Why does paging not work well with certain types of modifications?

Paging involves dividing a data set into manageable chunks or 'pages' for more efficient retrieval, particularly when handling large datasets. When it comes to modifying queried columns, issues arise because modifying these columns can result in a change in their underlying order or position within the dataset. When a cursor (which is used to track the current position within the dataset) is relying on specific positions to manage paging, any modification to a column can shift the data around, causing the cursor to refer to an incorrect location. This disruption affects the integrity of the paging mechanism, leading to inconsistencies and potential errors in retrieving the expected data.

The requirement for a constant data structure stems from the need for stability in the dataset during operations, ensuring that the pagination remains accurate and reliable as users navigate through data. While paging does have some constraints, such as primarily supporting read operations and varying impacts on application performance, the primary concern when it comes to modifications specifically pertains to how these changes can disrupt the cursor's positioning within the paged structure.