US2008016057A1PendingUtilityA1

Data aggregation server for managing a multi-dimensional database and database management system having data aggregation server integrated therein

Assignee: BAKALASH REUVEPriority: Feb 28, 2000Filed: Jul 6, 2007Published: Jan 17, 2008
Est. expiryFeb 28, 2020(expired)· nominal 20-yr term from priority
Y10S707/99935G06F 16/283G06F 16/2455Y10S707/954G06F 16/24556Y10S707/99932G06F 16/24539Y10S707/99934Y10S707/99943Y10S707/957G06F 16/30
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Claims

Abstract

Improved method of and apparatus for aggregating data elements in multidimensional databases (MDDB). In one aspect of the present invention, the apparatus is realized in he form of a high-performance stand-alone (i.e. external) aggregation server which can be plugged-into conventional OLAP systems to achieve significant improvements in system performance. In accordance with the principles of the present invention, the stand-alone aggregation server contains a scalable MDDB and a high-performance aggregation engine that are integrated into the modular architecture of the aggregation server. The stand-alone aggregation server of the present invention can uniformly distribute data elements among a plurality of processors, for balanced loading and processing, and therefore is highly scalable. The stand-alone aggregation server of the present invention can be used to realize (i) and improved MDDB for supporting on-line analytical processing (OLAP) operations, (ii) an improved Internet URL Directory for supporting on-line information searching operations by Web-enabled client machines, as well as (iii) diverse types of MDDB-based systems for supporting real-time control of processes in response to complex states of information reflected in the MDDB. In another aspect of the present invention, the apparatus is integrated within a database management system (DBMS). The improved DBMS can be used to realize achieving a significant increase in system performance (e.g. decreased access/search time), user flexibility and ease of use. The improved DBMS system of the present invention can be used to realize an improved Data Warehouse for supporting on-line analytical processing (OLAP) operations or to realize an improved information database system, operational database system, or the like.

Claims

exact text as granted — not AI-modified
1 . A relational database management system (RDBMS) for supporting online analytical processing (OLAP) conducted through one or more client machines, said RDBMS comprising: 
 (A) a query servicing mechanism including    (1) a RDBMS query interface adapted to receive query statements from said one or more client machines;    (2) a RDBMS query handler operably coupled to said RDBMS query interface; and    (3) a RDBMS query processing mechanism for processing each query statement received from said RDBMS query interface, and generating a series of query requests by disintegrating the query statement via parsing, so that each said query request specifies a set of dimensions;    (B) relational tables for storing fact data, and a meta-data store for storing a dictionary containing dimension data, and a support mechanism for supporting said relational tables and said meta-data store;    (C) a multi-dimensional data (MDD) aggregation module integrated within said RDBMS, and including    (1) a multi-dimensional database (MDDB) for storing aggregated fact data;    (2) a data loader, in data communication with said support mechanism by way of a first data communication interface, for loading said meta-data and said fact data into said MDD aggregation module;    (3) an aggregation engine for receiving fact data from said data loader, and calculating aggregated multi-dimensional data from the fact data according to a multi-dimensional data aggregation process;    (4) a data handler for storing aggregated multi-dimensional data in said MDDB and retrieving aggregated multi-dimensional data from said MDDB;    (5) a MDDB query handler operably coupled to a second data communication interface, for (i) receiving each query request from said RDBMS query handler, (ii) extracting a set of dimensions associated with said query request, (iii) providing said dimensions as multi-dimensional coordinates to said data handler so that (i) said data handler can retrieve aggregated multi-dimensional data from said MDDB specified by said multi-dimensional coordinates, and/or (ii) said aggregation engine can dynamically generate, on demand, aggregated multi-dimensional data, and (iv) forwarding retrieved aggregated multi-dimensional data to said RDBMS query processing mechanism for subsequent processing, if needed; and    wherein when said RDBMS query handler receives a given query statement from said RDBMS query interface, and said RDBMS query processing mechanism determines that servicing of the given query statement requires data stored in said relational tables, then said RDBMS query processing mechanism automatically routes one or more query requests to said relational data tables, so that the support mechanism can access data from said relational tables and forward the accessed data to said RDBMS query processing mechanism for use in servicing the given query statement, in a manner transparent to said client machine; and    wherein when said RDBMS query handler receives a given query statement from said RDBMS query interface, and said RDBMS query processing mechanism determines that servicing of the given query statement requires aggregated data stored in said MDDB, then said RDBMS query processing mechanism automatically routes one or more query requests to said MDDB query handler, so that said data handler can access aggregated data stored in said MDDB, and then forward the aggregated data to said RDBMS query processing mechanism for use in servicing the given query statement, in a manner transparent to said client machine.    
     
     
         2 . The RDBMS of  claim 1 , wherein after data loading operations, the fact data is initially aggregated along at least one of the dimensions extracted from said dictionary and aggregated multi-dimensional data results are stored in said MDDB, and 
 wherein during query servicing operations, the fact data is aggregated on demand along additional dimensions extracted from said query request and aggregated multi-dimensional data results are stored in said MDDB.    
     
     
         3 . The RDBMS of  claim 1 , wherein said MDDB comprises a non-relational type of multi-dimensional data storage structure.  
     
     
         4 . The RDBMS of  claim 3 , wherein said non-relational type of multi-dimensional data storage structure comprises a plurality of data storage cells, and wherein each said data storage cell is indexed with multiple dimensions and stores either a base data value or an aggregated multi-dimensional data value.  
     
     
         5 . The RDBMS of  claim 3 , wherein during data loading operations, said data loader extracts dimension data from the dictionary in said meta-data store, and forwards the dimension data over said first data communication interface to said aggregation engine and configures said MDDB using said dimension data.  
     
     
         6 . The RDBMS of claim  154 , wherein during aggregation operations, said data loader extracts fact data from said relational tables, and forwards the fact data to said aggregation engine over said first data communication interface; and wherein said aggregation engine calculates aggregated multi-dimensional data from the fact data according to said multi-dimensional data aggregation process, and stores the aggregated multi-dimensional data in said MDDB specified by a set of multi-dimensional coordinates.  
     
     
         7 . The RDBMS of  claim 1 , wherein said MDD aggregation module further comprises a control module for managing the operation of said data loader, said aggregation engine, said data handler and said MDDB query handler.  
     
     
         8 . The RDBMS of  claim 1 , wherein said query statement is an SQL-type query statement and each query request is an SQL-type query request.  
     
     
         9 . The RDBMS of  claim 1 , wherein said first data communication interface is a standard interface elected from the group selected from OLDB, OLE-DB, ODBC, SQL, API, and JDBC.  
     
     
         10 . The RDBMS of  claim 1 , wherein said second data communication interface is a standard interface selected from the group selected from OLDB, OLE-DB, ODBC, SQL, API, and JDBC.  
     
     
         11 . The RDBMS of  claim 1 , wherein said RDBMS query interface is implemented in a module within said RDBMS.  
     
     
         12 . The RDBMS of  claim 1 , wherein a user interacts with said client machine using a web-enabled browser to generate a natural language type query statement, and said natural language type query statement is communicated to said RDBMS query interface.  
     
     
         13 . The RDBMS of  claim 1 , wherein said MDDB query handler further includes means for transforming each query request so as to optimize the query request for efficient query handling.  
     
     
         14 . The RDBMS of  claim 1 , wherein said MDDB query handler further includes an adapter for mapping the data types of the query statement issued by said RDBMS query handler, and/or for mapping a standard data type used to represent the query request issued by said RDBMS query handler into the data types used in said MDD aggregation module.  
     
     
         15 . The RDBMS of  claim 1 , wherein said multi-dimensional aggregation process supported by said aggregation engine further operates as follows: 
 (a) if the aggregated multi-dimensional data required to service a given query statement is already pre-calculated and stored within said MDDB, then the pre-aggregated multi-dimensional data is retrieved by said data handler and returned to said client machine via said RDBMS query handler; and    (b) if the required multi-dimensional data is not already pre-aggregated and stored within said MDDB, then the required aggregated multi-dimensional data is calculated on demand by said aggregation engine, and the aggregated multi-dimensional data result is automatically forwarded to said client machine, via said RDBMS query processing mechanism, while being simultaneously stored within said MDDB by said data handler.    
     
     
         16 . The RDBMS of  claim 1 , wherein said MDD aggregation module is a cartridge-style data aggregation module, in which said first and second data communication interfaces are standard interfaces enabling cartridge-style interfacing of said MDD aggregation module within said RDBMS.

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