Method for processing data of resource description framework

Abstract

The invention discloses a method for processing data of a resource description framework. The method comprises the following steps of: (1) processing the data of the resource description framework by using a Hash algorithm to generate an N*3 matrix, wherein N is an integer of more than 1, and three columns of the matrix respectively represent a subject array, a predicate array and an object array; (2) determining a maximum value eidmax in the subject array and the object array and a maximum value pidmax in the predicate array; (3) establishing an associated matrix M of the data of the resource description framework, wherein the size of the associated matrix is (eidmax+1)*N, and initializing all bits of the associated matrix M to 0; (4) according to the matrix, setting a bit value in the associated matrix, and converting the data of the resource description framework; and (5) compressing the associated matrix M. By adoption of the method, a large number of data of the resource description framework can be efficiently stored.

Description

technical field [0001] The invention relates to the field of data storage, and more specifically, the invention relates to a method for processing resource description framework data. Background technique [0002] Resource Description Framework (RDF) has become one of the standard formats for data exchange. It describes the properties of a resource on the Internet and its relationship to other resources. Formally, RDF can be represented by a triple: subject, predicate, and object. [0003] In RDF data, entities are usually represented by Uniform Resource Identifier (URI) or literal (Literal), and many of them are repeated, so these URIs or literals are usually converted into IDs when storing (integer) for storage. This reduces the storage space and facilitates processing in queries. On this basis, according to the distribution characteristics of IDs, various compression methods are proposed to reduce the space occupied by IDs. In addition, compressing the ID in data que...

AI Technical Summary

Problems solved by technology

BitMat uses the D-Gap compression method, although it has a good compression effect, but its compression method is not conducive to fast decompression; RDF-3X uses the block-based Delta compression method, but its compression method cannot quickly locate A specific RDF triple data, and in order to improve the query speed, there is a lot of redundancy in the stored data

All in all, the relationship between data compression efficiency and data decompression is not well balanced in these systems

Images