When you’re facing a scenario where updating a fact table via a linked server query in SQL Server takes an exorbitant amount of time it’s valid to be concerned about the consequences this has on the transaction log’s ability to clear, not just on the initiating server but on the linked server as well. Long-running transactions are notorious for their capacity to prevent the transaction log from being truncated because SQL Server cannot clear out log records for transactions that are still in progress. This can lead to inflated transaction logs, potentially filling up the disk space and impacting overall database performance.

You might wonder if employing the NOLOCK hint could serve as a remedy in this scenario. Typically, NOLOCK is used to implement the “read uncommitted” isolation level, allowing a query to read data without waiting for other concurrent transactions to complete, effectively ignoring locks and potentially reading uncommitted changes. While this can reduce locking contention and improve read query performance, it’s crucial to understand that NOLOCK is not a silver bullet, especially for operations that modify data.

In the context of an update operation—NOLOCK isn’t directly applicable. This is because NOLOCK primarily affects read operations and doesn’t alter the fundamental behavior of how SQL Server handles transaction logs for updates or inserts. For modifications, SQL Server needs to ensure data integrity and transactional consistency, which requires acquiring the appropriate locks and logging changes in the transaction log, irrespective of the NOLOCK hint.

Given the situation, a more effective strategy might involve optimizing the update process to reduce its duration and impact on the transaction log. This could include breaking the update into smaller batches, which can help by limiting the amount of data locked at any one time and reducing the size of the transaction, allowing for more frequent log truncation. Additionally, reviewing the query and indexes involved might reveal opportunities for optimization that could significantly reduce the update time.

In short:

• Long-running update operation can indeed prevent the transaction log from clearing on both the originating and linked servers.
• Employing NOLOCK in this context wouldn’t help in managing the transaction log’s size or facilitate its clearance, as NOLOCK is more relevant to read-only operations and doesn’t affect the transaction logging mechanism for updates.

In summary, while NOLOCK can be beneficial in specific scenarios to mitigate read contention, it doesn’t offer a solution for managing transaction log growth during extensive update operations. Instead, focusing on optimizing the update strategy and considering transaction log management practices is more pertinent to addressing the challenges posed by long-running updates in SQL Server.