Script Processor
editScript Processor
editAllows inline and stored scripts to be executed within ingest pipelines.
See 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 Script Caching.
Table 54. Script Options
Name | Required | Default | Description |
---|---|---|---|
|
no |
"painless" |
The scripting language |
|
no |
- |
The stored script id to refer to |
|
no |
- |
An inline script to be executed |
|
no |
- |
Script Parameters |
|
no |
- |
Conditionally execute this processor. |
|
no |
- |
Handle failures for this processor. See Handling Failures in Pipelines. |
|
no |
|
Ignore failures for this processor. See Handling Failures in Pipelines. |
|
no |
- |
An identifier for this processor. Useful for debugging and metrics. |
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:
{ "script": { "lang": "painless", "source": "ctx.field_a_plus_b_times_c = (ctx.field_a + ctx.field_b) * params.param_c", "params": { "param_c": 10 } } }
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:
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.
PUT any_index/_doc/1?pipeline=my_index { "message": "text" }
The response from the above index request:
{ "_index": "my_index", "_type": "_doc", "_id": "1", "_version": 1, "result": "created", "_shards": { "total": 2, "successful": 1, "failed": 0 }, "_seq_no": 89, "_primary_term": 1, }
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.