What is one of the main advantages of using a Partition Primary Index (PPI)?

One of the main advantages of using a Partition Primary Index (PPI) is that it improves access speed through sorting. A PPI organizes data across multiple partitions based on the values of the indexed columns. This partitioning means that when queries are executed, the database can efficiently narrow down the search to specific partitions that are relevant to the query, rather than scanning the entire table. By accessing only the partitions necessary for a given query, the overall query performance is enhanced, leading to faster retrieval of data.

This design helps in managing large datasets more effectively because it reduces the amount of data that needs to be scanned, therefore speeding up the query execution process. The PPI feature also supports better maintenance of data over time by allowing for more efficient data management operations, such as inserts, updates, and deletes, by working within defined partitions rather than the entire dataset.

The other choices do not correctly reflect the advantages of a PPI: using a PPI does not inherently increase the complexity of queries, limit the number of columns in tables, or allow for data duplication. Instead, it streamlines data access and enhances performance, making it a beneficial feature for managing large amounts of data in Teradata.