What is a .Parquet file?
Parquet is a columnar storage format that powers much of modern big-data analytics.
- Did you know
- Parquet’s columnar layout makes huge datasets fast and cheap to query.
- Parquet was created in 2013 by engineers at Twitter and Cloudera, drawing on Google’s Dremel paper.
- Its record-shredding columnar layout lets queries read just the columns they need, skipping the rest of the file.
- What Analyser reads
- Identify and read developer and data-serialisation files: dependency lockfiles (npm/Yarn/pnpm/Cargo/Poetry/Bundler/Composer - locked-package count), binary serialisations (MessagePack, CBOR, BSON, raw Protobuf messages and descriptor sets), Python pickles with a security note, NumPy .npz and Java jar/war/ear archives, IDL schemas (FlatBuffers/Thrift/Cap n Proto/HCL), MATLAB MAT-files, Redis RDB dumps and columnar big-data containers (Apache Arrow/Feather, Parquet, ORC). The JSON supersets JSON5/JSONC/Hjson now open in a full viewer - see Notebooks & data above.
- Depth of analysis
- .Parquet is an identification-grade format: Analyser recognises it from its bytes and decodes the header metadata it carries, rather than opening it in a full viewer. Formats that do get a full viewer are marked "Full" on the formats page.
- Open a .Parquet file
- Drag a .Parquet file onto the Analyser home page (or tap to pick one). It is identified entirely in your browser - nothing is uploaded, there is no account, and it works offline once installed.