Abstract: Constraint processing for a relational database generates primary (e.g., based on primary key values) and constraint index records (e.g., based on foreign key values) during table load operations that are then sorted in a manner that rapidly and unambiguously identifies rows that fail the specified constraint test. Rows so identified may be deleted to maintain the constraint (e.g., referential) integrity of a child table. In one case, child table row data may be processed in constraint key order, eliminating the need first load the child table with row data and then delete those rows that subsequently fail the integrity test.

Abstract: Constraint processing for a relational database generates primary (e.g., based on primary key values) and constraint index records (e.g., based on foreign key values) during table load operations that are then sorted in a manner that rapidly and unambiguously identifies rows that fail the specified constraint test. Rows so identified may be deleted to maintain the constraint (e.g., referential) integrity of a child table. In one case, child table row data may be processed in constraint key order, eliminating the need first load the child table with row data and then delete those rows that subsequently fail the integrity test.

Abstract: Constraint processing for a relational database generates primary (e.g., based on primary key values) and constraint index records (e.g., based on foreign key values) during table load operations that are then sorted in a manner that rapidly and unambiguously identifies rows that fail the specified constraint test. Rows so identified may be deleted to maintain the constraint (e.g., referential) integrity of a child table. In one case, child table row data may be processed in constraint key order, eliminating the need first load the child table with row data and then delete those rows that subsequently fail the integrity test.

Abstract: A time-efficient means for identifying and processing cascading deletes due to referential constraint violations includes: logging, to an error file, all primary key (“PK”) errors detected during table load operations; building a foreign key (“FK”) index for each child table; recursively probing each relevant FK index to identify all loaded rows that violate a referential constraint due to a PK error; logging all identified FK errors to the error file; and using the (preferably sorted) error file contents to identify, mark and physically delete table rows that violate a referential constraint. The described cascade delete processing methods make only a single pass through the table data, using ordinary computer files to track and organize rows identified for deletion. Use of error files rather than tablescans (multiple passes through the loaded table data) can provide a significant reduction in table load times, especially for large or intricately “related” tables.