Parquet Metadata Reader

View the metadata of your Parquet files in one click. No server-side processing, everything happens in your browser. To view the Parquet Schema, check out our Parquet Schema Reader tool.

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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
    Inspect file metadata

    View overall file information including schema, row count, and row group locations.

  3. 3
    Explore row groups and columns

    Drill into row group metadata, column chunk details, compression, encodings, and statistics.

  4. 4
    Use the insights

    Optimize queries, plan data skipping strategies, or jump to the Schema Reader for structural analysis.

Specs

Max file size
~500 MB
Input
.parquet
Engine
DuckDB WASM

Data stays on your device

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

Our Parquet metadata reader uses WebAssembly to parse and display Parquet file metadata directly in your browser. Explore row groups, column chunks, compression stats, encodings, and min/max statistics — all without installing software or uploading data.

~500 MB

Max file size

0 bytes

Data transmitted

11 displayed

Metadata fields

100% Free

Our Parquet metadata 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 metadata.

No Installation Required

Use the metadata reader directly in your web browser — no software needed.

Is this metadata reader private?

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

What metadata fields are displayed?

It shows file name, row group IDs, row counts, column IDs, schema paths, data types, min/max stats, compression methods, encodings, and compressed/uncompressed sizes.

Can I use this offline?

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

What is the difference between metadata and schema?

Schema shows the structural field definitions, while metadata includes row group statistics, compression details, column chunk sizes, and encoding information.

Understanding Parquet File Structure and Metadata

Parquet files use a hierarchical structure that optimizes both storage and query performance. Understanding this structure and its metadata is crucial for efficient data processing.

Row Groups

Horizontal partitions of data, each containing a subset of rows from the file.

Column Chunks

Data for specific columns within each row group, optimized for columnar access.

Pages

Smallest storage units in Parquet, containing encoded data values within column chunks.

Parquet Metadata Levels

File Metadata

Overall file information, including schema, number of rows, and row group locations.

Row Group Metadata

Information about each row group, such as the number of rows and column chunk locations.

Column Chunk Metadata

Details about each column chunk, including data type, encoding, compression, and statistics.

Page Header Metadata

Information about individual pages within column chunks, such as encoding and compression details.

Key Metadata Fields

file_name

Name of the Parquet file

row_group_id

Unique identifier for each row group

row_group_num_rows

Number of rows in each row group

column_id

Identifier for each column within a row group

path_in_schema

Column name in the file schema

type

Data type of the column

stats_min, stats_max

Minimum and maximum values in the column chunk

compression

Compression method used for the column chunk

encodings

Encoding methods used for the column chunk data

total_compressed_size

Size of the compressed column chunk

total_uncompressed_size

Size of the uncompressed column chunk

Benefits of Understanding Parquet Metadata

Optimize query performance using statistics

Implement efficient data skipping

Understand data distribution

Plan data processing strategies

Troubleshoot performance issues