To speed up the website's response time for product searches, which technique should the e-commerce company implement?

To speed up the website's response time for product searches, which technique should the e-commerce company implement?

• A. Index creation
• B. Data normalization
• C. Table partitioning
• D. Replication

Answer: (A)

Creating an index is a highly effective technique for improving the response time of product searches on a website. An index works similarly to a book index, where it allows the database to quickly locate and access specific rows in a table without having to scan each row individually. This becomes particularly beneficial when dealing with large datasets, such as those typical in e-commerce applications, because it significantly reduces the amount of data the database server must sift through to find relevant search results. When an index is created on the columns most frequently queried, it allows the database management system (DBMS) to execute search queries much more efficiently. The optimization gained from indexing can lead to faster query performance, thus enhancing the user experience on the e-commerce site as customers receive their search results more quickly. In contrast, data normalization is focused on organizing a database to reduce redundancy and improve data integrity rather than directly speeding up response times for searches. Table partitioning can be useful in managing large tables by breaking them into smaller, more manageable pieces, but it does not inherently improve search speed like indexing does. Replication, which involves creating copies of data across multiple servers for load balancing and redundancy, may improve availability but does not directly enhance the speed of a specific search query. Therefore, implementing

Creating an index is a highly effective technique for improving the response time of product searches on a website. An index works similarly to a book index, where it allows the database to quickly locate and access specific rows in a table without having to scan each row individually. This becomes particularly beneficial when dealing with large datasets, such as those typical in e-commerce applications, because it significantly reduces the amount of data the database server must sift through to find relevant search results.

When an index is created on the columns most frequently queried, it allows the database management system (DBMS) to execute search queries much more efficiently. The optimization gained from indexing can lead to faster query performance, thus enhancing the user experience on the e-commerce site as customers receive their search results more quickly.

In contrast, data normalization is focused on organizing a database to reduce redundancy and improve data integrity rather than directly speeding up response times for searches. Table partitioning can be useful in managing large tables by breaking them into smaller, more manageable pieces, but it does not inherently improve search speed like indexing does. Replication, which involves creating copies of data across multiple servers for load balancing and redundancy, may improve availability but does not directly enhance the speed of a specific search query.

Therefore, implementing