Database Calculation Engine With Nested Multiprovider Merging

• US 20160350374A1
• Filed: 05/27/2015
• Published: 12/01/2016
• Est. Priority Date: 05/27/2015
• Status: Active Grant

• Current Assignee: SAP SE
• Original Assignee: SAP SE
• Inventors: Weyerhaeuser, Christoph, Mindnich, Tobias, Merx, Johannes, Schwing, Julian, Patejdl, Daniel, Pekel, Isil
• Granted Patent: US 10,324,930 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G06F 16/24544 Join order optimisation
• CPC Class Codes: G06F 16/278 Data partitioning, e.g. horizontal or vertical partitioning
• CPC Class Codes: G06F 16/285 Clustering or classification

Abstract

A query is received by a database server from a remote application server that is associated with a calculation scenario that defines a data flow model including one or more calculation nodes including stacked multiproviders. Subsequently, the database server instantiates the calculation scenario and afterwards optimizes the calculation scenario. As part of the optimization, the calculation scenario is optimized by merging the two multiproviders. Thereafter, the operations defined by the calculation nodes of the optimized calculation scenario can be executed to result in a responsive data set. Next, the data set is provided to the application server by the database server.

Claims

1. A method comprising:

receiving, by a database server from a remote application server, a query that is associated with a calculation scenario that defines a data flow model that includes one or more calculation nodes arranged in a hierarchy, the data flow initially specifying two or more stacked multiproviders that each respectively have two or more associated part providers, the uppermost multiprovider being a root multiprovider and each child multiprovider being a sub multiprovider;

instantiating and optimizing, by the database server, the calculation scenario, the optimizing comprising merging at least one sub multiprovider with the root multiprovider;

executing, by the database server, the operations defined by the calculation nodes of the optimized calculation scenario to result in a responsive data set; and

providing, by the database server to the application server, the data set.

2. The method of claim 1, wherein the merging comprises combining attributes specifying the at least one sub multiprovider and at least one part provider with attributes of the root multiprovider.

3. The method of claim 1, wherein the merging comprises adding each part provider of each sub multiprovider to the root multiprovider.

4. The method of claim 1, wherein the merging comprises:

summing up all count key figures of the at least one sub multiprovider at the root multiprovider.

5. The method of claim 4, wherein the summing comprising:

mapping count key figures on the at least one sub multiprovider to sum key figures on the root multiprovider and summing up all count key figures using a calculated attribute.

6. The method of claim 1, wherein there are a plurality of sub multiproviders and the mapping comprises:

determining which of the plurality of sub multiproviders can be merged and which of the sub multiproviders cannot be merged such that only the sub multiproviders determined to be mergeable are merged with the root multiprovider.

7. The method of claim 1, wherein at least a portion of paths and/or attributes defined by the calculation scenario are not required to respond to the query, and wherein the instantiated calculation scenario omits the paths and attributes defined by the calculation scenario that are not required to respond to the query.

8. The method of claim 1, wherein at least one of the calculation nodes filters results obtained from the database server.

9. The method of claim 1, wherein at least one of the calculation nodes sorts results obtained from the database server.

10. The method of claim 1, wherein the calculation scenario is instantiated in a calculation engine layer by a calculation engine.

11. The method of claim 1, wherein the calculation scenario is optimized in a calculation engine layer by a calculation engine.

12. The method of claim 11, wherein the calculation engine layer interacts with a physical table pool and a logical layer, the physical table pool comprising physical tables containing data to be queried, and the logical layer defining a logical metamodel joining at least a portion of the physical tables in the physical table pool.

13. The method of claim 12, wherein the calculation engine invokes an SQL processor for executing set operations.

14. The method of claim 1, wherein an input for each calculation node comprises one or more of:

a physical index, a join index, an OLAP index, and another calculation node.

15. The method of claim 13, wherein each calculation node has at least one output table that is used to generate the data set.

16. The method of claim 14, wherein at least one calculation node consumes an output table of another calculation node.

17. The method of claim 1, wherein the executing comprises:

forwarding the query to a calculation node in the calculation scenario that is identified as a default node if the query does not specify a calculation node at which the query should be executed.

18. The method of claim 1, wherein the calculation scenario comprises database metadata.

19. A non-transitory computer program product storing instructions which, when executed by at least one data processor forming part of at least one computing device, result in operations comprising:

receiving, by a database server from a remote application server, a query that is associated with a calculation scenario that defines a data flow model that includes one or more calculation nodes arranged in a hierarchy, the data flow initially specifying two or more stacked multiproviders that each respectively have two or more associated part providers, the uppermost multiprovider being a root multiprovider and each child multiprovider being a sub multiprovider;

instantiating and optimizing, by the database server, the calculation scenario, the optimizing comprising merging at least one sub multiprovider with the root multiprovider;

executing, by the database server, the operations defined by the calculation nodes of the optimized calculation scenario to result in a responsive data set; and

providing, by the database server to the application server, the data set.

20. A system comprising

at least one data processor;

and

memory storing instructions which, when executed by the at least one data processor, result in operations comprising;

receiving, by a database server from a remote application server, a query that is associated with a calculation scenario that defines a data flow model that includes one or more calculation nodes arranged in a hierarchy, the data flow initially specifying two or more stacked multiproviders that each respectively have two or more associated part providers, the uppermost multiprovider being a root multiprovider and each child multiprovider being a sub multiprovider;

instantiating and optimizing, by the database server, the calculation scenario, the optimizing comprising merging at least one sub multiprovider with the root multiprovider;

executing, by the database server, the operations defined by the calculation nodes of the optimized calculation scenario to result in a responsive data set; and

providing, by the database server to the application server, the data set.