0 - 7 of 7 tags for load utilities

Teradata is a message passing system.  Messages are sent from parsing engines to AMPs, and from  AMPs to AMPs, and from AMPs to parsing engines.  That’s the key way that components in a shared nothing architecture pass data and work requests among themselves.

When a message arrives on an AMP and the message represents work that needs to get done on the AMP, that message is assigned a“work type”, depending on the importance of the work-to-be-done.  There are 16 different work types supported:  Work00 to Work15.      

Under usual conditions, all load utility jobs and all queries run using AMP worker tasks (AWTs) of the same message work types:  Work00, Work01, and Work02.  However, if you increase AWTs per AMP above a certain threshold, then all your utility jobs will be assigned to different work types and given their own reserve pools.   

If you are someone who monitors or is otherwise interested in AWTs and how they are being used, this posting describes changes related to your utility jobs, and what options you have for managing these changes.

Hi Experts,
Are there any differences b/w the multiple sessions that are invoked through BTEQ and loader utilities.  If so, what are they.

How to load rows from Nth record to N+10 records from flat file to a table by using BTEQ Import and Fastload?

I'd like to know behind covers - how these 2 utilites differ. I am aware of the glaring differences : empty tables vs non , single vs multi-table , upserts, fastload locking etc.

How do you pick the number of sessions to assign to your utility jobs?  Chances are you guess.  In Teradata 13.10 the task of deciding the number of sessions has been moved inside the database, meaning one less thing for you to worry about.  Read on for a quick intoduction to how this feature works.

In TPump and higher releases the maximum pack factor has been increased from 600 to 2430.

TPump users use "PACK <statements>" in the "BEGIN LOAD" command to specify the number of data records to be packed into one request, where PACK is a TPump keyword and “statements” actually refers to the number of data records to be packed.

Packing improves network/channel efficiency by reducing the number of sends and receives between the application and the Teradata Database.

A high-availability system must have the ability to identify and correct errors, exceptions and failures in a timely and reliable manner to meet challenging service level objectives. The Teradata database and the utilities and components (used to both load and access data) provide capabilities to implement reliable error and exception handling functionality. These capabilities combined with a well designed high availability architecture allow a Teradata Active Enterprise Intelligence (AEI) system to meet the service level objectives required to support mission critical business processes.