Skyline inquiry method based on multi-tenant data base in SaaS environment

Abstract

The invention discloses a skyline inquiry method based on a multi-tenant data base in SaaS environment. The method comprises the following steps that (1) a data base based on multi-tenant facing the SaaS environment is built; (2) a B+ tree index array is built on a pivot table; (3) each candidate link is built according to the B+ tree index array, and candidate nodes are sequentially traversed in turns on each candidate link; and (4) when a Skyline object is traversed, the node is output, in addition, the node is deleted from each candidate link, and the operation returns to the third step if the candidate link is not completed. The skyline inquiry method provided by the invention has great improvement in aspects of reaction time, compatibility and efficiency.

Description

technical field [0001] The present invention relates to the field of data processing of computer technology, in particular to a Skyline query optimization processing method, especially a Skyline query method based on a multi-tenant database in a SaaS environment. Background technique [0002] Skyline query is a research hotspot in the field of database query processing technology in multi-dimensional space in recent years. Skyline is widely used in preference query, multi-criteria decision support, and data mining and visualization. Skyline query is one of the major problems to be solved urgently in the field of massive database management. Skyline query refers to selecting a subset from a given set S of D-dimensional data objects, and any data object in the subset cannot be dominated by any other data object in S. The so-called dominance relationship means that in the data set S in the D-dimensional space, if the data object p is due to another data object q at least in a ...

AI Technical Summary

Problems solved by technology

[0006] The existing Skyline query method mainly uses the pivot table for storage. Repeated, large and unnecessary self-join operations are inevitable in the pivot table mode, so the existing method is not only time-consuming and laborious, but also produces a large number of intermediate results. Ineffective

Therefore, in view of the fact that the existing Skyline query method cannot effectively perform efficient query in a multi-tenant environment, an efficient query method is designed: that is, on the basis of the pivot table mode, a B+ tree index is established, which is the pivot table model. On the axis table, a B+ index is established for each attribute belonging to different private tables, and combined with the characteristics of the SaaS environment, an MDOS (Multi-Tenant Database Oriented Skyline) algorithm based on the index structure is used, and efficient pruning is adopted on this basis Strategy, gradually reduce the size of the candidate chain, and repeatedly test the dominance of sibling objects and eliminate ordinary objects, so as to design a high-efficiency and low-cost Skyline query method, and can ensure the efficiency of Skyline query processing and the accuracy of query results

Images