PaaS architecture-based statistical graph data real-time calculation system and method

Abstract

The invention relates to a PaaS architecture-based statistical graph data real-time calculation system and method. The method comprises the steps that total calculation is performed on a defined indexrule through an offline service, and factors influencing an index result are stored in a database; the real-time service compares the details of the user business data change with the factors influencing the index result, selects the fields influenced by the business data change for incremental computation, and updates the data in real time; and performing total calculation within fixed time every day to finish analysis. According to the method, based on a PaaS-based architecture and a general table design concept, a user can define statistical indexes of any field of any object, the universality is good, and the operation is flexible. According to the invention, the event-driven calculation model is established based on the user data change, so that the calculation frequency and the resource consumption are reduced. And the updating time of the index data reaches a minute level, so that the user experience is optimized.

Description

technical field [0001] The present invention relates to the technical field of data statistical analysis, in particular to a system and method for real-time calculation of statistical graph data based on PaaS architecture. Background technique [0002] More and more fields now require big data analysis. For example, the financial industry needs to use big data systems combined with VaR (value at risk) or machine learning solutions for credit risk control. Various IOT scenarios require big data systems to continuously aggregate and analyze time series data. , major technology companies need to establish a big data analysis platform and so on. The data analysis that supports the needs of these scenarios spans real-time data and historical data. It requires both low-latency real-time data analysis and comprehensive data analysis of historical data. At present, enterprises are using statistical charts to analyze data. When there are the following problems: [0003] 1. The defi...

AI Technical Summary

Problems solved by technology

[0003] 1. The definition of various indicators of statistical charts is not flexible enough, the indicators that can be configured are limited, and it is difficult to support analysis for custom objects

[0004] 2. Usually, the data update strategy of statistical charts is updated every other day. If the data update time is too long, the data analysis work will lag behind.

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