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4fe9fc488c
This commit adds deprecation warning for when the `remove_binary` setting is unset. In the future we want to change the default to `true` (it is currently `false`), so this will let a user know they should be explicit about setting this to ensure the behavior does not change in a future (breaking) release. Relates to #86014
429 lines
12 KiB
Text
429 lines
12 KiB
Text
[[attachment]]
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=== Attachment processor
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++++
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<titleabbrev>Attachment</titleabbrev>
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++++
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The attachment processor lets Elasticsearch extract file attachments in common formats (such as PPT, XLS, and PDF) by
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using the Apache text extraction library https://tika.apache.org/[Tika].
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The source field must be a base64 encoded binary. If you do not want to incur
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the overhead of converting back and forth between base64, you can use the CBOR
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format instead of JSON and specify the field as a bytes array instead of a string
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representation. The processor will skip the base64 decoding then.
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[[using-attachment]]
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==== Using the attachment processor in a pipeline
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[[attachment-options]]
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.Attachment options
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[options="header"]
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|======
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| Name | Required | Default | Description
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| `field` | yes | - | The field to get the base64 encoded field from
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| `target_field` | no | attachment | The field that will hold the attachment information
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| `indexed_chars` | no | 100000 | The number of chars being used for extraction to prevent huge fields. Use `-1` for no limit.
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| `indexed_chars_field` | no | `null` | Field name from which you can overwrite the number of chars being used for extraction. See `indexed_chars`.
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| `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`
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| `ignore_missing` | no | `false` | If `true` and `field` does not exist, the processor quietly exits without modifying the document
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| `remove_binary` | no | `false` | If `true`, the binary `field` will be removed from the document
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| `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].
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|======
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[discrete]
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[[attachment-json-ex]]
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==== Example
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If attaching files to JSON documents, you must first encode the file as a base64
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string. On Unix-like systems, you can do this using a `base64` command:
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[source,shell]
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----
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base64 -in myfile.rtf
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----
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The command returns the base64-encoded string for the file. The following base64
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string is for an `.rtf` file containing the text `Lorem ipsum dolor sit amet`:
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`e1xydGYxXGFuc2kNCkxvcmVtIGlwc3VtIGRvbG9yIHNpdCBhbWV0DQpccGFyIH0=`.
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Use an attachment processor to decode the string and extract the file's
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properties:
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[source,console]
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----
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PUT _ingest/pipeline/attachment
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{
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"description" : "Extract attachment information",
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"processors" : [
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{
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"attachment" : {
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"field" : "data",
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"remove_binary": false
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}
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}
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]
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}
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PUT my-index-000001/_doc/my_id?pipeline=attachment
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{
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"data": "e1xydGYxXGFuc2kNCkxvcmVtIGlwc3VtIGRvbG9yIHNpdCBhbWV0DQpccGFyIH0="
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}
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GET my-index-000001/_doc/my_id
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----
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The document's `attachment` object contains extracted properties for the file:
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[source,console-result]
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----
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{
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"found": true,
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"_index": "my-index-000001",
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"_id": "my_id",
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"_version": 1,
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"_seq_no": 22,
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"_primary_term": 1,
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"_source": {
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"data": "e1xydGYxXGFuc2kNCkxvcmVtIGlwc3VtIGRvbG9yIHNpdCBhbWV0DQpccGFyIH0=",
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"attachment": {
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"content_type": "application/rtf",
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"language": "ro",
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"content": "Lorem ipsum dolor sit amet",
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"content_length": 28
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}
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}
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}
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----
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// TESTRESPONSE[s/"_seq_no": \d+/"_seq_no" : $body._seq_no/ s/"_primary_term" : 1/"_primary_term" : $body._primary_term/]
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NOTE: Keeping the binary as a field within the document might consume a lot of resources. It is highly recommended
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to remove that field from the document. Set `remove_binary` to `true` to automatically remove the field.
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[[attachment-fields]]
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==== Exported fields
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The fields which might be extracted from a document are:
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* `content`,
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* `title`,
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* `author`,
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* `keywords`,
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* `date`,
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* `content_type`,
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* `content_length`,
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* `language`,
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* `modified`,
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* `format`,
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* `identifier`,
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* `contributor`,
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* `coverage`,
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* `modifier`,
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* `creator_tool`,
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* `publisher`,
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* `relation`,
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* `rights`,
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* `source`,
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* `type`,
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* `description`,
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* `print_date`,
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* `metadata_date`,
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* `latitude`,
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* `longitude`,
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* `altitude`,
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* `rating`,
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* `comments`
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To extract only certain `attachment` fields, specify the `properties` array:
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[source,console]
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----
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PUT _ingest/pipeline/attachment
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{
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"description" : "Extract attachment information",
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"processors" : [
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{
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"attachment" : {
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"field" : "data",
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"properties": [ "content", "title" ],
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"remove_binary": false
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}
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}
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]
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}
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----
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NOTE: Extracting contents from binary data is a resource intensive operation and
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consumes a lot of resources. It is highly recommended to run pipelines
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using this processor in a dedicated ingest node.
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[[attachment-cbor]]
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==== Use the attachment processor with CBOR
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To avoid encoding and decoding JSON to base64, you can instead pass CBOR data to
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the attachment processor. For example, the following request creates the
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`cbor-attachment` pipeline, which uses the attachment processor.
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[source,console]
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----
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PUT _ingest/pipeline/cbor-attachment
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{
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"description" : "Extract attachment information",
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"processors" : [
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{
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"attachment" : {
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"field" : "data",
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"remove_binary": false
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}
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}
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]
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}
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----
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The following Python script passes CBOR data to an HTTP indexing request that
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includes the `cbor-attachment` pipeline. The HTTP request headers use a
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`content-type` of `application/cbor`.
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NOTE: Not all {es} clients support custom HTTP request headers.
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[source,python]
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----
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import cbor2
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import requests
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file = 'my-file'
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headers = {'content-type': 'application/cbor'}
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with open(file, 'rb') as f:
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doc = {
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'data': f.read()
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}
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requests.put(
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'http://localhost:9200/my-index-000001/_doc/my_id?pipeline=cbor-attachment',
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data=cbor2.dumps(doc),
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headers=headers
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)
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----
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[[attachment-extracted-chars]]
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==== Limit the number of extracted chars
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To prevent extracting too many chars and overload the node memory, the number of chars being used for extraction
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is limited by default to `100000`. You can change this value by setting `indexed_chars`. Use `-1` for no limit but
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ensure when setting this that your node will have enough HEAP to extract the content of very big documents.
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You can also define this limit per document by extracting from a given field the limit to set. If the document
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has that field, it will overwrite the `indexed_chars` setting. To set this field, define the `indexed_chars_field`
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setting.
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For example:
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[source,console]
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--------------------------------------------------
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PUT _ingest/pipeline/attachment
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{
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"description" : "Extract attachment information",
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"processors" : [
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{
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"attachment" : {
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"field" : "data",
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"indexed_chars" : 11,
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"indexed_chars_field" : "max_size",
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"remove_binary": false
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}
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}
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]
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}
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PUT my-index-000001/_doc/my_id?pipeline=attachment
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{
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"data": "e1xydGYxXGFuc2kNCkxvcmVtIGlwc3VtIGRvbG9yIHNpdCBhbWV0DQpccGFyIH0="
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}
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GET my-index-000001/_doc/my_id
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--------------------------------------------------
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Returns this:
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[source,console-result]
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--------------------------------------------------
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{
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"found": true,
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"_index": "my-index-000001",
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"_id": "my_id",
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"_version": 1,
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"_seq_no": 35,
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"_primary_term": 1,
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"_source": {
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"data": "e1xydGYxXGFuc2kNCkxvcmVtIGlwc3VtIGRvbG9yIHNpdCBhbWV0DQpccGFyIH0=",
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"attachment": {
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"content_type": "application/rtf",
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"language": "is",
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"content": "Lorem ipsum",
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"content_length": 11
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}
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}
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}
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--------------------------------------------------
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// TESTRESPONSE[s/"_seq_no": \d+/"_seq_no" : $body._seq_no/ s/"_primary_term" : 1/"_primary_term" : $body._primary_term/]
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[source,console]
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--------------------------------------------------
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PUT _ingest/pipeline/attachment
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{
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"description" : "Extract attachment information",
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"processors" : [
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{
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"attachment" : {
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"field" : "data",
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"indexed_chars" : 11,
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"indexed_chars_field" : "max_size",
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"remove_binary": false
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}
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}
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]
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}
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PUT my-index-000001/_doc/my_id_2?pipeline=attachment
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{
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"data": "e1xydGYxXGFuc2kNCkxvcmVtIGlwc3VtIGRvbG9yIHNpdCBhbWV0DQpccGFyIH0=",
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"max_size": 5
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}
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GET my-index-000001/_doc/my_id_2
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--------------------------------------------------
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Returns this:
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[source,console-result]
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--------------------------------------------------
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{
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"found": true,
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"_index": "my-index-000001",
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"_id": "my_id_2",
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"_version": 1,
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"_seq_no": 40,
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"_primary_term": 1,
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"_source": {
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"data": "e1xydGYxXGFuc2kNCkxvcmVtIGlwc3VtIGRvbG9yIHNpdCBhbWV0DQpccGFyIH0=",
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"max_size": 5,
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"attachment": {
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"content_type": "application/rtf",
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"language": "sl",
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"content": "Lorem",
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"content_length": 5
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}
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}
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}
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--------------------------------------------------
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// TESTRESPONSE[s/"_seq_no": \d+/"_seq_no" : $body._seq_no/ s/"_primary_term" : 1/"_primary_term" : $body._primary_term/]
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[[attachment-with-arrays]]
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==== Using the attachment processor with arrays
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To use the attachment processor within an array of attachments the
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{ref}/foreach-processor.html[foreach processor] is required. This
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enables the attachment processor to be run on the individual elements
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of the array.
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For example, given the following source:
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[source,js]
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--------------------------------------------------
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{
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"attachments" : [
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{
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"filename" : "ipsum.txt",
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"data" : "dGhpcyBpcwpqdXN0IHNvbWUgdGV4dAo="
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},
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{
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"filename" : "test.txt",
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"data" : "VGhpcyBpcyBhIHRlc3QK"
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}
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]
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}
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--------------------------------------------------
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// NOTCONSOLE
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In this case, we want to process the data field in each element
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of the attachments field and insert
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the properties into the document so the following `foreach`
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processor is used:
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[source,console]
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--------------------------------------------------
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PUT _ingest/pipeline/attachment
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{
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"description" : "Extract attachment information from arrays",
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"processors" : [
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{
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"foreach": {
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"field": "attachments",
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"processor": {
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"attachment": {
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"target_field": "_ingest._value.attachment",
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"field": "_ingest._value.data",
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"remove_binary": false
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}
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}
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}
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}
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]
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}
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PUT my-index-000001/_doc/my_id?pipeline=attachment
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{
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"attachments" : [
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{
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"filename" : "ipsum.txt",
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"data" : "dGhpcyBpcwpqdXN0IHNvbWUgdGV4dAo="
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},
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{
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"filename" : "test.txt",
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"data" : "VGhpcyBpcyBhIHRlc3QK"
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}
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]
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}
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GET my-index-000001/_doc/my_id
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--------------------------------------------------
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Returns this:
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[source,console-result]
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--------------------------------------------------
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{
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"_index" : "my-index-000001",
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"_id" : "my_id",
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"_version" : 1,
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"_seq_no" : 50,
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"_primary_term" : 1,
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"found" : true,
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"_source" : {
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"attachments" : [
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{
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"filename" : "ipsum.txt",
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"data" : "dGhpcyBpcwpqdXN0IHNvbWUgdGV4dAo=",
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"attachment" : {
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"content_type" : "text/plain; charset=ISO-8859-1",
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"language" : "en",
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"content" : "this is\njust some text",
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"content_length" : 24
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}
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},
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{
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"filename" : "test.txt",
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"data" : "VGhpcyBpcyBhIHRlc3QK",
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"attachment" : {
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"content_type" : "text/plain; charset=ISO-8859-1",
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"language" : "en",
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"content" : "This is a test",
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"content_length" : 16
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}
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}
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]
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}
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}
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--------------------------------------------------
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// TESTRESPONSE[s/"_seq_no" : \d+/"_seq_no" : $body._seq_no/ s/"_primary_term" : 1/"_primary_term" : $body._primary_term/]
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Note that the `target_field` needs to be set, otherwise the
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default value is used which is a top level field `attachment`. The
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properties on this top level field will contain the value of the
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first attachment only. However, by specifying the
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`target_field` on to a value on `_ingest._value` it will correctly
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associate the properties with the correct attachment.
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