Elasticsearch is a NoSQL database. It is based on the Lucene search engine, and it is built with RESTful APIS. It offers simple deployment, maximum reliability, and easy management. It also provides advanced queries to perform detailed analysis and stores all the data centrally. It helps execute a quick search of the documents.
In an Elastic search, a document is a basic unit of information that can be indexed. It is expressed in JSON (key: value) pair. ‘{“user”: “nullcon”}’. Every single Document is associated with a type and a unique id.
Every index can be split into several shards to be able to distribute data. The shard is the atomic part of an index, which can be distributed over the cluster if you want to add more nodes.
The ELK Stack is a collection of three open-source products — Elasticsearch, Logstash, and Kibana. They are all developed, managed, and maintained by the company Elastic.
A Tokenizer breakdown fields which values of a document into a stream. Inverted indexes are created and updated by using these values. After that, these stream of values are stored in the document.
Mapping is a process that helps you define how a document is mapped to the search engine. Its searchable characteristics are included fields are tokenized as well as searchable.
Apache Lucene is an open-source information retrieval software library. It is originally written in Java language.
NRT is a full form of (Near Real-Time Search) platform. It is a near real-time search platform. It means there is a slight latency (mostly one second) from when you index a document until it becomes very searchable.
Ingest node is use for pre-process documents before the actual document indexing happens. It helps you to intercepts bulk and index requests. It also applies transformations, and then it passes the documents back to the bulk API and index.
The aggregations framework helps you to provide aggregated data based on a search query. It is based on simple building blocks known as aggregations. It can be composed to build complex summaries of the data.
Elasticsearch offers full Query DSL (Domain Specific Language) based on JSON to define queries.
Data nodes hold shards that handle indexed documents. They help you to execute data related CRUD and search aggregation operations etc. However, you need to Set node.data=true to make node as Data Node.
Dynamic mapping helps the user to index documents without unwanted configurations for the field name. Instead, it will be added automatically through the Elasticsearch with some custom rules.
Fuzzy search is a process in which web page document locations should be identified. That is resembling with the search argument. It also works when the argument is not relevant to the search correspondent for particular information.