Mapping

Mapping is the process of defining how a document, and the fields it contains, are stored and indexed. For instance, use mappings to define:

A mapping definition has:

Each field has a data type which can be:

It is often useful to index the same field in different ways for different purposes. For instance, a string field could be indexed as a text field for full-text search, and as a keyword field for sorting or aggregations. Alternatively, you could index a string field with the standard analyzer, the english analyzer, and the french analyzer.

This is the purpose of multi-fields. Most datatypes support multi-fields via the fields parameter.

Defining too many fields in an index is a condition that can lead to a mapping explosion, which can cause out of memory errors and difficult situations to recover from. This problem may be more common than expected. As an example, consider a situation in which every new document inserted introduces new fields. This is quite common with dynamic mappings. Every time a document contains new fields, those will end up in the index’s mappings. This isn’t worrying for a small amount of data, but it can become a problem as the mapping grows. The following settings allow you to limit the number of field mappings that can be created manually or dynamically, in order to prevent bad documents from causing a mapping explosion:

Fields and mapping types do not need to be defined before being used. Thanks to dynamic mapping, new field names will be added automatically, just by indexing a document. New fields can be added both to the top-level mapping type, and to inner object and nested fields.

The dynamic mapping rules can be configured to customise the mapping that is used for new fields.

You know more about your data than Elasticsearch can guess, so while dynamic mapping can be useful to get started, at some point you will want to specify your own explicit mappings.

You can create field mappings when you create an index and add fields to an existing index.

You can use the create index API to create a new index with an explicit mapping.

PUT /my-index
{
  "mappings": {
    "properties": {
      "age":    { "type": "integer" },  
      "email":  { "type": "keyword"  }, 
      "name":   { "type": "text"  }     
    }
  }
}

You can use the put mapping API to add one or more new fields to an existing index.

The following example adds employee-id, a keyword field with an index mapping parameter value of false. This means values for the employee-id field are stored but not indexed or available for search.

PUT /my-index/_mapping
{
  "properties": {
    "employee-id": {
      "type": "keyword",
      "index": false
    }
  }
}

Except for supported mapping parameters, you can’t change the mapping or field type of an existing field. Changing an existing field could invalidate data that’s already indexed.

If you need to change the mapping of a field, create a new index with the correct mapping and reindex your data into that index.

Renaming a field would invalidate data already indexed under the old field name. Instead, add an alias field to create an alternate field name.

You can use the get mapping API to view the mapping of an existing index.

GET /my-index/_mapping

The API returns the following response:

{
  "my-index" : {
    "mappings" : {
      "properties" : {
        "age" : {
          "type" : "integer"
        },
        "email" : {
          "type" : "keyword"
        },
        "employee-id" : {
          "type" : "keyword",
          "index" : false
        },
        "name" : {
          "type" : "text"
        }
      }
    }
  }
}

If you only want to view the mapping of one or more specific fields, you can use the get field mapping API.

This is useful if you don’t need the complete mapping of an index or your index contains a large number of fields.

The following request retrieves the mapping for the employee-id field.

GET /my-index/_mapping/field/employee-id

The API returns the following response:

{
  "my-index" : {
    "mappings" : {
      "employee-id" : {
        "full_name" : "employee-id",
        "mapping" : {
          "employee-id" : {
            "type" : "keyword",
            "index" : false
          }
        }
      }
    }
  }
}