Elastic search tutorial or what is elastic search in java and why it is very important we have shown in this video of code decode also we have covered most asked elastic search interview questions asked for experienced candidates
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What Is ElasticSearch?
Elasticsearch is a NoSQL database.
ElasticSearch is an open source Search Engine based on Apache Lucene as inverted Text Data structure and it is built with RESTful APIS.
We use it for Storing, searching and Managing
Logs
Search Backend with terrific speed and flexibility.
It mainly consist of
Indexes - similar to Database in relational Terms
Documents - Rows - JSON objects
Fields - Columns
It mainly has Read and write operation. you need to update this as soon as you update the main Database and Read it when FE needs Autocomplete feature.
Why ES ? Most common usage of ElasticSearch?
In Autocomplete in search Box FrontEnd.
If you hit Normal DB then Client will wait for a lot of time till it fetch the data and if it change again in worst case the time doubles again
Such a poor User Experience is not acceptable in User friendly apps.
Hence ElasticSearch came in for the Rescue.
Elasticsearch is a fast, distributed , reliable search engine:
What is a Cluster in Elasticsearch? Explain Node?
Cluster is a collection of single or multiple nodes that holds your entire data and offers centralized indexing and search abilities across all nodes.
A node is an elastic search Instance. It is created when an elasticsearch instance begins.
What is a document in ElasticSearch?
The document is very similar to a row in relational databases. Every document in the index possess different structure but has the same data type for respective fields.
MySQL = Databases = Tables = Columns/Rows
ElasticSearch = Indices = Types = Documents with Properties
Type : Type is a logical index partition whose semantics are dependent upon the user.
An Elasticsearch cluster can contain multiple Indices (databases), which in turn contain multiple Types (tables). These types hold multiple Documents (rows), and each document has Properties(columns). EG = University - (students, teachers, subjects) - all internal details of that type
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