Time series data management
View Patent ↗Methods and apparatus, including computer program products, are provided for storing data in a database. The data, whose structures are configurable, may comprise a time series, the time series comprising a set of key figure values of individual time periods, the key figure values being associated with a combination of parameter values, wherein the set of key figure values is organized in a number of configurable clusters.
1. A computer-readable storage medium comprising program code, which when executed on a processor causes the processor to perform a method, the method comprising:
storing data in a database designed for supply chain management and planning scenarios, wherein the data, whose structures are configurable, comprise of a time series;
providing a set of key figure values, each key figure value in the set of key figure values being associated with an individual time period, wherein the time series comprises two or more consecutive individual time periods; and
associating the set of the key figure values with a combination of parameter values,
wherein the set of key figure values is organized and stored in a number of configurable clusters based on the association of the key figure values and the individual time periods in the time series, a size of a configurable cluster being based on either (i) a number of key figure values in the set of key figure values in each entry in a database table within the database or (ii) a semantic relation between the individual time periods and a cluster time period.
2. The method of claim 1 , wherein values for several time periods are stored into adjacent fields of one entry.
3. The method of claim 1 , wherein the numbers of individual time periods are selected according to semantic criteria.
4. The method of claim 3 , wherein the clusters are configured according to time aggregates, each time aggregate comprising a number of the individual time periods, respectively.
5. The method of claim 4 , wherein the numbers of individual time periods are selected according to numeric criteria.
6. The method of claim 1 , wherein each time period has the same fixed length.
7. The method of claim 1 , wherein each time period can be individually described by begin and end time.
8. The method of claim 1 , wherein data which is related to each other is placed at the same location.
9. The method of claim 1 , wherein the time series data is partitioned across a plurality of areas, each time series data area comprising a set of tables useful for managing a partition of the data.
10. The method of claim 1 further comprising storing pointers to predefined documents from a document management service in relation to the time series.
11. The method of claim 1 , wherein a change to the set of the key figure values is logged in a predefined table.
12. The method of claim 11 , wherein the tables are organized in a number of configurable clusters, and are partitioned across a plurality of areas.
13. A computer-readable storage medium comprising instructions, which when executed on a processor cause the processor to store a configurable database structure used to design supply chain management and planning scenarios, the database structure comprising:
time series data,
wherein the time series data comprises a set of key figure values, each key figure value in the set of key figure values being associated with an individual time period and the time series further comprising two or more consecutive individual time periods,
wherein the set of the key figure values are associated with a combination of parameter values, and
wherein the set of key figure values is organized and stored in a number of configurable clusters based on the association of key figure values and the individual time periods in the time series, a size of a configurable cluster being based on either (i) a number of key figure values in the set of key figure values in each entry in a database table within the database structure or (ii) a semantic relation between the individual time periods and a cluster time period.
14. The computer-readable storage medium of claim 13 , wherein values for several time periods are stored into adjacent fields of one entry.
15. The computer-readable storage medium of claim 13 , wherein the numbers of individual time periods are selected according to semantic criteria.
16. The computer-readable storage medium of claim 15 , wherein the clusters are configured according to time aggregates, each time aggregate comprising a number of the individual time periods, respectively.
17. The computer-readable storage medium of claim 16 , wherein the numbers of individual time periods are selected according to numeric criteria.
18. The computer-readable storage medium of claim 13 , wherein each time period has the same fixed length.
19. The computer-readable storage medium of claim 13 , wherein each time period can be individually described by begin and end time.
20. The computer-readable storage medium of claim 13 , wherein data which is related to each other is placed at the same location.
21. The computer-readable storage medium of claim 13 , wherein the time series data is partitioned across a plurality of areas, each time series data area comprising a set of tables useful for managing a partition of the data.
22. The computer-readable storage medium of claim 13 further comprising pointers to predefined documents from a document management service in relation to the time series data.
23. The computer-readable storage medium of claim 13 , wherein a change to the set of the key figure values is logged in a predefined table.
24. The computer-readable storage medium of claim 23 , wherein the tables are organized in a number of configurable clusters, and are partitioned across a plurality of areas.