An efficient RDF data storage and query system

A data storage and query system technology, applied in database indexing, structured data retrieval, etc., can solve problems such as slow query speed, improve query efficiency, and speed up query performance.

Pending Publication Date: 2019-04-26
TIANJIN UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0006] Although the method mentioned above has realized the function of RDF storage and query, but with the increase of data volume, the slow query speed has become the Achilles heel of this type of system

Method used

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  • An efficient RDF data storage and query system
  • An efficient RDF data storage and query system
  • An efficient RDF data storage and query system

Examples

Experimental program
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Embodiment 1

[0033] HTStore is a graph-based triple system that can dynamically support RDF data storage and SPARQL query. In the HTStore system, RDF data is stored in the form of an adjacency list, and at the same time, the embodiment of the present invention also establishes a hash index according to the vertices of the RDF graph.

[0034] The main advantage of hash index is fast retrieval, especially when the amount of data is large. However, there are some inherent defects in the traditional hash index, therefore, the embodiment of the present invention needs to improve the index structure.

[0035] In the RDF data storage and query system constructed in the embodiment of the present invention, a composite index structure including a hash table and a hash tree is used to store RDF data. Hash tables are built for fast access, while hash trees are built to efficiently resolve hash collisions.

[0036] Next, the embodiment of the present invention will describe the design of the HTStore...

Embodiment 2

[0045] Combine below Figure 1-Figure 6 Carry out feasibility verification to the scheme in embodiment 1, see the following description for details:

[0046] see figure 1 , is an index graph of a system that supports RDF storage and SPARQL query, wherein RDF data can be regarded as an RDF graph, and the embodiment of the present invention creates an index for each node in the graph to speed up the query.

[0047] see figure 2 , which are the different situations that may arise from inserting a node in an index. The first case means that there is an empty position in the corresponding position of the hash table, and the insertion is successful. The second case indicates that the location of the hash table is occupied, but the root node of the hash tree is not occupied, then the root node of the tree is created and the insertion is successful. The third case indicates that the location of the hash table has been occupied and the root node of the hash tree has also been esta...

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Abstract

The invention discloses an efficient RDF data storage and query system which adopts a composite index structure of a hash table and a hash tree and is used for storing RDF data. Wherein the compositeindex structure comprises a Hash layer serving as a first layer of Hash table and a tree layer serving as a second layer of Hash tree; Wherein the hash layer is a static hash table, and the tree layeris a dynamic hash tree, so that the query efficiency is improved; In the first layer, constructing a static hash table with the length of m; In the second layer, a Hash tree is dynamically constructed based on the prime number sequence; The system also utilizes a hash tree to solve the conflict problem in the hash table. Through the designed data storage query system, the RDF storage efficiency and the SPARQL query efficiency are improved, and various requirements in practical application are met.

Description

technical field [0001] The invention relates to the field of indexes and storage structures, in particular to an efficient RDF (Resource Description Framework) data storage and query system. Background technique [0002] In the past few decades, the amount of RDF data has increased significantly, so how to effectively store and manage massive RDF data has become a huge challenge. Several existing systems support RDF storage and query, such as gStore, RDF-3x, etc. According to the data management method, these systems can be divided into three categories: relational database-based systems, triple-based systems, and graph-based systems. [0003] A relational database-based system converts RDF data into relational data tables for storage. When querying, SPARQL (Query Language and Data Acquisition Protocol) queries also need to be converted into SQL (Structured Query Language) language. These systems can be further subdivided into three-column-based systems, attribute-table-ba...

Claims

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Application Information

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IPC IPC(8): G06F16/22
Inventor 李雯雯饶国政张冰怡
Owner TIANJIN UNIV
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