Final answer:
When optimized with clustering, a database arranges related records together on the physical disk, which improves read performance by reducing disk I/O operations. Clustering uses indexes to group similar or related records, improving the efficiency of queries involving these records.
Step-by-step explanation:
When a database has been optimized with clustering, the records are arranged on the physical drive in a way that groups together records that are similar, or related, based on one or more clustering indexes. This means that records which are often accessed together are stored physically close to each other on the disk. The aim of clustering is to reduce the amount of disk I/O (input/output operations) needed when queries are executed that involve these related records. For instance, if a database holds customer data and an index has been created that clusters records by geographical location, all customers from a specific area would be stored in adjacent locations on the disk.
An important benefit of this approach is the improvement in performance for read-intensive operations, especially when dealing with large volumes of data. However, it's worth noting that while clustering can significantly improve read performance, it might have an impact on write performance since the database may need to reorganize records to maintain the clustering when new data is inserted or existing records are updated.