At the Partners 2012 I presented the session “How to compare tables between TD systems in a dual active environment” - see attached slides for details if of interest for you.

Oracle (Sun) JDK 6.0 and JDK 7.0 include the Apache Derby database, which is implemented in 100% Java. 

This article is not about the Apache Derby database; instead, this is about a command-line interactive SQL tool that is included with Apache Derby. 

The Apache Derby "ij" interactive SQL tool is quite useful. It is a command-line SQL tool similar to BTEQ, and it works with any JDBC Driver and any database, not just the Apache Derby database. 

The following instructions show how to use the ij tool with the Teradata JDBC Driver. 

In earlier postings I’ve described how TASM system events can detect such things as AMP worker task shortages, and automatically react to change workload managements settings.   These system events tell TASM to look out for and gracefully react to resource shortages without your direct intervention, by doing things like adjusting throttle limits temporarily downwards for the less critical work.

This switchover happens as a result of TASM moving you from one Health Condition to another, and as a result, from one state to another state.  But how does this shift to a new actually state happen?  And under what conditions you will you be moved back to the previous state?

Statistical information is vital for the optimizer when it builds query plans.  But collecting statistics can involve time and resources.  By understanding and combining several different statistics gathering techniques, users of Teradata can find the correct balance between good query plans and the time required to ensure adequate statistical information is always available.

This recently-updated compilation of statistics collection recommendations are intended for sites that are on any of the Teradata 14.0 software release levels.   Some of these recommendations apply to releases earlier than Teradata 14.0, however some rely on new features available only in Teradata 14.0.

Contributors:  Carrie Ballinger, Rama Krishna Korlapati, Paul Sinclair, February 12, 2013

As you approach full use of your AMP worker tasks, monitoring in-use counts becomes a more important exercise.  The ResUsageSAWT (SAWT) table provides a wealth of information about AWT usage when you need to dive into details.

ResUsageSAWT provides you with several categories of information, including AMP worker task usage and high-water marks broken out by work type, as well as message queue depth/ flow control frequency metrics. 

Continuing on the “42” theme, Chris Anderson drills done on the impact of big data on health and agriculture. 

“42” is the Answer to the Ultimate Question of Life, the Universe, and Everything.  But for Big Data, the answer is simply “everything.” 

Teradata Database supports Inline and Deferred Large Object Retrieval modes. The LOB retrieval modes control the content of rows and accessibility of LOB columns. 

For sites using Teradata Active System Management (TASM), workload classification determines which workload will manage the AMP activity when a query executes.  Workload classification takes place after all the parsing engine (PE) work for a query has completed, including optimization.

But at what priority does the parsing happen?  And can the priority of parsing be raised?   

Most of us are aware of AMP worker tasks, and some of us are even obsessive about not running out of this finite resource.  But that’s on the AMP.  What about the tasks supporting user work on the parsing engine (PE)?  Should we be just as vigilant about what’s happening with tasks at the PE level?

Not really.  Here’s why.