Software resource system based on field-level blood relationship and establishment method thereof

Abstract

The invention discloses a software resource system based on a field-level blood relationship and an establishment method thereof. The system comprises an analysis device, a heterogeneous environment data import device and a function classification device. The analysis device is used for obtaining a query statement from a predetermined distributed file system, analyzing the query statement into anabstract syntax tree, traversing through a depth-first traversal algorithm to obtain node data in the abstract syntax tree, and obtaining a field-level blood relationship of the query statement according to the node data and an association relationship thereof; the heterogeneous environment data import device is used for acquiring heterogeneous data corresponding to a source table in a metadata management system, and supplementing the heterogeneous data into the blood relationship according to the corresponding relationship between the heterogeneous data and the blood relationship; and the function classification device is used for classifying scripts according to the script categories, and establishing and generating a tree structure based on the field-level blood relationship to obtain asoftware resource system according to the logic association between the function categories of the scripts and the blood relationship after the heterogeneous data is supplemented.

Description

technical field [0001] The invention relates to a structured query language in the field of big data and a field-level kinship analysis tool for the structured query language, in particular to a software resource system based on a field-level kinship relationship and its establishment method. Background technique [0002] With the rapid development of big data technology, data is undoubtedly a very important asset for every enterprise, and the use of data to mine relevant value information has become a new driving force for economic growth. In addition, with the growth and use of data, data quality problems such as erroneous data, junk data, and redundant data have become increasingly prominent, so data governance has been established as a long-term priority. [0003] However, data governance is a systematic work. From data generation to data final landing, there may be several relevant departments. In the existing software resource system, application development basically ...

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Problems solved by technology

[0003] However, data governance is a systematic work. From data generation to data final landing, there may be several relevant departments. In the existing software resource system, application development basically adopts chimney development, and there are different degrees of differences between applications. Technical or data barriers lead to the fact that various applications do not understand each other's technical and logical architectures in the process of data governance. In order to deal with these problems, data governance applications usually develop some small tools (for example, through the common character processing method rough Sorting out the logical structure of the data processing of the party) is convenient for the staff to sort out the logical context of the problem, and finally add manual intervention to promote the process of data governance. As the form of data governance becomes more and more severe, some simple and discrete methods are adopted Small tools not only cannot continuously and rapidly advance the progress of data governance, but also fail to achieve the goal of precise data governance due to the increase in data governance issues

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