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Field data typesedit

Each field has a field data type, or field type. This type indicates the kind of data the field contains, such as strings or boolean values, and its intended use. For example, you can index strings to both text and keyword fields. However, text field values are analyzed for full-text search while keyword strings are left as-is for filtering and sorting.

Field types are grouped by family. Types in the same family have exactly the same search behavior but may have different space usage or performance characteristics.

Currently, there are two type families, keyword and text. Other type families have only a single field type. For example, the boolean type family consists of one field type: boolean.

Common typesedit

binary
Binary value encoded as a Base64 string.
boolean
true and false values.
Keywords
The keyword family, including keyword, constant_keyword, and wildcard.
Numbers
Numeric types, such as long and double, used to express amounts.
Dates
Date types, including date and date_nanos.
alias
Defines an alias for an existing field.

Objects and relational typesedit

object
A JSON object.
flattened
An entire JSON object as a single field value.
nested
A JSON object that preserves the relationship between its subfields.
join
Defines a parent/child relationship for documents in the same index.

Structured data typesedit

Range
Range types, such as long_range, double_range, date_range, and ip_range.
ip
IPv4 and IPv6 addresses.
version
Software versions. Supports Semantic Versioning precedence rules.
murmur3
Compute and stores hashes of values.

Aggregate data typesedit

aggregate_metric_double
Pre-aggregated metric values.
histogram
Pre-aggregated numerical values in the form of a histogram.

Text search typesedit

text fields
The text family, including text and match_only_text. Analyzed, unstructured text.
annotated-text
Text containing special markup. Used for identifying named entities.
completion
Used for auto-complete suggestions.
search_as_you_type
text-like type for as-you-type completion.
token_count
A count of tokens in a text.

Document ranking typesedit

dense_vector
Records dense vectors of float values.
sparse_vector
Records sparse vectors of float values.
rank_feature
Records a numeric feature to boost hits at query time.
rank_features
Records numeric features to boost hits at query time.

Spatial data typesedit

geo_point
Latitude and longitude points.
geo_shape
Complex shapes, such as polygons.
point
Arbitrary cartesian points.
shape
Arbitrary cartesian geometries.

Other typesedit

percolator
Indexes queries written in Query DSL.

Arraysedit

In Elasticsearch, arrays do not require a dedicated field data type. Any field can contain zero or more values by default, however, all values in the array must be of the same field type. See Arrays.

Multi-fieldsedit

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

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

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