Service automatic generation and deployment method for data open system

Abstract

The invention relates to the technical field of Web data services, in particular to a service automatic generation and deployment method for a data open system. According to the method, a defined service description file is used, a management node automatically generates data service source code files and binary files of different formats according to the service description file, and services are automatically deployed into service nodes; if deployment is succeeded, portal nodes are informed, and the portal nodes automatically generate introduction pages of the data services according to the service description files of data and carry out deployment and demonstration. After the deployment is succeeded, the service nodes receive service requests of client sides, execute the previous automatically generated service codes, and feed back results. By the adoption of the service automatic generation and deployment method for the data open system, the development and deployment time of data services can be shortened effectively, and therefore data can be opened effectively; the expandability of system functions is increased, operations of the data services, data sources of the data services, coupling between formats of the data services can be eliminated, and the data services can be updated and evolved independently.

Description

technical field [0001] The invention relates to the technical field of Web data services, in particular to an automatic service generation and deployment method for an open data system. Background technique [0002] In the current era of data explosion, opening the data owned by organizations to the society as a service is an inevitable means to fully tap the value of big data. In the process of developing and deploying data services, the usual steps are: developers need to write different service code programs according to different service types, such as SOAP service in XML format, REST service in XML format or REST service in JSON format, etc. ; It is also necessary to write different data source access programs according to the different data sources of the service, such as relational databases, formatted files or external data services, etc.; then compile the source code into a two-level file, and package and deploy it to the data server cluster ; At the same time, the...

AI Technical Summary

Problems solved by technology

The above processes are all done manually, which is time-consuming, labor-intensive and has a lot of repetitive work, which is prone to errors and cannot meet the requirements of quickly generating and deploying data services in the era of big data, so as to open data efficiently; and due to data service operations and data service formats, data Sources are tightly coupled. Every time a new data service format or new type of data source is added, all codes need to be rewritten, and independent upgrades and evolutions cannot be achieved.

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