Pather-level hierarchical query method, device and equipment and storage medium

Abstract

The invention discloses a parent level query method and device, equipment and a storage medium, and relates to the technical field of big data, and the method comprises the following steps: obtaining object information of each object in all levels except the highest level in an organizational structure diagram, and integrating the object information of each object to obtain a plurality of first integrated data; integrating all the first integrated data into one line to obtain second integrated data; inputting the second integrated data into a self-defined user definition table generation function; and when it is monitored that a parent level of a target object in the organizational structure diagram needs to be queried, querying parent primary keys of all levels of the target object from the second integrated data through the user definition table generation function, and outputting the parent primary keys. According to the method and the device, the parent primary keys of the objects in the specified type hierarchy in the organizational structure diagram can be simply, conveniently and intuitively output through the user-defined table generation function, so that the query efficiency is improved, and the query cost is saved.

Description

technical field [0001] The present application relates to the field of big data technologies, and in particular, to a parent-level query method, apparatus, device, and storage medium. Background technique [0002] At present, it is usually necessary to write complicated code when querying the parent level of the objects in the organizational chart, which leads to low query efficiency and is not conducive to subsequent maintenance and upgrades. When applied to query scenarios with a large amount of data, the query effect will be worse, and for intergenerational queries, the accuracy is not very high. For example, in a big data offline computing scenario, when the number of levels cannot be determined, when searching for all parent levels of a child level (such as a store level), the query efficiency is low due to the large amount of data. [0003] To sum up, how to quickly query the parent level of the objects in the organizational chart is a problem that needs to be further...

AI Technical Summary

Problems solved by technology

[0002] At present, it is usually necessary to write complicated codes when querying the parent level of the objects in the organization chart, resulting in low query efficiency and is not conducive to subsequent maintenance and upgrades

When applied to query scenarios with a large amount of data, the query effect will be worse, and for intergenerational queries, the accuracy is not very high

For example, in the big data offline computing scenario, when the number of levels cannot be determined, when looking for all parent levels of the child level (such as the store level), the query efficiency is low due to the large amount of data

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