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Design an Accurate Click Aggregator

Last updated: Apr 22, 2026

Quick Overview

This question evaluates a candidate's ability to design reliable, high-throughput event processing and analytics systems, emphasizing data modeling, ingestion, deduplication, aggregation, and correctness under scale with a primary focus on accuracy.

  • medium
  • Apple
  • System Design
  • Software Engineer

Design an Accurate Click Aggregator

Company: Apple

Role: Software Engineer

Category: System Design

Difficulty: medium

Interview Round: Technical Screen

Design an ad click aggregation system. The system receives click events from multiple sources, including web, mobile apps, and TV devices. It must ingest a high volume of click data, handle duplicates and retries, and produce accurate aggregated click counts for downstream analytics and reporting. Accuracy is a primary requirement. Discuss: - the event schema or API contract - the ingestion pipeline - how to normalize data from different client sources - how to deduplicate events and avoid overcounting - how to aggregate counts by dimensions such as ad, campaign, source, and time window - storage choices for raw data and aggregated results - how to handle late or out-of-order events - how to scale the system while preserving correctness and availability

Quick Answer: This question evaluates a candidate's ability to design reliable, high-throughput event processing and analytics systems, emphasizing data modeling, ingestion, deduplication, aggregation, and correctness under scale with a primary focus on accuracy.

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Apple logo
Apple
Dec 22, 2025, 12:00 AM
Software Engineer
Technical Screen
System Design
5
0
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Design an ad click aggregation system.

The system receives click events from multiple sources, including web, mobile apps, and TV devices. It must ingest a high volume of click data, handle duplicates and retries, and produce accurate aggregated click counts for downstream analytics and reporting. Accuracy is a primary requirement.

Discuss:

  • the event schema or API contract
  • the ingestion pipeline
  • how to normalize data from different client sources
  • how to deduplicate events and avoid overcounting
  • how to aggregate counts by dimensions such as ad, campaign, source, and time window
  • storage choices for raw data and aggregated results
  • how to handle late or out-of-order events
  • how to scale the system while preserving correctness and availability

Solution

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