elasticsearch/docs/reference/mapping/types.asciidoc

[[mapping-types]]
== Field data types

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 <<analysis,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 support the same
search functionality but may have different space usage or performance
characteristics.

Currently, the only type family is `keyword`, which consists of the `keyword`,
`constant_keyword`, and `wildcard` field types. Other type families have only a
single field type. For example, the `boolean` type family consists of one field
type: `boolean`.


[discrete]
[[_core_datatypes]]
==== Common types

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


[discrete]
[[object-types]]
==== Objects and relational types

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


[discrete]
[[structured-data-types]]
==== Structured data types

<<range,Range>>::   Range types, such as `long_range`, `double_range`,
                    `date_range`, and `ip_range`.
<<ip,`ip`>>::       IPv4 and IPv6 addresses.
<<version,`version`>>::  Software versions. Supports https://semver.org/[Semantic Versioning]
precedence rules.
{plugins}/mapper-murmur3.html[`murmur3`]:: Compute and stores hashes of
values.


[discrete]
[[aggregated-data-types]]
==== Aggregate data types

<<histogram,`histogram`>>:: Pre-aggregated numerical values.


[discrete]
[[text-search-types]]
==== Text search types

<<text,`text`>>:: Analyzed, unstructured text.
{plugins}/mapper-annotated-text.html[`annotated-text`]:: Text containing special
markup. Used for identifying named entities.
<<completion-suggester,`completion`>>:: Used for auto-complete suggestions.
<<search-as-you-type,`search_as_you_type`>>:: `text`-like type for
as-you-type completion.
<<token-count,`token_count`>>:: A count of tokens in a text.


[discrete]
[[document-ranking-types]]
==== Document ranking types

<<dense-vector,`dense_vector`>>::   Records dense vectors of float values.
<<rank-feature,`rank_feature`>>::   Records a numeric feature to boost hits at
                                    query time.
<<rank-features,`rank_features`>>:: Records numeric features to boost hits at
                                    query time.


[discrete]
[[spatial_datatypes]]
==== Spatial data types

<<geo-point,`geo_point`>>::     Latitude and longitude points.
<<geo-shape,`geo_shape`>>::     Complex shapes, such as polygons.
<<point,`point`>>::             Arbitrary cartesian points.
<<shape,`shape`>>::             Arbitrary cartesian geometries.


[discrete]
[[other-types]]
==== Other types

<<percolator,`percolator`>>::   Indexes queries written in <<query-dsl,Query DSL>>.


[discrete]
[[types-array-handling]]
=== Arrays
In {es}, 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 <<array>>.

[discrete]
=== Multi-fields

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 <<analysis-standard-analyzer,`standard` analyzer>>, the
<<english-analyzer,`english`>> analyzer, and the
<<french-analyzer,`french` analyzer>>.

This is the purpose of _multi-fields_. Most field types support multi-fields
via the <<multi-fields>> parameter.

include::types/alias.asciidoc[]

include::types/array.asciidoc[]

include::types/binary.asciidoc[]

include::types/boolean.asciidoc[]

include::types/date.asciidoc[]

include::types/date_nanos.asciidoc[]

include::types/dense-vector.asciidoc[]

include::types/flattened.asciidoc[]

include::types/geo-point.asciidoc[]

include::types/geo-shape.asciidoc[]

include::types/histogram.asciidoc[]

include::types/ip.asciidoc[]

include::types/parent-join.asciidoc[]

include::types/keyword.asciidoc[]

include::types/nested.asciidoc[]

include::types/numeric.asciidoc[]

include::types/object.asciidoc[]

include::types/percolator.asciidoc[]

include::types/point.asciidoc[]

include::types/range.asciidoc[]

include::types/rank-feature.asciidoc[]

include::types/rank-features.asciidoc[]

include::types/search-as-you-type.asciidoc[]

include::types/shape.asciidoc[]

include::types/text.asciidoc[]

include::types/token-count.asciidoc[]

include::types/unsigned_long.asciidoc[]

include::types/version.asciidoc[]