Metadata model-based search method and search device based on metadata model

Abstract

The invention discloses a metadata model-based search method and a search device based on a metadata model. The search method based on the metadata model comprises the steps of mapping the field in the user document into an index field through the metadata model; carrying out schema dynamic matching on the index field to obtain a query result document; mapping the query result document to the field in the user document by the metadata model. Through the technical scheme, when the user document type changes, the metadata model is directly updated, the related configurations in the index server are not needed to be updated, and the reloading is saved, so the updating complexity is reduced, the development becomes more simple and efficient, the purpose of less resources and more stable service is achieved.

Description

technical field [0001] The present invention relates to the field of computer technology, in particular to a metadata model-based retrieval method and a metadata model-based retrieval device. Background technique [0002] At present, the function of retrieval is to retrieve and provide the content that the user most wants under the premise of a keyword given by the user. However, with the development of cloud application technology, more and more applications are deployed on the cloud. At the same time, with the increase in the number of users, the application data is also increasing. Simply using the search function in the database will not only achieve Not good, it will also affect the use of other functions of the database. For this reason, developers generally use independent servers to build search services independently. [0003] However, in this solution, the deployment and maintenance costs of a single application are too high, and the development requires too much ...

AI Technical Summary

Problems solved by technology

However, with the development of cloud application technology, more and more applications are deployed on the cloud. At the same time, with the increase in the number of users, the application data is also increasing. Simply using the search function in the database will not only achieve Not good, it will also affect the use of other functions of the database. For this reason, developers generally use independent servers to build search services separately

[0003] However, in this solution, the deployment and maintenance costs of a single application are too high, and the development requires too much time and effort. In the cloud environment, if the developers of each application use their own services, the deployment cluster must be used Not to mention multiple servers, during the development process, users need to keep the application information consistent with the fields defined by the schema (Extensible Markup Language Architecture) of Solr (an independent enterprise-level search application). When the application changes, It is necessary to modify the schema-related information in the cluster synchronously and reload the modified configuration. This process is extremely complicated. If one of the steps is missed, the update index and query will fail

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