Blood relationship analysis method of structured query language and tool thereof

Abstract

The embodiment of the invention discloses a blood relationship analysis method of a structured query language, and a tool thereof. The blood relationship analysis method comprises the steps: extracting service systems of a plurality of different types of databases, and continuously importing the structured query language of the service systems into a message queue list in batches; preprocessing structured query languages containing static parameters and dynamic parameters in the message queue list respectively; performing grammatical proofreading on the preprocessed structured query language,generating abstract syntax trees matching the structured query languages of the different types of databases, traversing the abstract syntax trees, and obtaining the blood relationship of the structured query languages; and obtaining blood relationship veins and key blood relationship data of the blood relationship, finally forming a blood relationship map, and finally completing analysis and prediction of the service system. According to the embodiment of the invention, dynamic and static structured query languages of various types of databases can be analyzed continuously in batches, and data traceability and prediction of a service system are completed, and an analysis result is accurate.

Description

technical field [0001] The invention relates to the field of data traceability and prediction, in particular to a blood relationship analysis method of a structured query language and a tool thereof. Background technique [0002] At present, various industries have paid more attention to big data, and the research on big data has been further deepened. The analysis of blood relationship in structured query language in data is also an important direction. [0003] However, there are many deficiencies in traditional structured query language lineage analysis. For example, the syntax rules designed for lineage analysis in structured query language are only applicable to a certain type of database, and the supported database type is single. If other types of databases are introduced, design In addition to the applicable grammatical rules, the compatibility of various structured query language grammars must also be considered, and the research cost is high. Therefore, the existin...

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Problems solved by technology

[0003] However, there are many deficiencies in traditional structured query language lineage analysis. For example, the syntax rules designed for lineage analysis in structured query language are only applicable to a certain type of database, and the supported database type is single. If other types of databases are introduced, design In addition to the applicable grammatical rules, the compatibility of various structured query language grammars must also be considered, and the research cost is high. Therefore, the existing structured query language analysis technology is relatively single and has poor scalability; moreover, the existing structured query language Language parsing technology only analyzes a single structured query language, cannot perform batch processing, and has poor continuity. The current structured query language analysis needs to manually input one or several structured query languages ​​as the data source for analysis, and parse through the parser , output the result, the parsing is over, there is no follow-up parsing power except manually adding structured query language, and it is impossible to perform continuous automatic parsing for a large number of structured query languages; further, the existing structured query language parsing technology only It is suitable for parsing static structured query language, and does not support the analysis of dynamic structured query language. If the structured query language contains dynamic parameters, the existing parsing technology will report a syntax error during the verification stage of the structured query language and the parsing will be terminated. Or replace dynamic parameters with characters that can be recognized by the parser in the stage of removing impurities in the structured query language, so that although the structured query language can be parsed normally, the analysis result will be distorted

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