Pivot order-status counts

Quick Overview

This interview question evaluates algorithm design, data structures, correctness, complexity, edge cases, and implementation details in a realistic interview setting. A strong answer for Pivot order-status counts states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.

Pivot order-status counts

Company: Instacart

Role: Software Engineer

Category: Coding & Algorithms

Difficulty: medium

Interview Round: Onsite

##### Question Given an orders table (order_id, shopper_id, order_date, status, …), pivot the data so that each row is one shopper and each column shows the count of orders for a specific status (e.g., DELIVERED, CANCELED, RETURNED). Provide an efficient Java solution that works on a platform without external date-parsing libraries.

Quick Answer: This interview question evaluates algorithm design, data structures, correctness, complexity, edge cases, and implementation details in a realistic interview setting. A strong answer for Pivot order-status counts states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.

Solution

# Solution Alignment The prompt asks for an implementation-level answer. The safest way to present it is to define the state, maintain clear invariants, then walk through complexity and tests. ## Problem Restatement ##### Question Given an orders table (order_id, shopper_id, order_date, status, …), pivot the data so that each row is one shopper and each column shows the count of orders for a specific status (e.g., DELIVERED, CANCELED, RETURNED). Provide an efficient Java solution that works on a platform without external date-parsing libraries. ## Recommended Approach Start with a brute-force baseline to confirm correctness, then identify the repeated work or ordering property that enables a better data structure such as a hash map, heap, stack, queue, two pointers, prefix sums, BFS/DFS, or dynamic programming. Write the implementation around a small invariant and test that invariant directly. ## Correctness The implementation should maintain an invariant after each loop or operation that directly matches the problem statement. At termination, that invariant implies the returned value has considered every valid candidate exactly once, or has preserved the required data-structure state after every API call. ## Complexity State the baseline complexity and the optimized complexity. For most interview constraints, justify why the optimized approach meets the expected input size. ## Edge Cases and Tests Empty and singleton inputs, duplicates, ties, invalid inputs, boundary values, and tests that exercise the main invariant.
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Aug 4, 2025, 10:55 AM
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Pivot order-status counts

Given an orders table (order_id, shopper_id, order_date, status, …), pivot the data so that each row is one shopper and each column shows the count of orders for a specific status (e.g., DELIVERED, CANCELED, RETURNED). Provide an efficient Java solution that works on a platform without external date-parsing libraries.

Clarifying Questions to Ask Guidance

  • Clarify input sizes, value ranges, mutability, return format, and tie-breaking.
  • State the target time and space complexity before coding.
  • Call out edge cases such as empty inputs, duplicates, invalid values, overflow, and boundary sizes.

What a Strong Answer Covers Guidance

  • A clear algorithm with the right data structures and enough pseudocode or code-level detail to implement it.
  • A correctness argument that explains why the algorithm covers all required cases.
  • Time and space complexity, plus at least one alternative approach when relevant.
  • Focused tests for normal cases, edge cases, and failure modes.

Follow-up Questions Guidance

  • How would the approach change if the input were streaming or too large for memory?
  • What invariants would you assert in production code?
  • Which tests would catch off-by-one, duplicate, or tie-breaking bugs?

Submit Your Answer to Earn 20XP

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