Abstract: Disclosed is technique for executing a query. A set of algebraic rules applicable to the query are identified, wherein each of the algebraic rules represents a relationship between two columns in a relational database table. A source column is identified by searching the query for a source predicate, wherein the source predicate is a range predicate. One or more candidate target columns are identified by searching the set of algebraic rules, wherein each of the candidate target columns occurs on one side of a binding expression and the source column occurs on the other side of the binding expression. For each of the one or more candidate target columns, a bounds subquery that provides a lower bound and an upper bound for a new range predicate is derived and the new range predicate is introduced into the query, wherein the query is executed to retrieve data from one or more data stores.

Abstract: Disclosed is a data processing system implemented method, a data processing system and an article of manufacture for executing a query having a union operator. The data processing system implemented method directs the data processing system to process a query against data objects. The data objects are operatively coupled to the data processing system. The query includes a parent operator. The parent operator references a union operator. The union operator references sub-queries. The sub-queries reference the data objects. The data processing system implemented method includes noting a set of partitionings for the union operator, the noted set of partitionings being based on the sub-queries and being based on the data objects reference by the sub-queries, and executing the query having the union operator, the execution of the query being based on the noted set of partitionings and the parent operator.

Abstract: Disclosed is a data processing system implemented method, a data processing system and an article of manufacture for executing a query having a union operator. A data processing system implemented method direct the data processing system to execute a query against a database having data objects. The query has sub-queries and having a union operator. The union operator is operable on sub-queries associated with the query. The database is operatively coupled to the data processing system.

Abstract: A system, apparatus, and program storage device implementing a method of optimizing queries used for searching a computerized database, wherein the method comprises providing a query comprising a sequence of inner joins and outerjoins; and rewriting the query by producing a sequence of outer Cartesian products for the query; producing a sequence of nullification operations on the query; and producing a sequence of best match operations on the query. The method further comprises optimizing the query using a query execution plan for processing the rewritten query, wherein the query execution plan expands a search space in the database for which the rewritten query may be run.

Abstract: A local database cache enabling persistent, adaptive caching of either full or partial content of a remote database is provided. Content of tables comprising a local cache database is defined on per-table basis. A table is either: defined declaratively and populated in advance of query execution, or is determined dynamically and asynchronously populated on-demand during query execution. Based on a user input query originally issued against a remote DBMS and referential cache constraints between tables in a local database cache, a Janus query plan, comprising local, remote, and probe query portions is determined. A probe query portion of a Janus query plan is executed to determine whether up-to-date results can be delivered by the execution of a local query portion against a local database cache, or whether it is necessary to retrieve results from a remote database by executing a remote query portion of Janus query plan.

Abstract: Disclosed is technique for executing a query. A query is matched to an outlier materialized query table. The query is searched for a source predicate. The outlier materialized query table is searched for a target column that corresponds to a source column in the source predicate. A new range predicate is derived based on the target column and introduced into the query.

Abstract: A method for using pre-computed information stored in auxiliary structures to speed up processing of expensive queries on hierarchical documents such as XML documents being queried using XPath. The invention defines a taxonomy of such structures such as indexes and materialized views for storing pre-computed XPath results (PXRs), determines what portion of the query can be evaluated by the structures, and computes the compensation for the results generated by the structures. The invention detects all structures applicable to the query and rewrites the query to use such structures, speeding up the performance of the queries. The invention identifies the matching structures by detecting containment mappings between XPath expressions in the query and the structure. The invention also includes a new representation for XPath expressions that is rich enough to express all features of XPath.

Abstract: A method, system, and computer program product to make query processing more robust in the face of optimization errors. The invention validates the statistics and assumptions used for compiling a query as the query is executed and, when necessary, progressively re-optimizes the query in mid-execution based on the knowledge learned during its partial execution. The invention selectively places a number of CHECK operators in a query execution plan to validate the optimizer's cardinality estimates against actual cardinalities. Errors beyond a threshold trigger re-optimization, and the optimizer decides whether the old plan is still optimal and whether to re-use previously computed results. The invention addresses arbitrary SQL queries whose plans can contain sub-queries, updates, trigger checking, and view maintenance operations.

Abstract: Disclosed is a method and system for incrementally maintaining algebraic functions in automatic summary tables (ASTs) of at least one relational database. The method associates a work area with each algebraic function in each AST. Each work area is comprised of one or more variables. The method populates the variables within each work area for each algebraic function when each AST is created and when each AST is updated. The method maintains each work area by adding and subtracting to and from its associated variables when the associated data changes in the relational database. The functions that compute the variables of the work areas are distributive and thus incrementally maintainable. The method computes and recomputes the algebraic function within an AST after the updates have changed one or more of the variables of its workarea.