Data query service authority processing method

Abstract

The invention discloses a data query service permission processing method, which belongs to the technical field of data query service permissions, and comprises the following steps: collecting metadata in OLTP and OLAP systems and storing the metadata in a MySQL system to form metadata information; based on the data query requirement of the client, the server distributes different metadata query permissions to each user; the server generates an abstract syntax tree according to the SQL language of the query demand, and traverses the abstract syntax tree based on a breadth traversal algorithm to obtain analyzed metadata; and the server performs verification according to the query permission and returns a query result to the client. The method is scientific and reasonable in design and convenient to use, the technical problem that data permission and data security are difficult to realize in existing data query is solved, and universal and secure output query of data is realized.

Description

technical field [0001] The invention belongs to the technical field of data query service authority, and in particular relates to a processing method for data query service authority. Background technique [0002] The big data platform extracts, loads, and transforms the data of all parties, and then outputs it for business needs. To this end, a general query data service is required for data query. However, data query involves issues such as data permissions and data security. There is no unified solution in the current big data industry. Various components have their own set of permission verification systems. The haddoop system comes with ranger permission management. , the druid database and the clickhouse database are separately configured with user permissions in their respective systems. For OLTP systems and OLAP systems that support SQL queries, the big data platform provides unified data services through rest-api, and it is difficult to verify permissions and imple...

AI Technical Summary

Problems solved by technology

However, data query involves issues such as data permissions and data security. There is no unified solution in the current big data industry. Various components have their own set of permission verification systems, and the haddoop system comes with ranger permission management. , the druid database and the clickhouse database configure user permissions separately in their respective systems

For OLTP systems and OLAP systems that support SQL queries, the big data platform provides unified data services through rest-api, and it is difficult to implement authorization verification and data security

First, the SQL syntax of different storage engines is different, and their parsing rules are also different. There is no service that shields parse details; second, there is no unified metadata system management for the parsed database table fields, even if there is open source metadata It is also difficult for the system to interact with the data services developed by itself; third, the implementation of various open source components is complicated, and the authority verification module has complicated functions

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