Apache Spark Sql Datasource Parquet - Latest Information & Updates 2026

Web Reference: Parquet is a columnar format that is supported by many other data processing systems. Spark SQL provides support for both reading and writing Parquet files that automatically preserves the schema of the original data. When reading Parquet files, all columns are automatically converted to be nullable for compatibility reasons. Parquet is a columnar format that is supported by many other data processing systems. Spark SQL provides support for both reading and writing Parquet files that automatically preserves the schema of the original data. When reading Parquet files, all columns are automatically converted to be nullable for compatibility reasons. The default is gzip. Currently, Spark looks up column data from Parquet files by using the names stored within the data files. This is different than the default Parquet lookup behavior of Impala and Hive. If data files are produced with a different physical layout due to added or reordered columns, Spark still decodes the column data correctly.

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Last Updated: April 2, 2026

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