Data in Parquet Format | Native Object Store | Teradata Python Package - 17.00 - Data in Parquet Format - Teradata Package for Python

Teradata® Package for Python User Guide

Teradata Package for Python
Release Number
Release Date
November 2021
Content Type
User Guide
Publication ID
English (United States)
Foreign table created in Parquet format usually contains the following columns:
  • Location
  • Several other user specified columns in Parquet format specified while creating foreign table

User can create a teradataml DataFrame on a foreign table using "DataFrame()" or "DataFrame.from_table()", the same way to create a teradataml DataFrame on a regular table. With the created DataFrame, user can easily access the data in these columns and process the data using teradataml DataFrame API or other Python packages.

How to access actual data and path variables

Unlike foreign tables on JSON and CSV format data, teradataml DataFrame on Parquet data provides direct access to the actual data in Parquet files, as described in Accessing Foreign Table Created On Parquet Data.