Abstract: In accordance with an embodiment, systems and methods can provide for load, aggregate, and batch calculation in in a multidimensional database environment. Metadata can be used to identify in which higher dimensions each leaf-level load is used. At such time, the data from the leaf level is aggregated to each of the higher dimensions where it is to be used. Then, the aggregate values are stored in memory until a completed sum (or other calculation) is completed at the higher levels. At such time, the aggregate values can be discarded from memory. The ability of the system to perform a load, aggregate, and batch calculation in one scan is particularly useful in processing very large sets of data, for example in big data environments, where it may not be desirable to load the data for all of the leaf nodes into current memory.

Abstract: In accordance with an embodiment, described herein are systems and methods for supporting slowly changing dimensions and metadata versioning in a multidimensional database, comprising. A system can comprise a computer that includes one or more microprocessors, and a multidimensional database server executing on the computer, wherein the multidimensional database server supports at least one hierarchical structure of data dimensions. A data dimension can slowly change over time. When such changes occur, metadata associated with the data dimension can be updated. Advantageously, a current snapshot of the data structure can allow searching of previous changes to the slowly changing dimension based upon the metadata.

Abstract: A system and method is described for use with a multidimensional database computing environment to provide support for parallel calculation of multidimensional slices. Users are able to specify a set of slices and a number of parallel threads to employ. The multidimensional database environment generates tasks that include calculations and/or aggregations, which are able to be executed by the system in parallel. Also described herein are mechanisms of utilizing variables within the calculations performed by respective threads, and combining thread variables after execution.

Abstract: In accordance with an embodiment, systems and methods can provide for load, aggregate, and batch calculation in a multidimensional database environment. Metadata can be used to identify in which higher dimensions each leaf-level load is used. At such time, the data from the leaf level is aggregated to each of the higher dimensions where it is to be used. Then, the aggregate values are stored in memory until a completed sum (or other calculation) is completed at the higher levels. At such time, the aggregate values can be discarded from memory. The ability of the system to perform a load, aggregate, and batch calculation in one scan is particularly useful in processing very large sets of data, for example in big data environments, where it may not be desirable to load the data for all of the leaf nodes into current memory.

Abstract: In accordance with an embodiment, described herein are systems and methods that enable client-side calculation with data provided at a multidimensional or other database server. Data provided at the server in accordance with a server-side model, can be transformed/prepared into a grid, for use with a client-side application, for example a client spreadsheet application. During preparation of the grid, one or more portions of the grid that are identified as client-side dynamic parameters, can be represented as dynamic formulas that are modifiable within the client-side application; while parameters of the server-side model that are outside of the grid can be represented as constant values. The grid provided to the client can be used to perform client-side calculations that allow for rapid calculations in response to changes in the client-side model, without introducing a round-trip performance lag between the client-side and server-side.

Abstract: In accordance with an embodiment, described herein are systems and methods for supporting slowly changing dimensions and metadata versioning in a multidimensional database, comprising. A system can comprise a computer that includes one or more microprocessors, and a multidimensional database server executing on the computer, wherein the multidimensional database server supports at least one hierarchical structure of data dimensions. A data dimension can slowly change over time. When such changes occur, metadata associated with the data dimension can be updated. Advantageously, a current snapshot of the data structure can allow searching of previous changes to the slowly changing dimension based upon the metadata.

Abstract: A system and method is described for use with a multidimensional database computing environment to provide support for parallel calculation of multidimensional slices. Users are able to specify a set of slices and a number of parallel threads to employ. The multidimensional database environment generates tasks that include calculations and/or aggregations, which are able to be executed by the system in parallel. Also described herein are mechanisms of utilizing variables within the calculations performed by respective threads, and combining thread variables after execution.

Abstract: In accordance with an embodiment, described herein are systems and methods that enable client-side calculation with data provided at a multidimensional or other database server. Data provided at the server in accordance with a server-side model, can be transformed/prepared into a grid, for use with a client-side application, for example a client spreadsheet application. During preparation of the grid, one or more portions of the grid that are identified as client-side dynamic parameters, can be represented as dynamic formulas that are modifiable within the client-side application; while parameters of the server-side model that are outside of the grid can be represented as constant values. The grid provided to the client can be used to perform client-side calculations that allow for rapid calculations in response to changes in the client-side model, without introducing a round-trip performance lag between the client-side and server-side.

Abstract: In accordance with an embodiment, described herein is a system and method for supporting queries having sub-select constructs in a multidimensional database computing environment. The system enables a sub-select construct to be provided as part of an input query, for example using a Multidimensional Expressions (MDX), or other type of query. The inner sub-select, specified by the input query, is not executed by the system before the main query, but is used to restrict the data space for execution of the main select. The approach to processing the sub-select enables support for security-sensitive or other types of aggregation use cases.

Abstract: In accordance with an embodiment, described herein is a system and method for use of a dynamic flow process (referred to herein in some examples as Query Processing Dynamic Flow (QPDF)) in a multidimensional database computing environment. The dynamic flow process enables hybrid use of, for example, aggregate storage option, block storage option, or other types of storage containers, and provides a common flow to process a received input query in bottom-up mode. The approach can be used to reduce the size of the cube, which provides for efficient calculation of dynamic members.

Abstract: In accordance with an embodiment, described herein is a system and method for supporting queries having sub-select constructs in a multidimensional database computing environment. The system enables a sub-select construct to be provided as part of an input query, for example using a Multidimensional Expressions (MDX), or other type of query. The inner sub-select, specified by the input query, is not executed by the system before the main query, but is used to restrict the data space for execution of the main select. The approach to processing the sub-select enables support for security-sensitive or other types of aggregation use cases.

Abstract: In accordance with an embodiment, described herein is a system and method for dependency analysis for a calculation script in a multidimensional database computing environment. A multidimensional database cube aggregation can be represented as a lattice of blocks or cube, arranged according to a database outline (e.g., intra-dimensional or member hierarchy). When the multidimensional database system performs computations in parallel for a given calculation script, portions of the cube that can be computed concurrently are identified.

Abstract: In accordance with an embodiment, described herein is a system and method for use of a dynamic flow process (referred to herein in some examples as Query Processing Dynamic Flow (QPDF)) in a multidimensional database computing environment. The dynamic flow process enables hybrid use of, for example, aggregate storage option, block storage option, or other types of storage containers, and provides a common flow to process a received input query in bottom-up mode. The approach can be used to reduce the size of the cube, which provides for efficient calculation of dynamic members.

Abstract: In accordance with an embodiment, described herein are systems and methods for real time data aggregation in a virtual cube in a multidimensional database, in accordance with an embodiment. A method can provide, at a computer that includes one or more microprocessors, a multidimensional database server executing on the computer, wherein the multidimensional database server supports at least one multidimensional cube, a data source associated with the multidimensional cube, and at least one source of real-time data accessible by the data source. The method can query, by the multidimensional cube, the data source, the query comprising an identification of the at least one source of real-time data. The method can provide, by the data source, on-demand access to the multidimensional cube to the at least one source of real-time data. The method can use targeted data from the at least one source of real-time data within the multidimensional cube without being stored therein.

Abstract: In accordance with an embodiment, described herein are systems and methods for automatic root cause analysis and generation of key metrics in a multidimensional database. A system can comprise a computer and a multidimensional database server executing on the computer, wherein the multidimensional database server supports at least one hierarchical structure of data dimensions. One or more one or more user logs are created, the one or must user logs representing a plurality of operations performed by a plurality of users of the multidimensional database server and accessing the at least one hierarchical structure of data dimensions. Based upon historical data of the at least one hierarchical structure of data dimensions, a change in a query result of a user is detected. Based upon the detection of a change, a set of data dimensions can be provided to the user that contains the data dimensions most contributing to the change.

Abstract: In accordance with an embodiment, described herein is a system and method for dependency analysis for a calculation script in a multidimensional database computing environment. A multidimensional database cube aggregation can be represented as a lattice of blocks or cube, arranged according to a database outline (e.g., intra-dimensional or member hierarchy). When the multidimensional database system performs computations in parallel for a given calculation script, portions of the cube that can be computed concurrently are identified.

Abstract: In accordance with an embodiment, described herein is a system and method for improving performance within a multidimensional database computing environment. A multidimensional database, utilizing a block storage option, performs numerous input/output (I/O) operations when executing calculations. To separate I/O operations from calculations, a background task queue is created to identify data blocks requiring I/O. The background task queue is utilized by background writer threads to execute the I/O operations in parallel with calculations.

Abstract: A system and method is described for use with a multidimensional database computing environment to provide support for parallel calculation of multidimensional slices. Users are able to specify a set of slices and a number of parallel threads to employ. The multidimensional database environment generates tasks that include calculations and/or aggregations, which are able to be executed by the system in parallel. Also described herein are mechanisms of utilizing variables within the calculations performed by respective threads, and combining thread variables after execution.

Abstract: In accordance with an embodiment, described herein is a system and method for improving performance within a multidimensional database computing environment. A multidimensional database, utilizing a block storage option, performs numerous input/output (I/O) operations when executing calculations. To separate I/O operations from calculations, a background task queue is created to identify data blocks requiring I/O. The background task queue is utilized by background writer threads to execute the I/O operations in parallel with calculations.

Abstract: A system and method is described for use with a multidimensional database computing environment to provide support for parallel calculation of multidimensional slices. Users are able to specify a set of slices and a number of parallel threads to employ. The multidimensional database environment generates tasks that include calculations and/or aggregations, which are able to be executed by the system in parallel. Also described herein are mechanisms of utilizing variables within the calculations performed by respective threads, and combining thread variables after execution.