Abstract: In managing multiple versions of triggers, a database system creates a first version of a trigger to apply a first set of actions in response to a first triggering event. The database system also creates a second version of the trigger to apply a second set of actions to the database object in response to a second triggering event. Upon receiving a command to set the current version of the trigger to the second version, the database system sets the second version as the current version of the trigger. When the triggering event of the trigger occurs, the database system determines that the second version is the current version of the trigger, retrieves the second set of actions in the second version, and executes the second set of actions.

Abstract: In managing multiple versions of triggers, a database system creates a first version of a trigger to apply a first set of actions in response to a first triggering event. The database system also creates a second version of the trigger to apply a second set of actions to the database object in response to a second triggering event. Upon receiving a command to set the current version of the trigger to the second version, the database system sets the second version as the current version of the trigger. When the triggering event of the trigger occurs, the database system determines that the second version is the current version of the trigger, retrieves the second set of actions in the second version, and executes the second set of actions.

Abstract: In managing multiple versions of triggers, a database system creates a first version of a trigger to apply a first set of actions in response to a first triggering event, which includes: creating a first package for the first version of the trigger to include the first set of actions; linking the first package to the database object; and setting the first package as a current version of the trigger. The database system creates a second version of the trigger to apply a second set of actions to the database object in response to a second triggering event, which includes: creating a second package for the second version of the trigger to include the second set of actions; and linking the second package to the database object. In response to a command, the database system sets the current version of the trigger to the second package.

Abstract: Dropping of columns from a table with data availability, where the columns in the table are each associated with a column number, includes: executing a statement to drop a given column in the table and deferring an application of the statement until a reorganization of a current data set including the table. When the reorganization of the current data set is performed, the reorganization includes: updating column numbers for columns in each row of the table using a mapping data structure to remove the given column; loading the plurality of data rows with the updated column numbers into a shadow data set; applying to the shadow data set any changes to the table that are concurrent with the reorganization; updating a schema definition of the table with the updated column numbers; and switching the current data set to the shadow data set.

Abstract: In managing multiple versions of triggers, a database system creates a first version of a trigger to apply a first set of actions in response to a first triggering event, which includes: creating a first package for the first version of the trigger to include the first set of actions; linking the first package to the database object; and setting the first package as a current version of the trigger. The database system creates a second version of the trigger to apply a second set of actions to the database object in response to a second triggering event, which includes: creating a second package for the second version of the trigger to include the second set of actions; and linking the second package to the database object. In response to a command, the database system sets the current version of the trigger to the second package.

Abstract: Recovering data to a point in time before pending definition changes are materialized in a relational database management system. One or more definition changes to a database schema are received. Original data base schema attributes are saved as point in time metadata in a catalog table until the one or more definition changes have been materialized. During recovery processing, it is determined for each object being recovered whether the object is being recovered to a point in time prior to which the one or more definition changes were materialized. In response to determining that an object is being recovered to a point in time prior to which the one or more definition changes were materialized, the saved point in time metadata is used for the object in the recovery process.

Abstract: Recovering data to a point in time before pending definition changes are materialized in a relational database management system. One or more definition changes to a database schema are received. Original data base schema attributes are saved and maintained as point in time metadata in a catalog table until the one or more definition changes have been materialized. During recovery processing, it is determined for each object being recovered whether the object is being recovered to a point in time prior to which the one or more definition changes were materialized. In response to determining that an object is being recovered to a point in time prior to which the one or more definition changes were materialized, the saved point in time metadata is used for the object in the recovery process.

Abstract: Dropping of columns from a table with data availability, where the columns in the table are each associated with a column number, includes: executing a statement to drop a given column in the table and deferring an application of the statement until a reorganization of a current data set including the table. When the reorganization of the current data set is performed, the reorganization includes: updating column numbers for columns in each row of the table using a mapping data structure to remove the given column; loading the plurality of data rows with the updated column numbers into a shadow data set; applying to the shadow data set any changes to the table that are concurrent with the reorganization; updating a schema definition of the table with the updated column numbers; and switching the current data set to the shadow data set.

Abstract: Recovering data to a point in time before pending definition changes are materialized in a relational database management system. One or more definition changes to a database schema are received. Original data base schema attributes are saved as point in time metadata in a catalog table until the one or more definition changes have been materialized. During recovery processing, it is determined for each object being recovered whether the object is being recovered to a point in time prior to which the one or more definition changes were materialized. In response to determining that an object is being recovered to a point in time prior to which the one or more definition changes were materialized, the saved point in time metadata is used for the object in the recovery process.

Abstract: Recovering data to a point in time before pending definition changes are materialized in a relational database management system. One or more definition changes to a database schema are received. Original data base schema attributes are saved and maintained as point in time metadata in a catalog table until the one or more definition changes have been materialized. During recovery processing, it is determined for each object being recovered whether the object is being recovered to a point in time prior to which the one or more definition changes were materialized. In response to determining that an object is being recovered to a point in time prior to which the one or more definition changes were materialized, the saved point in time metadata is used for the object in the recovery process.

Abstract: Dropping of columns from a table with data availability, where the columns in the table are each associated with a column number, includes: executing a statement to drop a given column in the table and deferring an application of the statement until a reorganization of a current data set including the table. When the reorganization of the current data set is performed, the reorganization includes: updating column numbers for columns in each row of the table using a mapping data structure to remove the given column; loading the plurality of data rows with the updated column numbers into a shadow data set; applying to the shadow data set any changes to the table that are concurrent with the reorganization; updating a schema definition of the table with the updated column numbers; and switching the current data set to the shadow data set.

Abstract: Dropping of columns from a table with data availability, where the columns in the table are each associated with a column number, includes: executing a statement to drop a given column in the table and deferring an application of the statement until a reorganization of a current data set including the table. When the reorganization of the current data set is performed, the reorganization includes: updating column numbers for columns in each row of the table using a mapping data structure to remove the given column; loading the plurality of data rows with the updated column numbers into a shadow data set; applying to the shadow data set any changes to the table that are concurrent with the reorganization; updating a schema definition of the table with the updated column numbers; and switching the current data set to the shadow data set.