Which of the following factors is crucial for workloads that require high throughput?

Large sequential I/O is a crucial factor for workloads that require high throughput because it allows for more efficient data transfers. In high-throughput environments, such as those found in big data and high-performance computing, the ability to read or write data in large contiguous blocks significantly reduces the overhead associated with individual I/O operations. This is because sequential I/O minimizes seek time and maximizes the use of available bandwidth within storage systems.

When I/O operations are conducted sequentially, they can benefit from optimizations in both software and hardware, such as caching and prefetching techniques that are designed to handle larger chunks of data more effectively. This results in improved overall performance and responsiveness of the system when processing large datasets.

In contrast, small data transactions and frequent data access tend to exacerbate overhead and latency, while high processing capability, although important, is not directly linked to maximizing I/O throughput. Therefore, the focus on large sequential I/O is essential for achieving optimal throughput in high-demand workloads.