A new feature in Teradata Database 15.0 gives the optimizer the choice to bypass all-AMP row redistributions under certain circumstances. This can be a good thing for queries that are redistributing just a few rows and the system has many AMPs. Without this feature all row redistributions, no matter of what size, would require that an AMP worker task be spawned and started up on each AMP in preparation for receiving rows.
If you are someone who uses Database Query Log (DBQL) to keep on top of how much resource your users and applications are consuming, you are probably aware that there are different DBQL tables that collect information related to usage. Starting in Teradata Database 15.0, if you are tracking usage for utilities, that detail is carried in two places: The DBQLogTbl and the DBQLUtilityTbl.
Which should you use? Should you combine usage from both tables? Or only consider the usage in one of the two tables?
Teradata Workload Management comes in two versions: Teradata Integrated Workload Management (TIWM) which includes basic functionality, and Teradata Active System Management (TASM) which has a richer set of capabilities. Both TIWM and TASM come with several system-defined workloads. This blog explains what these workloads are, why they are there, and whether you can ignore them or not.
AMP worker tasks (AWT) are a critical resource in the Teradata Database. In previous blog postings I’ve explained how the load and export utilities, as well as ARC backup and restore, use AMP worker tasks. In this posting we’ll consider the replacement for ARC, Data Stream Architecture (DSA), and its use of AWTs.
This is an update to an earlier posting in which data dictionary statistics recommendations in Teradata Database 14.0 were shared. This posting makes similar recommendations for data dictionary statistics from the 15.10 perspective.
Both system-level and workload-level throttles can manage the concurrency of load utility jobs in the Teradata Database. However, the point at which they release their respective throttle slots differs. This article explains that difference.
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
Tactical workload exceptions are in place to prevent tactical queries from consuming unreasonable amounts of resources. It is important to have this protection because the super-priority and almost unlimited access to resources given to work running in the Tactical tier with SLES