Abstract: Systems, clients, servers, methods, and computer-readable media of varying scope are described in which, two extensions for a multidimensional database query language extensions, AddCalculatedMembers and StripCalculatedMembers, allow an OLAP client to easily control the integration of calculated members into the results of OLAP database queries. The OLAP client need not be aware of the details of which calculated members are defined within the multidimensional database and need not explicitly request the inclusion or removal of each calculate member from the output data set of the query.

Abstract: A system and method for analytically modeling data in a data cube is disclosed. A first dimension of the data cube is modeled according to a first table having a referencing attribute. A second dimension of the data cube is modeled according to a second table having a referenced attribute. The first dimension is tied to the second dimension according to the referencing attribute and the referenced attribute.

Abstract: A system and method for analytically modeling data organized according to non-referred attributes is disclosed. Data stored in a first and a second relational data table is analytically modeled in a data cube. The first table organizes a first type according to a first attribute. The second table organizes a second type according to the first attribute and a second attribute. A first measure is modeled according to the first type of the first table. A first dimension is modeled according to the first attribute of the first and second tables. A second dimension is modeled according to the second attribute of the second table. The first measure is tied to the first dimension according to the first attribute of the first table to allow the first measure to be analyzed by the first dimension according to the first attribute. The first measure is tied to the second dimension by, for each entry of the first dimension, allocating the entry to each entry of the second dimension in a predetermined manner.

Abstract: A system and method for analytically modeling data from different measure groups onto a single cube are disclosed. The single cube preferably includes a first measure associated with a first measure group with a first set of corresponding dimensions. The single cube preferably also includes a second measure associated with a second measure group with a second set of corresponding dimensions. The single cube preferably also includes each dimension in both the first and second set of dimensions. Each measure is preferably tied to each corresponding dimension according to data in an underlying relational data table. Each measure is preferably tied to each non-corresponding dimension according to an approximation.

Abstract: A system and method for analytically modeling data with related attributes is disclosed. A single dimension is used to provide data according to each of the related attributes, and, thus, may be said to play the role of each related attribute depending on a received query. The measure of the analytical data model is tied to the dimension according to both data attributes to allow the measure to be analyzed by the dimension according to both attributes.

Abstract: Visualization of high-dimensional data sets is disclosed, particularly the display of a network model for a data set. The network, such as a dependency or a Bayesian network, has a number of nodes having dependencies thereamong. The network can be displayed items and connections, corresponding to nodes and dependencies, respectively. Selection of a particular item in one embodiment results in the display of the local distribution associated with the node for the item. In one embodiment, only a predetermined number of the items are shown, such as only the items representing the most popular nodes. Furthermore, in one embodiment, in response to receiving a user input, a sub-set of the connections is displayed, proportional to the user input.

Abstract: Systems, clients, servers, methods, and computer-readable media of varying scope are described in which, a data retrieval module of database client implements an aggressive caching scheme that seeks to predict what data cells will be needed to satisfy future queries. The data retrieval module applies an adaptive algorithm to dynamically determine the granularity of data to retrieve from a database server. The data retrieval module adaptively balances the benefit of satisfying future queries locally with the cost of retrieving larger data set from remote database server.

Abstract: Systems and methods for creating and maintaining virtual cubes are disclosed. A virtual cube is a logical representation of a subset of the dimensions and measures of at least one physical cube maintained by an OLAP server. Metadata defines the mappings from the dimensions and measures of the virtual cube to the dimensions and measures of the physical cube. Client applications can manipulate the virtual cube as if it were a physical cube.

Abstract: Systems, clients, servers, methods, and computer-readable media of varying scope are described in which, a database client applies an adaptive method to dynamically determines whether a particular request should execute on the client-side or the server-side of a client-server database system. In determining where a particular request should be executed, the database client analyzes the size of the data sets involved and the data flow generated by the data sets.

Abstract: A method, apparatus, and software are disclosed for analyzing the data in an OLAP or other type of database. The data is analyzed as if it were indexed by desired dimensions without actually creating the dimensions. Relations known as virtual dimensions are defined in relation to existing base dimensions in the database rather than in relation to the underlying detailed data. Functions operating on these virtual dimensions are translated into functions that operate on the existing base dimensions. As a result, the need to perform certain precalculations is avoided, thereby promoting efficient use of computing resources.

Abstract: A method, apparatus, and software are disclosed for efficient estimation of the size of an aggregation, or summary of data, in a database. This estimate is used in selecting which aggregations are materialized in an OLAP system or relational database. The estimate is based on cardinalities of aggregation levels and of dimension groups consisting of related dimensions, as well as on the size of the underlying detailed data.

Abstract: Creating and maintaining cell data records in a multidimensional database is disclosed using flexible dimension paths is disclosed. The systems and methods of the invention define an efficient mechanism to specify a cell's location within the multidimensional database where there are hierarchies of levels within a dimension. The flexible dimension path does not change when a member is moved from a first point to a second point on a dimension thereby avoiding the need to rebuild the OLAP database. The format used lends itself well to indexing, and also to creating aggregations of the cell data.

Abstract: Creating and maintaining cell data records in a multidimensional database is disclosed. The systems and methods of the invention define an efficient mechanism to specify a cell's location within the multidimensional database where there are hierarchies of levels within a dimension. The format used lends itself well to indexing, and also to creating aggregations of the cell data.

Abstract: Designing aggregations according to a weighted benefit/cost ratio is disclosed. Usage statistics including frequency counts are maintained for queries issued to the system. The usage statistics determine the domain of potentially useful aggregations. The system maintains benefit and cost data for aggregations in terms of row scans saved and number of rows required to store an aggregation. In addition, query frequency counts are used to scale the aggregation benefit/cost for a set of aggregations. The weighted benefit/cost ration determines the aggregations to instantiate, thereby providing an optimal combination of performance and cost.

Abstract: Compressing system paths in a database is disclosed. The systems and methods of the invention define an efficient mechanism to specify a cell's location within the database where there are hierarchies of levels within a dimension. The compressed system paths allow random access of the data without decompressing the data. The format used lends itself well to indexing, and also to creating aggregations of the cell data.

Abstract: A method and system for compressing and decompressing read only data in records that have a fixed size. A plurality of records are divided into segments having a predetermined size. For each segment, the records are arranged in a table with rows for each record and a column for each field in each record. The width of each column of repeated data is compressed to zero bits and the repeated data is referenced in a header of the segment. The width of each column of integer data is compressed to the minimum number of bits required to represent the largest integer value in the fields of the column. Floating point data in each column is converted to integer data and the width of the each column with converted integer data is set to the minimum width necessary to represent the largest converted integer in each column. The conversion to integer data is calculated for floating point and real numbers with a minimum precision exponent that is stored in the header for the segment.

Abstract: A facility for multidimensional, multilevel databases has a query syntax for specifying that aggregate-data cells representing higher levels of the database in a report include only the data from certain ones of the lower-level database items, rather than from all of them. A database engine extracts data from the lower-level query items from the database, and aggregates only the data from those items into one or more aggregate cells in accordance with a function named in the query.

Abstract: A method, apparatus, and software are disclosed for efficient estimation of the performance gain associated with using a set of proposed aggregations, or summaries of data, in a database. This estimate is used in selecting which aggregations are materialized in an OLAP system or relational database. The estimate is based on the minimum and maximum costs of executing a given set of queries, as well as the cost of executing the given set of queries using the set of proposed aggregations. By expressing the estimate as a unitless constant with known upper and lower limits, the system conveys information as to the performance gain in a form that is readily understood by the user.

Abstract: A method, apparatus, and software are disclosed for efficient selection of aggregations, or summaries of data in a database, for answering queries. Benefit/cost ratings are maintained for possible aggregations and are used in determining which aggregations should be selected. Lists of candidate and selected aggregations are also maintained, and aggregations are moved between these lists based on their benefit/cost ratings. These ratings are adjusted as aggregations are moved between the lists.