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FAQ about Apache HUDI Files

Q1: Can I edit a HUDI file directly?

A1: No, you shouldn't directly edit the underlying files that constitute a Hudi table. All modifications (inserts, updates, deletes) should be performed through Hudi's API and the processing engines (like Spark) to ensure data consistency and integrity.

Q2: Is Apache Hudi only for really large datasets?

A2: While Hudi excels with large-scale data, its benefits like ACID transactions, schema evolution, and efficient updates are valuable for many sizes of analytical datasets where changes happen frequently. However, for extremely small, static datasets, its overhead might not be justified.

Q3: How do I convert data into a Hudi table?

A3: You typically use a data processing framework like Apache Spark to write data to a Hudi table. You would read your existing data (from CSV, Parquet, etc.) into a Spark DataFrame and then use the Hudi writer API to store it in the Hudi format.