-shard ranking

Core Architecture

Proposed a sharded/distributed design with consistent hashing for routing
Designed each shard with a HashMap for O(1) lookup plus a separate rank-ordered structure for eviction
Identified a concrete rank structure (min-heap with index map, or skip list) and justified O(log n) update/evict complexity
Included a backing store as source of truth with cache-aside or write-through/write-back fill strategy

APIs & Schema

Defined get/put/update-score/delete endpoints with reasonable request/response shapes
Specified per-key metadata needed for ranking (score, lastAccessTime, accessCount, node_ref/index)

Core Flows

Walked through cache hit and cache miss flows including score/rank structure updates
Walked through eviction flow triggered by capacity pressure
Described a background process for score decay or refresh

Deep Dives / Trade-offs

Addressed the cost of updating rank structure on every access and proposed batching/lazy updates to avoid thrashing
Discussed heap vs skip-list (or equivalent) trade-off for eviction/top-K support
Addressed hot-key/skewed score distribution problem (replication, score capping/decay)
Addressed cache-backing store consistency trade-off (write-through vs write-back)

Communication

Structured the session within time budget, prioritizing high-level design before deep dives
Clearly articulated trade-offs rather than presenting one "correct" answer
Gave a concise, confident opening/summary framing of the overall design

Solution

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