In Elasticsearch, an index is structured as a collection of documents that have similar characteristics, such as the same data structure and type of content. Each document in an index is a JSON object that contains a set of key-value pairs representing the document’s fields and their values.
The structure of an Elasticsearch index is defined by its mapping, which specifies the types and properties of the fields in the index. The mapping is used to define the structure of the index when it is created, and it can be updated to add or modify fields in the index.
The mapping for an index includes the following information:
1. Field types: Each field in the index is assigned a data type, such as string, integer, or date.
2. Field properties: Each field can have additional properties that define how the field is indexed and searched. For example, a field can be marked as “analyzed” to allow for full-text search, or it can be marked as “not_analyzed” to allow for exact matches.
3. Dynamic mapping: Elasticsearch can automatically detect new fields in documents and add them to the mapping. Dynamic mapping can be configured to control how new fields are added to the mapping.
4. Sharding and replication: The mapping can specify the number of shards and replicas for the index, which determines how the index is distributed across the nodes in the Elasticsearch cluster.
Overall, the structure of an Elasticsearch index is defined by its mapping, which specifies the types and properties of the fields in the index. The mapping is used to organize and store large amounts of data in a way that allows for efficient indexing and searching, as well as scalability and fault tolerance.