Memory Allocation for Streaming Pipelines | Dataford Interview Questions

Write a function to optimize the memory allocation for a streaming data pipeline. Given memory requests as [start, end, blocks], where end is exclusive, assign reusable integer block IDs to every request. Requests whose lifetimes overlap must not share blocks. Return allocations in input order and the minimum peak number of blocks required. Use def optimize_memory_allocation(requests):, with output {"allocations": List[List[int]], "peak_blocks": int}. Requests may be unsorted, and a request ending at time t may share blocks with one starting at t].

Constraints

1 <= len(requests) <= 500
Each request has the form [start, end, blocks]
0 <= start < end <= 10^9
1 <= blocks <= 10^5
The total number of requested blocks can be large
Block IDs must be nonnegative integers and allocations must be disjoint for overlapping lifetimes

Function Signature

def optimize_memory_allocation(requests):

Your question is Memory Allocation for Streaming Pipelines. 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(requests) <= 500
Each request has the form [start, end, blocks]
0 <= start < end <= 10^9
1 <= blocks <= 10^5
The total number of requested blocks can be large
Block IDs must be nonnegative integers and allocations must be disjoint for overlapping lifetimes

Function Signature

def optimize_memory_allocation(requests):

Your question is Memory Allocation for Streaming Pipelines. 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.