Optimizing memory by sharing datasets between workspaces

• US 10,445,299 B2
• Filed: 12/23/2016
• Issued: 10/15/2019
• Est. Priority Date: 12/23/2016
• Status: Active Grant

• Current Assignee: SAP SE
• Original Assignee: SAP SE
• Inventors: Jain, Nikita, Vinnakota, Devicharan
• Primary Examiner(s): Khong, Alexander
• Application Number:
  US15/389,455
• Publication Number:
  US 20180181597A1
• Time in Patent Office: 1,026 Days
• CPC Class Codes: G06F 16/176 Support for shared access to files; File sharing support
• CPC Class Codes: G06F 16/21 Design, administration or maintenance of databases
• CPC Class Codes: G06F 16/22 Indexing; Data structures therefor; Storage structures
• CPC Class Codes: G06F 16/283 Multi-dimensional databases or data warehouses, e.g. MOLAP or ROLAP
• CPC Class Codes: G06F 16/9024 Graphs; Linked lists G06F16/9027 takes precedence

Abstract

Methods and system are disclosed that optimize memory consumed, by sharing datasets between workspaces. In one aspect, multiple workspaces may be instantiated by retrieving multiple datasets from multiple data sources. An input to execute transformations on the multiple datasets may be received. Based on a determination of execution of a transformation on the multiple datasets, a dataset context analyzer may be executed to analyze a current context of data in the multiple datasets. Based on a result of execution of the dataset context analyzer, a transformation graph analyzer may be executed to compute a current context of transformations on the multiple datasets. Based on the determined current context of data and the current context of the transformations on the dataset, memory consumed may be optimized by sharing the multiple datasets between the multiple workspaces.

Claims

1. A computer implemented method to optimize memory consumption, by sharing datasets between workspaces, comprising:

upon instantiating a plurality of workspaces, retrieving a plurality of datasets from one or more data sources into the plurality of workspaces, wherein a plurality of workspace contexts are defined corresponding to the plurality of workspaces, wherein a workspace context of the plurality of workspace contexts defines boundaries for accessing data from a corresponding dataset in relation to an execution of a transformation, and wherein a first dataset from the plurality of datasets is provided into at least two workspaces and is associated with at least two contexts correspondingly defined at the at least two workspaces;

receiving an input to execute a transformation on the first dataset from the plurality of datasets to generate a transformed dataset, the transformation being executed at a first workspace of the at least two workspaces, wherein the transformed dataset is stored at a data source corresponding to the first dataset after executing the transformation;

based on the transformation, analyzing a first current context of data in the first dataset in the first workspace of the at least two workspaces and a second current context of the data in a second workspace, wherein the second workspace is different from the first workspace;

based on the analysis of the first current context of data in the first workspace, computing a third current context of transformation on the first dataset, wherein the current context of the transformation on the first dataset is determined by comparing the first dataset prior to executing the transformation and the transformed dataset; and

when the first current context of data in the first workspace, the second current context of the data in the second workspace, and the third current context of the transformation of the first dataset are equal, providing the transformed dataset as shared between the first workspace and the second workspace to optimize the memory consumption.

2. The computer implemented method of claim 1, further comprising analyzing a current context of the data in one or more datasets, comprises:

based on a comparison of one or more contexts of the one or more datasets, determining whether the one or more datasets are retrieved from an identical data source of the one or more data sources;

determining whether one or more attributes associated with the one or more datasets are identical; and

based on the comparison and the determination that the one or more datasets are identical, determining the current context of data in the one or more datasets.

3. The computer implemented method of claim 2, wherein the one or more attributes associated with the one or more datasets are selected from a group consisting of a measure, a dimension and a visualization.

4. The computer implemented method of claim 1, further comprises:

when the plurality of workspaces are instantiated, map the plurality of datasets from the one or more data sources to the plurality of workspaces by the dataset manager.

5. The computer implemented method of claim 1, wherein the transformation is selected from a group consisting of:

adding data to the first dataset, deleting data from the first dataset, and modifying data from the first dataset.

15. The method of claim 1, further comprising;

associating a reference count to the first dataset, wherein the reference count defines a number of workspaces between which the first dataset is shared; and

adjusting the reference count when the first dataset is shared between the first workspace and the second workspace.

16. The method of claim 1, further comprising, when the first current context of data in the first workspace, the second current context of the data in the second workspace, and the current context of the transformation of the first dataset are different:

replicating the first dataset into a second copy of the first dataset to correspond to the second workspace, wherein the second copy of the first dataset is provided for accessing and transformation executions from the second workspace independent of the first dataset provided from the first workspace.

6. A computer system to optimize memory consumed, by sharing datasets between workspaces, comprising:

a memory storing computer instructions; and

a processor communicatively coupled with the memory to execute the instructions to perform operations, comprising;

upon instantiating a plurality of workspaces, retrieving a plurality of datasets from one or more data sources into the plurality of workspaces, wherein a plurality of workspace contexts are defined corresponding to the plurality of workspaces, wherein a workspace context of the plurality of workspace contexts defines boundaries for accessing data from a corresponding dataset in relation to an execution of a transformation, and wherein a first dataset from the plurality of datasets is provided into at least two workspaces and is associated with at least two contexts correspondingly defined at the at least two workspaces;

receiving an input to execute a transformation on the first dataset the plurality of datasets to generate a transformed dataset, the transformation being executed at a first workspace of the at least two workspaces, wherein the transformed dataset is stored at a data source corresponding to the first dataset after executing the transformation

based on the transformation, analyzing a first current context of data in the first dataset in the first workspace of the at least two workspaces and a second current context of the data in a second workspace, wherein the second workspace is different from the first workspace;

based on the analysis of the first current context of data in the first workspace, computing a third current context of transformation on the first dataset, wherein the current context of the transformation on the first dataset is determined by comparing the first dataset prior to executing the transformation and the transformed dataset; and

when the first current context of data in the first workspace, the second current context of the data in the second workspace, and the third current context of the transformation of the first dataset are equal, providing the transformed dataset as shared between the first workspace and the second workspace to optimize the memory consumption.

7. The computer system of claim 6, wherein the memory further comprises instructions which when executed cause to perform:

analyzing a current context of the data in one or more datasets comprising;

based on a comparison of one or more contexts of the one or more datasets, determining whether the one or more datasets are retrieved from an identical data source of the one or more data sources;

determining whether one or more attributes associated with the one or more datasets are identical; and

based on the comparison and the determination that the one or more datasets are identical, determining the current context of data in the one or more datasets.

8. The computer system of claim 7, wherein the one or more attributes associated with the one or more datasets are selected from a group consisting of a measure, a dimension and a visualization.

9. The computer system of claim 6, further comprising:

when the plurality of workspaces are instantiated, map the plurality of datasets from the one or more data sources to the plurality of workspaces by the dataset manager.

10. The computer system of claim 6, wherein the transformation is selected from a group consisting of:

adding data to the first dataset, deleting data from the first dataset, and modifying data from the first dataset.

11. A non-transitory computer readable storage medium tangibly storing instructions, which when executed by a computer, cause the computer to execute operations comprising:

upon instantiating a plurality of workspaces, retrieving a plurality of datasets from one or more data sources into the plurality of workspaces, wherein a plurality of workspace contexts are defined corresponding to the plurality of workspaces, wherein a workspace context of the plurality of workspace contexts defines boundaries for accessing data from a corresponding dataset in relation to an execution of a transformation, and wherein a first dataset from the plurality of datasets is provided into at least two workspaces and is associated with at least two contexts correspondingly defined at the at least two workspaces;

receiving an input to execute a transformation on the first dataset from the plurality of datasets to generate a transformed dataset, the transformation being executed at a first workspace of the at least two workspaces, wherein the transformed dataset is stored at a data source corresponding to the first dataset after executing the transformation;

based on the transformation, analyzing a first current context of data in the first dataset in the first workspace of the at least two workspaces and a second current context of the data in a second workspace, wherein the second workspace is different from the first workspace;

based on the analysis of the first current context of data in the first workspace, computing a third current context of transformation on the first dataset, wherein the current context of the transformation on the first dataset is determined by comparing the first dataset prior to executing the transformation and the transformed dataset; and

when the first current context of data in the first workspace, the second current context of the data in the second workspace, and the third current context of the transformation of the first dataset are equal, providing the transformed dataset as shared between the first workspace and the second workspace to optimize the memory consumption.

12. The non-transitory computer readable storage medium of claim 11, further comprising instructions, which when executed cause to

analyze a current context of the data in the plurality of datasets, comprising:

based on a comparison of one or more contexts of the one or more datasets, determining whether the one or more datasets are retrieved from an identical data source of the one or more data sources;

determining whether one or more attributes associated with the one or more datasets are identical; and

based on the comparison and the determination that the one or more datasets are identical, determining the current context of data in the one or more datasets.

13. The non-transitory computer readable storage medium of claim 12, wherein the one or more attributes associated with the one or more datasets are selected from a group consisting of a measure, a dimension and a visualization.

14. The non-transitory computer readable storage medium of claim 11, further comprising:

when the plurality of workspaces are instantiated, map the plurality of datasets from the one or more data sources to the plurality of workspaces by the dataset manager.