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:

Each index has one or more mapping types, which are used to divide the documents in an index into logical groups. User documents might be stored in a user type, and blog posts in a blogpost type.

[6.0.0] Deprecated in 6.0.0. See Removal of mapping types .

A mapping type 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 mapping types and 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 types and 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 mapping types and field mappings when you create an index, and you can add mapping types and fields to an existing index with the PUT mapping API.

Other than where documented, existing type and field mappings cannot be updated. Changing the mapping would mean invalidating already indexed documents. Instead, you should create a new index with the correct mappings and reindex your data into that index.

Mapping types are used to group fields, but the fields in each mapping type are not independent of each other. Fields with:

If a title field exists in both the user and blogpost mapping types, the title fields must have exactly the same mapping in each type. The only exceptions to this rule are the copy_to, dynamic, enabled, ignore_above, include_in_all, and properties parameters, which may have different settings per field.

Usually, fields with the same name also contain the same type of data, so having the same mapping is not a problem. When conflicts do arise, these can be solved by choosing more descriptive names, such as user_title and blog_title.

A mapping for the example described above could be specified when creating the index, as follows:

PUT my_index 
{
  "mappings": {
    "user": { 
      "_all":       { "enabled": false  }, 
      "properties": { 
        "title":    { "type": "text"  }, 
        "name":     { "type": "text"  }, 
        "age":      { "type": "integer" }  
      }
    },
    "blogpost": { 
      "_all":       { "enabled": false  }, 
      "properties": { 
        "title":    { "type": "text"  }, 
        "body":     { "type": "text"  }, 
        "user_id":  {
          "type":   "keyword" 
        },
        "created":  {
          "type":   "date", 
          "format": "strict_date_optional_time||epoch_millis"
        }
      }
    }
  }
}