elasticsearch/docs/reference/ingest/processors/script.asciidoc

[[script-processor]]
=== Script Processor

Allows inline and stored scripts to be executed within ingest pipelines.

See <<modules-scripting-using, How to use scripts>> to learn more about writing scripts. The Script Processor
leverages caching of compiled scripts for improved performance. Since the
script specified within the processor is potentially re-compiled per document, it is important
to understand how script caching works. To learn more about
caching see <<modules-scripting-using-caching, Script Caching>>.

[[script-options]]
.Script Options
[options="header"]
|======
| Name                   | Required  | Default    | Description
| `lang`                 | no        | "painless" | The scripting language
| `id`                   | no        | -          | The stored script id to refer to
| `source`               | no        | -          | An inline script to be executed
| `params`               | no        | -          | Script Parameters
include::common-options.asciidoc[]
|======

One of `id` or `source` options must be provided in order to properly reference a script to execute.

You can access the current ingest document from within the script context by using the `ctx` variable.

The following example sets a new field called `field_a_plus_b_times_c` to be the sum of two existing
numeric fields `field_a` and `field_b` multiplied by the parameter param_c:

[source,js]
--------------------------------------------------
{
  "script": {
    "lang": "painless",
    "source": "ctx.field_a_plus_b_times_c = (ctx.field_a + ctx.field_b) * params.param_c",
    "params": {
      "param_c": 10
    }
  }
}
--------------------------------------------------
// NOTCONSOLE

It is possible to use the Script Processor to manipulate document metadata like `_index` and `_type` during
ingestion. Here is an example of an Ingest Pipeline that renames the index and type to `my_index` no matter what
was provided in the original index request:

[source,console]
--------------------------------------------------
PUT _ingest/pipeline/my_index
{
    "description": "use index:my_index and type:_doc",
    "processors": [
      {
        "script": {
          "source": """
            ctx._index = 'my_index';
            ctx._type = '_doc';
          """
        }
      }
    ]
}
--------------------------------------------------

Using the above pipeline, we can attempt to index a document into the `any_index` index.

[source,console]
--------------------------------------------------
PUT any_index/_doc/1?pipeline=my_index
{
  "message": "text"
}
--------------------------------------------------
// TEST[continued]

The response from the above index request:

[source,console-result]
--------------------------------------------------
{
  "_index": "my_index",
  "_type": "_doc",
  "_id": "1",
  "_version": 1,
  "result": "created",
  "_shards": {
    "total": 2,
    "successful": 1,
    "failed": 0
  },
  "_seq_no": 89,
  "_primary_term": 1,
}
--------------------------------------------------
// TESTRESPONSE[s/"_seq_no": \d+/"_seq_no" : $body._seq_no/ s/"_primary_term" : 1/"_primary_term" : $body._primary_term/]

In the above response, you can see that our document was actually indexed into `my_index` instead of
`any_index`. This type of manipulation is often convenient in pipelines that have various branches of transformation,
and depending on the progress made, indexed into different indices.