• The parameterized job must be embedded in an iterative job. See “About Iterative
Jobs” on page 505.
• The parameters from the parameterized job must be mapped on the Parameter
Mapping tab of the properties window for the iterative job.
• The tables that you need to process through query created in the SQL Join
transformation must be included in the control table for the iterative job. See
“Creating a Control Table” on page 512.
Constructing a SAS Scalable Performance Data
Server Star Join
You want to construct SAS Scalable Performance Data (SPD) Server star joins.
You can use the SAS Data Integration Studio SQL Join transformation to construct SAS
SPD Server star joins when you use SAS SPD Server version 4.3 or later.
Construct an SPD Server Star Join
Star joins are useful when you query information from dimensional models that are
constructed of two or more dimension tables that surround a centralized fact table, which
is known as a star schema. SAS SPD Server star joins are queries that validate, optimize,
and execute SQL queries in the SAS SPD Server database for performance. If the star
join is not used, the SQL is processed in the SAS SPD Server by using pair-wise joins,
which require one step for each table to complete the join. When the SAS SPD Server
options are set, the star join is enabled.
You must meet the following requirements in order to enable a SAS SPD Server star
• All dimension tables must surround a single fact table.
• Dimension-to-fact table joins must be equal joins, and there should be one join per
• You must have two or more dimension tables in the join condition.
• The fact table must have at least one subsetting condition placed on it.
• All subsetting and join conditions must be specified in the WHERE clause.
• Star join optimization must be enabled through the setting of options on the SAS
SPD Server library.
In order to enable star join optimization, code that runs on the generated Pass SAS SPD
Server system library must have the following options added to the library:
478 Chapter 21 • Working with SQL Join Transformations