Supported field types
You can specify data types for your fields when creating a mapping. The following table lists all data field types that OpenSearch supports.
Category | Field types and descriptions |
---|---|
Alias | alias: An additional name for an existing field. |
Binary | binary: A binary value in Base64 encoding. |
Numeric | A numeric value (byte , double , float , half_float , integer , long , unsigned_long, scaled_float , short ). |
Boolean | boolean: A Boolean value. |
Date | date: A date stored in milliseconds. date_nanos: A date stored in nanoseconds. |
IP | ip: An IP address in IPv4 or IPv6 format. |
Range | A range of values (integer_range , long_range , double_range , float_range , date_range , ip_range ). |
Object | object: A JSON object. nested: Used when objects in an array need to be indexed independently as separate documents. flat_object: A JSON object treated as a string. join: Establishes a parent-child relationship between documents in the same index. |
String | keyword: Contains a string that is not analyzed. text: Contains a string that is analyzed. token_count: Stores the number of analyzed tokens in a string. |
Autocomplete | completion: Provides autocomplete functionality through a completion suggester. search_as_you_type: Provides search-as-you-type functionality using both prefix and infix completion. |
Geographic | geo_point: A geographic point. geo_shape: A geographic shape. |
Rank | Boosts or decreases the relevance score of documents (rank_feature , rank_features ). |
k-NN vector | knn_vector: Allows indexing a k-NN vector into OpenSearch and performing different kinds of k-NN search. |
Percolator | percolator: Specifies to treat this field as a query. |
Arrays
There is no dedicated array field type in OpenSearch. Instead, you can pass an array of values into any field. All values in the array must have the same field type.
PUT testindex1/_doc/1
{
"number": 1
}
PUT testindex1/_doc/2
{
"number": [1, 2, 3]
}
Multifields
Multifields are used to index the same field differently. Strings are often mapped as text
for full-text queries and keyword
for exact-value queries.
Multifields can be created using the fields
parameter. For example, you can map a book title
to be of type text
and keep a title.raw
subfield of type keyword
.
PUT books
{
"mappings" : {
"properties" : {
"title" : {
"type" : "text",
"fields" : {
"raw" : {
"type" : "keyword"
}
}
}
}
}
}
Null value
Setting a field’s value to null
, an empty array, or an array of null
values makes this field equivalent to an empty field. Therefore, you cannot search for documents that have null
in this field.
To make a field searchable for null
values, you can specify its null_value
parameter in the index’s mappings. Then, all null
values passed to this field will be replaced with the specified null_value
.
The null_value
parameter must be of the same type as the field. For example, if your field is a string, the null_value
for this field must also be a string.
Example
Create a mapping to replace null
values in the emergency_phone
field with the string “NONE”:
PUT testindex
{
"mappings": {
"properties": {
"name": {
"type": "keyword"
},
"emergency_phone": {
"type": "keyword",
"null_value": "NONE"
}
}
}
}
Index three documents into testindex. The emergency_phone
fields of documents 1 and 3 contain null
, while the emergency_phone
field of document 2 has an empty array:
PUT testindex/_doc/1
{
"name": "Akua Mansa",
"emergency_phone": null
}
PUT testindex/_doc/2
{
"name": "Diego Ramirez",
"emergency_phone" : []
}
PUT testindex/_doc/3
{
"name": "Jane Doe",
"emergency_phone": [null, null]
}
Search for people who do not have an emergency phone:
GET testindex/_search
{
"query": {
"term": {
"emergency_phone": "NONE"
}
}
}
The response contains documents 1 and 3 but not document 2 because only explicit null
values are replaced with the string “NONE”:
{
"took" : 1,
"timed_out" : false,
"_shards" : {
"total" : 1,
"successful" : 1,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : {
"value" : 2,
"relation" : "eq"
},
"max_score" : 0.18232156,
"hits" : [
{
"_index" : "testindex",
"_type" : "_doc",
"_id" : "1",
"_score" : 0.18232156,
"_source" : {
"name" : "Akua Mansa",
"emergency_phone" : null
}
},
{
"_index" : "testindex",
"_type" : "_doc",
"_id" : "3",
"_score" : 0.18232156,
"_source" : {
"name" : "Jane Doe",
"emergency_phone" : [
null,
null
]
}
}
]
}
}
The _source
field still contains explicit null
values because it is not affected by the null_value
.