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JSON processor
The json
processor serializes a string value field into a map of maps, which can be useful for various data processing and enrichment tasks.
The following is the syntax for the json
processor:
{
"processor": {
"json": {
"field": "<field_name>",
"target_field": "<target_field_name>",
"add_to_root": <boolean>
}
}
}
Configuration parameters
The following table lists the required and optional parameters for the json
processor.
Parameter | Required/Optional | Description |
---|---|---|
field | Required | The name of the field containing the JSON-formatted string to be deserialized. |
target_field | Optional | The name of the field in which the deserialized JSON data is stored. When not provided, the data is stored in the field field. If target_field exists, its existing value is overwritten with the new JSON data. |
add_to_root | Optional | A Boolean flag that determines whether the deserialized JSON data should be added to the root of the document (true ) or stored in the target_field (false ). If add_to_root is true , then target-field is invalid. Default value is false . |
description | Optional | A description of the processor’s purpose or configuration. |
if | Optional | Specifies to conditionally execute the processor. |
ignore_failure | Optional | Specifies to ignore processor failures. See Handling pipeline failures. |
on_failure | Optional | Specifies a list of processors to run if the processor fails during execution. These processors are executed in the order they are specified. |
tag | Optional | An identifier tag for the processor. Useful for debugging in order to distinguish between processors of the same type. |
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 my-json-pipeline
that uses the json
processor to process JSON data and enrich the documents with additional information:
PUT _ingest/pipeline/my-json-pipeline
{
"description": "Example pipeline using the JsonProcessor",
"processors": [
{
"json": {
"field": "raw_data",
"target_field": "parsed_data"
"on_failure": [
{
"set": {
"field": "error_message",
"value": "Failed to parse JSON data"
}
},
{
"fail": {
"message": "Failed to process JSON data"
}
}
]
}
},
{
"set": {
"field": "processed_timestamp",
"value": ""
}
}
]
}
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/my-json-pipeline/_simulate
{
"docs": [
{
"_source": {
"raw_data": "{\"name\":\"John\",\"age\":30,\"city\":\"New York\"}"
}
},
{
"_source": {
"raw_data": "{\"name\":\"Jane\",\"age\":25,\"city\":\"Los Angeles\"}"
}
}
]
}
Response
The following example response confirms that the pipeline is working as expected:
{
"docs": [
{
"doc": {
"_index": "_index",
"_id": "_id",
"_source": {
"processed_timestamp": "2024-05-30T15:24:48.064472090Z",
"raw_data": """{"name":"John","age":30,"city":"New York"}""",
"parsed_data": {
"name": "John",
"city": "New York",
"age": 30
}
},
"_ingest": {
"timestamp": "2024-05-30T15:24:48.06447209Z"
}
}
},
{
"doc": {
"_index": "_index",
"_id": "_id",
"_source": {
"processed_timestamp": "2024-05-30T15:24:48.064543006Z",
"raw_data": """{"name":"Jane","age":25,"city":"Los Angeles"}""",
"parsed_data": {
"name": "Jane",
"city": "Los Angeles",
"age": 25
}
},
"_ingest": {
"timestamp": "2024-05-30T15:24:48.064543006Z"
}
}
}
]
}
Step 3: Ingest a document
The following query ingests a document into an index named my-index
:
POST my-index/_doc?pipeline=my-json-pipeline
{
"raw_data": "{\"name\":\"John\",\"age\":30,\"city\":\"New York\"}"
}
Response
The response confirms that the document containing the JSON data from the raw_data
field was successfully indexed:
{
"_index": "my-index",
"_id": "mo8yyo8BwFahnwl9WpxG",
"_version": 1,
"result": "created",
"_shards": {
"total": 2,
"successful": 1,
"failed": 0
},
"_seq_no": 3,
"_primary_term": 2
}
Step 4 (Optional): Retrieve the document
To retrieve the document, run the following query:
GET my-index/_doc/1