Senior LevelSystem Design & Architecture
How do you design a High-Throughput Ad Click Tracking System (millions of events/sec)?
❓ Interview Prompt: Explain Ad Tech Click Tracking architecture, edge HTTP ingestion, Kafka partitioning, Bloom Filter click deduplication, and Flink streaming aggregation.
Designing a High-Throughput Ad Click Tracking & Billing System (millions of events/sec):
Key Components:
1
Edge Ingestion: Lightweight HTTP endpoints return '202 Accepted' or transparent '1x1 GIF' pixels immediately.
2
Click Deduplication: Uses Redis Bloom Filters to reject duplicate fraud clicks within a 10-minute window.
3
Streaming Aggregations: Apache Flink windowed streams aggregate clicks by advertiser account every 10 seconds for real-time billing updates.
Code Implementation Example
markdown
High-Throughput Ad Click Tracking Architecture:
[User Click] ──> [Edge Ingestion (Go)] ──> [Kafka Event Stream]
│
(Flink Stream Window)
│
├──> [Redis Bloom Filter (Deduplication)]
└──> [Real-Time Billing DB]💡High-throughput ad click tracking pipeline using Kafka, Flink, and Bloom Filters.
🎯 Interview Key Takeaway
Design click tracking pipelines using edge ingestion, Kafka streams, and Flink windowed aggregations for real-time billing.
#System Design#Ad Tech#Kafka#Flink#Senior
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