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In this article, we will understand Relevance Search in ElasticSearch using Kibana. Click here for a basic CRUD operation demon on ElasticSearch using Kibana . Relevance Search: In Elasticsearch relevance search means the output of the search can be done in 2 different ways like 'Precision', 'Recall'. The 'Precision' result means the most accurate results from the ElasticSearch. This means it fetches exact matches of the search value. So in this search output will be more accurate, but the total output results count might be very very less. Here all green color docs are more accurate documents for the search. Here all red color docs are either less accurate documents or not matching documents for the search. Here we can observe search results contain only accurate documents which means it is a 'Precision' result. The 'Recall' results mean more in the count of the output results because it fetches partially matched data along with accurate dat

In this article, we will understand the way to implement Elasticsearch CRUD operation using the Kibana tool. Elasticsearch: Elasticsearch is a distributed, free, and open search and analytics engine for all types of data, including textual, numerical, geospatial, structured, and unstructured. It provides simple REST APIs, distributed nature, speed, and scalability. Elasticsearch stores data in JSON format. so each JSON format data record in elastic search is called a document. So documents are queried or searched by the Index, Index holds the reference to respective documents. Elasticsearch use cases: Application Search Website Search Enterprise search Loggin and log analytics Infrastructure metrics and container monitoring Application performance monitoring Kibana: Kibana is a free and open frontend application that sits on top of the Elastic Stack, providing search and data visualization capabilities for data indexed in Elasticsearch. Run Elasticsearch And Kibana Docker Containe