parquet
What is a .parquet file?
application/vnd.apache.parquet
Apache Parquet (.parquet) is a binary, columnar storage format for analytical data. It stores each column separately with per-column compression and encoding, embeds a schema and statistics, and is the de-facto standard for data lakes and engines like Spark, DuckDB, and pandas/pyarrow.
How to use a .parquet file
Use an example .parquet file to test columnar readers (pyarrow, DuckDB, Spark), schema and predicate-pushdown handling, and Parquet-to-CSV/JSON converters.
Download example .parquet files
- Parquet: Columnar TableA small employee table as Apache Parquet: the columnar format at the heart of modern data lakes and analytics. For testing Parquet readers (pandas, Spark, DuckDB) and conversion.
- E-commerce Products (Parquet, 200 rows)The e-commerce products table as Apache Parquet: the columnar twin, for testing analytics engines (pandas, DuckDB, Spark).
- E-commerce Orders (Parquet, 2000 rows)The e-commerce orders table as Apache Parquet: the columnar twin, for testing analytics engines (pandas, DuckDB, Spark).
- Parquet: Null-heavy ColumnsTiny Parquet table with null name/score/note cells. Tests null handling in columnar readers.
- Parquet: Dictionary-encoded ColumnParquet with dictionary-encoded string column. Tests dictionary page decoding.
- Parquet: Nested Struct ColumnParquet with a struct column. Tests nested type round-trips.
- Parquet: List ColumnParquet with a list-of-string column. Tests repeated-field decoding.
- Parquet: Empty TableEmpty Parquet file with schema but no rows: edge case for readers.
and 5 more in the library.