Today, I read a magazine along with my morning tea and came across the word “ubiquitous.” Unknowingly my eyebrows went up with a doubt hitting my vocabulary list. Then I found out that it is one of my most commonly used words omnipresent through Google. Nowadays, it has evolved into something more than a search engine. Technically there are many search engines. And there is no rocket science involved in it. Search engines keep track of their customers’ surfing activities and share that data with marketers and other interested parties.
What is Elastic search?
Elasticsearch was created as an output of the third version of the compass by Shay Banon. He developed “a distributed solution from the ground up” and employed a standard interface, JSON via HTTP, that could be used by programs written in languages other than Java. Elasticsearch was launched in February 2010. It is a software that enables you to store, search easily, and analyse large amounts of data in near real-time, with responses arriving in milliseconds.
How does it work?
The best way to understand what is elasticsearch and how it works is to know the basic concept in what way it organizes the data and its back-end components. The basic or logical components are documents, indices, and inverted indexes. Documents are the basic units, and index is the collection of documents that are logically related. In Elasticsearch, an index is an inverted index, which is how all search engines operate. It’s a data structure that stores a mapping between information (such as words or integers) and their places in a document or series of documents.
On the other hand, backend components are clusters, nodes, shards, and replicas. Elasticsearch cluster is what gives it its power. A node is a storage device that also participates in the cluster’s indexing and search functions. Elasticsearch allows you to split the index into shards, which are smaller portions of the index. Replicas provide redundant copies of your data to defend against hardware failure and boost capacity to satisfy read demands such as document searches and retrieval.
Why is Elasticsearch preferable?
Elasticsearch is the most prominent and popular search engine. It uses the Lucene library as its foundation. It’s a full-text search engine with a distributed, multitenant capability, an HTTP web interface, and schema-free JSON documents. It is written in Java and is dual-licensed under the open-source Server-Side Public License and the Elastic license. Some sections are under the Elastic commercial license (source-available) L’elastique.
Elasticsearch is an important search engine that focuses on documents. It searches an index rather than the text directly, and it is possible to provide quick search results. It can be used in several use cases like search for an application, a website, or a company, Logging and Analysis of logs, Container monitoring and infrastructure metrics, Monitoring the performance of an application, Analysis and display of geospatial data, Analytical security, and Analytical business. It has made web services rapid and more effective, especially in business and information technology. The potential is increasing day by day, and so the productivity. Elasticsearch is super fast because it’s built on top of Lucane, it works amazingly at full-text-search, a document is indexed within a short time period sometimes within one second, I know it’s crazy!
Elasticsearch is super fast because it’s built on top of Lucane, it works amazingly at full-text-search, a document is indexed within a short time period sometimes within one second, I know it’s crazy!
