Multi-source database global search method and system

Abstract

The invention belongs to the field of data search, and provides a multi-source database global search method and system. The multi-source database global search method comprises the steps: gathering and writting table fields in a multi-source database into a database dictionary table for field management; automatically processing table fields in the multi-source database according to a self-defined global search automation rule to generate a global search database dictionary table; taking a union set of a global search field and a global display field in the global search database dictionary table, dynamically generating a full-text retrieval data storage structure by taking the union set as a reference, and taking an original library table name as an index and a type; synchronizing all the original library table data which can be globally searched into a service database; and performing engine analysis on the business database according to the database dictionary table and the full-text retrieval data storage structure, and sending an analysis result to a front-end page for display.

Description

technical field [0001] The invention belongs to the field of data search, in particular to a multi-source database global search method and system. Background technique [0002] The statements in this section merely provide background information related to the present invention and do not necessarily constitute prior art. [0003] With the rapid development of network and information technology, the transparency of society is promoted, and data from all walks of life is gradually opened up. At present, with the continuous construction of various institutions and systems, the amount of accumulated data is increasing, and the types are becoming more and more abundant. Due to the wide variety of data, if a global search from these data requires a lot of manpower to understand the specific business data, often the front-end engineers of a certain system construction do not need to pay attention to the specific business, resulting in a gap between the front-end development engi...

AI Technical Summary

Problems solved by technology

[0005] (1) Data sources are diversified, whether they are collected from the Internet or from other manufacturers, or internal data provided by an organization or department. Each data source may provide dozens or hundreds of tables of data, but their data The structure is completely different and the meaning of the business fields is also independent. Manual comparison of hundreds of classification tables is not only time-consuming and labor-intensive, but also has some differences in the understanding of the business fields.

[0006] (2) In the case of multi-source data sources, it is necessary to ensure that the original data structure and data are not destroyed, and further standardize the global search field. Using the traditional method requires manual normalization of the fields in each table, and normalized The fields are input to the dictionary configuration table at the specified location, and problems such as manual errors and wrong table configurations are prone to occur during the manual entry process

[0007] (3) When the format of multi-source data is chaotic and complex, the form is not uniform, and the total amount of various types of data is large, various problems will occur when processing data synchronization, making global search more difficult

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