What risk may arise from using a batch size that is too small during a Bulk API integration?

Using a batch size that is too small during a Bulk API integration can lead to very long bulk job execution times. This is primarily because each batch has its own overhead in terms of communication and processing. When the batch size is reduced excessively, the system ends up making multiple calls to process a relatively small amount of data, which accumulates significant total execution time.

As each batch requires its own transaction processing and can involve setup and teardown overhead, a smaller batch size translates to more transactions that need to be managed. This increased number of calls can therefore lead to latency and inefficiencies, making the overall execution of the bulk job take much longer than if larger batches were used.

A balancing act is essential when determining batch size. While too large a batch size can risk hitting system limits, too small a size primarily results in inefficiencies and prolonged processing times.