[[mapper-attachments]]
=== Mapper Attachments Plugin
The mapper attachments plugin lets Elasticsearch index file attachments in common formats (such as PPT, XLS, PDF)
using the Apache text extraction library http://lucene.apache.org/tika/[Tika].
In practice, the plugin adds the `attachment` type when mapping properties so that documents can be populated with
file attachment contents (encoded as `base64`).
[[mapper-attachments-install]]
[float]
==== Installation
This plugin can be installed using the plugin manager:
[source,sh]
----------------------------------------------------------------
sudo bin/plugin install mapper-attachments
----------------------------------------------------------------
The plugin must be installed on every node in the cluster, and each node must
be restarted after installation.
[[mapper-attachments-remove]]
[float]
==== Removal
The plugin can be removed with the following command:
[source,sh]
----------------------------------------------------------------
sudo bin/plugin remove mapper-attachments
----------------------------------------------------------------
The node must be stopped before removing the plugin.
[[mapper-attachments-helloworld]]
==== Hello, world
Create a property mapping using the new type `attachment`:
[source,js]
--------------------------
POST /trying-out-mapper-attachments
{
"mappings": {
"person": {
"properties": {
"cv": { "type": "attachment" }
}}}}
--------------------------
// AUTOSENSE
Index a new document populated with a `base64`-encoded attachment:
[source,js]
--------------------------
POST /trying-out-mapper-attachments/person/1
{
"cv": "e1xydGYxXGFuc2kNCkxvcmVtIGlwc3VtIGRvbG9yIHNpdCBhbWV0DQpccGFyIH0="
}
--------------------------
// AUTOSENSE
Search for the document using words in the attachment:
[source,js]
--------------------------
POST /trying-out-mapper-attachments/person/_search
{
"query": {
"query_string": {
"query": "ipsum"
}}}
--------------------------
// AUTOSENSE
If you get a hit for your indexed document, the plugin should be installed and working.
[[mapper-attachments-usage]]
==== Usage
Using the attachment type is simple, in your mapping JSON, simply set a certain JSON element as attachment, for example:
[source,js]
--------------------------
PUT /test
PUT /test/person/_mapping
{
"person" : {
"properties" : {
"my_attachment" : { "type" : "attachment" }
}
}
}
--------------------------
// AUTOSENSE
In this case, the JSON to index can be:
[source,js]
--------------------------
PUT /test/person/1
{
"my_attachment" : "... base64 encoded attachment ..."
}
--------------------------
// AUTOSENSE
Or it is possible to use more elaborated JSON if content type, resource name or language need to be set explicitly:
[source,js]
--------------------------
PUT /test/person/1
{
"my_attachment" : {
"_content_type" : "application/pdf",
"_name" : "resource/name/of/my.pdf",
"_language" : "en",
"_content" : "... base64 encoded attachment ..."
}
}
--------------------------
// AUTOSENSE
The `attachment` type not only indexes the content of the doc in `content` sub field, but also automatically adds meta
data on the attachment as well (when available).
The metadata supported are:
* `date`
* `title`
* `name` only available if you set `_name` see above
* `author`
* `keywords`
* `content_type`
* `content_length` is the original content_length before text extraction (aka file size)
* `language`
They can be queried using the "dot notation", for example: `my_attachment.author`.
Both the meta data and the actual content are simple core type mappers (string, date, …), thus, they can be controlled
in the mappings. For example:
[source,js]
--------------------------
PUT /test/person/_mapping
{
"person" : {
"properties" : {
"file" : {
"type" : "attachment",
"fields" : {
"content" : {"index" : "no"},
"title" : {"store" : "yes"},
"date" : {"store" : "yes"},
"author" : {"analyzer" : "myAnalyzer"},
"keywords" : {"store" : "yes"},
"content_type" : {"store" : "yes"},
"content_length" : {"store" : "yes"},
"language" : {"store" : "yes"}
}
}
}
}
}
--------------------------
// AUTOSENSE
In the above example, the actual content indexed is mapped under `fields` name `content`, and we decide not to index it, so
it will only be available in the `_all` field. The other fields map to their respective metadata names, but there is no
need to specify the `type` (like `string` or `date`) since it is already known.
[[mapper-attachments-copy-to]]
==== Copy To feature
If you want to use http://www.elasticsearch.org/guide/en/elasticsearch/reference/current/mapping-core-types.html#copy-to[copy_to]
feature, you need to define it on each sub-field you want to copy to another field:
[source,js]
--------------------------
PUT /test/person/_mapping
{
"person": {
"properties": {
"file": {
"type": "attachment",
"fields": {
"content": {
"type": "string",
"copy_to": "copy"
}
}
},
"copy": {
"type": "string"
}
}
}
}
--------------------------
// AUTOSENSE
In this example, the extracted content will be copy as well to `copy` field.
[[mapper-attachments-querying-metadata]]
==== Querying or accessing metadata
If you need to query on metadata fields, use the attachment field name dot the metadata field. For example:
[source,js]
--------------------------
DELETE /test
PUT /test
PUT /test/person/_mapping
{
"person": {
"properties": {
"file": {
"type": "attachment",
"fields": {
"content_type": {
"type": "string",
"store": true
}
}
}
}
}
}
PUT /test/person/1?refresh=true
{
"file": "IkdvZCBTYXZlIHRoZSBRdWVlbiIgKGFsdGVybmF0aXZlbHkgIkdvZCBTYXZlIHRoZSBLaW5nIg=="
}
GET /test/person/_search
{
"fields": [ "file.content_type" ],
"query": {
"match": {
"file.content_type": "text plain"
}
}
}
--------------------------
// AUTOSENSE
Will give you:
[source,js]
--------------------------
{
"took": 2,
"timed_out": false,
"_shards": {
"total": 5,
"successful": 5,
"failed": 0
},
"hits": {
"total": 1,
"max_score": 0.16273327,
"hits": [
{
"_index": "test",
"_type": "person",
"_id": "1",
"_score": 0.16273327,
"fields": {
"file.content_type": [
"text/plain; charset=ISO-8859-1"
]
}
}
]
}
}
--------------------------
[[mapper-attachments-indexed-characters]]
==== Indexed Characters
By default, `100000` characters are extracted when indexing the content. This default value can be changed by setting
the `index.mapping.attachment.indexed_chars` setting. It can also be provided on a per document indexed using the
`_indexed_chars` parameter. `-1` can be set to extract all text, but note that all the text needs to be allowed to be
represented in memory:
[source,js]
--------------------------
PUT /test/person/1
{
"my_attachment" : {
"_indexed_chars" : -1,
"_content" : "... base64 encoded attachment ..."
}
}
--------------------------
// AUTOSENSE
[[mapper-attachments-error-handling]]
==== Metadata parsing error handling
While extracting metadata content, errors could happen for example when parsing dates.
Parsing errors are ignored so your document is indexed.
You can disable this feature by setting the `index.mapping.attachment.ignore_errors` setting to `false`.
[[mapper-attachments-language-detection]]
==== Language Detection
By default, language detection is disabled (`false`) as it could come with a cost.
This default value can be changed by setting the `index.mapping.attachment.detect_language` setting.
It can also be provided on a per document indexed using the `_detect_language` parameter.
Note that you can force language using `_language` field when sending your actual document:
[source,js]
--------------------------
{
"my_attachment" : {
"_language" : "en",
"_content" : "... base64 encoded attachment ..."
}
}
--------------------------
[[mapper-attachments-highlighting]]
==== Highlighting attachments
If you want to highlight your attachment content, you will need to set `"store": true` and
`"term_vector":"with_positions_offsets"` for your attachment field. Here is a full script which does it:
[source,js]
--------------------------
DELETE /test
PUT /test
PUT /test/person/_mapping
{
"person": {
"properties": {
"file": {
"type": "attachment",
"fields": {
"content": {
"type": "string",
"term_vector":"with_positions_offsets",
"store": true
}
}
}
}
}
}
PUT /test/person/1?refresh=true
{
"file": "IkdvZCBTYXZlIHRoZSBRdWVlbiIgKGFsdGVybmF0aXZlbHkgIkdvZCBTYXZlIHRoZSBLaW5nIg=="
}
GET /test/person/_search
{
"fields": [],
"query": {
"match": {
"file.content": "king queen"
}
},
"highlight": {
"fields": {
"file.content": {
}
}
}
}
--------------------------
// AUTOSENSE
It gives back:
[source,js]
--------------------------
{
"took": 9,
"timed_out": false,
"_shards": {
"total": 1,
"successful": 1,
"failed": 0
},
"hits": {
"total": 1,
"max_score": 0.13561106,
"hits": [
{
"_index": "test",
"_type": "person",
"_id": "1",
"_score": 0.13561106,
"highlight": {
"file.content": [
"\"God Save the Queen\" (alternatively \"God Save the King\"\n"
]
}
}
]
}
}
--------------------------
[[mapper-attachments-standalone]]
==== Stand alone runner
If you want to run some tests within your IDE, you can use `StandaloneRunner` class.
It accepts arguments:
* `-u file://URL/TO/YOUR/DOC`
* `--size` set extracted size (default to mapper attachment size)
* `BASE64` encoded binary
Example:
[source,sh]
--------------------------
StandaloneRunner BASE64Text
StandaloneRunner -u /tmp/mydoc.pdf
StandaloneRunner -u /tmp/mydoc.pdf --size 1000000
--------------------------
It produces something like:
[source,text]
--------------------------
## Extracted text
--------------------- BEGIN -----------------------
This is the extracted text
---------------------- END ------------------------
## Metadata
- author: null
- content_length: null
- content_type: application/pdf
- date: null
- keywords: null
- language: null
- name: null
- title: null
--------------------------