Abstract: Systems, methods, and other embodiments associated with visualizing data using summary graphs are described. One example method includes constructing a summary graph for display. The summary graph represents the data as a summary node having a plurality of property edges connected to the summary node. The summary node represents the set of values for the node in the data.

Abstract: Techniques for generating hash values for instances of distinct data values. In the techniques, each distinct data value is mapped to hash value generation information which describes how to generate a unique hash value for instances of the distinct data value. The hash value generation information for a distinct data value is then used to generate the hash value for an instance of the distinct data value. The hash value generation information may indicate whether a collision has occurred in generating the hash values for instances of the distinct data values and if so, how the collision is to be resolved. The techniques are employed to normalize RDF triples by generating the UIDS employed in the normalization from the triples' lexical values.

Abstract: Systems, methodologies, media, and other embodiments associated with supporting queries with hard time constraints are described. One exemplary system embodiment includes logic for accepting a query having a hard time constraint. The example system may also include logic for selectively rewriting the query having the hard time constraint into a query having a row limitation or a sample percentage limitation. In one example, the row limitation or sample percentage limitation are computed by repetitively comparing an estimated query execution time to the hard time constraint. The example system may also include logic for establishing a timer(s) associated with the rewritten query.

Abstract: A method, system, and computer program product provides improved performance for rebuild of user-defined indexes during partition maintenance operations (partition split, merge, and move). A method of maintaining a index of a partitioned database table comprises performing a partition maintenance operation on the partitioned database table wherein a plurality of rows of the partitioned database table are moved from one partition to another, storing mapping information for at least some of the plurality of moved rows, including an old mapping for each of the moved rows and a corresponding new mapping for each of the moved rows, and when rebuilding the index, replacing an old mapping in the index for each of the plurality of moved rows with the corresponding stored new mapping for each of the plurality of moved rows.

Abstract: Systems, methodologies, media, and other embodiments associated with supporting queries with soft time constraints are described. One exemplary system embodiment includes logic for accepting a query having a soft time constraint. The example system may also include logic for rewriting the query having the soft time constraint into a query having a row limitation or a sample percentage limitation. In one example, the row limitation or sample percentage limitation are computed by repetitively comparing an estimated query execution time to the soft time constraint.

Abstract: Systems, methodologies, media, and other embodiments associated with supporting reference partitioned tables in a relational database are described. One example method includes identifying a partitioning strategy (e.g., range, list, hash) associated with a parent table that is related to a child table by a referential constraint. The example method may also include creating the child table to be a reference-partitioned table partitioned according to the partitioning strategy associated with the parent table. The example method may also include creating the child table to be equi-partitioned with respect to the parent table. The child table is not to replicate a partition key of the parent table but rather is to inherit a partitioning key associated with the parent table through a foreign key relationship.

Abstract: Systems, methodologies, media, and other embodiments associated with supporting materialized views with user-defined aggregates are described. One example system includes logic for exposing a set of interface actions to support a user-defined aggregate in a materialized view associated with a base table. The materialized view may store both the user-defined aggregate and a user-defined aggregate context that facilitates logically connecting the user-defined aggregate to the base table. The example system may also include logic for supporting the user-defined aggregate. The support may be based on the set of interface actions. Example systems and methods may, therefore, facilitate incremental updating of the materialized view and/or rewriting a query to access the materialized view.

Abstract: A system for organizing and accessing a database. The system includes a primary B+tree index, a secondary B+tree index, a plurality of mapping table row identifiers stored in the secondary B+tree index and a plurality of database addresses for leaf blocks of the primary B+tree index corresponding to mapping table rows.

Abstract: A database management system that has bitmap values in which set bits in a representation of a bitstring specify a set of objects whose definitions are built into the database management system. The database management system further includes user-accessible operations on the bitmap values. The bitmap values are represented by means of a mapping specifier that specifies a range of the set of objects and a representation of a string of bits that has been mapped onto the set of object specified by the range specifier. Objects containing bitmap values may be indexed by means of an index tree that includes summary bitmap values.

Abstract: Systems, methods, and other embodiments associated with visualizing data using summary graphs are described. One example method includes constructing a summary graph for display. The summary graph represents the data as a summary node having a plurality of property edges connected to the summary node. The summary node represents the set of values for the node in the data.

Abstract: The TABLE function mechanism available in a RDBMS is used to integrate RDF models into SQL queries. The table function invocation takes parameters including an RDF pattern, an RDF model, and an RDF rule base and returns result rows to the SQL query that contain RDF triples resulting from the application of the pattern to the triples of the model and the triples inferred by applying the rule base to the model. The RDBMS includes relational representations of the triples and the rules. Optimizations include indexes and materialized views of the representations of the triples, precomputed inferred triples, and a method associated with the TABLE function that rewrites the part of the SQL query that contains the TABLE function invocation as an equivalent SQL string. The latter technique is generally applicable to TABLE functions.

Abstract: An un-indexed, partitioned temporary table and an exchange table are used in the inferencing of semantic data in a relational database system. The exchange table has the same structure as a semantic data table storing the semantic data. In the inferencing process, a new partition is created in the semantic data table. Inference rules are executed on the semantic data table, and any newly inferred semantic data generated is added to the temporary table. Once no new data is generated, the inferred semantic data is copied from the temporary table into the exchange table. Indexes that are the same as indexes for the semantic data table are built for the exchange table. The indexed data in the exchange table is then exchanged into the new partition in the semantic data table. By use of the un-indexed, partitioned temporary table, incremental maintenance of indexes is avoided, thus allowing for greater efficiency.

Abstract: Techniques for generating hash values for instances of distinct data values. In the techniques, each distinct data value is mapped to hash value generation information which describes how to generate a unique hash value for instances of the distinct data value. The hash value generation information for a distinct data value is then used to generate the hash value for an instance of the distinct data value. The hash value generation information may indicate whether a collision has occurred in generating the hash values for instances of the distinct data values and if so, how the collision is to be resolved. The techniques are employed to normalize RDF triples by generating the UIDS employed in the normalization from the triples' lexical values.

Abstract: A domain index for a partitioned database can be created using a user-defined indexing scheme. Partition maintenance operations performed on the partitioned database objects cause corresponding partition maintenance operations to be performed on the domain indexes. The user-supplied partitioning code is partition operation-unaware.

Abstract: A method, system, and computer program product provides improved performance for rebuild of user-defined indexes during partition maintenance operations (partition split, merge, and move). A method of maintaining a index of a partitioned database table comprises performing a partition maintenance operation on the partitioned database table wherein a plurality of rows of the partitioned database table are moved from one partition to another, storing mapping information for at least some of the plurality of moved rows, including an old mapping for each of the moved rows and a corresponding new mapping for each of the moved rows, and when rebuilding the index, replacing an old mapping in the index for each of the plurality of moved rows with the corresponding stored new mapping for each of the plurality of moved rows.

Abstract: Systems, methodologies, media, and other embodiments associated with supporting reference partitioned tables in a relational database are described. One example method includes identifying a partitioning strategy (e.g., range, list, hash) associated with a parent table that is related to a child table by a referential constraint. The example method may also include creating the child table to be a reference-partitioned table partitioned according to the partitioning strategy associated with the parent table. The example method may also include creating the child table to be equi-partitioned with respect to the parent table. The child table is not to replicate a partition key of the parent table but rather is to inherit a partitioning key associated with the parent table through a foreign key relationship.

Abstract: Systems, methodologies, media, and other embodiments associated with supporting materialized views with user-defined aggregates are described. One example system includes logic for exposing a set of interface actions to support a user-defined aggregate in a materialized view associated with a base table. The materialized view may store both the user-defined aggregate and a user-defined aggregate context that facilitates logically connecting the user-defined aggregate to the base table. The example system may also include logic for supporting the user-defined aggregate. The support may be based on the set of interface actions. Example systems and methods may, therefore, facilitate incremental updating of the materialized view and/or rewriting a query to access the materialized view.

Abstract: Systems, methodologies, media, and other embodiments associated with supporting queries with hard time constraints are described. One exemplary system embodiment includes logic for accepting a query having a hard time constraint. The example system may also include logic for selectively rewriting the query having the hard time constraint into a query having a row limitation or a sample percentage limitation. In one example, the row limitation or sample percentage limitation are computed by repetitively comparing an estimated query execution time to the hard time constraint. The example system may also include logic for establishing a timer(s) associated with the rewritten query.

Abstract: Systems, methodologies, media, and other embodiments associated with supporting queries with soft time constraints are described. One exemplary system embodiment includes logic for accepting a query having a soft time constraint. The example system may also include logic for rewriting the query having the soft time constraint into a query having a row limitation or a sample percentage limitation. In one example, the row limitation or sample percentage limitation are computed by repetitively comparing an estimated query execution time to the soft time constraint.

Abstract: The method for processing data in a relational database wherein ontology data that specifies terms and relationships between pairs of said terms expressed in an OWL document is stored in the database, database queries that include a semantic matching operator are formed which identify the ontology data and further specify a stated relationship between two input terms, and the query is executed to invoke the semantic matching operator to determine if the two input terms are related by the stated relationship by consulting said ontology data.