📄 Convert Parquet, Feather, ORC & Avro Files with ParquetReader
This workflow allows you to upload and inspect Parquet, Feather, ORC, or Avro files via the ParquetReader API. It instantly returns a structured JSON preview of your data — including rows, schema, and metadata — without needing to write any custom code.
✅ Perfect For
- Validating schema and structure before syncing or transformation
- Previewing raw columnar files on the fly
- Automating QA, ETL, or CI/CD workflows
- Converting Parquet, Avro, Feather, or ORC to JSON
⚙️ Use Cases
- Catch schema mismatches before pipeline runs
- Automate column audits in incoming data files
- Enrich metadata catalogs with real-time schema detection
- Integrate file validation into automated workflows
🚀 How to Use This Workflow
📥 Trigger via File Upload
You can trigger this flow by sending a POST
request with a file using curl, Postman, or from another n8n flow.
🔧 Example (via curl
):
curl -X POST http://localhost:5678/webhook-test/convert \
-F "file=@converted.parquet"
Replace
converted.parquet
with your local file path. You can also send Avro, ORC or Feather files.
🔁 Reuse from Other Flows
You can reuse this flow by calling the webhook from another n8n workflow using an HTTP Request node.
Make sure to send the file as form-data with the field name file
.
🔍 What This Flow Does:
- Receives the uploaded file via webhook (
file
) - Sends it to
https://api.parquetreader.com/parquet
asmultipart/form-data
(field name:file
) - Receives parsed data (rows), schema, and metadata in JSON format
🧪 Example JSON Response from this flow
{
"data": [
{
"full_name": "Pamela Cabrera",
"email": "bobbyharrison@example.net",
"age": "24",
"active": "True",
"latitude": "-36.1577385",
"longitude": "63.014954",
"company": "Carter, Shaw and Parks",
"country": "Honduras"
}
],
"meta_data": {
"created_by": "pyarrow",
"num_columns": 21,
"num_rows": 10,
"serialized_size": 7598,
"format_version": "0.12"
},
"schema": [
{ "column_name": "full_name", "column_type": "string" },
{ "column_name": "email", "column_type": "string" },
{ "column_name": "age", "column_type": "int64" },
{ "column_name": "active", "column_type": "bool" },
{ "column_name": "latitude", "column_type": "double" },
{ "column_name": "longitude", "column_type": "double" },
{ "column_name": "company", "column_type": "string" },
{ "column_name": "country", "column_type": "string" }
]
}
🔐 API Info
- Authentication: None required
- Supported formats: .parquet, .avro, .orc, .feather
- Free usage: No signup needed; API is currently open to the public
- Limits: Usage and file size limits may apply in the future (TBD)