A user uploads the same 50MB video five times because their network kept dropping. Your storage costs just quintupled for a single file.

A message queue retries a failed message. The consumer processes it again. Now there are two charges on the customer's credit card.

A distributed system syncs data across nodes. The same record arrives from three different sources. Your database now has three copies of "truth."

These scenarios share the same root cause: duplicate data. In distributed systems, duplicates are a normal condition to design for. Networks drop packets. Services retry requests. Users double-click submit buttons.

The interview question is not "how do I prevent every duplicate?" It is "where can duplicates appear, and how do I make the operation safe when they do?"

This chapter covers how to detect and handle duplicates across different scenarios: file storage, message processing, database records, and API requests. The important skill is choosing the right deduplication boundary: content, message, record, or request.