To utilize high processing power on a DB2 Server during SPSS Modeler analysis, which feature is required?

Using SQL Push Back is crucial for leveraging high processing power on a DB2 Server during SPSS Modeler analysis. This feature allows for processing operations to be pushed back to the database server rather than having the data pulled into the Modeler for analysis. By doing this, it enables the heavy lifting of data processing to take place directly on the DB2 server, which is designed to handle extensive computations and large volumes of data efficiently.

When using SQL Push Back, complex calculations and data manipulations can be performed using SQL queries, taking full advantage of the DB2's optimized processing capabilities. This not only improves performance by reducing the amount of data transferred over the network but also allows users to handle larger datasets more effectively, as the processing does not burden the local resources where Modeler is running.

In contrast, the other features like Partitioning, Clustering, and Sampling involve different aspects of data manipulation and analysis but do not specifically address the need for high processing power utilization directly on a DB2 Server in the same way. Partitioning relates to organizing data into manageable segments, Clustering is about grouping similar data points, and Sampling is used to select a representative subset of data for analysis, none of which inherently enhances processing power on the database server itself.