Abstract: Embodiments provide an approach for efficiently searching a temporal key index as well as enforcing key distinctiveness property in a database table corresponding to the index. For example, by addressing time range overlaps in an index having a sort order for temporal keys, a database management tool of a server system may efficiently process client requests while enforcing a temporal key property in the database table.

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.

Abstract: Embodiments provide an approach for efficiently searching a temporal key index as well as enforcing key distinctiveness property in a database table corresponding to the index. For example, by addressing time range overlaps in an index having a sort order for temporal keys, a database management tool of a server system may efficiently process client requests while enforcing a temporal key property in the database table.

Abstract: Embodiments provide an approach for efficiently searching a temporal key index as well as enforcing key distinctiveness property in a database table corresponding to the index. For example, by addressing time range overlaps in an index having a sort order for temporal keys, a database management tool of a server system may efficiently process client requests while enforcing a temporal key property in the database table.

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.

Abstract: A method and system for providing a scalable storage scheme for native hierarchically structured data of relational tables, includes a base table with indicator columns with information pertaining to hierarchically structured data of a document, data tables for storing the hierarchically structured data corresponding to the indicator columns, and node identifier indexes corresponding to the data tables for mapping between the indicator columns and the hierarchically structured data in the data tables. In an embodiment, actual data for each hierarchically structured data (such as XML) column is stored in a separate data table, and each data table has a separate node identifier index. The node identifier index is searched with a key containing the document identifier and a logical node identifier is used, and a record identifier of a record in the data table containing the node assigned the logical node identifier is retrieved.

Abstract: Embodiments provide an approach for efficiently searching a temporal key index as well as enforcing key distinctiveness property in a database table corresponding to the index. For example, by addressing time range overlaps in an index having a sort order for temporal keys, a database management tool of a server system may efficiently process client requests while enforcing a temporal key property in the database table.

Abstract: Techniques are provided that determine that a query includes at least one subquery that may be correlated or decorrelated. An internal representation of the query that represents the subquery in both correlated and decorrelated form is generated, wherein the internal representation includes at least one virtual table.

Abstract: Techniques are provided that determine that a query includes at least one subquery that may be correlated or decorrelated. An internal representation of the query that represents the subquery in both correlated and decorrelated form is generated, wherein the internal representation includes at least one virtual table.

Abstract: Techniques are provided that determine that a query includes at least one subquery that may be correlated or decorrelated. An internal representation of the query that represents the subquery in both correlated and decorrelated form is generated, wherein the internal representation includes at least one virtual table.

Abstract: A method and system for providing a scalable storage scheme for native hierarchically structured data of relational tables, includes a base table with indicator columns with information pertaining to hierarchically structured data of a document, data tables for storing the hierarchically structured data corresponding to the indicator columns, and node identifier indexes corresponding to the data tables for mapping between the indicator columns and the hierarchically structured data in the data tables. In an embodiment, actual data for each hierarchically structured data (such as XML) column is stored in a separate data table, and each data table has a separate node identifier index. The node identifier index is searched with a key containing the document identifier and a logical node identifier is used, and a record identifier of a record in the data table containing the node assigned the logical node identifier is retrieved.

Abstract: A method, apparatus, and article of manufacture for optimizing a query in a computer system, wherein the query is performed by the computer system to retrieve data from a database stored on the computer system. The optimization is performed by identifying a correlated subquery in the query that qualifies for transformation, transitively closing a local filtering predicate within the identified correlated subquery that is on a same column as a correlation join predicate within the identified correlated subquery, and pulling out or bubbling up the transitively closed predicate from the correlated subquery to a parent query block of the query.

Abstract: Techniques are provided that determine that a query includes at least one subquery that may be correlated or decorrelated. An internal representation of the query that represents the subquery in both correlated and decorrelated form is generated, wherein the internal representation includes at least one virtual table.

Abstract: A method, apparatus, and article of manufacture for optimizing a query in a computer system, wherein the query is performed by the computer system to retrieve data from a database stored on the computer system. The optimization is performed by identifying a correlated subquery in the query that qualifies for transformation, transitively closing a local filtering predicate within the identified correlated subquery that is on a same column as a correlation join predicate within the identified correlated subquery, and pulling out or bubbling up the transitively closed predicate from the correlated subquery to a parent query block of the query.

Abstract: A technique for optimizing execution of a query that accesses data stored on a data store connected to a computer. Query predicates involving different data types are identified. A second query predicate is generated which includes matching data types, and if necessary, converted operators. The second query predicate with the matching data types and/or converted operators is executed to obtain a subset of records using an index manager or data manager. The subset of records is converted to the data types of the remaining query predicates. The first query predicate is applied against the subset of records to obtain a result, and the remaining query predicates of the original query are applied to the result of the first query predicate and any other additional converted query predicates to obtain a final result.

Abstract: A method, apparatus, and article of manufacture for analyzing a query and extending an access path selection for the query, in order to optimize joined table expressions and complex join operations in the query. The extension of the access path selection occurs in two phases: (1) an access path selection router analyzes and divides the query into portions, so that the overall access path selection is divided into smaller access path selections for processing by a join enumerator; and (2) the join enumerator is provided to handle joined table expressions and complex join operators, wherein the join enumerator can be continuously enhanced as more powerful query optimization techniques become available.

Abstract: A technique for optimizing execution of a query that accesses data stored on a data store connected to a computer. Query predicates involving different data types are identified. A second query predicate is generated which includes matching data types, and if necessary, converted operators. The second query predicate with the matching data types and/or converted operators is executed to obtain a subset of records using an index manager or data manager. The subset of records is converted to the data types of the remaining query predicates. The first query predicate is applied against the subset of records to obtain a result, and the remaining query predicates of the original query are applied to the result of the first query predicate and any other additional converted query predicates to obtain a final result.

Abstract: A query optimizer analyzes a query and triggers a sequence of transformations to achieve optimal performance for joined table expressions. The transformations include pushing down predicates for joined table expressions and pushing down non-null predicates to simplify join operators for joined table expressions.