What benefit does breaking down large jobs into smaller tasks provide in Relativity Web Processing?

Breaking down large jobs into smaller tasks in Relativity Web Processing enhances the overall processing times. This approach allows the system to process each smaller job independently, which can make more efficient use of available resources and reduce the wait time for the final output. Smaller tasks can be distributed across various processing nodes, enabling parallel processing. As a result, multiple tasks can be completed simultaneously, significantly speeding up the overall workflow.

Additionally, this method facilitates better error handling; if an error occurs within one small task, it can be addressed without interrupting the entire process. This means that issues can be resolved more swiftly, contributing to the efficiency gains in processing time. Overall, the ability to process smaller tasks concurrently enhances throughput and effectiveness in handling large datasets, thus leading to faster processing times.