ERWIN model software updating method and device

Abstract

The invention provides an ERWIN model software updating method. The method includes steps of temporarily storing copy of ERD (ERWIN data) of old version to each local equipment, comparing the ERD of old and new versions on the local equipment to obtain modification lists of various inlaid objects, combining the modification lists of the local equipment and updating the ERD. By parallelly processing updating of the ERD, updating efficiency is remarkably improved for occasions of high-capacity updating. Besides, the invention further provides a corresponding device. By the ERWIN model software updating method and device, parallel updating of the large-scale ERWIN model is realized, and parallel data processing speed and accuracy can be improved.

Description

technical field [0001] The present invention relates to the field of computer software, more specifically, to a method and device for updating ERWIN model software. Background technique [0002] ERWIN is one of the most widely used modeling tools at home and abroad. Its full name is AllFuusin ERwin Data Modeler. It is a data modeling tool under the AllFuusin brand of CA company and supports all mainstream database systems. When the ERWIN model reaches a certain scale, especially when it involves parallel development of multiple subject domains (for example, involving more than 100 subject domains), the maintenance and management of ERWIN model files is very difficult. Taking China Construction Bank Corporation as an example, the enterprise-level ERD model file has exceeded 90 megabytes, containing more than 100 subject domains, more than 2,000 entities, more than 20,000 attributes, and nearly 5,000 domains, and receives upstream and downstream data every day Various types o...

AI Technical Summary

Problems solved by technology

Taking China Construction Bank Corporation as an example, the enterprise-level ERD model file has exceeded 90 megabytes, containing more than 100 subject domains, more than 2,000 entities, more than 20,000 attributes, and nearly 5,000 domains, and receives upstream and downstream data every day Various types of data requirements are proposed, and in such a large-scale application scenario, the processing efficiency of manual update and maintenance operations is relatively low

In addition, there are various interrelationships between model data, and ERWIN itself cannot intelligently judge the update sequence of each built-in object. If it is processed by manual judgment, the efficiency is low and the probability of error is high

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