How does Elasticsearch work?
Elastic search (site) is a tool for open source search that has the capacity to handle large amounts of data in real time. It is used by companies such as Google, GitHub, Twitter, SoundClud, Yelp and Foursquare, for example.
Developed by Shay Bannon in 2010, the distributed search server is based on Apache Lucene and developed in Java using a common interface, JSON over HTTP. It has customers for major programming languages and was developed from scratch in order to be used distributed in cluster. The scalable tool is ideal for working with Big Data.
One of the most used features is the filter that uses cache to perform repeated searches. When performing a search that has already been conducted before, the tool already knows where the documents are, which ensures plenty of speed for carrying out searches for exact values. As for the search by queries, it is possible to rank results by relevance, creating greater convenience for the users.
Remember when you do a search on Google with a wrong term and it responds with “What do you mean?” This is a very useful resource in the Elasticsearch. In addition, it has the autofill feature to streamline the process of searching for users.
Among the full-text search engine main advantages are the availability of data in real time (inear-realtime), the high availability to handle large volumes of data and data storage as documents. It also has many other features like geolocation and analytics. That is, it is a powerful and flexible tool that offers a robust set of APIs and DSLs of queries.
