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Mapping
You can define how documents and their fields are stored and indexed by creating a mapping.
If you’re just starting to build out your cluster and data, you may not know exactly how your data should be stored. In those cases, you can use dynamic mappings, which tell OpenSearch to dynamically add data and its fields. However, if you know exactly what types your data falls under and want to enforce that standard, then you can use explicit mappings.
For example, if you want to indicate that year
should be of type text
instead of an integer
, and age
should be an integer
, you can do so with explicit mappings. Using dynamic mapping OpenSearch might interpret both year
and age
as integers.
This section provides an example for how to create an index mapping, and how to add a document to it that will get ip_range validated.
Table of contents
Dynamic mapping
When you index a document, OpenSearch adds fields automatically with dynamic mapping. You can also explicitly add fields to an index mapping.
Dynamic mapping types
Type | Description |
---|---|
null | A null field can’t be indexed or searched. When a field is set to null, OpenSearch behaves as if that field has no values. |
boolean | OpenSearch accepts true and false as boolean values. An empty string is equal to false. |
float | A single-precision 32-bit floating point number. |
double | A double-precision 64-bit floating point number. |
integer | A signed 32-bit number. |
object | Objects are standard JSON objects, which can have fields and mappings of their own. For example, a movies object can have additional properties such as title , year , and director . |
array | Arrays in OpenSearch can only store values of one type, such as an array of just integers or strings. Empty arrays are treated as though they are fields with no values. |
text | A string sequence of characters that represent full-text values. |
keyword | A string sequence of structured characters, such as an email address or ZIP code. |
date detection string | Enabled by default, if new string fields match a date’s format, then the string is processed as a date field. For example, date: "2012/03/11" is processed as a date. |
numeric detection string | If disabled, OpenSearch may automatically process numeric values as strings when they should be processed as numbers. When enabled, OpenSearch can process strings into long , integer , short , byte , double , float , half_float , scaled_float , and unsigned_long . Default is disabled. |
Explicit mapping
If you know exactly what your field data types need to be, you can specify them in your request body when creating your index.
PUT sample-index1
{
"mappings": {
"properties": {
"year": { "type" : "text" },
"age": { "type" : "integer" },
"director":{ "type" : "text" }
}
}
}
Response
{
"acknowledged": true,
"shards_acknowledged": true,
"index": "sample-index1"
}
To add mappings to an existing index or data stream, you can send a request to the _mapping
endpoint using the PUT
or POST
HTTP method:
POST sample-index1/_mapping
{
"properties": {
"year": { "type" : "text" },
"age": { "type" : "integer" },
"director":{ "type" : "text" }
}
}
You cannot change the mapping of an existing field, you can only modify the field’s mapping parameters.
Mapping example usage
The following example shows how to create a mapping to specify that OpenSearch should ignore any documents with malformed IP addresses that do not conform to the ip
data type. You accomplish this by setting the ignore_malformed
parameter to true
.
Create an index with an ip
mapping
To create an index, use a PUT request:
PUT /test-index
{
"mappings" : {
"properties" : {
"ip_address" : {
"type" : "ip",
"ignore_malformed": true
}
}
}
}
You can add a document that has a malformed IP address to your index:
PUT /test-index/_doc/1
{
"ip_address" : "malformed ip address"
}
This indexed IP address does not throw an error because ignore_malformed
is set to true.
You can query the index using the following request:
GET /test-index/_search
The response shows that the ip_address
field is ignored in the indexed document:
{
"took": 14,
"timed_out": false,
"_shards": {
"total": 1,
"successful": 1,
"skipped": 0,
"failed": 0
},
"hits": {
"total": {
"value": 1,
"relation": "eq"
},
"max_score": 1,
"hits": [
{
"_index": "test-index",
"_id": "1",
"_score": 1,
"_ignored": [
"ip_address"
],
"_source": {
"ip_address": "malformed ip address"
}
}
]
}
}
Get a mapping
To get all mappings for one or more indexes, use the following request:
GET <index>/_mapping
In the above request, <index>
may be an index name or a comma-separated list of index names.
To get all mappings for all indexes, use the following request:
GET _mapping
To get a mapping for a specific field, provide the index name and the field name:
GET _mapping/field/<fields>
GET /<index>/_mapping/field/<fields>
Both <index>
and <fields>
can be specified as one value or a comma-separated list.
For example, the following request retrieves the mapping for the year
and age
fields in sample-index1
:
GET sample-index1/_mapping/field/year,age
The response contains the specified fields:
{
"sample-index1" : {
"mappings" : {
"year" : {
"full_name" : "year",
"mapping" : {
"year" : {
"type" : "text"
}
}
},
"age" : {
"full_name" : "age",
"mapping" : {
"age" : {
"type" : "integer"
}
}
}
}
}
}