OpenSearch/docs/reference/mapping.asciidoc

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[[mapping]]
= Mapping
[partintro]
--
Mapping is the process of defining how a document, and the fields it contains,
are stored and indexed. For instance, use mappings to define:
* which string fields should be treated as full text fields.
* which fields contain numbers, dates, or geolocations.
* the <<mapping-date-format,format>> of date values.
* custom rules to control the mapping for
<<dynamic-mapping,dynamically added fields>>.
[float]
[[mapping-type]]
== Mapping Type
Each index has one _mapping type_ which determines how the document will be
indexed.
deprecated[6.0.0,See <<removal-of-types>>].
A mapping type has:
<<mapping-fields,Meta-fields>>::
Meta-fields are used to customize how a document's metadata associated is
treated. Examples of meta-fields include the document's
<<mapping-index-field,`_index`>>, <<mapping-type-field,`_type`>>,
<<mapping-id-field,`_id`>>, and <<mapping-source-field,`_source`>> fields.
<<mapping-types,Fields>> or _properties_::
A mapping type contains a list of fields or `properties` pertinent to the
document.
[float]
[[field-datatypes]]
== Field datatypes
Each field has a data `type` which can be:
* a simple type like <<text,`text`>>, <<keyword,`keyword`>>, <<date,`date`>>, <<number,`long`>>,
<<number,`double`>>, <<boolean,`boolean`>> or <<ip,`ip`>>.
* a type which supports the hierarchical nature of JSON such as
<<object,`object`>> or <<nested,`nested`>>.
* or a specialised type like <<geo-point,`geo_point`>>,
<<geo-shape,`geo_shape`>>, or <<completion-suggester,`completion`>>.
It is often useful to index the same field in different ways for different
purposes. For instance, a `string` field could be <<mapping-index,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 <<analysis-standard-analyzer,`standard` analyzer>>, the
<<english-analyzer,`english`>> analyzer, and the
<<french-analyzer,`french` analyzer>>.
This is the purpose of _multi-fields_. Most datatypes support multi-fields
via the <<multi-fields>> parameter.
[[mapping-limit-settings]]
[float]
=== Settings to prevent mappings explosion
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:
`index.mapping.total_fields.limit`::
The maximum number of fields in an index. Field and object mappings, as well as
field aliases count towards this limit. The default value is `1000`.
`index.mapping.depth.limit`::
The maximum depth for a field, which is measured as the number of inner
objects. For instance, if all fields are defined at the root object level,
then the depth is `1`. If there is one object mapping, then the depth is
`2`, etc. The default is `20`.
`index.mapping.nested_fields.limit`::
The maximum number of distinct `nested` mappings in an index, defaults to `50`.
`index.mapping.nested_objects.limit`::
The maximum number of `nested` JSON objects within a single document across
all nested types, defaults to 10000.
`index.mapping.field_name_length.limit`::
Setting for the maximum length of a field name. The default value is
Long.MAX_VALUE (no limit). This setting isn't really something that addresses
mappings explosion but might still be useful if you want to limit the field length.
It usually shouldn't be necessary to set this setting. The default is okay
unless a user starts to add a huge number of fields with really long names.
[float]
== Dynamic mapping
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,`object`>> and <<nested,`nested`>> fields.
The <<dynamic-mapping,dynamic mapping>> rules can be configured to customise
the mapping that is used for new fields.
[float]
== Explicit mappings
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-mapping,create an index>> and
<<add-field-mapping,add fields to an existing index>>.
[float]
[[create-mapping]]
== Create an index with an explicit mapping
You can use the <<indices-create-index,create index>> API to create a new index
with an explicit mapping.
[source,console]
----
PUT /my-index
{
"mappings": {
"properties": {
"age": { "type": "integer" }, <1>
"email": { "type": "keyword" }, <2>
"name": { "type": "text" } <3>
}
}
}
----
<1> Creates `age`, an <<number,`integer`>> field
<2> Creates `email`, a <<keyword,`keyword`>> field
<3> Creates `name`, a <<text,`text`>> field
[float]
[[add-field-mapping]]
== Add a field to an existing mapping
You can use the <<indices-put-mapping, 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
<<mapping-index,`index`>> mapping parameter value of `false`. This means values
for the `employee-id` field are stored but not indexed or available for search.
[source,console]
----
PUT /my-index/_mapping
{
"properties": {
"employee-id": {
"type": "keyword",
"index": false
}
}
}
----
// TEST[continued]
[float]
[[update-mapping]]
=== Update the mapping of a field
include::{docdir}/indices/put-mapping.asciidoc[tag=put-field-mapping-exceptions]
[float]
[[view-mapping]]
== View the mapping of an index
You can use the <<indices-get-mapping, get mapping>> API to view the mapping of
an existing index.
[source,console]
----
GET /my-index/_mapping
----
// TEST[continued]
The API returns the following response:
[source,console-result]
----
{
"my-index" : {
"mappings" : {
"properties" : {
"age" : {
"type" : "integer"
},
"email" : {
"type" : "keyword"
},
"employee-id" : {
"type" : "keyword",
"index" : false
},
"name" : {
"type" : "text"
}
}
}
}
}
----
[float]
[[view-field-mapping]]
== View the mapping of specific fields
If you only want to view the mapping of one or more specific fields, you can use
the <<indices-get-field-mapping, 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.
[source,console]
----
GET /my-index/_mapping/field/employee-id
----
// TEST[continued]
The API returns the following response:
[source,console-result]
----
{
"my-index" : {
"mappings" : {
"employee-id" : {
"full_name" : "employee-id",
"mapping" : {
"employee-id" : {
"type" : "keyword",
"index" : false
}
}
}
}
}
}
----
--
include::mapping/removal_of_types.asciidoc[]
include::mapping/types.asciidoc[]
include::mapping/fields.asciidoc[]
include::mapping/params.asciidoc[]
include::mapping/dynamic-mapping.asciidoc[]