Block chain-based data structure adaptive change upgrading method and device, equipment and product

Abstract

The invention discloses a block chain-based data structure adaptive change upgrading method. The method comprises the steps of receiving change parameters of a data structure; calling a data configuration transaction, and triggering a first smart contract and a second smart contract through the data configuration transaction, so that the first smart contract and the second smart contract generate a third smart contract including data structure change logic according to the change parameter; and calling a data upgrading transaction, and triggering a fourth smart contract through the data upgrading transaction, so that the fourth smart contract executes the data structure change logic in the third smart contract to complete adaptive change upgrading of the data structure. According to the method, human intervention in the data structure change process is greatly reduced, the labor cost is reduced, and the data structure change efficiency is improved; and the auditing performance of the data structure change process is realized.

Description

technical field [0001] The invention belongs to the technical field of block chains, and in particular relates to a block chain-based data structure self-adaptive change upgrade method, device, equipment and products. Background technique [0002] Data element (Data Element), also known as data element, is a data unit that describes its definition, identification, representation, and allowed values ​​with a set of attributes, such as fields in a data table in a database. Metadata (Meta Data), also known as intermediary data or relay data, is data used to describe other data (data about other data), or structured data (structured data) used to provide information about certain resources. The data element has its own metadata (Meta Data), which is used to describe the length, type, and value range of the data element, such as the field value length, field value type, and field value range of fields in the data table. [0003] The data structure of the data model is composed o...

AI Technical Summary

Problems solved by technology

[0005] 1) Manual customization of data structure change commands will result in high labor costs and low efficiency;

[0006] 2) There are uncontrollable risks in manually modifying the data structure of each database, and the data structure changes of each database are not uniform;

[0007] 3) There are no traceability and tamperability in the process of recording data structure changes in the form of logs, so auditing cannot be performed

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