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11 Jun 2013

Collecting statistics on data dictionary tables is an excellent way to tune long-running queries that access multi-table dictionary views.  Third party tools often access the data dictionary several times, primarily using the X views.  SAS, for example, accesses DBC views including IndicesX and TablesX for metadata discovery.  Without statistics, the optimizer may do a poor job in building plans for these complex views, some of which are composed of over 200 lines of code.

In an earlier blog posting I discussed the value of collecting statistics against data dictionary tables, and provided some suggestions about how you can use DBQL to determine which tables and which columns to include.  Go back and review that posting.  This posting is a more comprehensive list of DBC statistics that is updated to include those recommended with JDBC.

06 Jun 2013

A state matrix is a construct that allows you to intersect your business processing windows with the health conditions of your system.  Why should you care about this abstraction?  The state matrix in TASM is the mechanism that supports an automated change in workload management setup as you move through your processing day, or should your system become degraded.  Not only is it automatic, but it's a significantly more efficient way to make a change in setup while work is running.

23 May 2013

Darryl McDonald, President of Teradata Applications, tweeted this link today:  a practical example of when many of the subjects discussed on this blog come together. 

21 May 2013

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.

15 May 2013

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. 

29 Mar 2013

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?

12 Feb 2013

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

22 Jan 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. 

28 Dec 2012

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