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Temporal RDF query method based on Spark GraphX

A query method and temporal technology, applied in the field of data, to achieve the effect of improving effectiveness and reducing waste of resources

Pending Publication Date: 2022-06-24
NANJING UNIV OF AERONAUTICS & ASTRONAUTICS
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Problems solved by technology

However, Web resources are dynamic, and the classic RDF model can only describe the current state of resources. The massive resources contained in the Semantic Web require large-scale temporal RDF data to describe

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  • Temporal RDF query method based on Spark GraphX
  • Temporal RDF query method based on Spark GraphX
  • Temporal RDF query method based on Spark GraphX

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Embodiment Construction

[0029] The present invention will be further described below with reference to the accompanying drawings.

[0030] The overall flow of the present invention is as follows figure 1 shown. The sub-module processes it contains are as follows figure 2 , image 3 , Figure 4 , Figure 5 , Image 6 , Figure 7 As shown, detailed description will be given below with reference to each figure.

[0031] The specific implementation steps are as follows, and the overall process is attached figure 1 . The invention is mainly divided into three parts: firstly, based on the Spark GraphX ​​distributed graph processing framework, the temporal RDF graph is converted into a labeled temporal attribute graph, and the temporal RDF graph data is queried and processed by graph parallel computing. optimization. Then, based on the optimized Pregel interface in GraphX, the subgraph matching query is performed on the temporal RDF graph data, and the T-SPARQL query is converted into a function ...

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Abstract

The invention discloses a tense RDF (Resource Description Framework) query method based on SparkGraphX. The method comprises the following steps: converting a tense RDF graph into a tense attribute graph with a label on the basis of a Spark GraphX distributed graph processing framework, performing sub-graph matching query on tense RDF graph data on the basis of an optimized Pregel interface in GraphX, converting T-SPARQL query into a function executed on a vertex, performing query processing and optimization on the tense RDF graph data in a graph parallel computing mode, and performing query processing and optimization on the tense RDF graph data. And two strategies of vertex calculation optimization and communication cost optimization are provided to improve the effectiveness of the algorithm. Various methods exist for storing tense RDF data and processing T-SPARQL query, but the graphic property of the RDF data causes a large amount of iterative connection, which has great influence on system performance, and the research of a tense RDF model mainly lies in integration of tense information and a classical RDF model, so that the relationship between the classical RDF model and the tense information needs to be coupled well. According to the method, large-scale query of the tense RDF data is carried out on a distributed platform, the characteristics of the time dimension and the graph structure are combined, storage and query of the tense RDF are efficiently carried out, the data set of the tense RDF model is better managed, and the query speed of the data set is increased.

Description

technical field [0001] The present invention studies the structure and semantic features of the temporal RDF model, and proposes a temporal RDF query method based on Spark GraphX. Based on the Spark GraphX ​​distributed graph processing framework, the temporal RDF graph is converted into a labeled temporal attribute graph, and the Query processing and optimization of temporal RDF graph data by graph parallel computing. Based on the optimized Pregel interface in GraphX, the subgraph matching query is performed on the temporal RDF graph data, the T-SPARQL query is converted into a function executed on the vertex, and two strategies of vertex calculation optimization and communication cost optimization are proposed to improve the effectiveness of the algorithm , which belongs to the field of distributed semantic query. Background technique [0002] Almost all information in reality contains temporal features explicitly or implicitly, and naturally has temporal properties. Wit...

Claims

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Application Information

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IPC IPC(8): G06F16/901G06F16/903
CPCG06F16/9024G06F16/90335
Inventor 贺振宇马宗民
Owner NANJING UNIV OF AERONAUTICS & ASTRONAUTICS
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