CLUSTER PROCESSING OF AN AGGREGATED DATASET

• US 20090006309A1
• Filed: 01/31/2008
• Published: 01/01/2009
• Est. Priority Date: 01/26/2007
• Status: Abandoned Application

• Current Assignee: Symphonyiri Group Incorporated (New Mountain Capital Group LLC)
• Original Assignee: Symphonyiri Group Incorporated (New Mountain Capital Group LLC)
• Inventors: Johnson, Arvid C., Bergeon, Cheryl G., Hudson, Gregory David Neil, Basilico, Andrea, Gibbs, Marshall Ashby, Chapa, Craig Joseph, Yusko, Jay Alan, Griglione, Bradley Michael, Mason, Trevor, Hunt, Herbert Dennis, Liu, Ting, Agostinelli, Alberto, West, John Randall
• Application Number:
  US12/023,267
• Publication Number:
  US 20090006309A1
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G06F 16/2453 Query optimisation
• CPC Class Codes: G06F 16/24556 Aggregation; Duplicate elimination
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising

Abstract

Systems and methods are presented that may involve receiving a aggregated dataset, wherein the aggregated dataset includes data from a panel data source, a fact data source, and a dimension data source that have been associated with a standard population database. The process may also involve storing the aggregated data in a partition within a partitioned database, wherein the partition is associated with a data characteristic. The process may also involve associating a master processing node with a plurality of slave nodes, wherein each of the plurality of slave nodes is associated with a partition of the partitioned database. The process may also involve submitting an analytic query to the master processing node. The process may also involve assigning analytic processing to at least one of the plurality of slave nodes by the master processing node, wherein the assignment is based at least in part on the association of the partition with the data characteristic. The process may also involve reading the aggregated data from the partitioned database by the assigned slave node. The process may also involve analyzing the aggregated data by the assigned slave node, wherein the analysis produces a result at each slave node. The process may also involve combining the results from each of the plurality of slave nodes by the master processing node into a master result and reporting the master result to a user interface.

Claims

1. A method comprising:

receiving an aggregated dataset, wherein the aggregated dataset includes data from a panel data source, a fact data source, and a dimension data source that have been associated with a standard population database;

storing the aggregated data in a partition within a partitioned database, wherein the partition is associated with a data characteristic;

associating a master processing node with a plurality of slave nodes, wherein each of the plurality of slave nodes is associated with a partition of the partitioned database;

submitting an analytic query to the master processing node;

assigning analytic processing to at least one of the plurality of slave nodes by the master processing node, wherein the assignment is based at least in part on the association of the partition with the data characteristic; and

reading the aggregated data from the partitioned database by the assigned slave node;

analyzing the aggregated data by the assigned slave node, wherein the analysis produces a result at each slave node;

combining the results from each of the plurality of slave nodes by the master processing node into a master result; and

reporting the master result to a user interface.