Parquet Viewer

Use Parquet Viewer, a parquet file reader in Chrome. Open parquet file data locally; inspect schema and up to 100 rows. No uploads.

Parquet Viewer helps you inspect one local file in Chrome, with its schema, column types and up to the first 100 rows in view. Use this parquet file viewer when you need to check a dataset before taking it into your usual analysis tools. The selected contents stay on your device. Start with a file you already have 1. Click the extension icon to open the local inspection page. 2. Choose a file, or drop an item from your device. 3. Review the metadata, schema and sample values once reading finishes. A focused first look parquet viewer brings the basic details together so you can answer practical questions without writing a script. Confirm that you chose the expected dataset, compare its columns with your requirements, and look at the opening records for context before continuing your work elsewhere. See what the file reports • File name and size help identify the selected item. • Total row count, when available, gives context for the sample. • Column count shows how many fields are present. These details describe the selected dataset; the preview does not display every record. Read the structure Use Parquet Viewer to review column names and their declared types. A name alone may not tell you whether a field contains text, numbers or timestamps. Reading the structure alongside sample values can help you spot an unexpected field or understand what a producer supplied. Check the opening records The table shows up to 100 rows. A short preview lets you look at example values alongside the schema rather than guessing from a filename. Treat those records as a sample: later entries may contain different values, and the opening rows cannot prove that an entire dataset is correct. Local processing from start to finish 📌 The parser is bundled with the extension. 📌 Reading happens locally in your browser. 📌 No upload or backend is used to process your selection. parquet viewer opens its own extension page in a tab, keeping inspection within your desktop Chrome workflow. For everyday checks Use this reader when a colleague sends a dataset, a pipeline produces an unfamiliar output, or you return to an older download. You can inspect the structure before deciding how to use it. The extension provides a readable starting point for those checks without turning a quick look into a larger setup task. Questions to answer while inspecting - Are the expected column names present? - Do the declared types fit the data you intend to use? - Do the first records look like the output you expected? Parquet Viewer puts the available details in one place, while you decide whether they match your task. How to view parquet file contents? Open the extension page, select one local item, and review the schema and initial records. The view is read-only. You can examine what is displayed, but this version does not edit the dataset or provide SQL queries, sorting, filtering, search or export. How to open parquet file data without uploading it? Choose the file from your device using the picker or drop it onto the page. The bundled parser reads the selected contents locally. There is no account or remote processing service in the inspection flow, and no URL or S3 loading is provided. Understand the preview limit parquet viewer is intended for a bounded first look, not a complete audit of all records. If a dataset contains more than 100 rows, the displayed table remains limited to the beginning. Use the reported metadata to understand the broader context, then use another suitable tool for deeper analysis when needed. When an item cannot be read ▸ Invalid inputs receive a readable error. ▸ Malformed or unsupported files may fail to open. ▸ A familiar filename extension does not guarantee readable contents. Parquet Viewer does not promise every compression codec or type combination, and it does not claim unlimited file-size support. Keep the task simple Work with one local file at a time. The extension is useful when your immediate question concerns structure and sample values, rather than transformations or calculations. Having the name, size, columns and initial records together helps you decide your next step with a clearer view of the material in front of you. Ready for another inspection Return to parquet viewer whenever you need the same focused workflow: choose a local dataset, review the available details, and check the opening rows. Keep your existing analysis process for work beyond that first look.