MongoDB Driver Admin Quick Tour

This is the second part of the MongoDB driver quick tour. In the quick tour we looked at how to use the Java driver to execute basic CRUD operations. In this section we’ll look at some of the administrative features available in the driver.

The following code snippets come from the QuickTourAdmin.java example code that can be found with the driver source.

Setup

To get use started we’ll quickly connect and create a mongoClient, database and collection variable for use in the examples below:

MongoClient mongoClient = new MongoClient();
MongoDatabase database = mongoClient.getDatabase("mydb");
MongoCollection<Document> collection = database.getCollection("test");

Getting A List of Databases

You can get a list of the available databases:

MongoClient mongoClient = new MongoClient();

for (String s : mongoClient.getDatabaseNames()) {
   System.out.println(s);
}

Calling mongoClient.getDB() does not create a database. Only when a database is written to will a database be created. Examples would be creating an index or collection or inserting a document.

Dropping A Database

You can drop a database by name using a MongoClient instance:

MongoClient mongoClient = new MongoClient();
mongoClient.dropDatabase("databaseToBeDropped");

Creating A Collection

There are two ways to create a collection. Inserting a document will create the collection if it doesn’t exist or calling the createCollection command.

An example of creating a capped sized to 1 megabyte:

db = mongoClient.getDB("mydb");
db.createCollection("testCollection", new BasicDBObject("capped", true)
        .append("size", 1048576));

Getting A List of Collections

You can get a list of the available collections in a database:

for (String s : db.getCollectionNames()) {
   System.out.println(s);
}

It should output

system.indexes
testCollection

Dropping A Collection

You can drop a collection by using the drop() method:

DBCollection coll = db.getCollection("testCollection");
coll.drop();
System.out.println(db.getCollectionNames());

And you should notice that testCollection has been dropped.

Getting a List of Indexes on a Collection

You can get a list of the indexes on a collection:

List<DBObject> list = coll.getIndexInfo();

for (DBObject o : list) {
   System.out.println(o.get("key"));
}

and you should see something like

{ "v" : 1 , "key" : { "_id" : 1} , "name" : "_id_" , "ns" : "mydb.testCollection"}
{ "v" : 1 , "key" : { "i" : 1} , "name" : "i_1" , "ns" : "mydb.testCollection"}
{ "v" : 1 , "key" : { "loc" : "2dsphere"} , "name" : "loc_2dsphere" , ... }
{ "v" : 1 , "key" : { "_fts" : "text" , "_ftsx" : 1} , "name" : "content_text" , ... }

Creating An Index

MongoDB supports indexes, and they are very easy to add on a collection. To create an index, you just specify the field that should be indexed, and specify if you want the index to be ascending (1) or descending (-1). The following creates an ascending index on the i field :

coll.createIndex(new BasicDBObject("i", 1));  // create index on "i", ascending

Geo indexes

MongoDB supports various geospatial indexes in this example we’ll be creating a 2dsphere index which we can query using standard GeoJson markup. To create a 2dsphere index specify the string literal “2dsphere” in the index document:

coll.createIndex(new BasicDBObject("loc", "2dsphere"));

There are various ways to query a [2dsphere index](http://docs.mongodb.org/manual//tutorial/query-a-2dsphere-index this example finds places within 500 meters of a location:

BasicDBList coordinates = new BasicDBList();
coordinates.put(0, -73.97);
coordinates.put(1, 40.77);
coll.insert(new BasicDBObject("name", "Central Park")
                .append("loc", new BasicDBObject("type", "Point").append("coordinates", coordinates))
                .append("category", "Parks"));

coordinates.put(0, -73.88);
coordinates.put(1, 40.78);
coll.insert(new BasicDBObject("name", "La Guardia Airport")
        .append("loc", new BasicDBObject("type", "Point").append("coordinates", coordinates))
        .append("category", "Airport"));


// Find whats within 500m of my location
BasicDBList myLocation = new BasicDBList();
myLocation.put(0, -73.965);
myLocation.put(1, 40.769);
myDoc = coll.findOne(
            new BasicDBObject("loc",
                new BasicDBObject("$near",
                        new BasicDBObject("$geometry",
                                new BasicDBObject("type", "Point")
                                    .append("coordinates", myLocation))
                             .append("$maxDistance",  500)
                        )
                )
            );
System.out.println(myDoc.get("name"));

It should print Central Park. See the geospatial documentation for more information.

Text indexes

MongoDB also provides text indexes to support text search of string content. Text indexes can include any field whose value is a string or an array of string elements. To create a text index specify the string literal “text” in the index document:

// create a text index on the "content" field
coll.createIndex(new BasicDBObject("content", "text"));

As of MongoDB 2.6 text indexes are now integrated into the main query language and enabled by default:

// Insert some documents
coll.insert(new BasicDBObject("_id", 0).append("content", "textual content"));
coll.insert(new BasicDBObject("_id", 1).append("content", "additional content"));
coll.insert(new BasicDBObject("_id", 2).append("content", "irrelevant content"));

// Find using the text index
BasicDBObject search = new BasicDBObject("$search", "textual content -irrelevant");
BasicDBObject textSearch = new BasicDBObject("$text", search);
int matchCount = coll.find(textSearch).count();
System.out.println("Text search matches: "+ matchCount);

// Find using the $language operator
textSearch = new BasicDBObject("$text", search.append("$language", "english"));
matchCount = coll.find(textSearch).count();
System.out.println("Text search matches (english): "+ matchCount);

// Find the highest scoring match
BasicDBObject projection = new BasicDBObject("score", new BasicDBObject("$meta", "textScore"));
myDoc = coll.findOne(textSearch, projection);
System.out.println("Highest scoring document: "+ myDoc);

and it should print:

Text search matches: 2
Text search matches (english): 2
Highest scoring document: { "_id" : 1 , "content" : "additional content" , "score" : 0.75}

For more information about text search see the text index and $text query operator documentation.