This is a forked MongoDB River Plugin for ElasticSearch, adding the possibility of specifying field mappings between mongodb documents and elasticsearch ones.

Example, with the following mapping:

curl -XPUT 'http://localhost:9200/_river/mongodb/_meta' -d '{
	"type": "mongodb",
	"mongodb": {
		"db": "testmongo",
		"collection": "person"
	},
	"index": {
		"name": "mongoindex",
		"type": "person"
	},
	"field_mappings": [{
		"generate": "FullName",
		"from": ["f","l"],
		"keep_source": true
	},
	{
		"generate": "age",
		"from": "a",
		"keep_source": false
	}]
}'

A new (generated) field called "FullName" would be present in the Elastic Search document, and it'd composed of both "f" and "l" fields, as an array containing all values. Since "keep_source" is true for this mapping, the original field "f" and "l" would also be present.

Also, a new field called "age" would be present in elastic search with the value of "a", and the the "a" field would not be present.

For a document in mongodb document like this:

PRIMARY> db.person.findOne()
{
	"_id" : 1,
	"f" : "David",
	"l" : "Cameron",
	"a" : 45
}

The Elastic Search equivalent document would be:

_source: {
		FullName: [
    		"David",
    		"Cameron",
		],
		f: "David",
		l: "Cameron",
		age: 45
}

Following is the original documentation of the plugin:

MongoDB River Plugin for ElasticSearch

---------------------------------------------------------
| MongoDB River Plugin     | ElasticSearch    | MongoDB |
--------------------------------------------------------|
| master                   | 0.19.11-> master | 2.2.1   |
--------------------------------------------------------|
| 1.5.0                    | 0.19.11          | 2.2.1   |
--------------------------------------------------------|
| 1.4.0                    | 0.19.8           | 2.0.5   |
--------------------------------------------------------|
| 1.3.0                    | 0.19.4           |         |
--------------------------------------------------------|
| 1.2.0                    | 0.19.0           |         |
--------------------------------------------------------|
| 1.1.0                    | 0.19.0           | 2.0.2   |
--------------------------------------------------------|
| 1.0.0                    | 0.18             |         |
--------------------------------------------------------|

Initial implementation by aparo

Modified to get the same structure as the others Elasticsearch river (like CouchDB)

The latest version monitor oplog capped collection and support attachment (GridFS).

For the initial implementation see tutorial

curl -XPUT 'http://localhost:9200/_river/mongodb/_meta' -d '{
	"type": "mongodb", 
	"mongodb": { 
		"db": "DATABASE_NAME", 
		"collection": "COLLECTION", 
		"gridfs": true
	}, 
	"index": { 
		"name": "ES_INDEX_NAME", 
		"type": "ES_TYPE_NAME" 
	}
}'

Example:

curl -XPUT 'http://localhost:9200/_river/mongodb/_meta' -d '{ 
	"type": "mongodb", 
	"mongodb": { 
		"db": "testmongo", 
		"collection": "person"
	}, 
	"index": {
		"name": "mongoindex", 
		"type": "person" 
	}
}'

Import data from mongo console:

use testmongo
var p = {firstName: "John", lastName: "Doe"}
db.person.save(p)

Query index:

curl -XGET 'http://localhost:9200/testmongo/_search?q=firstName:John'

curl -XPUT 'http://localhost:9200/_river/mongodb/_meta' -d '{ 
	"type": "mongodb", 
	"mongodb": { 
		"db": "testmongo", 
		"collection": "files", 
		"gridfs": true 
	}, 
	"index": {
		"name": "mongoindex", 
		"type": "files" 
	}
}'

Import binary content in mongo:

%MONGO_HOME%\bin>mongofiles.exe --host localhost:27017 --db testmongo --collection files put test-document-2.pdf
connected to: localhost:27017
added file: { _id: ObjectId('4f230588a7da6e94984d88a1'), filename: "test-document-2.pdf", chunkSize: 262144, uploadDate: new Date(1327695240206), md5: "c2f251205576566826f86cd969158f24", length: 173293 }
done!

Query index:

curl -XGET 'http://localhost:9200/files/4f230588a7da6e94984d88a1?pretty=true'

See more details check the wiki