Last Updated: 5/8/2026

Feldera can ingest and output data in the Parquet format .

• via ingress and egress REST endpoints by specifying ?format=parquet in the URL
• as a payload received from or sent to a connector

We document the Parquet format and how it interacts with different SQL types in this page.

Types

The parquet file is expected to be a valid parquet file with a schema. The schema (row name and type) must match the table definition in the Feldera pipeline program. We use Arrow  to specify the data-types in parquet. The following table shows the mapping between Feldera SQL types and Arrow types .

Example

In this example, we configure a table to load data from a Parquet file.

create table PARTS (
  part bigint not null,
  vendor bigint not null,
  price bigint not null
) with ('connectors' = '[{
  "transport": {
    "name": "url_input",
    "config": { "path": "https://feldera-basics-tutorial.s3.amazonaws.com/parts.parquet" }
  },
  "format": {
    "name": "parquet",
    "config": {}
  }
}]');

For reference, the following python script was used to generate the parts.parquet file:

import pyarrow as pa
import pyarrow.parquet as pq
 
data = {
    'PART': [1, 2, 3],
    'VENDOR': [2, 1, 3],
    'PRICE': [10000, 15000, 9000]
}
table = pa.Table.from_pydict(data)
pq.write_table(table, 'parts.parquet')