When should you enable PK chunking for querying tables?

Enabling PK chunking is particularly beneficial when querying tables that contain a large volume of records, specifically more than 10 million. This method allows the query process to be more efficient by dividing the workload into manageable chunks based on primary key ranges. This segregation helps prevent timeouts and improves overall performance, especially in environments where large datasets can lead to heavy processing loads.

When dealing with large tables, the performance overhead can be significant, risk of hitting governor limits is higher, and retrieval times can increase dramatically. PK chunking helps to mitigate these issues by optimizing how data is fetched. Each chunk can be processed in parallel, making the overall data retrieval faster and more efficient.

For smaller datasets, such as those with less than a million records, or specific scenarios like querying archived records or only custom objects, the benefits of applying PK chunking may not be as pronounced and could even lead to unnecessary complexity in the querying process. Thus, the choice of enabling PK chunking is most appropriate for large tables with significant record counts.