Which practice can enhance the efficiency of a database when handling large volumes of search queries?

• A. Implementing clustering
• B. Creating indexes on key attributes
• C. Archiving old data
• D. Using distributed databases

Answer: (B)

Creating indexes on key attributes is a fundamental practice for enhancing the efficiency of a database, especially when handling large volumes of search queries. Indexes function similarly to an index in a book, allowing the database management system to quickly locate data without scanning every row in a table. This significantly reduces the amount of data the system needs to process for each query, thereby improving performance and reducing response times.

When a query is executed, the database looks for relevant indexes that can help expedite the retrieval process. By indexing key attributes—such as columns that are frequently searched or filtered—the database can effectively narrow down the search area, which results in faster query execution. This practice is particularly beneficial in tables with many rows, as it streamlines the search process and optimizes overall database performance.

In contrast, while implementing clustering, archiving old data, and using distributed databases can also contribute to database efficiency, they do not specifically address the immediate needs of optimizing search query performance as directly and effectively as indexing. Clustering can enhance the physical organization of data, which is helpful in certain scenarios, but it does not replace the efficiency provided by indexing. Archiving old data helps with management and may reduce the size of active datasets, but does not inherently speed up search operations on