A Population rule-set is a file used by the SSA-NAME3 callable routine to modify its behavior for different countries, languages or data populations.
Population rule-sets may be one of three types:
Standard Populations are provided with the product.
A Custom Population may be built by an Informatica Corporation consultant for a customer with unusual or special needs.
A Local Population is the result of local rules modifications done via the Population Override Manager or Edit RuleWizard.
It is possible for a system to have all three types of Population rule-sets. If so, there is an order of precedence in loading by SSA-NAME3. If a Local Population of file extension,
.YLP
is present in the folder identified by the "System" Control, then it is loaded. If a Custom Population is present of file extension,
.YCP
then it is loaded. If the Standard Population of file extension,
.YSP
is present then it is loaded.
A Population rule-set is loaded when an SSA-NAME3 session is opened, and will not be reloaded unless the Callable routine is terminated and restarted, or a reload is triggered. A reload may be triggered either through the use of the UNLOAD Control in the
ssan3_close
API call, and then reloading will occur only after all sessions have been closed, or by using the TERM Control of the
ssan3_close
API call. The TERM Control should be used with care, as it will force a close on all current sessions. For valuable information on the UNLOAD and TERM Controls, it is important to see
API REFERENCE
guide.
Both the Population Override Manager and the Edit Rule Wizard will always load a copy of the Population from disk for their own use. However, no user of the standard API, including the Developer’s Workbench, will see the changes made by either client until the changes are committed, the Population copied to the appropriate location, and a reload of the Population triggered.
Some changes made by the Population Override Manager require the SSA-NAME3 keys to be re-built before taking effect.
The task of developing name search and matching systems is a balancing act between:
"Performance" and "Quality";
"Under-matching" versus "Over-matching";
"Missing the Right data" versus "Finding Wrong data".