Why is Parquet's schema at the end of the file?

Because the writer only knows final statistics after writing all the data. Putting the footer last lets it be written in a single pass, and readers just seek to the end to get everything they need.

When should I use Avro instead of Parquet?

Avro for streaming and record-at-a-time writes, where whole rows are read together. Parquet for analytical queries that read a few columns from many rows.

Can I read a Parquet file's data here?

This tool focuses on the metadata and schema. Reading the encoded column chunks requires a full Parquet reader — but the schema is usually what you actually needed.

Parquet / Avro Header Decoder

Read Parquet and Avro file headers, schemas and metadata.

on the roadmapFile Format & Archivesfree · no sign-up

This bench is being wired up

The parquet-avro-decoder decoder is on the roadmap. The heavier binary and cryptographic parsers ship after the core text and token decoders — all of which are already live and working.

Browse the live decoders

Input is processed on your device. Nothing you paste is sent anywhere.

What is the Parquet / Avro Header Decoder?

A Parquet/Avro decoder reads the metadata sections of these two big-data file formats — Parquet's footer schema and row-group statistics, Avro's JSON schema header — to reveal a file's structure without scanning its data.

Parquet is columnar: values from the same column are stored together, which compresses far better and lets a query engine read only the columns it needs. The schema and per-row-group statistics live in a footer at the end of the file, immediately before the PAR1 magic, so metadata is read with a single seek to the tail.

Avro is row-oriented and self-describing in a different way: the writer's schema is embedded as JSON in the file header, followed by blocks of records separated by a sync marker. That design makes Avro good for streaming and for schema evolution, where readers reconcile their expected schema against the writer's.

In practice you reach for the metadata when a pipeline breaks. Parquet's row-group min/max statistics explain why predicate pushdown did or didn't skip data, and Avro's embedded schema explains why a consumer can't read what a producer wrote.

Parquet / Avro Header Decoder at a glance

Parquet magic: PAR1 at both start and end of file
Parquet layout: Columnar, row groups, footer holds the schema
Avro header: Obj1 magic plus a JSON schema
Avro layout: Row-oriented blocks with a 16-byte sync marker

How to use the Parquet / Avro Header Decoder

1Load the file — only the header and footer regions need to be read.
2Review the recovered schema: field names, types and nesting.
3For Parquet, check row-group counts and column statistics.

When you would reach for it

Confirming the schema of a Parquet file before writing a query against it.
Diagnosing an Avro schema-evolution mismatch between producer and consumer.
Checking row-group sizing when a Parquet dataset queries slowly.

Parquet / Avro Header Decoder — frequently asked questions

Last reviewed 25 July 2026 · questions or corrections: contact@decoder.tools