Elasticsearch is a search engine that is built on top of the Apache Lucene library. It is designed to index and search large volumes of data quickly and efficiently.
When data is ingested into Elasticsearch, it is first divided into small chunks called shards. These shards are distributed across the nodes in the Elasticsearch cluster and stored in an inverted index, which is a data structure that allows for fast search and retrieval of data.
The inverted index is created by tokenizing the text of each document and creating a list of all the unique tokens (or terms) that appear in the document, along with the positions in the document where they appear. This allows Elasticsearch to efficiently search for specific terms within a document or set of documents.
Elasticsearch also uses a process called sharding to scale horizontally across multiple nodes in a cluster. This allows the index to be distributed and search requests to be executed in parallel, improving search performance and enabling Elasticsearch to handle large volumes of data.
In addition to the inverted index, Elasticsearch also uses a real-time search engine called Elasticsearch Query DSL to process search queries and return results. The Query DSL allows for complex search queries to be constructed using a JSON-based syntax and uses various query types, such as match, term, and range queries, to search for specific documents or groups of documents within the indexed data.
Overall, Elasticsearch combines the power of the inverted index and the Elasticsearch Query DSL to provide fast and efficient search capabilities for large volumes of data.