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Home/Questions/Spark/Big Data/Your Kafka producer schema has changed, and the new data includes additional fields. How would you ensure backward compatibility using Schema Registry while consuming data from the same topic?

Your Kafka producer schema has changed, and the new data includes additional fields. How would you ensure backward compatibility using Schema Registry while consuming data from the same topic?

Spark/Big Datamedium0.6 min readPremium
Frequency
Low
Asked at 1 company
Category
452
questions in Spark/Big Data
Difficulty Split
88E|81M|283H
in this category
Total Bank
1,863
across 7 categories
Asked at these companies
Dunnhumby
Key Concepts Tested
partition
Expert AnswerPremium
129 wordsInterview-ready
**Why It Matters (Architectural Logic)**: Strict schemas reject malformed data at read time—fail fast vs. silent corruption. FAILFAST mode prevents partial loads. Schema Registry enables schema evolution. Backward compatibility: new schema adds optional fields; old consumers ignore them. Use Avro/Protobuf with `schema.registry.url`. Consumer: fetch schema by id/version, deserialize. Config: `auto.register.schemas=false`, `use.latest.version=true` or `use.specific.avro.reader=true`....
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