An architecture and methodology for designing, deploying, and managing a distributed application onto a distributed computing system is described.

Architecture for distributed computing system and automated design, deployment, and management of distributed applications

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.

Mapping of an RDBMS schema onto a multidimensional data model

In a first exemplary media implementation, one or more processor-accessible media include processor-executable instructions that, when executed, direct a system to perform actions that include: accumulating host status information at multiple hosts; and sending the accumulated host status information from the multiple hosts In a second exemplary media implementation, one or more processor-accessible media include processor-executable instructions that, when executed, direct a system to perform actions that include: receiving host status information from multiple hosts; and making load balancing decisions responsive to the received host status information In a third exemplary media implementation, one or more processor-accessible media include processor-executable instructions that, when executed, direct a system to perform actions that include: determining health and load information on a per application basis; and selecting an application from among multiple applications responsive to the health and load information

Network load balancing with host status information

In an exemplary method implementation, a method includes: receiving a packet requesting a new connection at a forwarding component; sending the packet from the forwarding component to a classifying component; selecting, by the classifying component, a route for the new connection; and plumbing, by the classifying component, the route for the new connection by causing a new entry to be added in a local routing table of the forwarding component. In an exemplary media implementation, one or more processor-accessible media include processor-executable instructions that, when executed, enable a system to perform actions including: receiving a first packet for a connection at first forwarding functionality; plumbing a route for the connection at the first forwarding functionality; receiving a second packet for the connection at second forwarding functionality; and plumbing the route for the connection at the second forwarding functionality using a distributed session tracking table.

Network load balancing with traffic routing

In a first exemplary implementation, one or more processor-accessible media include processor-executable instructions that, when executed, direct a system to perform actions including: receiving host status information from multiple hosts; and making load balancing decisions responsive to the received host status information. In a second exemplary implementation, a system includes: session tracking infrastructure that is adapted to acquire session information; and load balancing infrastructure that is adapted to utilize the session information when routing connection requests to multiple hosts. In a third exemplary implementation, one or more processor-accessible media include processor-executable instructions that, when executed, direct a system to perform actions including: acquiring session information for multiple session contexts from one or more applications that established the multiple session contexts; and routing network traffic to the one or more applications responsive to the acquired session information.

Network load balancing with session information

An enterprise business planning system includes a database having a relational data area and a transactional data area, and a server to store within the transactional data area contribution data received from a set of enterprise contributors. The server publishes the contribution data from the transactional data area to the relational data area. The transactional data area may include a set of contribution slots and a set of aggregations slots hierarchically related on accordance with an enterprise model. The relational area includes a set of related tables defined in accordance with the enterprise contributors, while the relational date area allows detailed statistical analysis and report generation.

Real-time aggregation of data within an enterprise planning environment

An enterprise planning system includes a plurality of application servers, and an administration console to generate a deployment map that associates each of a set of enterprise planning models with a respective set of the application servers. The administration console, either automatically or in response to input from a system administrator, may finely control the allocation of computing resources to enterprise planning. The administrator console may adjust the deployment map based on approaching deadlines for the enterprise planning activities. When administrating a task associated with an enterprise planning activity, the administration console may break the task into a number of jobs, each job associated with a different slice of the model in accordance with the organizational hierarchy defined by the model. Consequently, allocation of computing resources to enterprise planning may be finely controlled, and may be adjusted to meet the current needs within the organizational hierarchy.

Deploying multiple enterprise planning models across clusters of applications servers

An enterprise planning and performance management system provides a variable-based modeling technique that enables users to interact with a more manageable variable-centric front-end for complex enterprise planning software. The system enables users to specify a plurality of variable definitions via a variable-based user interface. Based on the plurality of variable definitions, the system generates, and in some instances automatically generates, model data that defines an enterprise planning model. The system uses the model data during subsequent enterprise planning sessions. Because model builders typically comprise financial analysts unfamiliar with traditional complex enterprise modeling techniques but familiar with common financial variables of an enterprise, this variable-based modeling technique may facilitate easier model building by allowing these financial analysts to generate model data from the perspective of the more readily understood variables.

Enterprise performance management software system having variable-based modeling

An enterprise business planning system includes a database having a relational data area and a transactional data area, and a server to store within the transactional data area contribution data received from a set of enterprise contributors. The server publishes the contribution data from the transactional data area to the relational data area. The transactional data area may include a set of contribution slots and a set of aggregations slots hierarchically related in accordance with an enterprise model. The relational area includes a set of related tables defined in accordance with the model. The transactional data area supports real-time interaction with the enterprise contributors, while the relational data area allows detailed statistical analysis and report generation.

George Duncan Pearson

Papers

Real-time aggregation of data within an enterprise planning environment

Deploying multiple enterprise planning models across clusters of applications servers

Enterprise performance management software system having variable-based modeling

Real-time aggregation of data within a transactional data area of an enterprise planning environment