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Performance Tuning Guide - EMC Community Network

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Designing the Application<br />

The database creates a separate table for each object type used, whether it is an SDT containing many<br />

attributes or a simple process variable containing a single attribute. When searching for attributes<br />

in different database tables, the database dynamically joins rows of database tables in order to<br />

retrieve pertinent data. Joining rows of database tables impacts performance. When using SDTs, a<br />

single database table contains the searchable attributes and avoids the performance impact of the<br />

join operation.<br />

Tip: Use SDTs to consolidate sets of attributes to the minimal number of object types on which your<br />

business process discretely operates.<br />

Figure 11, page 38 illustrates how the database models two simple process variables of different types<br />

(string and int), resulting in two different database tables. Any search against these two process<br />

variables employs multiple unions for each simple process variable, which slows down performance.<br />

In addition, the database cannot create a composite index, which would otherwise provide additional<br />

performance improvements (Creating composite indexes, page 38).<br />

Figure 11. Separate data tables for different process variable types<br />

Model the two process variables (branch and loantype) as attributes of a single SDT, in which case<br />

the database stores all metadata in a single database table (Figure 12, page 38). The database table<br />

can then be searched without the performance overhead of creating unions, as in Figure 11, page<br />

38. In addition, you can create a composite index for SDTs, which provides additional database<br />

performance improvements (Creating composite indexes, page 38).<br />

Figure 12. Single table representation for an SDT<br />

Creating composite indexes<br />

xCP provides developers with the ability to create composite indexes for SDT attribute values.<br />

Creating a composite index can improve database performance, especially when performing complex<br />

(conditional) searches against a large database of different attributes in the same SDT.<br />

38 <strong>EMC</strong> Documentum xCP 1.0 <strong>Performance</strong> <strong>Tuning</strong> <strong>Guide</strong>

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