Compare streaming frameworks and delivery semantics
Company: Mercor
Role: Software Engineer
Category: System Design
Difficulty: medium
Interview Round: Technical Screen
Name popular streaming/data-processing frameworks (e.g., Kafka-based stacks, Flink, Spark Streaming, etc.).
Explain **at-most-once**, **at-least-once**, and **exactly-once** processing/delivery semantics. Include what guarantees they provide, typical implementation techniques, and trade-offs.
Overview: This question evaluates understanding of stream processing frameworks and message delivery semantics—at-most-once, at-least-once, and exactly-once—by probing knowledge of the guarantees, common implementation techniques, and trade-offs involved in distributed data pipelines.