TTL Caching for Microservices | Dataford Interview Questions

Implement a custom caching mechanism with Time-To-Live (TTL) expiration for high-frequency API responses in a distributed microservices environment. Implement ttl_cache(operations, ttl) using simulated timestamps. Each operation is ['set', key, value, timestamp] or ['get', key, timestamp]; return the values from GET operations in order, using -1 for misses or expired entries. An entry expires when current_time >= insertion_time + ttl.

Constraints

1 <= len(operations) <= 1000
1 <= ttl <= 10^9
Each operation is either ['set', key, value, timestamp] or ['get', key, timestamp]
key and value are non-empty strings
0 <= timestamp <= 10^9
Operation timestamps are nondecreasing
SET values and GET results are compared as strings; cache misses return -1

Function Signature

def ttl_cache(operations, ttl):

Your question is TTL Caching for Microservices. Start with the requirements in the Question tab.

Run and submit as often as you like. When you're ready, talk me through your approach or go straight to the code.

Problem

Constraints

1 <= len(operations) <= 1000
1 <= ttl <= 10^9
Each operation is either ['set', key, value, timestamp] or ['get', key, timestamp]
key and value are non-empty strings
0 <= timestamp <= 10^9
Operation timestamps are nondecreasing
SET values and GET results are compared as strings; cache misses return -1

Function Signature

def ttl_cache(operations, ttl):

Your question is TTL Caching for Microservices. Start with the requirements in the Question tab.

Run and submit as often as you like. When you're ready, talk me through your approach or go straight to the code.