Mapper Attachments Type for Elasticsearch
=========================================
The mapper attachments plugin lets Elasticsearch index file attachments in common formats (such as PPT, XLS, PDF) using the Apache text extraction library [Tika](http://lucene.apache.org/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`).
Installation
------------
In order to install the plugin, run:
```sh
bin/plugin install mapper-attachments
```
Hello, world
------------
Create a property mapping using the new type `attachment`:
```javascript
POST /trying-out-mapper-attachments
{
"mappings": {
"person": {
"properties": {
"cv": { "type": "attachment" }
}}}}
```
Index a new document populated with a `base64`-encoded attachment:
```javascript
POST /trying-out-mapper-attachments/person/1
{
"cv": "e1xydGYxXGFuc2kNCkxvcmVtIGlwc3VtIGRvbG9yIHNpdCBhbWV0DQpccGFyIH0="
}
```
Search for the document using words in the attachment:
```javascript
POST /trying-out-mapper-attachments/person/_search
{
"query": {
"query_string": {
"query": "ipsum"
}}}
```
If you get a hit for your indexed document, the plugin should be installed and working.
Usage
------------------------
Using the attachment type is simple, in your mapping JSON, simply set a certain JSON element as attachment, for example:
```javascript
PUT /test
PUT /test/person/_mapping
{
"person" : {
"properties" : {
"my_attachment" : { "type" : "attachment" }
}
}
}
```
In this case, the JSON to index can be:
```javascript
PUT /test/person/1
{
"my_attachment" : "... base64 encoded attachment ..."
}
```
Or it is possible to use more elaborated JSON if content type, resource name or language need to be set explicitly:
```
PUT /test/person/1
{
"my_attachment" : {
"_content_type" : "application/pdf",
"_name" : "resource/name/of/my.pdf",
"_language" : "en",
"_content" : "... base64 encoded attachment ..."
}
}
```
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:
```javascript
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"}
}
}
}
}
}
```
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.
Copy To feature
---------------
If you want to use [copy_to](http://www.elasticsearch.org/guide/en/elasticsearch/reference/current/mapping-core-types.html#copy-to)
feature, you need to define it on each sub-field you want to copy to another field:
```javascript
PUT /test/person/_mapping
{
"person": {
"properties": {
"file": {
"type": "attachment",
"fields": {
"content": {
"type": "string",
"copy_to": "copy"
}
}
},
"copy": {
"type": "string"
}
}
}
}
```
In this example, the extracted content will be copy as well to `copy` field.
Querying or accessing metadata
------------------------------
If you need to query on metadata fields, use the attachment field name dot the metadata field. For example:
```
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"
}
}
}
```
Will give you:
```
{
"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"
]
}
}
]
}
}
```
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:
```
PUT /test/person/1
{
"my_attachment" : {
"_indexed_chars" : -1,
"_content" : "... base64 encoded attachment ..."
}
}
```
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`.
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:
```javascript
{
"my_attachment" : {
"_language" : "en",
"_content" : "... base64 encoded attachment ..."
}
}
```
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:
```
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": {
}
}
}
}
```
It gives back:
```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"
]
}
}
]
}
}
```
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:
```sh
StandaloneRunner BASE64Text
StandaloneRunner -u /tmp/mydoc.pdf
StandaloneRunner -u /tmp/mydoc.pdf --size 1000000
```
It produces something like:
```
## 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
```