Data processing systems and methods

• US 20050289129A1
• Filed: 06/17/2005
• Published: 12/29/2005
• Est. Priority Date: 06/23/2004
• Status: Active Grant

• Current Assignee: SAP SE
• Original Assignee: SAP AG (SAP SE)
• Inventors: Schmitt, Winfried
• Granted Patent: US 7,743,015 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G06F 16/283 Multi-dimensional databases or data warehouses, e.g. MOLAP or ROLAP

Abstract

Data processing systems and methods are provided having an on-line transaction processing (OLTP) database and an on-line analysis processing (OLAP) database. The OLAP and OLTP databases are synchronized periodically, e.g., during the night. In response to a user'"'"'s query, OLAP cube data that is available in the OLAP database is complimented with data from the OLTP database for inclusion of up-to-date data into the on-line analysis processing.

Claims

1. A data processing system, comprising:

a relational database for storage of transaction data;

an OLAP database for storage of a replication of the transaction data in an OLAP cube;

means for storing data indicative of a replication time;

a random access memory;

means for receiving a data request, the data request specifying at least a first time interval;

means for reading OLAP cube data from the OLAP cube;

means for storing the OLAP cube data in the random access memory;

means for determining the replication time using the data indicative of the replication time;

means for generating a query for the relational database specifying a second time interval, the second time interval having a lower limit given by the replication time and an upper limit given by the upper limit of the first time interval;

means for receiving replication data from the relational database in response to the query;

means for storing the replication data in the random access memory; and

means for generating an output using the OLAP cube data and the replication data stored in the random access memory.

2. The data processing system of claim 1, wherein the relational database is an OLTP database.

3. The data processing system of claim 1, wherein the OLAP database includes a plurality of OLAP cubes and structural cube definition data for each of the plurality of such OLAP cubes, wherein the data request specifies one of the OLAP cubes and the system further comprises means for using the structural cube definition data of the specified OLAP cube for generating the query.

4. The data processing system of claim 1, wherein the query comprises an SQL statement corresponding to the structural cube definition data of the specified OLAP cube.

5. The data processing system of claim 1, further comprising a time reference, wherein the data indicative of the replication time specifies a replication time scheme, such that the replication time is determined by the replication time scheme and the actual time provided by the time reference when the data request is received.

6. The data processing system of claim 1, wherein the output is a data table.

7. A computerized data processing method, comprising:

receiving a data request, the data request specifying at least a first time interval;

reading OLAP cube data from an OLAP cube of an OLAP database storing a replication of transaction data;

storing the OLAP cube data in a random access memory;

determining a replication time;

electronically generating a query for a relational database storing up-to-date transaction data, the query specifying a second time interval, the second time interval having a lower limit given by the replication time and an upper limit given by the upper limit of the first time interval;

electronically receiving replication data from the relational database in response to the query;

storing the replication data in the random access memory; and

generating an output as a response to the data request using the OLAP cube data and the replication data stored in the random access memory.

8. The method of claim 7, wherein the relational database is an OLTP database that is coupled to a transaction data source.

9. The data processing method of claim 7, wherein the OLAP database includes a plurality of OLAP cubes and structural cube definition data for each such OLAP cube, and further comprises specifying one of the OLAP cubes in the data request, wherein the query is generated using the structural cube definition data of the specified OLAP cube.

10. The data processing method of claim 7, further comprising reading an actual time from a time reference and determining the replication time using the actual time and a replication time scheme.

11. The data processing method of claim 10, wherein the replication scheme is stored as part of customizing data.

12. A computer program product, comprising computer executable instructions for performing a method, the method comprising the steps of:

receiving a data request, the data request specifying at least a first time interval;

reading OLAP cube data from an OLAP cube of an OLAP database storing a replication of transaction data;

storing the OLAP cube data in a random access memory;

determining a replication time;

electronically generating a query for a relational database storing up-to-date transaction data, the query specifying a second time interval, the second time interval having a lower limit given by the replication time and an upper limit given by the upper limit of the first time interval;

electronically receiving replication data from the relational database in response to the query;

storing the replication data in the random access memory; and

generating an output as a response to the data request using the OLAP cube data and the replication data stored in the random access memory.

13. The computer program product of claim 12, wherein the OLAP database includes a plurality of OLAP cubes and structural cube definition data for each such OLAP cube, and one of the OLAP cubes being specified in the data request, and further comprising instructions for generating the query using the structural cube definition data of the specified OLAP cube.

14. The computer program product of claim 12, further comprising instructions for reading an actual time from a time reference and determining the replication time using the actual time and a replication time scheme.

15. A computerized data processing method, comprising:

receiving a data request, the data request specifying at least a first period;

reading OLAP cube data from an OLAP cube of an OLAP database storing a replication of transaction data;

storing the OLAP cube data in a random access memory;

determining a replication time;

electronically generating a query for a relational database storing up-to-date transaction data, the query specifying a second period, the second period having a lower limit given by the replication time and an upper limit given by the upper limit of the first period;

electronically receiving replication data from the relational database in response to the query;

storing the replication data in the random access memory; and

generating an output as a response to the data request using the OLAP cube data and the replication data stored in the random access memory.

16. The method of claim 15, wherein the relational database is an OLTP database that is coupled to a transaction data source.

17. The data processing method of claim 15, wherein the OLAP database includes a plurality of OLAP cubes and structural cube definition data for each such OLAP cube, and further comprises specifying one of the OLAP cubes in the data request, wherein the query is generated using the structural cube definition data of the specified OLAP cube.

18. The data processing method of claim 15, further comprising reading an actual time from a time reference and determining the replication time using the actual time and a replication time scheme.

19. The data processing method of claim 18, wherein the replication scheme is stored as part of customizing data.

20. The data processing method of claim 15, wherein the data request comprises at least one of a specified time or specified period.