249 results about "Foreign key" patented technology

A Relational Database Management System (RDBMS) having any arbitrary structure is translated into a multi-dimensional data model suitable for performing OLAP operations upon. If a relational table defining the relational model includes any tables with cardinality of 1,1 or 0,1, the tables are merged into a single table. If the relational table is not normalized, then normalization is performed and a relationship between the original table and the normalized table is created. If the relational table is normalized, but not by dependence between columns, such as in the dimension table in a snowflake schema, the normalization process is performed using the foreign key in order to generate the normalized table. Once the normalized table is generated, OLAP measures are derived from the normalized relational table by an automated method. In addition, OLAP dimensions are derived from the normalized relational table and the results of the OLAP measures derivation by an automated method according to the present invention. According to an aspect, it is possible to associate a member of a dimension to another member of the same or another dimension. According to another aspect, it is possible to create a new dimension of analysis, the members of which are all the different values that a scalar expression can take on. According to yet another aspect, it is possible to access the various instances of a Reporting Object as members in an OLAP dimension. According to the yet another aspect, it is possible to apply opaque filters or a combination of them to the data that underlies analysis.

The invention concerns a detection of duplicate tuples in a database. Previous domain independent detection of duplicated tuples relied on standard similarity functions (e.g., edit distance, cosine metric) between multi-attribute tuples. However, such prior art approaches result in large numbers of false positives if they are used to identify domain-specific abbreviations and conventions. In accordance with the invention a process for duplicate detection is implemented based on interpreting records from multiple dimensional tables in a data warehouse, which are associated with hierarchies specified through key-foreign key relationships in a snowflake schema. The invention exploits the extra knowledge available from the table hierarchy to develop a high quality, scalable duplicate detection process.

A computerized system and method for transforming (formatting or aggregating) the results of a query into a hierarchical information stream, such as an extensible Markup Language (XML) data stream is disclosed. A database server receives a query and generates a rowset. A rowset processor, using the mode specified in the query, processes the rowset and query to generate the XML data stream. For the “auto1” mode, the rowset processor transforms a rowset into an XML data stream using primary-foreign key information specified in the query to determine nesting. For the “auto2” mode, the rowset processor transforms a rowset into an XML data stream using table ordering information included in the query to determine nesting. For the “explicit” mode, the rowset processor transforms a rowset into an XML data stream using the explicit organizational information specified in the query. In one embodiment, it is easier for a developer to compose expressions to generate nested hierarchical structures than previous formulations and simpler semantics are provided without implicit hierarchy inference. The syntax of an embodiment of the hierarchical formatting function includes optional arguments including a name option, a root option, map option, namespace options and a null option.

Instructions are generated to manipulate target objects and relationships in a relational database when a source object having a one-to-many relationship of privately owned type with the target objects is manipulated. To generate instructions, mapping meta-data is used which contains information as to how object classes of the object model map to tables in the database and how relationships map to foreign keys.