Parquet to CSV Converter
Drop any .parquet file to instantly convert it to a downloadable CSV. Nothing leaves your browser.
About This Tool
The Parquet to CSV Converter is a free online utility that converts Apache Parquet files directly in your browser — no software to install, no account to create, and no data sent to any server.
Parquet is a columnar storage format widely used in big-data pipelines with tools like Apache Spark, AWS Athena, Google BigQuery, and pandas. CSV is the universal, human-readable format compatible with Excel, Google Sheets, R, and virtually every data tool in existence. This converter bridges the two instantly in your browser.
Whether you are exploring a dataset, exporting Spark job output for a stakeholder, or spot-checking row values before a pipeline runs, the Parquet to CSV Converter gives you fast results with no login and no server-side processing whatsoever.
Common Use Cases
- Export data to Excel or Google Sheets — Turn
.parquetoutput from Spark or Athena jobs into a CSV a stakeholder can open without any special tooling. - Inspect a dataset without a cluster — Quickly peek at row content, column names, and types without spinning up Spark, Hive, or a Jupyter notebook.
- Debug ETL pipeline output — Verify that a Parquet file written by an ETL job matches the expected schema and value ranges before downstream processing.
- Share data with non-engineers — Convert columnar Parquet into universally-supported CSV for analysts, finance teams, or external partners who need a flat file.
- Keep sensitive data private — All conversion happens client-side; no data ever leaves your device, making this safe for restricted or personally identifiable datasets.
How It Works
.parquet file onto the drop zone, or click browse to pick one from disk. The file is read locally into an ArrayBuffer — nothing is transmitted to a server.PAR1 magic bytes, reads the Thrift-encoded footer metadata, decodes every row group and data page, and handles common encodings (PLAIN, RLE, DELTA) and codecs (Snappy, Gzip, uncompressed) — all using the hyparquet engine running entirely in JavaScript.What Gets Processed
- Magic-byte validation — Confirms the file begins and ends with the Parquet magic bytes
PAR1before attempting a full parse, catching truncated or mis-labelled files early. - Footer metadata extraction — Reads column names, logical types, and row group layout from the Thrift-encoded file footer so CSV headers are accurate.
- Row group decoding — Iterates over every row group and data page, decoding values regardless of encoding —
PLAIN,RLE_DICTIONARY,DELTA_BINARY_PACKED, and others. - Compression handling — Supports Snappy, Gzip, and uncompressed page codecs commonly found in files produced by Spark and pandas.
- RFC 4180 CSV escaping — Values containing commas, double quotes, or newline characters are properly quoted and escaped so the output is valid CSV that any parser will handle correctly.
- Null-value mapping — Parquet nulls are written as empty fields in the CSV, preserving row alignment without corrupting downstream parsers or introducing spurious values.
🔒 Privacy & Security
All processing is performed locally using the Web File API and the hyparquet JavaScript library. Your file is read into an ArrayBuffer in memory and never sent to any server — suitable for sensitive, confidential, or personally-identifiable datasets.