MongoDB Ruby Driver Tutorial

This tutorial gives many common examples of using MongoDB with the Ruby driver. If you're looking for information on data modeling, see MongoDB Data Modeling and Rails. Links to the various object mappers are listed on our object mappers page.

Interested in GridFS? See GridFS in Ruby.

As always, the latest source for the Ruby driver can be found on github.

Installation

The mongo-ruby-driver gem is served through Rubygems.org. To install, make sure you have the latest version of rubygems.

gem update --system

Next, install the mongo rubygem:

gem install mongo

The required bson gem will be installed automatically.

For optimum performance, install the bson_ext gem:

gem install bson_ext

After installing, you may want to look at the examples directory included in the source distribution. These examples walk through some of the basics of using the Ruby driver.

Getting started

Note that the output in the following has been updated to Ruby 1.9, so if you are using Ruby 1.8, you will see some minor differences. To follow this tutorial interactively, at the command line, run the Interactive Ruby Shell.

irb

As you execute commands, irb will output the result using the inspect method. If you are editing and running a script for this tutorial, you can view output using the puts or p methods.

Using the gem

Use the mongo gem via the require kernel method.

require 'rubygems'  # not necessary for Ruby 1.9
require 'mongo'

Making a Connection

An Mongo::Connection instance represents a connection to MongoDB. You can optionally specify the MongoDB server address and port when connecting. The following example shows three ways to connect to the local machine:

connection = Mongo::Connection.new # (optional host/port args)
connection = Mongo::Connection.new("localhost")
connection = Mongo::Connection.new("localhost", 27017)

Listing All Databases

connection.database_names
connection.database_info.each { |info| puts info.inspect }

The database_info method returns a hash mapping database names to the size of the database in bytes.

Using a Database

You use a Connection instance to obtain an Mongo::DB instance, which represents a named database. The database doesn't have to exist - if it doesn't, MongoDB will create it for you. The following examples use the database "mydb":

db = connection.db("mydb")
db = Mongo::Connection.new.db("mydb")

At this point, the db object will be a connection to a MongoDB server for the specified database. Each DB instance uses a separate socket connection to the server.

If you're trying to connect to a replica set, see Replica Sets in Ruby.

Authentication

MongoDB can be run in a secure mode where access to databases is controlled through name and password authentication. When run in this mode, any client application must provide a name and password before doing any operations. In the Ruby driver, you simply do the following with the connected mongo object:

auth = db.authenticate(my_user_name, my_password)

If the name and password are valid for the database, auth will be true. Otherwise, it will be false. You should look at the MongoDB log for further information if available.

Using a Collection

You can get a collection to use using the collection method:

coll = db.collection("testCollection")

This is aliased to the [] method:

coll = db["testCollection"]

Once you have this collection object, you can now do create, read, update, and delete (CRUD) functions on persistent storage.

Creating Documents with insert

Once you have the collection object, you can create or insert documents into the collection. For example, lets make a little document that in JSON would be represented as

  {
     "name" : "MongoDB",
     "type" : "database",
     "count" : 1,
     "info" : {
                 x : 203,
                 y : 102
               }
  }

Notice that the above has an "inner" document embedded within it. To do this, we can use a Hash or the driver's OrderedHash (which preserves key order) to create the document (including the inner document), and then just simply insert it into the collection using the insert method.

doc = {"name" => "MongoDB", "type" => "database", "count" => 1, "info" => {"x" => 203, "y" => '102'}}
id = coll.insert(doc)

We have saved the id for future use below. Now the collection has been created and you can list it.

Getting a List Of Collections

Each database has zero or more collections. You can retrieve a list of them from the db (and print out any that are there):

db.collection_names

You should see

\["testCollection", "system.indexes"\]

Adding Multiple Documents

To demonstrate some more interesting queries, let's add multiple simple documents to the collection. These documents will have the following form:

{
    "i" : value
}

Here's how to insert them:

100.times { |i| coll.insert("i" => i) }

Notice that we can insert documents of different "shapes" into the same collection. These records are in the same collection as the complex record we inserted above. This aspect is what we mean when we say that MongoDB is "schema-free".

Reading Documents with find_one and find

Reading the First Document in a Collection using find_one

To retrieve the document that we inserted, we can do a simple find_one method to get the first document in the collection. This method returns a single document directly.

coll.find_one

and you should something like:

{"_id"=>BSON::ObjectId('4f7b1ea6e4d30b35c9000001'), "name"=>"MongoDB", "type"=>"database", "count"=>1, "info"=>{"x"=>203, "y"=>"102"}}

Note the _id element has been added automatically by MongoDB to your document.

Reading All of the Documents with a Cursor using find

To get all the documents from the collection, we use the find method. find returns a Cursor object, which allows us to iterate over the set of documents that matches our query. The Ruby driver's Cursor implemented Enumerable, which allows us to use Enumerable#each, `Enumerable#map}, etc. For instance:

coll.find.each { |row| puts row.inspect }

and that should print all 101 documents in the collection. You can take advantage of Enumerable#to_a.

puts coll.find.to_a

Important note - using to_a pulls all of the full result set into memory and is inefficient if you can process by each individual document. To process with more memory efficiency, use the each method with a code block for the cursor.

Specific Queries

We can create a query hash to pass to the find method to get a subset of the documents in our collection. To check that our update worked, find the document by id:

coll.find("_id" => id).to_a

If we wanted to find the document for which the value of the "i" field is 71, we would do the following:

coll.find("i" => 71).to_a

and it should just print just one document:

{"_id"=>BSON::ObjectId('4f7b20b4e4d30b35c9000049'), "i"=>71}

Counting Documents in a Collection

Now that we've inserted 101 documents (the 100 we did in the loop, plus the first one), we can check to see if we have them all using the count method.

coll.count

and it should print 101.

Getting a Set of Documents With a Query

We can use the query to get a set of documents from our collection. For example, if we wanted to get all documents where "i" > 50, we could write:

puts coll.find("i" => {"$gt" => 50}).to_a

which should print the documents where i > 50. We could also get a range, say 20 < i <= 30:

puts coll.find("i" => {"$gt" => 20, "$lte" => 30}).to_a

Selecting a Subset of Fields for a Query

Use the :fields option to specify fields to return.

puts coll.find("_id" => id, :fields => ["name", "type"]).to_a

Querying with Regular Expressions

Regular expressions can be used to query MongoDB. To find all names that begin with 'a':

puts coll.find({"name" => /^M/}).to_a

You can also construct a regular expression dynamically. To match a given search string:

params = {'search' => 'DB'}
search_string = params['search']

# Constructor syntax
puts coll.find({"name" => Regexp.new(search_string)}).to_a

# Literal syntax
puts coll.find({"name" => /#{search_string}/}).to_a

Although MongoDB isn't vulnerable to anything like SQL-injection, it may be worth checking the search string for anything malicious.

Updating Documents with update

We can update the previous document using the update method. There are a couple ways to update a document. We can rewrite it:

doc["name"] = "MongoDB Ruby"
coll.update({"_id" => id}, doc)

Or we can use an atomic operator to change a single value:

coll.update({"_id" => id}, {"$set" => {"name" => "MongoDB Ruby"}})

Verify the update.

puts coll.find("_id" => id).to_a

Read [more about updating documents|Updating].

Deleting Documents with remove

Use the remove method to delete documents.

coll.count
coll.remove("i" => 71)
coll.count
puts coll.find("i" => 71).to_a

The above shows that the count has been reduced and that the document can no longer be found.

Without arguments, the remove method deletes all documents.

coll.remove
coll.count

Please program carefully.

Indexing

Creating An Index

MongoDB supports indexes, and they are very easy to add on a collection. To create an index, you specify an index name and an array of field names to be indexed, or a single field name. The following creates an ascending index on the "i" field:

# create_index assumes ascending order; see method docs
# for details
coll.create_index("i")

To specify complex indexes or a descending index you need to use a slightly more complex syntax - the index specifier must be an Array of [field name, direction] pairs. Directions should be specified as Mongo::ASCENDING or Mongo::DESCENDING:

# Explicit "ascending"
coll.create_index([["i", Mongo::ASCENDING]])

Use the explain method on the cursor to show how MongoDB will run the query.

coll.find("_id" => id).explain
coll.find("i" => 71).explain
coll.find("type" => "database").explain

The above shows that the query by _id and i will use faster indexed BtreeCursor, while the query by type will use a slower BasicCursor.

Getting a List of Indexes on a Collection

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

coll.index_information

Creating and Querying on a Geospatial Index

First, create the index on a field containing long-lat values:

people.create_index([["loc", Mongo::GEO2D]])

Then get a list of the twenty locations nearest to the point 50, 50:

people.find({"loc" => {"$near" => [50, 50]}}, {:limit => 20}).each do |p|
  puts p.inspect
end

Dropping

Drop an Index

To drop a secondary index, use the drop_index method on the collection.

coll.drop_index("i_1")
coll.index_information

The dropped index is no longer listed.

Drop All Indexes

To drop all secondary indexes, use the drop_indexes method on the collection.

coll.drop_indexes
coll.index_information

Only the primary index "id" is listed.

Drop a Collection

To drop a collection, use the drop method on the collection.

coll.drop
db.collection_names

The dropped collection is no longer listed. The drop_collection method can be used on the database as an alternative.

db.drop_collection("testCollection")

Drop a Database

To drop a database, use the drop_database method on the connection.

connection.drop_database("mydb")
connection.database_names

The dropped database is no longer listed.

Database Administration

A database can have one of three profiling levels: off (:off), slow queries only (:slow_only), or all (:all). To see the database level:

puts db.profiling_level   # => off (the symbol :off printed as a string)
db.profiling_level = :slow_only

Validating a collection will return an interesting hash if all is well or raise an exception if there is a problem. p db.validatecollection('collname')

See Also