What is Schema Evolution in Parquet?

Schema evolution is the ability to change a Parquet dataset's schema over time without rewriting existing files. Parquet natively supports:

• Adding columns — new columns appear as null in older files when read together with newer files.
• Renaming columns — supported via field IDs (used in formats like Iceberg on top of Parquet).
• Widening types — e.g., INT32 → INT64 is safe; narrowing is not.

In Apache Spark, set mergeSchema = true to merge schemas across multiple Parquet files automatically:

df = spark.read.option("mergeSchema", "true").parquet("s3://bucket/data/")

Schema evolution is critical for long-lived data lakes where upstream producers add new fields without co-ordinating with all downstream consumers.

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