Elasticsearch is an open-source and standalone database server. Generally, it is used for full-text-search and analysis. It takes a lot of data from various sources and stores it in a sophisticated format that is highly optimized for language-based searches. Guide of ElasticSearch, Elasticsearch uses Apache Lucene at its core for indexing and searching. Since Lucene is just a library; working with it is really complex. But you don’t have to worry about it as Elasticsearch hides all the complexities by providing access to the API. These API is in the form of an HTTP Restful API that uses JSON as the data exchange format. Using Elasticsearch you can store, search, and analyze big volumes of data in a quick and efficient manner. It is especially useful while dealing with semi-structured data that is natural language. We are Complete Guide of ElasticSearch
It is a document-oriented database designed to store, retrieve, and manage data. It is widely used by plenty of big companies, due to the consistency of the core product and a wide number of tools added to it every year.
Guide of ElasticSearch is a product of the company name is Elastic, which was founded in 2012. Elasticsearch is an open-source product along with Logstash, Kibana, and Beats. Guide of ElasticSearch: Features and Advantages.
Elasticsearch features
- Index API – Used to document the Index
- Get API – Used to retrieve the document
- Search API – Used to submit your query and get the result
- Put Mapping API – Used to override default choices and define our own mapping
Key concepts of Elasticsearch
Index
Index is a collection of documents having similar characteristics. It stores the data in one or more indices using SQL analogies. It is used to store and read the documents from it. In Elasticsearch, an index is identified by a unique name and must be in all lowercase. This name is then used to refer to a particular index while performing various activities on the documents present in it. In a cluster, there can be a number of indexes.
Document
A document is a basic unit of information which we can index. These documents consist of different fields and each of these fields is identified by its name and can contain one or more values. These documents are schema-free and may have a different set of fields. This document is a JSON (JavaScript Object Notation). Within an index n number of documents can be stored.
Type
In Elasticsearch, a type is defined for documents that have a common set of fields. It is a logical category/ partition of an index whose semantics is completely up to the user. You can also define more than one type within an index.
Node
It is a single instance of the Elasticsearch server which stores the data. It participates in the cluster’s indexing and searching capabilities. A node is identified by a name. By default, a random Universally Unique IDentifier (UUID) is assigned to the node at the startup. This name is used for administration purposes. You identify which servers in your network correspond to which nodes in your Elasticsearch cluster using these names.
Cluster
A cluster is a collection of one or more Elasticsearch servers that work together. It holds the entire data and provides easy indexing and search capabilities across all the nodes. This distributed nature grant the easy handling of data that is too large for a single node to handle on its own. Like a node, a cluster is also identified by a unique name. By default, the name is “Elasticsearch”. A node can only be part of a cluster if the node is set up to join the cluster by its name and that’s why the name of the cluster is very important.
Shards
Using a cluster, you can store large volumes of information that can exceed the abilities of a single server. Elasticsearch allows you to divide your index into multiple pieces which are called shards. so many shards needed can be defined while creating an index. Every shard is a fully-functional and independent “index” which can be hosted on any node within the cluster.
Replicas
To avoid any kind of accidental failures, such as a shard or node going offline for some Replicas. It’s always recommended having a failover mechanism. Thus as a solution, Elasticsearch provides replicas. Replicas are just an additional copy of a shard and can be used for queries just as the original shards.
Advantages
Scalability
Elasticsearch is very easy to scale and reliable as well. It is a very important feature which helps to simplify the complex architectures and save time during the implementation of projects.
Speed
Elasticsearch is used for distributed inverted indices to find the best matches for your full-text searches. It makes really fast even when searching for very large data sets.
Easy to use API
Elasticsearch provides simple RESTful APIs and uses schema-free JSON documents which make searching, indexing, and querying the data really easy.
Multilingual
One of the most important features Elasticsearch has is, it is multilingual. It supports a wide variety of documents written in different languages like Arabic, Brazilian, Chinese, English, French, Hindi, Korean etc.
Document-Oriented
Elasticsearch stores complex entities as structured JSON documents and indexes all fields by default to make the data searchable. Since there are no rows and columns of data, you can perform complex full-text search easily.
Auto-completion
Elasticsearch also provides auto-completion functionality. By predicting the word using very few characters, auto-completion speeds up human-computer interaction.
Schema-Free
Elasticsearch is schema-free as it accepts JSON documents. It tries to detect the data structure, index the data and thus makes the data searchable.
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