LOADING COLLABORATIVE DATASETS INTO DATA STORES FOR QUERIES VIA DISTRIBUTED COMPUTER NETWORKS

• US 20170364538A1
• Filed: 06/19/2016
• Published: 12/21/2017
• Est. Priority Date: 06/19/2016
• Status: Active Grant

• Current Assignee: Data.World, Inc.
• Original Assignee: Data.World, Inc.
• Inventors: Jacob, Bryon Kristen, Griffith, David Lee, Le, Triet Minh, Loyens, Jon, Hurt, Brett A., Keen, Arthur Albert
• Granted Patent: US 10,699,027 B2
• Time in Patent Office: Days
• CPC Class Codes: G06F 16/2471 Distributed queries
• CPC Class Codes: G06F 16/252 between a Database Management System and a front-end application
• CPC Class Codes: G06F 16/254 Extract, transform and load [ETL] procedures, e.g. ETL data flows in data warehouses
• CPC Class Codes: G06F 16/27 Replication, distribution or synchronisation of data between databases or within a distributed database system; Distributed database system architectures therefor
• CPC Class Codes: G06F 21/6227 where protection concerns the structure of data, e.g. records, types, queries

Abstract

Various embodiments relate generally to data science and data analysis, computer software and systems, and wired and wireless network communications to provide an interface between repositories of disparate datasets and computing machine-based entities that seek access to the datasets, and, more specifically, to a computing and data storage platform that facilitates consolidation of one or more datasets, whereby a collaborative data layer and associated logic facilitate, for example, efficient access to, and implementation of, collaborative datasets. In some examples, a system may include an atomized workflow loader configured to receive an atomized dataset to load into a data store, and to determine resource requirements data to describe at least one resource requirement. The atomized workflow loader may be further configured to select a data store type based on a resource requirement, and perform a load operation of the atomized dataset as a function of the data store type.

Claims

1. A method comprising:

receiving an atomized dataset to load into a data store;

determining resource requirements data to describe at least one resource requirement;

selecting a data store type based on the at least one resource requirement; and

performing a load operation of the atomized dataset as a function of the data store type.

2. The method of claim 1 wherein determining the resource requirements comprises:

identifying operating characteristics of a data store to load the atomized dataset as graph data.

3. The method of claim 2 wherein the data store is a triple store.

4. The method of claim 2 wherein determining the resource requirements comprises:

determining an operating characteristic of the data store related to a text search; and

identifying the data store for selection.

5. The method of claim 2 wherein determining the resource requirements comprises:

determining an operating characteristic of the data store related to geo-spatial information; and

identifying the data store for selection.

6. The method of claim 2 wherein determining the resource requirements comprises:

determining an operating characteristic of the data store related to graphic processing unit (“

GPU”

)-optimized data; and

identifying the data store for selection.

7. The method of claim 1 wherein selecting the data store type comprises:

selecting a product having a proprietary storage architecture.

8. The method of claim 7 wherein selecting the product comprises:

selecting a triple having a specific storage architecture.

9. A system comprising:

an atomized workflow loader configured to receive an atomized dataset to load into a data store, and to determine resource requirements data to describe at least one resource requirement, the atomized workflow loader further configured to select a data store type based on the at least one resource requirement, and perform a load operation of the atomized dataset as a function of the data store type.

10. The system of claim 9 further comprising:

a dataset requirement determinator configured to identify operating characteristics of a data store to load the atomized dataset as graph data.

11. The system of claim 10 wherein the data store is a triple store.

12. The system of claim 10 wherein the dataset requirement determinator is configured to:

determine an operating characteristic of the data store related to a text search; and

identify the data store for selection.

13. The system of claim 10 wherein the dataset requirement determinator is configured to:

determine an operating characteristic of the data store related to geo-spatial information; and

identify the data store for selection.

14. The system of claim 10 wherein the dataset requirement determinator is configured to:

determine an operating characteristic of the data store related to graphic processing unit (“

GPU”

)-optimized data; and

identify the data store for selection.

15. The system of claim 9 further comprises:

a product selector configured to select a product having a proprietary storage architecture.

16. The system of claim 15 wherein the product selector is further configured to:

select a triple having a specific storage architecture.