Extensibility covers the mechanisms by which you, as the user or developer, can extend the functionality of the Teradata Database, for example with the use of User Defined Functions, or UDFs.

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A Quick Tour of the XML Type

A Quick Tour of XML Type

Teradata Query Grid and Machine Learning in Hadoop

This article describes how to use Teradata query grid to execute a Mahout machine learning algorithm on a Hadoop cluster based on data sourced from the Teradata Integrated Data Warehouse. Specifically the Mahout K-means cluster analysis algorithm is demonstrated.  K-means is a computationally expensive algorithm that under certain conditions is advantageous to execute on the Hadoop cluster. Query Grid is an enabling technology for the Teradata Unified Data Architecture (UDA).

XML Query

Querying XML

Teradata 14.10 XML Data Type
This feature provides the following new capabilities:
Teradata XML Services

Teradata XML Services provide assistance in database transformation of XML structures to and from relational structures. This is primarily an enterprise fit feature. XML in this context is regarded as a data format that is used to describe incoming or outgoing warehouse data. A key concept for this feature is that we are not transforming to store XML but rather to maintain a relational data model or to integrate relational data into an enterprise XML message structure! The relational data model is bested suited for enterprise analytics. XML structures are best suited for enterprise integration.

Running Unsupported Queries from a Stored Procedure


Stored Procedures


SQL Stored Procedures were added to Teradata around 2003 with the release of Teradata V2R5.1. Since then the capabilities of SQL Stored Procedure s has been expanded. However, there are still some queries that cannot be run directly from within a Stored Procedure.

 

In database multiple variable linear regression using the CM_Solve Table Operator

In a prior article [1] we described how to use the Teradata 14.10 CalcMatrix operator and R to perform a multiple variable linear regression analysis. This article extends that concept with a comprehensive in database solution by introducing a new in database table operator named “CM_Solve”. This approach has value in cases when you want to solve a large number of independent systems of equations or you simply do NOT want to use the R client for solving the system of equations based on the SSCP matrix.

In database linear regression using the CalcMatrix table operator

Linear Regression

In statistics, linear regression is an approach to model the relationship between a scalar dependent variable y and one or more independent variables denoted x. Linear regression is one of the oldest and most fundamental types of analysis in statistics. The British scientist Sir Francis Galton originally developed it in the latter part of the 19th century. The term "regression" derives from the nature of his original study in which he found that the children of both tall and short parents tend to "revert" or "regress" toward average heights.

K-means clustering and Teradata 14.10 table operators

Table Operators

This article discusses how to implement a Teradata 14.10 table operator using K-means clustering as an example use case. 

The Heatmap Table Function is now available

As part of Teradata Database 14.10 Teradata Intelligent Memory (TIM) feature, a table function was developed to provide the heatmap report for a specific AMP for database object(s) for systems in which data temperature collection is enabled[1].     This HeatMap table function is being provided for sites that are interested in looking at the relative temperature of tables, which tables (cylinders) are targeted for the TIM cache and which tables are targeted for what temperature range

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