integrating elastic search with mongodb using no-sql
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Insight about Elastic search
Elastic Search is an immensely extensive Open Source search designed for nearly real-time search. It
helps you to think through Herculean sized data. Elastic search is a type of distributed one. It indicates
that each index can further be split into Shards and those themselves can have their many clones or
none. Basic concepts of elastic search are NRT, Cluster, Node, Index, Type, Document, Shards & Replicas.
First of all download and install both the MongoDB and Elastic Search.
Introduction to the integration of MongoDB and Elastic search
Maneuvering over furthermore you have to grab your attention on versions of varied elements. The synthesis of Elastic Search with MongoDB through a River plugin is liable to transferring the flow of data.
Addition Of Plugins Considering The Suitable Version:
NOTE: Above configurations are provided relating Linux system.
Execute that command in terminal:
Once you install River plugin thereafter you have to start elasticsearch.bat file which is accessible in elastic search bin folder.
To view River MongoDB plugin you need to give the URL in the browser:
Configuring MongoDBThe only way to connect MongoDB and Elastic Search by exporting and then importing the data into the Elastic Search with the usage of the replication of the system of MongoDB.For a more detailed description here you will find complete instructions related to create MongoDB replica.A thorough description with complete instructions corresponding to the making of MongoDB and elastic search is provided as follows.
Create a new index running river:
Syntax:
Write the db Name, collection Name, index name , index type:Example:
View index data in elastic search:
View specific index detail by “id”:
Discussion had been carried out about “How to integrate Elastic Search and MongoDB ?”. Store large amount of schema-less data in mongoDB development and make data analytic and full text search using Elastic Search. MongoDB providing a big data solution for large enterprise application.
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