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This question is commonly asked for Data Engineer candidates at Netflix during technical interviews.

Implement a Weighted Eviction Cache | Netflix Interview Question

Quick Overview

This question evaluates proficiency with data structures and algorithmic design for resource-constrained caching, specifically weight-aware eviction policies combined with LRU tie-breaking, and the ability to reason about efficiency and stateful operation under capacity limits.

Design an in-memory cache whose capacity is limited by total weight rather than by the number of entries.

Each entry has:

a key
a value
a positive integer weight

Support the following operations:

get(key) : return the value associated with key , or -1 if the key is not present.
put(key, value, weight) : insert a new entry or update an existing one.

The cache has a maximum allowed total weight W. After every put, if the sum of weights of all cached entries exceeds W, repeatedly evict entries until the total weight is at most W.

Eviction rule:

Evict the entry with the largest weight first.
If multiple entries have the same weight, evict the least recently used among them.

Additional rules:

A successful get makes the entry most recently used.
Updating an existing key through put also makes it most recently used.
If a single entry's weight is greater than W , it should not remain in the cache.

Implement this data structure efficiently.

Implement a Weighted Eviction Cache

Quick Overview

Implement a Weighted Eviction Cache

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