Data index storage method, system and device capable of randomly expanding dimensions

Abstract

The invention provides a data index storage method, system and device capable of randomly expanding dimensions. The method comprises the steps of obtaining corresponding data indexes by processing service data according to different service requirements, and querying a data table to construct index IDs of the data indexes; calling a storage table of a data index based on the index ID, and expanding the dimension of the data index by adding a data row in the storage table of the data index so as to store the data index according to a corresponding field. According to the scheme, dimension expansion is carried out at will by increasing data rows, the dimensions can be freely combined, and each row of data can be interpreted through different identified index IDs; for the indexes of the same measurement under different dimensions, the data indexes can be conveniently stored, simply expanded and easily called, and the uniformity of the indexes is ensured.

Description

technical field [0001] The present invention relates to the technical field of data index storage, in particular to a data index storage method, system and device that can expand dimensions arbitrarily. Background technique [0002] In the current big data background, various business scenarios will refine a large amount of business data into business data indicators; indicators are composed of metrics and dimensions, and metrics are "aggregated statistical values, which are the results of aggregation operations, usually continuous values, Such as: order quantity, etc., and the dimension is "the angle of observing data, usually a set of discrete values, such as: city, date, etc." Under the premise of the same measurement, the combination of dimensions can be endless. In the existing In terms of data index storage, the usual data index storage uses a two-dimensional table, adding index fields to columns and placing index values ​​at corresponding positions; this storage metho...

AI Technical Summary

Problems solved by technology

In this way, the operation of converting data indicators into storage forms in two-dimensional tables (calculation of dimensions and measures), writing data (storage), and reading data (retrieval, access) are relatively complex, data processing efficiency, storage access The efficiency is low, and the flexibility of arbitrarily scalable is small. With the increase of data, especially in the face of data processing of big data and massive data, storage access is complicated, efficiency is reduced, and the computing resources and consumption of storage access process will also increase. (i.e. high computational cost, excessive consumption of computer processing resources, and long time)

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