Overview
Introduction
JSON is the format most scripts, APIs, and JavaScript tooling expect, but Parquet files arrive as compressed columnar binary data. This converter turns one into the other directly in the browser.
Upload a .parquet file and get back a pretty-printed JSON array, one object per row, with real types preserved rather than flattened to strings.
What Is Parquet to JSON Converter?
A Parquet-to-JSON converter that reads a file's complete row set as plain JavaScript objects and serializes them as an indented JSON array.
It's the mirror image of this site's JSON to Parquet Converter, taking Parquet's compact columnar data back to JSON's flexible, nested, human-readable text form.
How Parquet to JSON Converter Works
The uploaded file is wrapped as an in-memory buffer and handed to a Parquet reader, which decodes every row into a plain JavaScript object keyed by column name, including any nested list or map structure the schema defines.
The resulting array is passed to JSON.stringify with a custom replacer function that converts any bigint value (from Parquet's INT64 columns) to a decimal string first, since JSON.stringify throws a TypeError on a raw bigint otherwise, then pretty-printed with two-space indentation.
When To Use Parquet to JSON Converter
Use it whenever a script, API, or JavaScript-based tool needs Parquet data as JSON, and preserving real types or nested structure matters.
It's also useful for quickly inspecting a Parquet file's nested columns (lists, maps) in their natural structured form, rather than as JSON-encoded text inside a CSV cell.
Often used alongside JSON to Parquet Converter and Parquet Reader and Viewer.
Features
Advantages
- Converts the complete dataset, not a capped preview, entirely client-side with no upload.
- Preserves real value types (numbers, booleans, nested objects and arrays) instead of flattening everything to text.
- Handles Parquet's 64-bit integer columns safely, converting bigint to a decimal string instead of crashing or losing precision.
Limitations
- Pretty-printed JSON for a very large file can be noticeably larger (and slower to render in a textarea) than the equivalent CSV.
- Very large Parquet files may take a noticeable moment to fully decode before the JSON output appears, since the whole file is read into memory.
Examples
Best Practices & Notes
Best Practices
- Use the Parquet Schema Reader first if you want to confirm column names and types before converting a large or unfamiliar file.
- Prefer this converter over the CSV converter whenever a nested list or map column needs to stay structured rather than becoming a JSON-encoded string inside a CSV cell.
- Use Parquet Metadata Reader first on a very large file to see the row count before converting, so a huge JSON output doesn't come as a surprise.
Developer Notes
The bigint-to-string replacer is applied inline in the `JSON.stringify` call rather than pre-transforming the row array, since a pre-transform would need to recursively walk arbitrarily nested objects and arrays looking for bigints, while `JSON.stringify`'s replacer is already called once per value at every depth during serialization.
Parquet to JSON Converter Use Cases
- Converting a Parquet data export into JSON for a script, API payload, or JavaScript application
- Inspecting a Parquet file's nested list or map columns in their natural structured form
- Handing Parquet data off to a system that expects a JSON array of records
Common Mistakes
- Assuming large INT64 values are unsupported because raw JSON.stringify throws on bigint elsewhere; this converter's replacer handles that case automatically.
- Expecting output to be a single JSON object rather than an array, when the file has more than one row it's always an array of row objects.
Tips
- Round-trip through this site's JSON to Parquet Converter to sanity-check that a conversion preserved every row correctly.
- Use the download button to save the output as converted.json directly, rather than copying and pasting large files.