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 MongoDB Scala 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.scala example code that can be found with the driver source.


See the installation guide for instructions on how to install the MongoDB Driver.

This guide uses the Helper implicits as covered in the Quick Tour Primer.


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

val mongoClient: MongoClient = MongoClient()
val database: MongoDatabase = mongoClient.getDatabase("mydb")
val collection: MongoCollection[Document] = database.getCollection("test")


Calling the getDatabase() on MongoClient does not create a database. Only when a database is written to will a database be created. Examples include the creation of an index or the insertion of a document into a previously non-existent collection.

Get A List of Databases

You can get a list of the available databases by calling the listDatabaseNames method. Here we use the implicit printResults helper so that we can print the list of database names:


Drop A Database

You can drop a database by name using a MongoClient instance. Here we block for the Observable to complete before continuing.


Create A Collection

Collections in MongoDB are created automatically simply by inserted a document into it. Using the createCollection method, you can also create a collection explicitly in order to customize its configuration. For example, to create a capped collection sized to 1 megabyte:

).printHeadResult("Collection Created! ")

Get A List of Collections

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

database.listCollectionNames().printResults("Collection Names: ")

Drop A Collection

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


Create An Index

MongoDB supports secondary indexes. To create an index, you just specify the field or combination of fields, and for each field specify the direction of the index for that field. For 1 ascending or -1 for descending. We can use the Indexes helpers to create index keys:

collection.createIndex(ascending("i")).printResults("Created an index named: ")

Get a List of Indexes on a Collection

Use the listIndexes() method to get a list of indexes.


The example should print the following indexes:

{ "v" : 1, "key" : { "_id" : 1 }, "name" : "_id_", "ns" : "mydb.test" }
{ "v" : 1, "key" : { "i" : 1 }, "name" : "i_1", "ns" : "mydb.test" }

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 use the Indexes.text static helper:

The following example creates a text index by specifying the string literal “text” in the index document, then insert some sample documents. Using a for comprehension we can combine the two operations:

val indexAndInsert = for {
  indexResults <- collection.createIndex(Document("content" -> "text"))
  insertResults <- collection.insertMany(List(
    Document("_id" -> 0, "content" -> "textual content"),
    Document("_id" -> 1, "content" -> "additional content"),
    Document("_id" -> 2, "content" -> "irrelevant content"))
} yield insertResults


As of MongoDB 2.6, text indexes are now integrated into the main query language and enabled by default (here we use the Filters.text helper):

// Find using the text index
collection.countDocuments(text("textual content -irrelevant")).printResults("Text search matches: ")

// Find using the $language operator
val textSearch: Bson = text("textual content -irrelevant", TextSearchOptions().language("english"))
collection.countDocuments(textSearch).printResults("Text search matches (english): ")

// Find the highest scoring match
  .printHeadResult("Highest scoring document: ")

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.

Running a command

While not all commands have a specific helper, however you can run any command by using the runCommand() method. Here we call the buildInfo command:

database.runCommand(Document("buildInfo" -> 1)).printHeadResult()


If no readPreference is passed to runCommand then the command will be run on the primary node.