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Version: 20.00.00.03 - Created: 29 Mar 2024

Overviewteradatamlspk is a Python package, built as an extension of teradataml, Teradata Python package. Syntax and user accessibility of teradatamlspk APIs are kept similar to PySpark APIs, allowing, the existing PySpark workloads, that run on Spark engine, can be easily run on Teradata Vantage with minimal changes to migrate PySpark workloads to Vantage.teradatamlspk offers another function pyspark2teradataml that enables conversion of a PySpark script to a teradatamlspk Python script. It also generates the HTML report for the conversion, that is useful for the user to understand the changes done and also carry out any manual changes in the generated script, so that the script can be run on Vantage.Dependent Python Packages: teradataml >= 20.00.00.06PrettyTableNbformatpytzpygments==2.19.0jinja2mistunePrerequisite: Python >= 3.9.0 on the client machine 

Version: 20.0.33 - Created: 16 Nov 2023

The Teradata SQL Driver for Node.js enables Node.js applications to connect to the Teradata database.For documentation, license information, and sample programs, please visit the driver GitHub page.For community support, please visit Teradata Community.For Teradata customer support, please visit Teradata Customer Service.We recommend that you follow the Installation instructions listed on the driver GitHub page.If the recommended installation procedure is not possible for you, then follow these manual installation steps:Download the .tgz file from the link above.In your command prompt or shell, run npm install tgzFileName

Version: 01.04.00.00 - Created: 15 Sep 2023

Teradata Partner API The Partner API is composed of two separate components.  The first component is an in-database function (a Table Operator named API_Request) that enables Vantage users to predict (score) machine learning models that are built on 3rd party partner platforms against Vantage data through a Vantage query.  For example, the release 1.4.0 release supports AWS SageMaker, Azure Machine Learning (and OpenAI), Google Vertex AI, and OpenAI model endpoints, with data passed from Vantage to these external platforms using a web services call, and the results are returned to the Vantage end user as results from the query. The second component is a Python library (named tdapiclient), which is a companion package of the Teradata Package for Python (teradataml), Teradata's Python package for client-side processing.  The tdapiclient Python packages allows AWS SageMaker, AzureML and/of Google VertexAI users of Vantage to call each CSP’s Python library interfaces to train and predict using data in Teradata Vantage tables.  tdapiclient also transparently converts and copies the Teradata DataFrame to S3, AzureBlob Storage or Google Cloud Storage for training as part of the fit() method which can invoke any of the API’s offered by the CSP.  For inference, it will use the data directly from Vantage input tables or queries via API_Request.  Test inferences on small amounts of data can also be done directly through the client library.  The tdapiclient also wraps the required BYOM calls to productionize the scoring process.  ** Note that for OpenAI and Azure OpenAI, only the API_Request static API is available in tdapiclient.  Download tdapiclient from:  https://pypi.org/project/tdapiclient/ For more information, see the Partner API Integration Guide on docs.teradata.com.

Version: 20.00.00.32 - Created: 18 Jul 2023

Teradata Call-Level Interface Version 2 is a collection of callable service routines that provide the interface between applications and the Teradata Gateway. Gateway is the interface between CLI and the Teradata Database. This download package is for the AIX platform.

Version: 17.20.00.49 - Created: 18 Jul 2023

Teradata Call-Level Interface Version 2 is a collection of callable service routines that provide the interface between applications and the Teradata Gateway. Gateway is the interface between CLI and the Teradata Database. This download package is for the Solaris platform.