opensearch-docs-cn/_ingest-pipelines/processors/csv.md

layout	title	parent	nav_order	redirect_from
default	CSV	Ingest processors	40	/api-reference/ingest-apis/processors/csv/

CSV

Introduced 1.0 {: .label .label-purple }

The csv processor is used to parse CSVs and store them as individual fields in a document. The processor ignores empty fields.

Example

The following is the syntax for the csv processor:

{
  "csv": {
    "field": "field_name",
    "target_fields": ["field1, field2, ..."]
  }
}

{% include copy-curl.html %}

Configuration parameters

The following table lists the required and optional parameters for the csv processor.

Parameter	Required	Description
field	Required	The name of the field that contains the data to be converted. Supports template snippets.
target_fields	Required	The name of the field in which to store the parsed data.
description	Optional	A brief description of the processor.
empty_value	Optional	Represents optional parameters that are not required or are not applicable.
if	Optional	A condition for running this processor.
ignore_failure	Optional	If set to true, failures are ignored. Default is false.
ignore_missing	Optional	If set to true, the processor will not fail if the field does not exist. Default is true.
on_failure	Optional	A list of processors to run if the processor fails.
quote	Optional	The character used to quote fields in the CSV data. Default is ".
separator	Optional	The delimiter used to separate the fields in the CSV data. Default is ,.
tag	Optional	An identifier tag for the processor. Useful for debugging to distinguish between processors of the same type.
trim	Optional	If set to true, the processor trims white space from the beginning and end of the text. Default is false.

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 csv-processor, that splits resource_usage into three new fields named cpu_usage, memory_usage, and disk_usage:

PUT _ingest/pipeline/csv-processor
{
  "description": "Split resource usage into individual fields",
  "processors": [
    {
      "csv": {
        "field": "resource_usage",
        "target_fields": ["cpu_usage", "memory_usage", "disk_usage"],
        "separator": ","
      }
    }
  ]
}

{% include copy-curl.html %}

Step 2 (Optional): Test the pipeline.

It is recommended that you test your pipeline before you ingest documents. {: .tip}

To test the pipeline, run the following query:

POST _ingest/pipeline/csv-processor/_simulate
{
  "docs": [
    {
      "_index": "testindex1",
      "_id": "1",
      "_source": {
        "resource_usage": "25,4096,10",
        "memory_usage": "4096",
        "disk_usage": "10",
        "cpu_usage": "25"
      }
    }
  ]
}

{% include copy-curl.html %}

Response

The following example response confirms that the pipeline is working as expected:

{
  "docs": [
    {
      "doc": {
        "_index": "testindex1",
        "_id": "1",
        "_source": {
          "memory_usage": "4096",
          "disk_usage": "10",
          "resource_usage": "25,4096,10",
          "cpu_usage": "25"
        },
        "_ingest": {
          "timestamp": "2023-08-22T16:40:45.024796379Z"
        }
      }
    }
  ]
}

Step 3: Ingest a document.

The following query ingests a document into an index named testindex1:

PUT testindex1/_doc/1?pipeline=csv-processor
{
  "resource_usage": "25,4096,10"
}

{% include copy-curl.html %}

Step 4 (Optional): Retrieve the document.

To retrieve the document, run the following query:

GET testindex1/_doc/1

{% include copy-curl.html %}