This documentation describes using the convert processor in OpenSearch ingest pipelines. Consider using the Data Prepper convert_entry_type processor, which runs outside the OpenSearch cluster, if your use case involves large or complex datasets.
Convert processor
The convert processor converts a field in a document to a different type, for example, a string to an integer or an integer to a string. For an array field, all values in the array are converted.
Syntax
The following is the syntax for the convert processor:
{
"convert": {
"field": "field_name",
"type": "type-value"
}
}
Configuration parameters
The following table lists the required and optional parameters for the convert processor.
| Parameter | Required/Optional | Description |
|---|---|---|
field | Required | The name of the field containing the data to be converted. |
type | Required | The type to convert the field value to. The supported types are integer, long, float, double, string, boolean, ip, and auto. If the type is boolean, then the value is set to true if the field value is a string true (ignoring case) and to false if the field value is a string false (ignoring case). Any other string value causes the processor to fail. If the type is set to ip, then this processor validates whether the field value adheres to the correct format for IPv4 or IPv6 addresses; if the value is invalid, an error is raised. If the type is set to auto, then the processor converts a string value to the first matching type in the following order: boolean, integer, long, float, and double. Because float is tried before double, a decimal string is always converted to a float, which can reduce precision. If the string doesn’t match any of these types, or the value isn’t a string, then the value isn’t changed. If target_field is specified, the unchanged value is still copied to target_field. If type isn’t one of the supported types, the pipeline is rejected. |
description | Optional | A brief description of the processor. |
if | Optional | A condition for running the processor. |
ignore_failure | Optional | Specifies whether the processor continues execution even if it encounters errors. If set to true, failures are ignored. Default is false. |
ignore_missing | Optional | Specifies whether the processor should ignore documents that do not contain the specified field. If set to true, the processor does not modify the document if the field does not exist or is null. Default is false. |
on_failure | Optional | A list of processors to run if the processor fails. |
tag | Optional | An identifier tag for the processor. Useful for debugging in order to distinguish between processors of the same type. For more information, see Using processor tags for monitoring and debugging. |
target_field | Optional | The name of the field in which to store the parsed data. If not specified, the value will be stored in the field field. Default is field. |
Using the processor
Follow these steps to use the processor in a pipeline.
Step 1: Create a pipeline
The following query creates a pipeline, named convert-price, that converts price to a floating-point number, stores the converted value in the price_float field, and sets the value to 0 if it is less than 0:
PUT _ingest/pipeline/convert-price
{
"description": "Pipeline that converts price to floating-point number and sets value to zero if price less than zero",
"processors": [
{
"convert": {
"field": "price",
"type": "float",
"target_field": "price_float"
}
},
{
"set": {
"field": "price",
"value": "0",
"if": "ctx.price_float < 0"
}
}
]
}
Step 2 (Optional): Test the pipeline
It is recommended that you test your pipeline before you ingest documents.
To test the pipeline, run the following query:
POST _ingest/pipeline/convert-price/_simulate
{
"docs": [
{
"_index": "testindex1",
"_id": "1",
"_source": {
"price": "-10.5"
}
}
]
}
Response
The following example response confirms that the pipeline is working as expected:
{
"docs": [
{
"doc": {
"_index": "testindex1",
"_id": "1",
"_source": {
"price_float": -10.5,
"price": "0"
},
"_ingest": {
"timestamp": "2023-08-22T15:38:21.180688799Z"
}
}
}
]
}
Step 3: Ingest a document
The following query ingests a document into an index named testindex1:
PUT testindex1/_doc/1?pipeline=convert-price
{
"price": "10.5"
}
Step 4 (Optional): Retrieve the document
To retrieve the document, run the following query:
GET testindex1/_doc/1
Converting values automatically
The following request uses the auto type to convert several string fields:
POST _ingest/pipeline/_simulate
{
"pipeline": {
"processors": [
{ "convert": { "field": "in_stock", "type": "auto" } },
{ "convert": { "field": "quantity", "type": "auto" } },
{ "convert": { "field": "weight_kg", "type": "auto" } },
{ "convert": { "field": "color", "type": "auto" } }
]
},
"docs": [
{
"_source": {
"in_stock": "TRUE",
"quantity": "42",
"weight_kg": "1.23456789",
"color": "dark gray"
}
}
]
}
The response shows that in_stock was converted to a Boolean and quantity was converted to an integer. The weight_kg value was converted to a float, so its precision was reduced. The color value doesn’t match any type, so it remains a string:
{
"docs": [
{
"doc": {
"_index": "_index",
"_id": "_id",
"_source": {
"in_stock": true,
"quantity": 42,
"weight_kg": 1.2345679,
"color": "dark gray"
},
"_ingest": {
"timestamp": "2026-10-14T19:42:37.458135758Z"
}
}
}
]
}