[[attachment]]
=== Attachment processor
++++
<titleabbrev>Attachment</titleabbrev>
++++

The attachment processor lets Elasticsearch extract file attachments in common formats (such as PPT, XLS, and PDF) by
using the Apache text extraction library https://tika.apache.org/[Tika].

The source field must be a base64 encoded binary. If you do not want to incur
the overhead of converting back and forth between base64, you can use the CBOR
format instead of JSON and specify the field as a bytes array instead of a string
representation. The processor will skip the base64 decoding then.

[[using-attachment]]
==== Using the attachment processor in a pipeline

[[attachment-options]]
.Attachment options
[options="header"]
|======
| Name                   | Required  | Default          | Description
| `field`                | yes       | -                | The field to get the base64 encoded field from
| `target_field`         | no        | attachment       | The field that will hold the attachment information
| `indexed_chars`        | no        | 100000           | The number of chars being used for extraction to prevent huge fields. Use `-1` for no limit.
| `indexed_chars_field`  | no        | `null`           | Field name from which you can overwrite the number of chars being used for extraction. See `indexed_chars`.
| `properties`           | no        | all properties   | Array of properties to select to be stored. Can be `content`, `title`, `name`, `author`, `keywords`, `date`, `content_type`, `content_length`, `language`
| `ignore_missing`       | no        | `false`          | If `true` and `field` does not exist, the processor quietly exits without modifying the document
| `remove_binary`        | no        | `false`          | If `true`, the binary `field` will be removed from the document
| `resource_name`        | no        |                  | Field containing the name of the resource to decode. If specified, the processor passes this resource name to the underlying Tika library to enable https://tika.apache.org/1.24.1/detection.html#Resource_Name_Based_Detection[Resource Name Based Detection].
|======

[discrete]
[[attachment-json-ex]]
==== Example

If attaching files to JSON documents, you must first encode the file as a base64
string. On Unix-like systems, you can do this using a `base64` command:

[source,shell]
----
base64 -in myfile.rtf
----

The command returns the base64-encoded string for the file. The following base64
string is for an `.rtf` file containing the text `Lorem ipsum dolor sit amet`:
`e1xydGYxXGFuc2kNCkxvcmVtIGlwc3VtIGRvbG9yIHNpdCBhbWV0DQpccGFyIH0=`.

Use an attachment processor to decode the string and extract the file's
properties:

[source,console]
----
PUT _ingest/pipeline/attachment
{
  "description" : "Extract attachment information",
  "processors" : [
    {
      "attachment" : {
        "field" : "data"
      }
    }
  ]
}
PUT my-index-000001/_doc/my_id?pipeline=attachment
{
  "data": "e1xydGYxXGFuc2kNCkxvcmVtIGlwc3VtIGRvbG9yIHNpdCBhbWV0DQpccGFyIH0="
}
GET my-index-000001/_doc/my_id
----

The document's `attachment` object contains extracted properties for the file:

[source,console-result]
----
{
  "found": true,
  "_index": "my-index-000001",
  "_id": "my_id",
  "_version": 1,
  "_seq_no": 22,
  "_primary_term": 1,
  "_source": {
    "data": "e1xydGYxXGFuc2kNCkxvcmVtIGlwc3VtIGRvbG9yIHNpdCBhbWV0DQpccGFyIH0=",
    "attachment": {
      "content_type": "application/rtf",
      "language": "ro",
      "content": "Lorem ipsum dolor sit amet",
      "content_length": 28
    }
  }
}
----
// TESTRESPONSE[s/"_seq_no": \d+/"_seq_no" : $body._seq_no/ s/"_primary_term" : 1/"_primary_term" : $body._primary_term/]

NOTE: Keeping the binary as a field within the document might consume a lot of resources. It is highly recommended
      to remove that field from the document. Set `remove_binary` to `true` to automatically remove the field.

[[attachment-fields]]
==== Exported fields

The fields which might be extracted from a document are:

* `content`,
* `title`,
* `author`,
* `keywords`,
* `date`,
* `content_type`,
* `content_length`,
* `language`,
* `modified`,
* `format`,
* `identifier`,
* `contributor`,
* `coverage`,
* `modifier`,
* `creator_tool`,
* `publisher`,
* `relation`,
* `rights`,
* `source`,
* `type`,
* `description`,
* `print_date`,
* `metadata_date`,
* `latitude`,
* `longitude`,
* `altitude`,
* `rating`,
* `comments`

To extract only certain `attachment` fields, specify the `properties` array:

[source,console]
----
PUT _ingest/pipeline/attachment
{
  "description" : "Extract attachment information",
  "processors" : [
    {
      "attachment" : {
        "field" : "data",
        "properties": [ "content", "title" ]
      }
    }
  ]
}
----

NOTE: Extracting contents from binary data is a resource intensive operation and
      consumes a lot of resources. It is highly recommended to run pipelines
      using this processor in a dedicated ingest node.

[[attachment-cbor]]
==== Use the attachment processor with CBOR

To avoid encoding and decoding JSON to base64, you can instead pass CBOR data to
the attachment processor. For example, the following request creates the
`cbor-attachment` pipeline, which uses the attachment processor.

[source,console]
----
PUT _ingest/pipeline/cbor-attachment
{
  "description" : "Extract attachment information",
  "processors" : [
    {
      "attachment" : {
        "field" : "data"
      }
    }
  ]
}
----

The following Python script passes CBOR data to an HTTP indexing request that
includes the `cbor-attachment` pipeline. The HTTP request headers use a
`content-type` of `application/cbor`.

NOTE: Not all {es} clients support custom HTTP request headers.

[source,python]
----
import cbor2
import requests

file = 'my-file'
headers = {'content-type': 'application/cbor'}

with open(file, 'rb') as f:
  doc = {
    'data': f.read()
  }
  requests.put(
    'http://localhost:9200/my-index-000001/_doc/my_id?pipeline=cbor-attachment',
    data=cbor2.dumps(doc),
    headers=headers
  )
----

[[attachment-extracted-chars]]
==== Limit the number of extracted chars

To prevent extracting too many chars and overload the node memory, the number of chars being used for extraction
is limited by default to `100000`. You can change this value by setting `indexed_chars`. Use `-1` for no limit but
ensure when setting this that your node will have enough HEAP to extract the content of very big documents.

You can also define this limit per document by extracting from a given field the limit to set. If the document
has that field, it will overwrite the `indexed_chars` setting. To set this field, define the `indexed_chars_field`
setting.

For example:

[source,console]
--------------------------------------------------
PUT _ingest/pipeline/attachment
{
  "description" : "Extract attachment information",
  "processors" : [
    {
      "attachment" : {
        "field" : "data",
        "indexed_chars" : 11,
        "indexed_chars_field" : "max_size"
      }
    }
  ]
}
PUT my-index-000001/_doc/my_id?pipeline=attachment
{
  "data": "e1xydGYxXGFuc2kNCkxvcmVtIGlwc3VtIGRvbG9yIHNpdCBhbWV0DQpccGFyIH0="
}
GET my-index-000001/_doc/my_id
--------------------------------------------------

Returns this:

[source,console-result]
--------------------------------------------------
{
  "found": true,
  "_index": "my-index-000001",
  "_id": "my_id",
  "_version": 1,
  "_seq_no": 35,
  "_primary_term": 1,
  "_source": {
    "data": "e1xydGYxXGFuc2kNCkxvcmVtIGlwc3VtIGRvbG9yIHNpdCBhbWV0DQpccGFyIH0=",
    "attachment": {
      "content_type": "application/rtf",
      "language": "is",
      "content": "Lorem ipsum",
      "content_length": 11
    }
  }
}
--------------------------------------------------
// TESTRESPONSE[s/"_seq_no": \d+/"_seq_no" : $body._seq_no/ s/"_primary_term" : 1/"_primary_term" : $body._primary_term/]


[source,console]
--------------------------------------------------
PUT _ingest/pipeline/attachment
{
  "description" : "Extract attachment information",
  "processors" : [
    {
      "attachment" : {
        "field" : "data",
        "indexed_chars" : 11,
        "indexed_chars_field" : "max_size"
      }
    }
  ]
}
PUT my-index-000001/_doc/my_id_2?pipeline=attachment
{
  "data": "e1xydGYxXGFuc2kNCkxvcmVtIGlwc3VtIGRvbG9yIHNpdCBhbWV0DQpccGFyIH0=",
  "max_size": 5
}
GET my-index-000001/_doc/my_id_2
--------------------------------------------------

Returns this:

[source,console-result]
--------------------------------------------------
{
  "found": true,
  "_index": "my-index-000001",
  "_id": "my_id_2",
  "_version": 1,
  "_seq_no": 40,
  "_primary_term": 1,
  "_source": {
    "data": "e1xydGYxXGFuc2kNCkxvcmVtIGlwc3VtIGRvbG9yIHNpdCBhbWV0DQpccGFyIH0=",
    "max_size": 5,
    "attachment": {
      "content_type": "application/rtf",
      "language": "sl",
      "content": "Lorem",
      "content_length": 5
    }
  }
}
--------------------------------------------------
// TESTRESPONSE[s/"_seq_no": \d+/"_seq_no" : $body._seq_no/ s/"_primary_term" : 1/"_primary_term" : $body._primary_term/]


[[attachment-with-arrays]]
==== Using the attachment processor with arrays

To use the attachment processor within an array of attachments the
{ref}/foreach-processor.html[foreach processor] is required. This
enables the attachment processor to be run on the individual elements
of the array.

For example, given the following source:

[source,js]
--------------------------------------------------
{
  "attachments" : [
    {
      "filename" : "ipsum.txt",
      "data" : "dGhpcyBpcwpqdXN0IHNvbWUgdGV4dAo="
    },
    {
      "filename" : "test.txt",
      "data" : "VGhpcyBpcyBhIHRlc3QK"
    }
  ]
}
--------------------------------------------------
// NOTCONSOLE

In this case, we want to process the data field in each element
of the attachments field and insert
the properties into the document so the following `foreach`
processor is used:

[source,console]
--------------------------------------------------
PUT _ingest/pipeline/attachment
{
  "description" : "Extract attachment information from arrays",
  "processors" : [
    {
      "foreach": {
        "field": "attachments",
        "processor": {
          "attachment": {
            "target_field": "_ingest._value.attachment",
            "field": "_ingest._value.data"
          }
        }
      }
    }
  ]
}
PUT my-index-000001/_doc/my_id?pipeline=attachment
{
  "attachments" : [
    {
      "filename" : "ipsum.txt",
      "data" : "dGhpcyBpcwpqdXN0IHNvbWUgdGV4dAo="
    },
    {
      "filename" : "test.txt",
      "data" : "VGhpcyBpcyBhIHRlc3QK"
    }
  ]
}
GET my-index-000001/_doc/my_id
--------------------------------------------------

Returns this:

[source,console-result]
--------------------------------------------------
{
  "_index" : "my-index-000001",
  "_id" : "my_id",
  "_version" : 1,
  "_seq_no" : 50,
  "_primary_term" : 1,
  "found" : true,
  "_source" : {
    "attachments" : [
      {
        "filename" : "ipsum.txt",
        "data" : "dGhpcyBpcwpqdXN0IHNvbWUgdGV4dAo=",
        "attachment" : {
          "content_type" : "text/plain; charset=ISO-8859-1",
          "language" : "en",
          "content" : "this is\njust some text",
          "content_length" : 24
        }
      },
      {
        "filename" : "test.txt",
        "data" : "VGhpcyBpcyBhIHRlc3QK",
        "attachment" : {
          "content_type" : "text/plain; charset=ISO-8859-1",
          "language" : "en",
          "content" : "This is a test",
          "content_length" : 16
        }
      }
    ]
  }
}
--------------------------------------------------
// TESTRESPONSE[s/"_seq_no" : \d+/"_seq_no" : $body._seq_no/ s/"_primary_term" : 1/"_primary_term" : $body._primary_term/]


Note that the `target_field` needs to be set, otherwise the
default value is used which is a top level field `attachment`. The
properties on this top level field will contain the value of the
first attachment only. However, by specifying the
`target_field` on to a value on `_ingest._value` it will correctly
associate the properties with the correct attachment.
