What implementation can efficiently update the account_current table during each hourly batch job?

The selection of filtering records using the last_updated field and writing a merge statement for updates and inserts is the most efficient implementation for updating the account_current table during each hourly batch job. This approach leverages the capabilities of the merge operation, which allows for the efficient handling of both updates and new records within a single transaction.

By filtering on the last_updated field, the process only considers the records that have changed since the last update, minimizing the volume of data that needs to be processed. This streamlined approach not only reduces the time taken for the operation but also decreases the resources required, leading to better overall performance in terms of throughput.

Using a merge statement allows for the handling of both insertions of new records and updates to existing records in one go, ensuring data integrity and consistency while maintaining efficient processing. This contrasts with the other options, which may involve unnecessary processing of all records or lack the optimization that comes from batching updates and inserts properly.

Therefore, this implementation strikes a balance between efficiency and data integrity, making it well-suited for a scenario that requires frequent updates on large datasets like account information.