A query optimization method for virtual asset data
A technology for query optimization and virtual assets, which is applied in the fields of electronic digital data processing, digital data information retrieval, and special data processing applications. The effect of reducing query time and improving query efficiency
Active Publication Date: 2019-06-14
NAT UNIV OF DEFENSE TECH
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[0004] However, the first method can only process one node at a time, which is not suitable for algebra-based query processing, and the query efficiency is poor
The genetic algorithm used in the second method needs to set different genetic operators for different problems, so there are deficiencies such as poor local search ability.
The third method does not take into account the update of the backend data, which may lead to inconsistency between the cached data and the backend data, resulting in lower accuracy of query results
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[0024] The technical scheme of the present invention will be further described below through specific embodiments:
[0025] The present invention provides a query optimization method for virtual asset data. The method realizes query optimization from three aspects: semantic cache, inverted index and node index. The overall design is as follows: figure 1 shown.
[0026] 1. Semantic cache
[0027] The large scale of virtual asset data leads to large-scale index files. Large-scale index files will affect query efficiency to a certain extent. However, virtual asset data mining applications often have specific mining objects (hotspots). Mining object data Only a small part of the virtual asset data. Aiming at the context information of the mining object and the locality of the query, the semantic caching technology for virtual asset association query can well support the fast association query of virtual assets.
[0028] For ease of discussion, the following concepts are defined...
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The invention discloses a query optimization method for virtual asset data. The query optimization method comprises the following steps that a semantic cache is queried, and returning is directly conducted to obtain a result if queried information is contained; otherwise, querying is classified, reverse index querying is conducted on specified-column-free querying, a querying result is directly obtained if the queried information is contained, and otherwise, node index querying is conducted; node querying is directly conducted on specified column querying; if a node index result contains a spare node, an operation jumps to a corresponding node, a general database is queried in order to obtain a corresponding result, and otherwise, node index querying is cyclically executed till the spare node is found to obtain the corresponding result. According to the query optimization method, the semantic cache, reverse indexes and node indexes are comprehensively taken into account, and by applying the query optimization method to querying of mass virtual asset information, the querying time can be greatly shortened, and the querying efficiency can be improved.
Description
technical field [0001] The technology belongs to the field of network and information security, and relates to a query optimization method for virtual asset data. Background technique [0002] With the rapid development of information science and technology, especially the rapid development of the Internet, it provides a broad platform for the generation and transaction of virtual assets, and promotes the prosperity and development of online transactions. At the same time, it also produces massive amounts of virtual asset data. How to quickly query effective information has become a huge challenge. Therefore, query optimization for massive databases is imperative. [0003] Based on this, literature [1] discusses Transform query processing in XQuery / Update in detail, and its core idea is the navigation processing technology based on XQuery. By constructing an automaton, according to the currently encountered nodes, perform related operations on the automaton. Literature [2]...
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IPC IPC(8): G06F16/2453
Inventor 邓璐贾焰韩伟红李树栋李虎全拥
Owner NAT UNIV OF DEFENSE TECH