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The DbLink facility allows Teradata users to access data in external systems. However, as distributed, it only supports accessing data from external Oracle and Teradata systems.

In this article we will look at what is required to add support for other data sources. As it turns out, not much, just some basic Java programming abilities.

Many databases provide the ability for accessing external data via a mechanism via a SELECT query. Examples include Linked Tables in MS-Access and External Tables in Oracle. A similar capability will become available in Teradata 15, it will be known as Query Grid. However users of Teradata prior to 15 are out of luck.

Teradata has provided the foundation for accessing external data via a SELECT query ever since Table UDF's were added in or around Teradata 12. There is even reference in the UDF programmers manuals to just such a facility (but no actual code to show how to do it).

In this article, you can download a working facility I've called DbLink that you can setup and use to access data from external data sources without having to write your own UDF.

With the introduction of Query Grid in Teradata 15, many people have been asking "what about me? I am on not going to be on TD 15 for some time.".

In this series of articles I provide a tool I call DbLink which provides a similar capability for versions of Teradata prior to 15.0. The DbLink tool consists of a Table UDF and supporting components that may be used to access data from a remote RDBMS via JDBC.

SQL provides a set of useful functions, but they might not satisfy all of the particular requirements you have to process your data.

User-defined functions (UDFs) allow you to extend SQL by writing your own functions in the C/C++ programming languages, installing them on the database, and then using them like standard SQL functions.

SQL provides a set of useful functions, but they might not satisfy all of the particular requirements you have to process your data.

User-defined functions (UDFs) allow you to extend SQL by writing your own functions in the Java programming languages, installing them on the database, and then using them like standard SQL functions.

Hadoop systems [1], sometimes called Map Reduce, can coexist with the Teradata Data Warehouse allowing each subsystem to be used for its core strength when solving business problems. Integrating the Teradata Database with Hadoop turns out to be straight forward using existing Teradata utilities and SQL capabilities. There are a few options for directly integrating data from a Hadoop Distributed File System (HDFS) with a Teradata Enterprise Data Warehouse (EDW), including using SQL and Fastload. This document focuses on using a Table Function UDF to both access and load HDFS data into the Teradata EDW. In our examples, there is historical data already in Teradata EDW, presumably derived from HDFS for trend analysis. We will show examples where the Table Function UDF approach is used to perform inserts or joins from HDFS with the data warehouse.