Abstract: A method for functionally rewriting iterative queries for a relational database management system (RDBMS) is provided. The method comprises receiving a first iterative query, the first iterative query having a first non-iterative part that defines a first main table and a first iterative part that generates values in rows of a first working table based on values in rows of the first main table, determining that the first iterative part modifies all of the rows of the first working table, and rewriting the first iterative part, including: adding a renaming operation to rename the first working table to a new first main table and to rename the first main table to a new first working table, adding a first Delete operation to delete each row of the new first working table, and adding a first loop operation to repeat the first iterative part until a first termination condition is met.

Abstract: A query processing device includes a communication interface accessing a database and database catalog, a memory storing instructions, and a processor coupled to the memory and the communication interface. The processor executes the instructions to parse a query and generate first and second execution plans for the query, retrieve respective previously determined cardinality values for previously executed logical steps of the first and second execution plans from the database catalog, select an execution plan from the first execution plan or the second execution plan, the selected execution plan having a lower cost based on the previously determined cardinality values, and execute the selected execution plan on data accessed from the database. The query processing system stores actual cardinality values determined during the execution of the logical steps in the database catalog for use by subsequent queries. The query processing device, therefore, re-uses previously determined cardinality values.

Abstract: A method for functionally rewriting iterative queries for a relational database management system (RDBMS) is provided. The method comprises receiving a first iterative query, the first iterative query having a first non-iterative part that defines a first main table and a first iterative part that generates values in rows of a first working table based on values in rows of the first main table, determining that the first iterative part modifies all of the rows of the first working table, and rewriting the first iterative part, including: adding a renaming operation to rename the first working table to a new first main table and to rename the first main table to a new first working table, adding a first Delete operation to delete each row of the new first working table, and adding a first loop operation to repeat the first iterative part until a first termination condition is met.

Abstract: A query processing device is provided, including a processor coupled to a communication interface and a query storage. The processor receives a current submission of a query in a training mode, a stored prior execution plan, and stored statistics for the prior execution plan. The processor generates a current execution plan for the query, executes the current execution plan, and collects statistics. The processor stores the current execution plan and the statistics in the query storage and determines, based on the current execution plan, that the query is not in the training mode. The processor selects an execution plan for the query from among a plurality of stored execution plans for the query, including the prior execution plan and the current execution plan, and stores the selected execution plan for the query in the query storage with an indication that the query is not in the training mode.

Abstract: A query processing device includes a communication interface accessing a database and database catalog, a memory storing instructions, and a processor coupled to the memory and the communication interface. The processor executes the instructions to parse a query and generate first and second execution plans for the query, retrieve respective previously determined cardinality values for previously executed logical steps of the first and second execution plans from the database catalog, select an execution plan from the first execution plan or the second execution plan, the selected execution plan having a lower cost based on the previously determined cardinality values, and execute the selected execution plan on data accessed from the database. The query processing system stores actual cardinality values determined during the execution of the logical steps in the database catalog for use by subsequent queries. The query processing device, therefore, re-uses previously determined cardinality values.

Abstract: The disclosure relates to technology for estimating selectivity of non-join multi-column (NJMC) predicates of multi-column table (MCT) database queries is disclosed. The selectivity may be geometrically estimated by representing the full space of the MCT as one polyhedron having at least one dimension for each column of the MCT, and representing the NJMC predicate space as another polyhedron having at least one dimension for each column of a predicate space determined by applying the NJMC predicate to the MCT. Then the selectivity of the NJMC predicate may be estimated by computing a percentage of the size of the NJMC predicate space polyhedron to the size of the full space polyhedron. This more accurate estimate helps database query optimizers produce better query execution plans that utilize system resources more efficiently.

Abstract: A nested database query can be optimized by effectively representing a filtering function or operation (e.g., SQL filtering operation) of its outer sub-query by a qualification or qualify operation (e.g., SQL qualification operation) associated with at least one windowing function of at least one of its inner sub-queries. It will be appreciated that this representation can yield a modified query that would be equivalent (e.g., semantically equivalent) to the original nested query as its execution can produce the same results when optimization rules are applied.

Abstract: A nested database query can be optimized by effectively representing a filtering function or operation (e.g., SQL filtering operation) of its outer sub-query by a qualification or qualify operation (e.g., SQL qualification operation) associated with at least one windowing function of at least one of its inner sub-queries. It will be appreciated that this representation can yield a modified query that would be equivalent (e.g., semantically equivalent) to the original nested query as its execution can produce the same results when optimization rules are applied.

Abstract: The invention relates to a method and database system for rewriting a SQL query having at least one null sensitive expression (NSE) in a select list of the query, the query comprising at least one outer join command to be performed on at least two tables and involving a view or a Derived Table (DT). The method comprising the steps of: identifying at least one unmatching row belonging to the view or DT using non-nullable fields that belong to the outermost table in the view or DT; converting the NSE(s) from the at least one identified rows into a SQL case construct; and performing the at least one outer join. The database system comprising means for rewriting a SQL query having at least one null sensitive expression (NSE) in a select list of the query, the query comprising at least one outer join command to be performed on at least two tables and involving a view or a Derived Table (DT).

Abstract: In general, the invention features a computer-implemented method for improving the efficiency of execution of a database query including a WHERE clause. The method includes analyzing the satisfiability of the conditions associated with the WHERE clause before executing the query. Furthermore, the method includes modifying the conditions to meet transitive closure, if necessary, before executing the query.

Abstract: The invention relates to a method and database system for rewriting a SQL query having at least one null sensitive expression (NSE) in a select list of the query, the query comprising at least one outer join command to be performed on at least two tables and involving a view or a Derived Table (DT). The method comprising the steps of: identifying at least one unmatching row belonging to the view or DT using non-nullable fields that belong to the outermost table in the view or DT; converting the NSE(s) from the at least one identified rows into a SQL case construct; and performing the at least one outer join. The database system comprising means for rewriting a SQL query having at least one null sensitive expression (NSE) in a select list of the query, the query comprising at least one outer join command to be performed on at least two tables and involving a view or a Derived Table (DT).

Abstract: Methods and systems for rewriting database queries, and in particular databases using Structured Query Language (SQL). The method comprises the steps of reviewing a SQL query statement having a SELECT list to determine if a view definition of the query has one or more unreferenced view columns; and removing at least one of the one or more unreferenced view columns from the view definition. The step of removing at least one of the one or more unreferenced view columns may also include removing all of the one or more unreferenced view columns from the view definition. This method improves performance of a query given that the spool file generated by the query rule contains minimal amount of data necessary for the query to be processed.

Abstract: A method, computer program, and database system are disclosed for executing database queries. The database includes a first table (T1) having a primary key (PK) column and a first correlated value column (CV1) and a second table (T2) having a foreign key (FK) column related to the primary key column of the first table and a second correlated value column (CV2). One implementation of the method includes preparing a database query for execution based at least in part on application of a derived constraint rule (DCR) having the form, (PK=FK)?CV2+C1?CV1?CV2+C2, where C1 and C2 are constants and “?” means “implies,” to produce an execution plan. A frequency of errors due to changes in DCRs is taken into account when preparing the execution plan. The plan is then executed.

Abstract: A method and computer system for improving the efficiency of execution of a database query that includes conditions is disclosed. Satisfiability of the conditions is analyzed before executing the query. If the conditions are satisfiable, the transitive closure of the conditions is analyzed and the conditions are modified to meet transitive closure, if necessary, before executing the query.