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Query-time analytics on graph queries spanning subgraphs

A subgraph and view technology, which is applied in the field of query time analysis of graph queries across subgraphs, can solve problems such as expensive computation, increased computational expense, and limitations.

Pending Publication Date: 2019-05-21
MICROSOFT TECH LICENSING LLC
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Graph queries are computationally expensive to run and may be otherwise limited in functionality; requiring users to run graph queries, extract subgraphs, and run separate analyzes on subgraphs is often done in separate programs or interface, which adds additional computational overhead for data analysis or graphing

Method used

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  • Query-time analytics on graph queries spanning subgraphs
  • Query-time analytics on graph queries spanning subgraphs
  • Query-time analytics on graph queries spanning subgraphs

Examples

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Embodiment Construction

[0012] The following detailed description refers to the accompanying drawings. Wherever possible, the same reference numbers are used in the drawings and the following description to refer to the same or like elements. While a number of examples are described, modifications, adaptations, and other implementations are possible. For example, substitutions, additions, or modifications may be made to elements shown in the figures, and methods described herein may be modified by substituting, reordering, or adding steps to disclosed methods. Accordingly, the following detailed description is non-limiting, but instead the proper scope is defined by the appended claims. Examples can take the form of a hardware implementation, or an entirely software implementation, or an implementation combining software and hardware aspects. Therefore, the following detailed description is not to be understood in a limiting sense.

[0013] Provided herein are systems, methods, and computer-readab...

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Abstract

Reductions in latencies and improvements in computational efficiency when analyzing data stored in a relational graph by integrating analytical capabilities into graph queries. Instead of a user having to run a graph query and then perform analytics on the resulting subgraph via separate requests, the user is enabled to run analytics at the time the graph query is run via a single request to the database maintaining the relationship graph, which improves the computationally efficiency of analyzing relational graphs and thereby improves the functionality of the computing devices hosting the relational graphs and running the queries and analytics.

Description

Background technique [0001] In a graph database, entities are represented as nodes and relationships between these entities are represented as edges from the perspective of a relational graph held by the graph database. Users can periodically query the relationship graph via graph query to understand the relationship between entities. For example, a user may issue a graph query to find friends or contacts within a social network, documents with which a given user has interacted, users with whom a given document has been accessed, entities satisfying various search criteria, etc. A graph query produces a subgraph in the queried relational graph that satisfies the query, which can be further analyzed by the user. Graph queries are computationally expensive to run and may be otherwise limited in functionality; requiring users to run graph queries, extract subgraphs, and run separate analyzes on subgraphs is often done in separate programs or interface, which adds additional com...

Claims

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Application Information

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IPC IPC(8): G06F16/242G06F16/9535
CPCG06F16/2425G06F16/24549G06F16/951G06F16/9024
Inventor T·克勒策S·维肯瓦尔瓦格A·克瓦尔内斯A·K·约翰森J-O·A·凯伯尔D·S·埃德森
Owner MICROSOFT TECH LICENSING LLC
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