Microsoft Technology Licensing, LLC

Alexander Berger

Mosha Pasumansky

Amir Netz

Cristian Petculescu

Marius Dumitru

Richard R Tkachuk

Irina Gorbach

Akshai Mirchandani

Thomas P Conlon

Paul Jonathon Sanders

Edward Melomed

Thulusalamatom Krishnamurthi Anand

Thomas Hargrove

C James MacLennan

Ioan Bogdan Crivat

Raman S Iyer

Alexander Gourkov Balikov

Rong Jian Guan

Thierry D'Hers

Adrian Dumitrascu

Grzegorz Guzik

Sergei Gringauze

Cristian Petrulescu

Dmitry Berger

Christian Petculescu

Systems and methods for generating distributed dataflow graphs and processing data elements in parallel utilizing the distributed dataflow graphs are provided. A sequential dataflow graph is formed from incoming data elements, and a variety of heuristics is applied to the sequential dataflow graph to determine which of the data transformation steps within the graph are capable of being processed multiple times in parallel. Once determined, the sequential dataflow graph is divided into subgraphs, which are then replicated, e.g., based on available resources and.or external constraints. The resulting subgraphs are connected, based on the semantics of each vertex, and a distributed dataflow graph is generated, which can efficiently process data elements, for instance, for data warehousing and the like.

Generating distributed dataflow graphs

Computer-readable media, systems, and methods for building a multidimensional data cube having one or more high-cardinality attributes are described. In embodiments, data is extracted from one or more databases. It is determined that one or more instances of the data are fact data and one or more instances of the data are dimension data. Each member of the fact data is one instance of a dimension and each instance of the dimension data includes an attribute for grouping the fact data. Moreover, in embodiments it is determined that one or more instances of the dimension data are high-cardinality attributes. The one or more high-cardinality attributes are processed with fact data and stored in fact tables on a computer storage medium.

Multidimensional data cubes with high-cardinality attributes

Systems and method for creating multidimensional data cubes containing data domains for analyzing large amounts of data are provided. Data domains may be included in the major object of a multidimensional data cube. Further embodiments of the present invention provide methods for querying multidimensional data cubes having data domains. Embodiments of the present invention provide for defining data domains by any object in the major object model and for defining parent and child data domains.

Data domains in multidimensional databases

The subject invention pertains to the integration of an object model and a multidimensional database query language such as MDX. In particular, multidimensional declarative query language entities can be exposed through objects in an object model. The object model enables generation and employment of procedural language functions, routines, or procedures that interact with multidimensional database data. This effectively provides an extension for multidimensional query languages. For example, procedures can be stored and invoked from a declarative language query. Furthermore, the object model disclosed herein can expose a context object to enable conditional procedures based on the context of execution.

Multidimensional database query extension systems and methods

Provided are systems and methods that facilitate direct write back in a multi-dimensional database. The system includes a delta cache component that receives a user request to change an original cell value and determines a delta value based at least in part upon the changed cell value. Also included is a write back partition component that selectively updates a data cell based at least in part upon the delta value without updating corresponding data cell values. The system and methods allow attributes to be added to any dimension of a cube without affecting the write back data. Adding, modifying or removing a hierarchy has no affect on write back data nor does deleting a dimension that is not referenced by a write back.

Direct write back systems and methodologies

A system, method, and related techniques are disclosed for processing data across a distributed network to a plurality of machines. The method may include receiving a first user-supplied transform and generating a first package based on the first user-supplied transform. The method may further include receiving a designated key and generating a second package based on the key. Furthermore, the method may include receiving a second user-supplied transform and generating a third package based on the second user-supplied transform. Moreover, the method may include distributing the first, second, and third packages to a plurality of machines using a cluster API.

Processing data across a distributed network

The subject invention pertains to systems and methods for interacting with fact dimensions. In particular, systems and methods are disclosed that optimize performance and scalability with respect to processing queries that involve fact dimensions. Furthermore, queries involving fact dimensions can be evaluated in distinct manners. For instance, queries can be processed such that regular dimensions restrict the scope of the data and only fact dimension members that are relevant to that scope are exposed.

Fact dimensions in multidimensional databases

A simple interface may be provided that enables the user to define parameters for aggregation of a semi-additive measure. The interface may enable the user to designate a measure as a semi-additive measure and to pair the measure with an additive aggregation function. The interface may also enable the user to select non-additive dimensions and to pair each non-additive dimension with a corresponding aggregation function. One such aggregation function is a by account aggregation function, which enables each account in an account dimension to be aggregated across a corresponding non-additive dimension according to an associated account type.

System and method for aggregating a measure over a non-additive account dimension

The subject invention relates to systems and methods that extend the network data access capabilities of mark-up language protocols. In one aspect, a network data transfer system is provided. The system includes a protocol component that employs a computerized mark-up language to facilitate data interactions between network components, whereby the data interactions were previously limited or based on a statement command associated with the markup language. An extension component operates with the protocol component to support the data transactions, where the extension component supplies at least one other command from the statement command to facilitate the data interactions.

Systems and methods of utilizing and expanding standard protocol

A system that facilitates analyzing content of a multi-dimensional structure comprises a calculation component that receives statements in a declarative language relating to one or more of an assignment and calculation and executes such statements against a multi-dimensional structure. A pass generation component creates a pass in order to maintain content of the multi-dimensional structure as it existed prior to execution of the statement, the pass is accessible upon reference to such pass.

System that facilitates database querying

A system that facilitates one or more of querying and updating a multi-dimensional structure comprises a component that receives a statement in a declarative language relating to a typed object associated with a multi-dimensional structure. A conversion component analyzes context associated with the statement and automatically converts the object to a disparate type as a function of the analysis. For example, an execution engine can comprise the conversion component, and the execution engine can be an Online Analytical Processing (OLAP) engine.

Database query tools

The ability to link dimensions and measure groups in one analysis database to a second database is provided. This feature enables the use of the dimension or measure group without physically creating and managing the contents of the cube so defined.

Linked dimension and measure groups

A data model for accessing data in a relational database in an OLAP system utilizes a multiple-hierarchy dimension. The dimension includes a set of attributes. Each attribute is bound to a column in the relational database. A logical structure is defined, indicating the relationships between the attributes. Hierarchies are defined. Each hierarchy includes a sequence of attributes. A hierarchy provides a common drill-down path that a database user can utilize to access the database. A hierarchy can include a single attribute or a combination of attributes. Both the relationships between the attributes and the sequence of attributes in a hierarchy are defined independent of any restrictions associated with the database.

System and method for online analytical processing using dimension attributes and multiple hierarchies where first hierarchy has at least one attribute from the defined dimension not present in the second hierarchy

Custom grouping for dimension members of an On-Line Analytical Processing (OLAP) cube is facilitated by an interface component that receives a grouping from a user. A modification component alters an attribute of a session OLAP data cube or a virtual OLAP multi-dimensional data cube so that the change becomes readily available without the time-consuming delay associated with rebuilding or reprocessing the underlying structure. A data scheme generation component produces a data definition language (DDL) definition of a user defined attribute executed by an execution component to affect the change to a data cube. Custom groupings can provide an intermediate dimension level for drill down and/or drill up or roll-up between a level with few members and a level with numerous members. A separate dimensional attribute or level can be created and a group defined comprising or mapping a set or collection of discrete members.

Custom grouping for dimension members

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.

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Sammamish, WA, United States of America

Alexander Berger