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One of the biggest benefits of Parallel Transporter is the ability to scale the load process on a client load server to circumvent performance bottlenecks.  This can sometimes offer huge performance gains as compared to the legacy Teradata Stand-alone load tools such as FastLoad and MultiLoad.

The Teradata Parallel Transporter (Teradata PT) operators play a vital role in high-speed data extraction and loading geared towards the Teradata Database. Besides interfacing with the Teradata Database, some of the Teradata PT operators provide access to external sources such as files, ODBC-compliant DBMS, and message-oriented middleware.

In Part 1, we looked at what Large Objects are and some tactics that we could employee to load them into Teradata. As I stated back in part 1, loading large objects is great, but by itself is pretty useless. In this article, we will look at extracting Binary Large Objects from Teradata for inclusion in a web application.

But before we get to that, we need to know something about the large objects we will be dealing with.

Lately it seems like there has been quite a few questions relating to the use of Large Objects on the various Teradata forums. Mostly these revolve around the question of how do I get Large Objects into the database. So it seems like there is a bit of mystery surrounding Large Objects.

For myself, the mystery is just who is “Large” and to what does he (or she) “Object”? Perhaps "Large" objects to the veil of mystery being lifted which is what this series of articles is about - working with Large Objects.

In part 1, we will look at getting those Large Objects of yours into the Teradata. One way or another we will get them into Teradata, kicking and screaming if need be (however, it will be relatively painless, I promise) and we will do this despite any "Objections" "Large" may have.

Later in part 2, we will drag those Large Objects back out and use them in a web application.

The purpose of the new Teradata 13.0 feature that allows you to create tables with no primary index is improved performance of FastLoad and Teradata Parallel Data Pump Array INSERT data loading operations.