Configure the mapping with the least number of transformations and expressions to do the most amount of work possible.

Delete unnecessary links between transformations to minimize the amount of data moved.

Choose an optimizer level that determines which optimization methods the Data Integration Service can apply to the mapping. When the Data Integration Service optimizes a mapping, it attempts to reduce the amount of data to process. For example, the Data Integration Service can use early selection optimization to move a filter closer to the source. It can use the cost-based optimization method to change the join processing order.

Choose a pushdown type to enable the Data Integration Service to determine whether it can pushdown partial or full transformation logic to the source database.

Configure data object caching to enable the Data Integration Service cache logical data objects and access pre-built logical data objects when it runs a mapping. By default, the Data Integration Service extracts source data and builds required data objects when it runs a mapping. Mapping performance increases when the Data Integration Service can access pre-built data objects.

Indicate if the SQL transformation, Web Service Consumer transformation, and the Java transformation do not have side effects when you configure these transformations. Some transformations have side effects that restrict optimization. For example, a transformation can have a side effect if the transformation writes to a file or database, adds to a count, raises an exception, or writes an email. In most cases, the Data Integration Service identifies which transformations have side effects that restrict optimization.