Data storage and search method, data storage and search system and computer readable storage medium

Abstract

The invention discloses a data storage and search method. The method comprises: reading data and storing corresponding data storage according to a corresponding data structure; carrying out binary system fluidization processing on the stored data; generating a new data file and establishing an index; and searching the file, and positioning the storage position of the building material in the datafile. Building material data in the building industry is stored locally in a file form, and a database is not used during access, so that the size of a data packet can be reduced, the transmission efficiency is improved, and the traffic overhead is saved. And meanwhile, by establishing the industry word segmentation lexicon and establishing the index, a full-text retrieval function can be realized, the accuracy of a search result can be ensured, and the data retrieval speed is increased.

Description

technical field [0001] The present invention relates to the fields of data processing technology and search, to a data storage and search method, in particular to a data storage and search method, system and computer-readable storage medium based on stream file conversion. Background technique [0002] A large amount of data information has been accumulated in the products used, how to quickly, comprehensively and accurately identify the required data information and use these data information efficiently has become a key factor affecting the use of products. For PC clients, the traditional data storage method is to build a database, but using a large database requires high hardware requirements, cumbersome management and maintenance, and complicated operations. At the same time, using a lightweight database such as SQLite is not suitable for high-concurrency and high-traffic application scenarios. Moreover, the performance of concurrent (including multi-process and multi...

AI Technical Summary

Problems solved by technology

For PC-side customers, the traditional data storage method is to build a database, but using a large database requires high hardware requirements, cumbersome management and maintenance, and complicated operations

At the same time, using a lightweight database such as SQLite is not suitable for high-concurrency and high-traffic application scenarios

Moreover, the performance of concurrent (including multi-process and multi-thread) reading and writing of the database on the PC client computer has not been ideal, and the dynamic addition and deletion of its data structure is relatively slow

At the same time, general databases can only search for some structured data, and the amount of information that can be searched is small, and the function of full-text search cannot be realized.

[0003] Although the traditional search engine is relatively powerful in function, it has few changes in the multi-packet search in the field of construction, a large number of visits, and special search terms The search scenario has two shortcomings: First, the search results are not complete and accurate, because ordinary search engines do not have semantic analysis or semantic analysis for search terms in the construction field. For example, search concrete, ordinary search engines are Can't find concrete

At the same time, for example, when searching for cement, the search results of traditional search engines include not only cement but also cement boards and cement columns, which is not very accurate. The search results contain a large amount of indirect building material information; second, the response speed is not fast enough

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