Distributed iceberg cubing over ordered dimensions

Patent metadata

Field	Value
Publication number	US-9760618-B2
Application number	US-201514658542-A
Country	US
Kind code	B2
Filing date	Mar 16, 2015
Priority date	Mar 16, 2015
Publication date	Sep 12, 2017
Grant date	Sep 12, 2017

Abstract

Methods, systems, and computer program products for distributed iceberg cubing over ordered dimensions are provided herein. A method includes calculating, from input data derived from a search query, a set of multiple cube measures for one or more combinations of multiple non-ordered dimensions; pruning the set of multiple cube measures based on one or more iceberg conditions to generate a sub-set of the cube measures; and determining a range for a set of ordered dimensions over a distributed processing platform based on (i) the sub-set of the cube measures and (ii) the one or more iceberg conditions.

First claim

What is claimed is:

1. A method, comprising:
calculating, from input data derived from a search query, a set of multiple cube measures for one or more combinations of multiple non-ordered dimensions, wherein said calculating is executed by a cubing component executing on a distributed computing platform;
pruning the set of multiple cube measures based on one or more iceberg conditions to generate a sub-set of the cube measures, wherein said pruning is executed by a cubing component executing on the distributed computing platform; and
determining a range for a set of ordered dimensions over a distributed processing platform based on (i) the sub-set of the cube measures and (ii) the one or more iceberg conditions, wherein said determining is executed by a range discovery component executing on the distributed computing platform.

2. The method of claim 1 , wherein said pruning comprises performing bottom-up cubing to prune each of the multiple cube measures that does not satisfy the one or more iceberg conditions.

3. The method of claim 1 , wherein said pruning comprises pruning in a scalable manner based on the one or more iceberg conditions.

4. The method of claim 1 , comprising:
executing a use-case calculation based on (i) the determined range for the set of ordered dimensions and (ii) the sub-set of the cube measures.

5. The method of claim 1 , wherein a cube associated with said set of multiple cube measures comprises a lattice cube.

6. The method of claim 5 , comprising:
dividing the lattice cube into multiple sub-lattices, wherein each of the multiple sub-lattices contains (i) a head and (ii) a leaf.

7. The method of claim 6 , wherein said dividing comprises reducing a number of data transfers required for processing data associated with the lattice cube.

8. A computer program product, the computer program product comprising a computer readable storage medium having program instructions embodied therewith, the program instructions executable by a computing device to cause the computing device to:
calculate, from input data derived from a search query, a set of multiple cube measures for one or more combinations of multiple non-ordered dimensions;
prune the set of multiple cube measures based on one or more iceberg conditions to generate a sub-set of the cube measures; and
determine a range for a set of ordered dimensions over a distributed processing platform based on (i) the sub-set of the cube measures and (ii) the one or more iceberg conditions.

9. The computer program product of claim 8 , wherein said pruning comprises performing bottom-up cubing to prune each of the multiple cube measures that does not satisfy the one or more iceberg conditions.

10. The computer program product of claim 8 , wherein said pruning comprises pruning in a scalable manner based on the one or more iceberg conditions.

11. The computer program product of claim 8 , wherein the program instructions executable by the computing device further cause the computing device to:
execute a use-case calculation based on (i) the determined range for the set of ordered dimensions and (ii) the sub-set of the cube measures.

12. The computer program product of claim 8 , wherein a cube associated with said set of multiple cube measures comprises a lattice cube.

13. The computer program product of claim 12 , wherein the program instructions executable by the computing device further cause the computing device to:
divide the lattice cube into multiple sub-lattices, wherein each of the multiple sub-lattices contains (i) a head and (ii) a leaf.

14. The computer program product of claim 13 , wherein said dividing comprises reducing a number of data transfers required for processing data associated with the lattice cube.

15. A system comprising:
a memory; and
at least one processor coupled to the memory and configured for:
calculating, from input data derived from a search query, a set of multiple cube measures for one or more combinations of multiple non-ordered dimensions;
pruning the set of multiple cube measures based on one or more iceberg conditions to generate a sub-set of the cube measures; and
determining a range for a set of ordered dimensions over a distributed processing platform based on (i) the sub-set of the cube measures and (ii) the one or more iceberg conditions.

16. A method, comprising:
calculating, from input data, a set of multiple cube measures for one or more combinations of multiple non-ordered dimensions, wherein said calculating is executed by a hybrid cube component executing on a distributed computing platform;
pruning the set of multiple cube measures based on one or more conditions to generate a sub-set of the multiple cube measures, wherein said pruning is executed by a cubing component executing on the distributed computing platform;
identifying one or more cube measures from the sub-set of cube measures based on user-specified confidence measures that are based on multiple ordered dimensions; and
defining one or more item-sets based on the one or more identified cube measures, wherein the one or more item-sets comprise a range of quantities from the multiple ordered dimensions which occur together in the input data.

17. The method of claim 16 , wherein said pruning comprises performing bottom-up cubing to prune each of the multiple cube measures that does not satisfy the one or more conditions.

18. The method of claim 16 , wherein said pruning comprises pruning in a scalable manner based on the one or more conditions.

19. The method of claim 16 , wherein a cube associated with said set of multiple cube measures comprises a lattice cube.

20. The method of claim 16 , comprising:
dividing the lattice cube into multiple sub-lattices, wherein each of the multiple sub-lattices contains (i) a head and (ii) a leaf, and wherein said dividing comprises reducing a number of data transfers required for processing data associated with the lattice cube.

Assignees

• IBM

Inventors

• Deshpande Prasad M
• Gupta Rajeev
• Gupta Ashu

Classifications

• G06F16/283 Primary

  Multi-dimensional databases or data warehouses, e.g. MOLAP or ROLAP · CPC title

• G06F16/3334

  Selection or weighting of terms from queries, including natural language queries · CPC title

• G06F17/30592 Primary

  Physics · mapped topic

• G06F17/30663

  Physics · mapped topic