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Mapper Attachments Type for Elasticsearch

The mapper attachments plugin adds the attachment type to Elasticsearch using Apache Tika.

In order to install the plugin, simply run: bin/plugin -install elasticsearch/elasticsearch-mapper-attachments/2.0.0.

For master elasticsearch versions, look at master branch.
For 1.2.x elasticsearch versions, look at es-1.2 branch.
For 1.1.x elasticsearch versions, look at es-1.1 branch.
For 1.0.x elasticsearch versions, look at es-1.0 branch.
For 0.90.x elasticsearch versions, look at es-0.90 branch.

Attachment Mapper Plugin	elasticsearch	Tika	Release date
3.0.0-SNAPSHOT	master	1.5	XXXX-XX-XX

Please read documentation relative to the version you are using:

3.0.0-SNAPSHOT

The attachment type allows to index different "attachment" type field (encoded as base64), for example, microsoft office formats, open document formats, ePub, HTML, and so on (full list can be found here).

The attachment type is provided as a plugin extension. The plugin is a simple zip file that can be downloaded and placed under $ES_HOME/plugins location. It will be automatically detected and the attachment type will be added.

Using the attachment type is simple, in your mapping JSON, simply set a certain JSON element as attachment, for example:

{
    "person" : {
        "properties" : {
            "my_attachment" : { "type" : "attachment" }
        }
    }
}

In this case, the JSON to index can be:

{
    "my_attachment" : "... base64 encoded attachment ..."
}

Or it is possible to use more elaborated JSON if content type or resource name need to be set explicitly:

{
    "my_attachment" : {
        "_content_type" : "application/pdf",
        "_name" : "resource/name/of/my.pdf",
        "content" : "... base64 encoded attachment ..."
    }
}

The attachment type not only indexes the content of the doc, 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:

{
    "person" : {
        "properties" : {
            "file" : {
                "type" : "attachment",
                "fields" : {
                    "file" : {"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 file, 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.

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.

Note, this feature is supported since 1.3.0 version.

Metadata parsing error handling

While extracting metadata content, errors could happen for example when parsing dates. Since version 1.9.0, 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, this feature is supported since 2.0.0 version.

Highlighting attachments

If you want to highlight your attachment content, you will need to store your file content and set term_vector as follow:

PUT test/my_type/_mapping
{
    "my_type" : {
        "properties" : {
            "my_html_file" : {
                "type" : "attachment",
                "fields" : {
                    "title" : { "store" : "yes" },
                    "my_html_file" : { "term_vector":"with_positions_offsets", "store":"yes" }
                }
            }
        }
    }
}

License

This software is licensed under the Apache 2 license, quoted below.

Copyright 2009-2014 Elasticsearch <http://www.elasticsearch.org>

Licensed under the Apache License, Version 2.0 (the "License"); you may not
use this file except in compliance with the License. You may obtain a copy of
the License at

    http://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
License for the specific language governing permissions and limitations under
the License.

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