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