Parquet Query
Query a Parquet file in your browser — pick columns, filter rows and limit the result, then export to CSV, Parquet or JSON. DataEngUtils runs the query locally on an Apache Arrow engine compiled to WebAssembly, so the file never leaves your machine and no warehouse or Spark cluster is needed. It is the fast path for the questions you ask a dataset a dozen times a day: what is in this extract, which rows match this predicate, and what does the slice look like. Because results are computed in a Web Worker with predicate pushdown over the file's own statistics, the page stays responsive even on large files.
Open it in the app
Parquet Query runs in the DataEngUtils browser app on a Rust engine (Apache Arrow) compiled to WebAssembly — part of the Pro workbench, entirely client-side, and nothing is uploaded.
How it works
1. Open Parquet Query
Open the tool in the DataEngUtils app. It is part of the Pro workbench — nothing is uploaded.
2. Drop a Parquet file
Select the columns you need and add filters. Row groups that cannot match are skipped using the file's statistics.
3. Export the result
Preview the result table, then export to CSV, Parquet or JSON.
Why not use an online tool?
Online inspectors tools require uploading your Parquet and CSV files to a third-party server. For production work, that is a security and compliance risk. DataEngUtils runs a client-side engine in your browser — same convenience, none of the exposure.