Compression storage method based on graph structure data

Abstract

The invention discloses a compression storage method based on graph structure data. The compression storage method comprises the following steps: acquiring graph structure data to be compressed and stored; inputting the graph structure data into the trained graph structure data classification model to obtain a classification result; determining a compression subset type corresponding to the graph structure data according to a classification result; segmenting the graph structure data according to the isomorphic sub-graph of the compressed subset type; compressing the segmented graph structure data different from the isomorphic sub-graphs according to a preset compression algorithm; and performing compression and partition storage on different compression subset types according to a preset compression algorithm. Through the technical scheme of the invention, the storage capacity required by the graph structure data is reduced, the retrieval efficiency of the data is improved, the random access amount is reduced, and the data is quickly positioned.

Description

technical field [0001] The invention relates to the technical field of data storage, in particular to a compression storage method based on graph structure data. Background technique [0002] In open or heterogeneous environments such as social networks, biotechnology, and semantic networks, graph structures have been widely used, and large-scale graph-structured datasets have emerged. For example, in the Semantic Web, the graph-structured RDF data model is used to represent data, and applications to billion-scale data sets have been widely proposed. [0003] In molecular biology, it is often necessary to calculate the transformation relationship between compounds, or to study the possible properties of compounds containing certain structures, etc., and graphs can well reflect the structural properties of compounds, and vertices can be used to represent the properties of compounds. Atoms, using edges to represent the connection relationship between atoms. This type of grap...

AI Technical Summary

Problems solved by technology

[0004] However, in the existing technology, for the storage of graph-structured data, based on the storage mode of graph-structured data and the corresponding basic query method, in the storage method that supports matching query, graph matching is required, but this process takes a long time Complexity. In practical applications, the query efficiency and time overhead of retrieving massive graph-structured data bring great difficulties to the graph matching problem. Storage and retrieval methods affect the development of graph-structured data

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