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hardSystem Design

How would you design a distributed cache?

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01

Understand the problem

Outline distributed caching.

distributed-cache
02

Attempt it yourself

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Nudge consolestandby

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03

Study the solution

Step 1: Outline use cases and constraints

Gather requirements and scope the problem. Ask questions to clarify use cases and constraints. Discuss assumptions.

Use cases

We'll scope the problem to handle only the following use cases

  • User performs core action described in How would you design a dis

Solution ready — 2 min read

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04

Read the code

Per-node LRU eviction
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from collections import OrderedDict

class LRUCache:
    def __init__(self, capacity):
        self.capacity = capacity
        self.store = OrderedDict()
    def get(self, key):
        if key not in self.store:
            return None
        self.store.move_to_end(key)          # mark most-recently-used
        return self.store[key]
    def put(self, key, value):
        self.store[key] = value
        self.store.move_to_end(key)
        if len(self.store) > self.capacity:
            evicted, _ = self.store.popitem(last=False)   # drop least-recently-used
            print("evicted", evicted)

c = LRUCache(2)
c.put("a", 1); c.put("b", 2)
c.get("a")                  # 'a' is now most-recently-used
c.put("c", 3)               # over capacity -> evicts 'b'
print("a:", c.get("a"), "b:", c.get("b"), "c:", c.get("c"))
05

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