Compute the Longest Run of Ones Across Multiple Machines

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Design an exact distributed reduction for the longest run of ones when a binary input is split across ordered machines. The solution derives a constant-size shard summary, proves the ordered merge rule, and covers all-one bridges, retries, shard identity, and reduction cost.

Compute the Longest Run of Ones Across Multiple Machines

Company: Molocoads

Role: Machine Learning Engineer

Category: System Design

Difficulty: medium

Interview Round: Onsite

# Compute the Longest Run of Ones Across Multiple Machines A binary sequence is too large for one machine and is split into contiguous, ordered shards. Design a distributed computation that returns the exact length of the longest contiguous run of `1` values in the original sequence. Shards may have different lengths, and the longest run may cross one or many shard boundaries. Explain the per-shard summary, the merge operation, correctness, communication cost, fault handling, and how the design preserves global shard order. ### Clarifying Questions to Ask - Are shard boundaries contiguous and nonoverlapping, and is their global order known? - Must the result be computed once for an immutable input or updated as shards arrive? - Can a coordinator retain one constant-size summary per shard? ### What a Strong Answer Covers - A constant-size summary containing shard length, all-ones status, prefix run, suffix run, and internal maximum. - A merge rule that handles runs spanning a boundary and composes summaries in global order. - An argument that the summary is sufficient even when an all-ones shard bridges two neighbors. - A tree reduction or ordered aggregation plan with bounded communication. - Retry, duplicate-result, missing-shard, and skew considerations. ### Follow-up Questions - Can the merge operation be made associative so a tree reduction is safe? - How would you update the answer after replacing one shard? - What metadata prevents duplicate or out-of-order shard summaries from corrupting the result?

Overview: Design an exact distributed reduction for the longest run of ones when a binary input is split across ordered machines. The solution derives a constant-size shard summary, proves the ordered merge rule, and covers all-one bridges, retries, shard identity, and reduction cost.

Read the full Molocoads Machine Learning Engineer interview experience this question came from

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Aug 26, 2026
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Compute the Longest Run of Ones Across Multiple Machines

A binary sequence is too large for one machine and is split into contiguous, ordered shards. Design a distributed computation that returns the exact length of the longest contiguous run of 1 values in the original sequence. Shards may have different lengths, and the longest run may cross one or many shard boundaries.

Explain the per-shard summary, the merge operation, correctness, communication cost, fault handling, and how the design preserves global shard order.

Clarifying Questions to Ask Guidance

  • Are shard boundaries contiguous and nonoverlapping, and is their global order known?
  • Must the result be computed once for an immutable input or updated as shards arrive?
  • Can a coordinator retain one constant-size summary per shard?

What a Strong Answer Covers Guidance

  • A constant-size summary containing shard length, all-ones status, prefix run, suffix run, and internal maximum.
  • A merge rule that handles runs spanning a boundary and composes summaries in global order.
  • An argument that the summary is sufficient even when an all-ones shard bridges two neighbors.
  • A tree reduction or ordered aggregation plan with bounded communication.
  • Retry, duplicate-result, missing-shard, and skew considerations.

Follow-up Questions Guidance

  • Can the merge operation be made associative so a tree reduction is safe?
  • How would you update the answer after replacing one shard?
  • What metadata prevents duplicate or out-of-order shard summaries from corrupting the result?

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