A customer imports data from an external system into Salesforce using Bulk API. These jobs have batch sizes of 2000 and are run in parallel mode. The batches fail frequently with the error “Max CPU time exceeded”. A smaller batch size will fix this error.
What should be considered when using a smaller batch size?
When using a smaller batch size in Bulk API, one important consideration is that a smaller batch size may increase the time required to execute bulk jobs. This is because processing smaller batches means that the system will need to handle more batches overall, which can lead to an increase in the total execution time for the bulk job.
Given the need to choose one answer, the most critical consideration would be the one that directly impacts the ability to process batches concurrently without hitting system limits. The option that best fits this criterion is: B. Smaller batch size can trigger “Too many concurrent batches” error. This is because reducing the batch size increases the number of batches processed, which directly impacts the concurrent processing capabilities and can quickly lead to hitting the "Too many concurrent batches" error, which is a more immediate concern compared to the other options.