Design And Implementation Of Chart Recommendation Algorithm And OLAP Operation On Multidimensional Pivot Table

As data resources continue to be enriched,multi-dimensional analysis of data becomes a powerful means for companies to gain insights.Currently,traditional multidimensional reporting tools are still lacking in terms of comprehensiveness,interactivity and portability,especially in the use of the open source OLAP engine,there is a lack of suitable front-end perspective tools.In this paper,two key problems are solved through the analysis of the current status of multidimensional data reporting tools at home and abroad and the study of technical concepts related to multidimensional data analysis and visualization,and a Web-based multidimensional pivot table system based on the open source OLAP engine Mondrian is designed and implemented.The main tasks are as follows:(1)A new table algebraic operator is proposed to achieve fast and agile computation of graphical pivot table configuration.When the user performs online analysis and processing of graphical pivot tables,the cached tree dimensional information can be used to quickly generate the pivot structure configuration and the properties of each cell of the table,and then convert the results of each cell of the table into MDX multidimensional query statements that interact with the Mondrian engine to calculate the cell results.(2)A recommended algorithm for graph pivot table configuration based on the graph language is proposed.Another key issue in multidimensional data exploration is how to recommend more intuitive and easy-to-understand graphical pivot tables to users.The paper summarizes and designs a marker type derivation rule based on data distribution,proposes the principle of data feature combination,and designs a multifield chart type priority recommendation algorithm based on the priority principle.(3)Designed and implemented the above-mentioned algorithm,the multidimensional pivot table system provides a general solution for multidimensional data visualization,which can help users to observe and analyze large amounts of data from multiple angles and levels,meeting the needs of SMEs for multidimensional analysis of data,with great promotion and application value.