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

Teradata® Package for Python User Guide

Deployment
VantageCloud
VantageCore
Edition
Enterprise
IntelliFlex
VMware
Product
Teradata Package for Python
Release Number
20.00
Published
March 2024
Language
English (United States)
Last Update
2024-04-09
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Product Category
Teradata Vantage
Foreign table created in Parquet format typically contains the following columns:
  • Location
  • Other user-specified columns in Parquet format specified while creating foreign table

You 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, you can easily access the data in these columns and process the data using teradataml DataFrame API or other Python packages.

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.