Parquet Schema Reader

View the schema of your Parquet files in one click, including field names, data types, logical types, and nested structures. Need row group statistics instead? Open the Parquet Metadata Reader, or use the Parquet Viewer to preview rows too.

PrivateFreeOffline

Quick start

  1. 1

    Load your Parquet file

    Drag-and-drop a Parquet file or click to browse. Parsing stays on your device.

  2. 2

    View the schema

    Instantly see every field name, physical type, repetition type, and logical type in your file.

  3. 3

    Explore nested structures

    Drill into nested fields, child counts, and converted types to understand complex schemas.

  4. 4

    Use the insights

    Plan your data processing strategy or jump to the Parquet Metadata Reader for row group statistics.

Data stays on your device

All processing runs locally in your browser. Nothing is sent to any server.

Our Parquet schema reader uses WebAssembly to parse and display Parquet file schemas directly in your browser. Explore field names, physical types, repetition types, logical types, decimal precision, and nested structures before you query, convert, or share a dataset.

~500 MB

Max file size

0 bytes

Data transmitted

11 displayed

Schema fields

100% Free

Our Parquet schema reader is completely free to use, with no hidden costs or subscriptions.

Privacy-Focused

Your data never leaves your device. All processing happens locally in your browser.

Fast and Efficient

Instantly parse even large Parquet files and display their full schema.

No Installation Required

Use the schema reader directly in your web browser with no software needed.

Is this schema reader private?

Yes. The reader runs entirely in your browser, so your Parquet files never leave your machine.

What information does the schema show?

It displays field names, data types, type lengths, repetition types, number of children, converted types, scale, precision, field IDs, and logical types.

Can I use this offline?

Yes. Once the page finishes loading, you can disconnect and continue reading schemas offline.

What is the difference between schema and metadata?

Schema shows the structure and field definitions of your Parquet file, while metadata includes row group statistics, compression details, and column chunk information.

Can I preview rows after checking the schema?

Yes. Open the Parquet Viewer when you want to inspect the schema and preview the actual row data in the same browser workflow.

Can I convert the file after reading its schema?

Yes. Use the Parquet to CSV converter for spreadsheet output, or use the CSV to Parquet converter when you need to rebuild a Parquet file from CSV.

Schema first, metadata next, conversion when you are ready

Use the schema reader to confirm column names, data types, and nested structures before loading a Parquet file into a warehouse, notebook, or pipeline. If you need file-level statistics, move to the Parquet Metadata Reader. If you need rows too, open the Parquet Viewer. To hand the data to a spreadsheet, finish with the Parquet to CSV Converter.

Understanding Parquet Schema

Parquet schema provides detailed information about the structure of your Parquet files. It includes field names, data types, and other important attributes that define the layout of your data.

Schema Fields Explained

The parquet_schema function returns the following fields:

  • file_name: Name of the Parquet file
  • name: Name of the field in the schema
  • type: Data type of the field
  • type_length: Length of the data type (if applicable)
  • repetition_type: Whether the field is required, optional, or repeated
  • num_children: Number of child fields (for nested types)
  • converted_type: Logical type conversion information
  • scale: Scale for decimal types
  • precision: Precision for decimal types
  • field_id: Unique identifier for the field
  • logical_type: Logical type of the field

Benefits of Reading Parquet Schema

  • Understand the structure and organization of your Parquet files
  • Plan data processing and analysis strategies based on field types
  • Identify nested structures and complex data types
  • Ensure compatibility when working with different data systems

Related tools

Parquet Viewer

Preview rows and inspect schema, metadata, and row groups together.

Open

Parquet Metadata Reader

Inspect row groups, column chunks, compression, and statistics.

Open

Parquet to CSV Converter

Convert Parquet datasets to CSV locally with no uploads.

Open

CSV to Parquet Converter

Create compressed Parquet files from CSV in your browser.

Open