Converter
JSON is common in APIs, fixtures, and debugging workflows. It can represent nested values that would otherwise need flattening for a CSV file.
viewparquet converts a local Parquet file to JSON Lines in your browser with DuckDB-WASM, without uploading the dataset to viewparquet. Open the file, optionally shape the output with SQL, and export newline-delimited JSON with one value per row.
Drag your .parquet file into viewparquet, or open it from S3 or a URL.
Nested columns can be exported as-is, or projected with dot notation (col.field) and UNNEST to reshape lists before export.
Click Export and choose JSON. viewparquet writes JSON Lines — one JSON object per row — generated locally and downloaded straight from your browser.
Open a local .parquet file in viewparquet and click Export → JSON. DuckDB-WASM performs the conversion in your browser — no Python or install — and the file contents are not uploaded to viewparquet.
DuckDB serializes supported nested Parquet values into JSON representations, such as objects and arrays. Because downstream tools handle nested and logical types differently, verify a sample of the JSON Lines output before relying on an exact schema mapping.
viewparquet exports JSON Lines (NDJSON): one JSON object per line, one line per row. JSON Lines streams well and is what most data tools, log pipelines, and jq workflows expect. Wrapping into a single array is a one-liner afterwards if a tool requires it.
No. For a local file, reading the Parquet data and writing JSON Lines both happen inside your browser tab via DuckDB-WASM; the dataset is not uploaded to a viewparquet server.
With the DuckDB CLI: COPY (SELECT * FROM read_parquet('data.parquet')) TO 'data.json' (FORMAT JSON). Use the browser for quick one-offs and the CLI for repeatable scripts.
Drop a Parquet, GeoParquet, CSV, or JSON file into viewparquet: browse rows, run DuckDB SQL, and export results in-browser without uploading the dataset to viewparquet. Optional AI sends messages and applicable context directly to the provider you choose; review Settings → AI before use.