ingest-attachment.asciidoc

Ingest Attachment Processor Plugin

The ingest attachment plugin lets Elasticsearch extract file attachments in common formats (such as PPT, XLS, and PDF) by using the Apache text extraction library Tika.

You can use the ingest attachment plugin as a replacement for the mapper attachment plugin.

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.

install_remove.asciidoc

Using the Attachment Processor in a Pipeline

Table 1. Attachment options

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

For example, this:

PUT _ingest/pipeline/attachment
{
  "description" : "Extract attachment information",
  "processors" : [
    {
      "attachment" : {
        "field" : "data"
      }
    }
  ]
}
PUT my_index/_doc/my_id?pipeline=attachment
{
  "data": "e1xydGYxXGFuc2kNCkxvcmVtIGlwc3VtIGRvbG9yIHNpdCBhbWV0DQpccGFyIH0="
}
GET my_index/_doc/my_id

Returns this:

{
  "found": true,
  "_index": "my_index",
  "_type": "_doc",
  "_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
    }
  }
}

To specify only some fields to be extracted:

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.

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:

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

Returns this:

{
  "found": true,
  "_index": "my_index",
  "_type": "_doc",
  "_id": "my_id",
  "_version": 1,
  "_seq_no": 35,
  "_primary_term": 1,
  "_source": {
    "data": "e1xydGYxXGFuc2kNCkxvcmVtIGlwc3VtIGRvbG9yIHNpdCBhbWV0DQpccGFyIH0=",
    "attachment": {
      "content_type": "application/rtf",
      "language": "sl",
      "content": "Lorem ipsum",
      "content_length": 11
    }
  }
}

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

Returns this:

{
  "found": true,
  "_index": "my_index",
  "_type": "_doc",
  "_id": "my_id_2",
  "_version": 1,
  "_seq_no": 40,
  "_primary_term": 1,
  "_source": {
    "data": "e1xydGYxXGFuc2kNCkxvcmVtIGlwc3VtIGRvbG9yIHNpdCBhbWV0DQpccGFyIH0=",
    "max_size": 5,
    "attachment": {
      "content_type": "application/rtf",
      "language": "ro",
      "content": "Lorem",
      "content_length": 5
    }
  }
}

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:

{
  "attachments" : [
    {
      "filename" : "ipsum.txt",
      "data" : "dGhpcyBpcwpqdXN0IHNvbWUgdGV4dAo="
    },
    {
      "filename" : "test.txt",
      "data" : "VGhpcyBpcyBhIHRlc3QK"
    }
  ]
}

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:

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/_doc/my_id?pipeline=attachment
{
  "attachments" : [
    {
      "filename" : "ipsum.txt",
      "data" : "dGhpcyBpcwpqdXN0IHNvbWUgdGV4dAo="
    },
    {
      "filename" : "test.txt",
      "data" : "VGhpcyBpcyBhIHRlc3QK"
    }
  ]
}
GET my_index/_doc/my_id

Returns this:

{
  "_index" : "my_index",
  "_type" : "_doc",
  "_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
        }
      }
    ]
  }
}

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.