The Elixir Driver for MongoDB

Features

supports MongoDB versions 4.x, 5.x, 6.x, 7.x, 8.x
connection pooling (through DBConnection 2.x)
streaming cursors
performant ObjectID generation
aggregation pipeline
replica sets
support for SCRAM-SHA-256 (MongoDB 4.x)
support for GridFS (See)
support for change streams api (See)
support for bulk writes (See)
support for driver sessions (See)
support for driver transactions (See)
support for command monitoring (See)
support for retryable reads (See)
support for retryable writes (See)
support for simple structs using the Mongo.Encoder protocol
support for complex and nested documents using the Mongo.Collection macros
support for streaming protocol (See)
support for migration scripts
support for compression for zlib and zstd (See)

Usage

Installation

Add mongodb_driver to your mix.exs deps.

defp deps do
  [{:mongodb_driver, "~> 1.5.0"}]
end

Then run mix deps.get to fetch dependencies.

Simple Connection to MongoDB

# Starts an unpooled connection
{:ok, top} = Mongo.start_link(url: "mongodb://localhost:27017/my-database")

top
|> Mongo.find("test-collection", %{})
|> Enum.to_list()

To specify a username and password, use the :username, :password, and :auth_source options.

# Starts an unpooled connection
{:ok, top} =
    Mongo.start_link(url: "mongodb://localhost:27017/db-name",
                     username: "test_user",
                     password: "hunter2",
                     auth_source: "admin_test")

top
|> Mongo.find("test-collection", %{})
|> Enum.to_list()

For secure requests, you may need to add some more options; see the "AWS, TLS and Erlang SSL ciphers" section below.

Failing operations return a {:error, error} tuple where error is a Mongo.Error object:

{:error,
 %Mongo.Error{
   code: 13435,
   error_labels: [],
   host: nil,
   message: "not master and slaveOk=false",
   resumable: true,
   retryable_reads: true,
   retryable_writes: true
 }}

Examples

Find

Using $and

@topology
|> Mongo.find("users", %{"$and" => [%{email: "my@email.com"}, %{first_name: "first_name"}]})
|> Enum.to_list()

Using $or

@topology
|> Mongo.find("users", %{"$or" => [%{email: "my@email.com"}, %{first_name: "first_name"}]})
|> Enum.to_list()

Using $in

@topology
|> Mongo.find("users", %{email: %{"$in" => ["my@email.com", "other@email.com"]}})
|> Enum.to_list()

How to use the `Mongo.Stream`?

Most query functions return a Mongo.Stream struct that implements the Enumerable protocol. The module checks out the session and streams the batches from the server until the last batch has been received. The session is then checked in for reuse. Sessions are temporary and reusable data structures, e.g. to support transactions. They are required by the Mongo DB driver specification.

The use of internal structures of the Mongo.Stream struct is therefore not planned. For example, the following code results in an open session and the docs will only contain the first batch:

%Mongo.Stream{docs: docs} = Mongo.aggregate(@topology, collection, pipeline, opts)
Enum.map(docs, fn elem -> elem end)

The Mongo.Stream struct should therefore always be processed by an Enum or Stream function so that the session management can take place automatically:

@topology
|> Mongo.aggregate(collection, pipeline, opts)
|> Enum.to_list()

Inserts

To insert a single document:

Mongo.insert_one(top, "users", %{first_name: "John", last_name: "Smith"})

To insert a list of documents:

Mongo.insert_many(top, "users", [
  %{first_name: "John", last_name: "Smith"},
  %{first_name: "Jane", last_name: "Doe"}
])

mongodb_ecto

The version 1.4.0 supports the mongodb_ecto package. A series of changes are required to support the adapter. Some BSON encoders and a missing generic update function were added for the adapter. Most notably, the find-then-modify command functions find_one_and_update and find_one_and_replace now return appropriate FindAndModifyResult structs that contain additional write information otherwise neglected, which the adapter requires.

After upgrading the driver to version 1.4.0 you need to change the code regarding the results of

Mongo.find_one_and_update
Mongo.find_one_and_replace

Data Representation

This driver chooses to accept both maps and lists of key-value tuples when encoding BSON documents (1), but will only decode documents into maps. Maps are convenient to work with, but Elixir map keys are not ordered, unlike BSON document keys.

That design decision means document key order is lost when encoding Elixir maps to BSON and, conversely, when decoding BSON documents to Elixir maps. However, see Preserve Document Key Order to learn how to preserve key order when it matters.

Additionally, the driver accepts both atoms and strings for document keys, but will only decode them into strings. Creating atoms from arbitrary input (such as database documents) is discouraged because atoms are not garbage collected.

BSON symbols (deprecated) can only be decoded (2).

BSON                Elixir
----------          ------
double              0.0
string              "Elixir"
document            [{"key", "value"}] | %{"key" => "value"} (1)
binary              %BSON.Binary{binary: <<42, 43>>, subtype: :generic}
UUID                %BSON.Binary{binary: <<42, 43>>, subtype: :uuid}
UUID (old style)    %BSON.Binary{binary: <<42, 43>>, subtype: :uuid_old}
object id           %BSON.ObjectId{value: <<...>>}
boolean             true | false
UTC datetime        %DateTime{}
null                nil
regex               %BSON.Regex{pattern: "..."}
JavaScript          %BSON.JavaScript{code: "..."}
timestamp           #BSON.Timestamp<value:ordinal>"
integer 32          42
integer 64          #BSON.LongNumber<value>
symbol              "foo" (2)
min key             :BSON_min
max key             :BSON_max
decimal128          Decimal{}

Preserve Document Key Order

Encoding from Elixir to BSON

For some MongoDB operations, the order of the keys in a document affect the result. For example, that is the case when sorting a query by multiple fields.

In those cases, driver users should represent documents using a list of tuples (or a keyword list) to preserve the order. Example:

@topology
|> Mongo.find("users", %{}, sort: [last_name: 1, first_name: 1, _id: 1])
|> Enum.to_list()

The query above will sort users by last name, then by first name and finally by ID. If an Elixir map had been used to specify :sort, query results would end up sorted unexpectedly wrong.

Decoding from BSON to Elixir

Decoded BSON documents are always represented by Elixir maps because the driver depends on that to implement its functionality.

If the order of document keys as stored by MongoDB is needed, the driver can be configured to use a BSON decoder module that puts a list of keys in the original order under the :__order__ key (and it works recursively).

config :mongodb_driver,
  decoder: BSON.PreserveOrderDecoder

It is possible to customize the key. For example, to use :original_order instead of the default :__order__:

config :mongodb_driver,
  decoder: {BSON.PreserveOrderDecoder, key: :original_order}

The resulting maps with annotated key order can be recursively transformed into lists of tuples. That allows for preserving the order again when encoding. Here is an example of how to achieve that:

defmodule MapWithOrder do
  def to_list(doc, order_key \\ :__order__) do
    do_to_list(doc, order_key)
  end

  defp do_to_list(%{__struct__: _} = elem, _order_key) do
    elem
  end

  defp do_to_list(doc, order_key) when is_map(doc) do
    doc
    |> Map.get(order_key, Map.keys(doc))
    |> Enum.map(fn key -> {key, do_to_list(Map.get(doc, key), order_key)} end)
  end

  defp do_to_list(xs, order_key) when is_list(xs) do
    Enum.map(xs, fn elem -> do_to_list(elem, order_key) end)
  end

  defp do_to_list(elem, _order_key) do
    elem
  end
end

# doc = ...
MapWithOrder.to_list(doc)

Note that structs are kept as-is, to handle special values such as BSON.ObjectId.

The decoder module is defined at compile time. The default decoder is BSON.Decoder, which does not preserve document key order. As it needs to execute fewer operations when decoding data received from MongoDB, it offers improved performance. Therefore, the default decoder is recommended for most use cases of this driver.

Writing your own encoding info

If you want to write a custom struct to your mongo collection - you can do that by implementing Mongo.Encoder protocol for your module. The output should be a map, which will be passed to the Mongo database.

Example:

defmodule CustomStruct do
  @fields [:a, :b, :c, :id]
  @enforce_keys @fields
  defstruct @fields
  defimpl Mongo.Encoder do
    def encode(%{a: a, b: b, id: id}) do
      %{
        _id: id,
        a: a,
        b: b,
        custom_encoded: true
      }
    end
  end
end

So, given the struct:

%CustomStruct{a: 10, b: 20, c: 30, id: "5ef27e73d2a57d358f812001"}

it will be written to database, as:

{
  "a": 10,
  "b": 20,
  "custom_encoded": true,
  "_id": "5ef27e73d2a57d358f812001"
}

Collections

While using the Mongo.Encoder protocol give you the possibility to encode your structs into maps the opposite way to decode those maps into structs is missing. To handle it you can use the Mongo.Collection which provides some boilerplate code for a better support of structs while using the MongoDB driver

automatic load and dump function
reflection functions
type specification
support for embedding one and many structs
support for after load function
support for before dump function
support for id generation
support for default values
support for derived values
support for alias attribute names

But in the case of queries and updates, a rewrite of the attribute names does not take place. It is still up to you to use the correct attribute names.

When using the MongoDB driver only maps and keyword lists are used to represent documents. If you prefer to use structs instead of the maps to give the document a stronger meaning or to emphasize its importance, you have to create a defstruct and fill it from the map manually:

defmodule Label do
  defstruct name: "warning", color: "red"
end

iex> label_map = Mongo.find_one(:mongo, "labels", %{})
  %{"name" => "warning", "color" => "red"}
iex> label = %Label{name: label_map["name"], color: label_map["color"]}

We have defined a module Label as defstruct, then we get the first label document the collection labels. The function find_one returns a map. We convert the map manually and get the desired struct. If we want to save a new structure, we have to do the reverse. We convert the struct into a map:

iex> label = %Label{}
iex> label_map = %{"name" => label.name, "color" => label.color}
iex> {:ok, _} = Mongo.insert_one(:mongo, "labels", label_map)

Alternatively, you can also remove the __struct__ key from label. The MongoDB driver automatically converts the atom keys into strings (Or use the Mongo.Encode protocol)

iex>  Map.drop(label, [:__struct__])
%{color: :red, name: "warning"}

If you use nested structures, the work becomes a bit more complex. In this case, you have to use the inner structures convert manually, too. If you take a closer look at the necessary work, two basic functions can be derived:

load Conversion of the map into a struct.
dump Conversion of the struct into a map.

Mongo.Collection provides the necessary macros to automate this boilerplate code. The above example can be rewritten as follows:

defmodule Label do
    use Mongo.Collection

    document do
      attribute :name, String.t(), default: "warning"
      attribute :color, String.t(), default: :red
    end
end

This results in the following module:

defmodule Label do

    defstruct [name: "warning", color: "red"]

    @type t() :: %Label{String.t(), String.t()}

    def new()...
    def load(map)...
    def dump(%Label{})...
    def __collection__(:attributes)...
    def __collection__(:types)...
    def __collection__(:collection)...
    def __collection__(:id)...

end

You can now create new structs with the default values and use the conversion functions between map and structs:

iex(1)> x = Label.new()
%Label{color: :red, name: "warning"}
iex(2)> m = Label.dump(x)
%{color: :red, name: "warning"}
iex(3)> Label.load(m, true)
%Label{color: :red, name: "warning"}

The load/2 function distinguishes between keys of type binarys load(map, false) and keys of type atoms load(map, true). The default is load(map, false):

iex(1)> m = %{"color" => :red, "name" => "warning"}
iex(2)> Label.load(m)
%Label{color: :red, name: "warning"}

If you would now expect atoms as keys, the result of the conversion is not correct in this case:

iex(3)> Label.load(m, true)
%Label{color: nil, name: nil}

The background is that MongoDB always returns binarys as keys and structs use atoms as keys. For more information look at the module documentation Mongo.Collection. Of course, using the Mongo.Collection is not free. When loading and saving, the maps are converted into structures, which increases CPU usage somewhat. When it comes to speed, it is better to use the maps directly.

Breaking changes

Prior to version 0.9.2 the dump function returns atoms as key. Since the dump/1 function is the inverse function of load/1, which uses binary keys as default, the dump/1 function should return binary keys as well. This increases the consistency and you can do:

l = Label.load(doc)
doc = Label.dump(l)
assert l == Label.load(doc)

Using the Repo Module

For convenience, you can also use the Mongo.Repo module in your application to configure the MongoDB application.

Simply create a new module and include the use Mongo.Repo macro:

defmodule MyApp.Repo do
  use Mongo.Repo,
    otp_app: :my_app,
    topology: :mongo
end

To configure the MongoDB add the configuration to your config.exs:

config :my_app, MyApp.Repo,
  url: "mongodb://localhost:27017/my-app-dev",
  timeout: 60_000,
  idle_interval: 10_000,
  queue_target: 5_000

Finally, we can add the Mongo.Repo instance to our application supervision tree:

  children = [
    # ...
    MyApp.Repo,
    # ...
  ]

In addition, the convenient configuration, the Mongo.Repo module will also include query functions to use with your Mongo.Collection modules.

For more information check out the Mongo.Repo module documentation and the Mongo module documentation.

Breaking changes

Prior to version 0.9.2 some Mongo.Repo functions use the dump/1 function for the query (and update) parameter. This worked only for some query that used only the attributes of the document. In the case of nested documents, it didn't work, so it is changed to be more consistent. The Mongo.Repo module is very simple without any query rewriting like Ecto does. In the case you want to use the :name option, you need to specify the query and update documents in the Mongo.Repo functions following the specification in the MongoDB. Example:

defmodule MyApp.Session do
    @moduledoc false
    use Mongo.Collection
    
    alias BSON.Binary
    
    collection :s do
        attribute :uuid, Binary.t(), name: :u 
    end
end

If you use the Mongo.Repo module and want to fetch a specific session document, this won't work:

MyApp.Repo.get_by(MyApp.Session, %{uuid: session_uuid})

because the get_by/2 function uses the query parameter without any rewriting. You need to change the query:

MyApp.Repo.get_by(MyApp.Session, %{u: session_uuid})

A rewriting is too complex for now because MongoDB has a lot of options.

Logging

You config the logging output by adding in your config file this line

config :mongodb_driver, log: true

The attribute log supports true, false or a log level like :info. The default value is false. If you turn logging on, then you will see log output (command, collection, parameters):

[info] CMD find "my-collection" [filter: [name: "Helga"]] db=2.1ms

Telemetry

The driver uses the :telemetry package to emit the execution duration for each command. The event name is [:mongodb_driver, :execution] and the driver uses the following meta data:

metadata = %{
    type: :mongodb_driver,
    command: command,
    params: parameters,
    collection: collection,
    options: Keyword.get(opts, :telemetry_options, [])
}

:telemetry.execute([:mongodb_driver, :execution], %{duration: duration}, metadata)

In a Phoenix application with installed Phoenix Dashboard the metrics can be used by defining a metric in the Telemetry module:

      summary("mongodb_driver.execution.duration",
        tags: [:collection, :command],
        unit: {:microsecond, :millisecond}
      ),

Then you see for each collection the execution time for each different command in the Dashboard metric page.

Network compression

The driver supports two compressors

zlib, which is supported by Erlang
zstd, which is optional and supported by https://github.com/silviucpp/ezstd bindings.

To activate zlib compression:

Append compressors=zlib to the URL connection string:

{:ok, top} = Mongo.start_link(url: "mongodb://localhost:27017/db?compressors=zlib")

To activate zstd compression:

Add {:ezstd, "~> 1.1"} to the dependencies of your mix.exs file. The driver will provide the related code.
Append compressors=zstd to the URL connection string:

{:ok, top} = Mongo.start_link(url: "mongodb://localhost:27017/db?compressors=zstd")

The driver uses compression for the following functions:

Mongo.aggregate/4
Mongo.find/4
Mongo.insert_one/4
Mongo.insert_many/4
Mongo.update/4
Mongo.update_documents/6
Mongo.find_one_and_update/5
Mongo.find_one_and_replace/5
Mongo.find_one_and_delete/4
Mongo.count/4
Mongo.distinct/5
Mongo.delete_documents/5
Mongo.create/4

You can disable the compression for a single function by using the option compression: false, for example:

Mongo.find(top, "tasks", %{}, compression: false) |> Enum.to_list()

The compression significantly reduces the amount of data, while increasing the load on the CPU. This is certainly interesting for environments in which network transmission has to be paid for.

zlib compression requires a greater penalty in terms of speed than zstd compression. The zstd compression offers a good compromise between compression rate and speed and is undoubtedly supported by all current MongoDB.

The speed also depends on the batch_size attribute. A higher speed is achieved for certain batch sizes. Simple experiments can be carried out here to determine which size shortens the duration of the queries:

:timer.tc(fn -> Mongo.find(top, "tasks", %{}, limit: 30_000, batch_size: 1000) |> Stream.reject(fn _x -> true end) |> Stream.run() end)

Connection Pooling

The driver supports pooling by DBConnection (2.x). By default mongodb_driver will start a single connection, but it also supports pooling with the :pool_size option. For 3 connections add the pool_size: 3 option to Mongo.start_link and to all function calls in Mongo using the pool:

# Starts an pooled connection
{:ok, top} = Mongo.start_link(url: "mongodb://localhost:27017/db-name", pool_size: 3)

# Gets an enumerable stream for the results
top
|> Mongo.find("test-collection", %{})
|> Enum.to_list()

If you're using pooling it is recommended to add it to your application supervisor:

def start(_type, _args) do

  children = [
    {Mongo, [name: :mongo_db, url: "mongodb://localhost:27017/test", pool_size: 3]}
  ]

  opts = [strategy: :one_for_one, name: MyApp.Supervisor]
  Supervisor.start_link(children, opts)
end

We can use the :mongo_db atom instead of a process pid. This allows us to call the Mongo functions directly from every place in the code.

Replica Sets

By default, the driver will discover the deployment's topology and will connect to the replica set automatically, using either the seed list syntax or the URI syntax. Assuming the deployment has nodes at hostname1.net:27017, hostname2.net:27017 and hostname3.net:27017, either of the following invocations will discover the entire deployment:

{:ok, pid} = Mongo.start_link(database: "test", seeds: ["hostname1.net:27017"])

{:ok, pid} = Mongo.start_link(url: "mongodb://hostname1.net:27017/test")

To ensure that the connection succeeds even when some of the nodes are not available, it is recommended to list all nodes in both the seed list and the URI, as follows:

{:ok, pid} = Mongo.start_link(database: "test", seeds: ["hostname1.net:27017", "hostname2.net:27017", "hostname3.net:27017"])

{:ok, pid} = Mongo.start_link(url: "mongodb://hostname1.net:27017,hostname2.net:27017,hostname3.net:27017/test")

Using an SRV URI also discovers all nodes of the deployment automatically.

Migration

Despite the schema-free approach, migration is still desirable. Migrations are used to maintain the indexes and to drop collections that are no longer needed. Capped collections must be migrated. The driver provides a workflow similar to Ecto that can be used to create migrations.

First we create a migration script:

mix mongo.gen.migration add_indexes

In priv/mongo/migrations you will find an Elixir script like 20220322173354_add_indexes.exs:

defmodule Mongo.Migrations.AddIndexes do
  def up() do
    indexes = [
      [key: [email: 1], name: "email_index", unique: true]
    ]

    Mongo.create_indexes(:my_db, "my_collection", indexes)
  end

  def down() do
    Mongo.drop_index(:my_db, "my_collection", "email_index")
  end
end

After that you can run the migration using a task:

mix mongo.migrate

🔒 migrations locked
⚡️ Successfully migrated Elixir.Mongo.Migrations.CreateIndex
🔓 migrations unlocked

Or let it run if your application starts:

defmodule MyApp.Release do
  @moduledoc """
  Used for executing DB release tasks when run in production without mix
  installed.
  """

  def migrate() do
    Application.load(:my_app)
    Application.ensure_all_started(:ssl)
    Application.ensure_all_started(:mongodb_driver)
    Mongo.start_link(name: :mongo_db, url: "mongodb://localhost:27017/my-database", timeout: 60_000, pool_size: 1, idle_interval: 10_000)

    Mongo.Migration.migrate()
  end
end

With the release features of Elixir you can add an overlay script like this:

#!/bin/sh
cd -P -- "$(dirname -- "$0")"
exec ./my_app eval MyApp.Release.migrate

#!/bin/sh
cd -P -- "$(dirname -- "$0")"
PHX_SERVER=true exec ./my_app start

And then you need just to call migrate before you start the server:

/app/bin/migrate && /app/bin/server

Or if you use a Dockerfile:

ENTRYPOINT /app/bin/migrate && /app/bin/server

The migration module tries to lock the migration collection to ensure that only one instance is running the migration. Unfortunately MongoDB does not support collection locks, so need to use a software lock:

Mongo.update_one(topology, 
  "migrations", 
  %{_id: "lock", used: false}, 
  %{"$set": %{used: true}}, 
  upsert: true)

You can lock and unlock the migration collection using these functions in case of an error:

Mongo.Migration.lock()
Mongo.Migration.unlock() or mix mongo.unlock

If nothing helps, just delete the document with {_id: "lock"} from the migration collection.

For more information see:

Mongo.Migration
Mix.Tasks.Mongo
https://hexdocs.pm/mix/1.14/Mix.Tasks.Release.html

Configuration:

You need to configure the migration module and specify at least the :otp_app and :topology values. Here are the default values:

config :mongodb_driver,
    migration:
        [
            topology: :mongo,
            collection: "migrations",
            path: "migrations",
            otp_app: :mongodb_driver
        ]

The following options are available:

:collection - Version numbers of migrations will be saved in a collection named migrations by default.
:path - the priv directory for migrations. :path defaults to "migrations" and migrations should be placed at "priv/mongo/migrations". The pattern to build the path is :priv/:topology/:path
:otp_app - the name of the otp_app to resolve the priv folder, defaults to :mongodb_driver. In most cases you use your application name.
:topology - the topology for running the migrations, :topology defaults to :mongo

Supporting multiple topologies:

Each function lock/1, unlock/1, migrate/1, drop/1 accepts a keyword list (options) to override the default config having full control of the migration process. The options are passed through the migration scripts.

That means you can support multiple topologies, databases and migration collections. Example

Mongo.start_link(name: :topology_1, url: "mongodb://localhost:27017/mig_test_1", timeout: 60_000, pool_size: 5, idle_interval: 10_000)
Mongo.start_link(name: :topology_2, url: "mongodb://localhost:27017/mig_test_2", timeout: 60_000, pool_size: 5, idle_interval: 10_000)

IO.puts("running default migration")
Mongo.Migration.migrate() ## default values specified in the configs

IO.puts("running topology_2 migration")
Mongo.Migration.migrate([topology: :topology_2]) ## override the topology

Adding the options parameter in the up/1 and down/1 function of the migration script is supported as well. It is possible to pass additional parameters to the migration scripts.

defmodule Mongo.Migrations.Topology.CreateIndex do
    def up(opts) do 
        IO.inspect(opts)
        ...
    end
    
    def down(opts) do
        IO.inspect(opts)
        ...
    end
end

The topology is part of the namespace and of the migration path as well. The default value is defined in the configuration. You can specify the topology in the case of creating a new migration script by appending the name to the script call:

mix mongo.gen.migration add_indexes topology_2

In priv/topology_2/migrations you will find an Elixir script like 20220322173354_add_indexes.exs:

defmodule Mongo.Migrations.Topology2.AddIndexes do
    ...
end

By using the :topology keyword, you can organise the migration scripts in different sub-folders. The migration path is prefixed with the priv folder of the application and the topology name.

If you call

Mongo.Migration.migrate([topology: :topology_2])

then the migration scripts under /priv/topology_2/ are used and the options keyword list is passed through to the up/1 function if it is implemented. That means you can create migration scripts for multiple topologies separated in sub folders and module namespaces.

Auth Mechanisms

For versions of Mongo 3.0 and greater, the auth mechanism defaults to SCRAM.

If connecting to MongoDB Enterprise Edition or MongoDB Atlas, the PLAIN auth mechanism is supported for LDAP authentication. The GSSAPI auth mechanism used for Kerberos authentication is not currently supported.

If you'd like to use MONGODB-X509 authentication, you can specify that as a start_link option.

You need roughly three additional configuration steps:

Deploy with x.509 Authentication
Add x.509 Certificate subject as a User
Authenticate with an x.509 Certificate

To get the x.509 authentication working you need to prepare the ssl configuration accordingly:

you need to set the ssl option: verify_peer
you need to specify the cacertfile because Erlang BEAM don't provide any CA certificate store by default
you maybe need to customize the hostname check to allow wildcard certificates
you need to specify the username from the subject entry of the user certificate

If you use a user certificate from Atlas a working configuration looks like this. First we use the castore package as the CA certificate store. After downloading the user certificate we extract the username subject entry from the PEM file:

openssl x509 -in <pathToClientPEM> -inform PEM -subject -nameopt RFC2253

> CN=cert-user

The configuration looks now:

  opts = [
      url: "mongodb+srv://cluster0.xxx.mongodb.net/myFirstDatabase?authSource=%24external&retryWrites=true&w=majority",
      ssl: true,
      username: "CN=cert-user",
      password: "",
      auth_mechanism: :x509,
      ssl_opts: [
        verify: :verify_peer,
        cacertfile: to_charlist(CAStore.file_path()),
        certfile: '/path-to-cert/X509-cert-2227052404946303101.pem',
        customize_hostname_check: [
          match_fun:
            :public_key.pkix_verify_hostname_match_fun(:https)
        ]
      ]]

    Mongo.start_link(opts)

Currently, we need to specify an empty password to get the x.509 auth module working. This will be changed soon.

x509 and using a dedicated MongoDB Atlas server

Using OTP 26 changed the default configuration regarding TLS. You may see issues when connecting to a dedicated Atlas Server using OTP 26. You can restrict the allowed versions and force to use TLS 1.2 instead of TLS 1.3.

   ...
    versions: [:"tlsv1.2"],
   ...

See also MongoDB Security and the Issue 226 for some background information.

AWS, TLS and Erlang SSL Ciphers

Some MongoDB cloud providers (notably AWS) require a particular TLS cipher that isn't enabled by default in the Erlang SSL module. In order to connect to these services, you'll want to add this cipher to your ssl_opts:

{:ok, pid} = Mongo.start_link(database: "test",
      ssl_opts: [
        ciphers: ['AES256-GCM-SHA384'],
        cacertfile: "...",
        certfile: "...")
      ]
)

See the example AWSX509.Example as well.

Timeout

The :timeout option sets the maximum time that the caller is allowed to hold the connection’s state (to send and to receive data). The default value is 15 seconds. The connection pool defines additional timeout values. You can use the :timeout as a global option to override the default value:

# Starts an pooled connection
{:ok, top} = Mongo.start_link(url: "mongodb://localhost:27017/db-name", timeout: 60_000)

Each single connection uses 60_000 (60 seconds) as the timeout value instead of 15_000. But you can override the default value by using the :timeout option, when running a single command:

Mongo.find(top, "dogs", %{}, timeout: 120_000)

Now the driver will use 120 seconds as the timeout for the single query.

Read Preferences

The :read_preference option sets read preference for the query. The read preference is a simple map, supporting the following keys:

:mode, possible values: :primary, :primary_preferred, :secondary, :secondary_preferred and :nearest
:max_staleness_ms, the maxStaleness value in milliseconds
:tags, the set of tags, for example: [dc: "west", usage: "production"]

The driver selects the server using the read preference.

prefs = %{
    mode: :secondary,
    max_staleness_ms: 120_000,
    tags: [dc: "west", usage: "production"]
}

Mongo.find_one(top, "dogs", %{name: "Oskar"}, read_preference: prefs)

Change Streams

Change streams are available in replica set and sharded cluster deployments and tell you about changes of documents in collections. They work like endless cursors.

The special thing about change streams is that they are resumable: in case of a resumable error, no exception is propagated to the application, but instead the cursor is re-scheduled at the last successful location.

The following example will never stop, thus it is a good idea to use a process for reading from change streams:

seeds = ["hostname1.net:27017", "hostname2.net:27017", "hostname3.net:27017"]
{:ok, top} = Mongo.start_link(database: "my-db", seeds: seeds, appname: "getting rich")
stream =  Mongo.watch_collection(top, "accounts", [], fn doc -> IO.puts "New Token #{inspect doc}" end, max_time: 2_000 )
Enum.each(stream, fn doc -> IO.puts inspect doc end)

An example with a spawned process that sends messages to the monitor process:

def for_ever(top, monitor) do
    stream = Mongo.watch_collection(top, "users", [], fn doc -> send(monitor, {:token, doc}) end)
    Enum.each(stream, fn doc -> send(monitor, {:change, doc}) end)
end

spawn(fn -> for_ever(top, self()) end)

For more information see Mongo.watch_collection/5

Indexes

To create indexes you can call the function Mongo.create_indexes/4:

indexes =  [[key: [files_id: 1, n: 1], name: "files_n_index", unique: true]]
Mongo.create_indexes(top, "my_collection", indexes, opts)

You specify the indexes parameter as a keyword list with all options described in the documentation of the createIndex command.

For more information see:

Mongo.create_indexes/4
Mongo.drop_index/4

Bulk Writes

The motivation for bulk writes lies in the possibility of optimization, the same operations to group. Here, a distinction is made between disordered and ordered bulk writes. In disordered, inserts, updates, and deletes are grouped as individual commands sent to the database. There is no influence on the order of the execution. A good use case is the import of records from one CSV file. The order of the inserts does not matter.

For ordered bulk writers, order compliance is important to keep. In this case, only the same consecutive operations are grouped.

Currently, all bulk writes are optimized in memory. This is unfavorable for large bulk writes. In this case, one can use streaming bulk writes that only have a certain set of group operation in memory and when the maximum number of operations has been reached, operations are written to the database. The size can be specified.

Using ordered bulk writes. In this example we first insert some dog's name, add an attribute kind and change all dogs to cats. After that we delete three cats. This example would not work with unordered bulk writes.

bulk = "bulk"
       |> OrderedBulk.new()
       |> OrderedBulk.insert_one(%{name: "Greta"})
       |> OrderedBulk.insert_one(%{name: "Tom"})
       |> OrderedBulk.insert_one(%{name: "Waldo"})
       |> OrderedBulk.update_one(%{name: "Greta"}, %{"$set": %{kind: "dog"}})
       |> OrderedBulk.update_one(%{name: "Tom"}, %{"$set": %{kind: "dog"}})
       |> OrderedBulk.update_one(%{name: "Waldo"}, %{"$set": %{kind: "dog"}})
       |> OrderedBulk.update_many(%{kind: "dog"}, %{"$set": %{kind: "cat"}})
       |> OrderedBulk.delete_one(%{kind: "cat"})
       |> OrderedBulk.delete_one(%{kind: "cat"})
       |> OrderedBulk.delete_one(%{kind: "cat"})

result = Mongo.BulkWrite.write(top, bulk, w: 1)

In the following example we import 1.000.000 integers into the MongoDB using the stream api:

We need to create an insert operation for each number. Then we call the Mongo.UnorderedBulk.stream function to import it. This function returns a stream function that accumulates all inserts operations until the limit 1000 is reached. In this case the operation group is send to MongoDB. So using the stream api you can reduce the memory using while importing big volume of data.

1..1_000_000
|> Stream.map(fn i -> Mongo.BulkOps.get_insert_one(%{number: i}) end)
|> Mongo.UnorderedBulk.write(:mongo, "bulk", 1_000)
|> Stream.run()

For more information see:

Mongo.UnorderedBulk
Mongo.OrderedBulk
Mongo.BulkWrite
Mongo.BulkOps

and have a look at the test units as well.

GridFS

The driver supports the GridFS specifications. You create a Mongo.GridFs.Bucket struct and with this struct you can upload and download files. For example:

    bucket = Bucket.new(top)
    upload_stream = Upload.open_upload_stream(bucket, "test.jpg")
    src_filename = "./test/data/test.jpg"
    File.stream!(src_filename, [], 512) |> Stream.into(upload_stream) |> Stream.run()

    file_id = upload_stream.id

In the example a new bucket with default values is used to upload a file from the file system (./test/data/test.jpg) to the MongoDB (using the name test.jpg). The upload_stream struct contains the id of the new file which can be used to download the stored file. The following code fragments downloads the file by using the file_id.

    dest_filename = "/tmp/my-test-file.jps"

    with {:ok, stream} <- Mongo.GridFs.Download.open_download_stream(bucket, file_id) do
      stream
      |> Stream.into(File.stream!(dest_filename))
      |> Stream.run
    end

For more information see:

Mongo.GridFs.Bucket
Mongo.GridFs.Download
Mongo.GridFs.Upload

Transactions

Since MongoDB 4.x, transactions for multiple write operations are possible. Transaction uses sessions, which just contain a transaction number for each transaction. The Mongo.Session is responsible for the details, and you can use a convenient api for transactions:

{:ok, ids} = Mongo.transaction(top, fn ->
{:ok, %InsertOneResult{:inserted_id => id1}} = Mongo.insert_one(top, "dogs", %{name: "Greta"})
{:ok, %InsertOneResult{:inserted_id => id2}} = Mongo.insert_one(top, "dogs", %{name: "Waldo"})
{:ok, %InsertOneResult{:inserted_id => id3}} = Mongo.insert_one(top, "dogs", %{name: "Tom"})
{:ok, [id1, id2, id3]}
end, w: 1)

The Mongo.transaction/3 function supports nesting. This allows the functions to be called from each other and all write operations are still in the same transaction. The session is stored in the process dictionary under the key :session. The surrounding Mongo.transaction/3 call creates the session and starts the transaction, storing the session in the process dictionary, commits or aborts the transaction. All other Mongo.transaction/3 calls just call the function parameter without other actions.

def insert_dog(top, name) do
  Mongo.insert_one(top, "dogs", %{name: name})
end

def insert_dogs(top) do
  Mongo.transaction(top, fn ->
    insert_dog(top, "Tom")
    insert_dog(top, "Bell")
    insert_dog(top, "Fass")
    :ok
  end)
end

:ok = Mongo.transaction(top, fn ->
    insert_dog(top, "Greta")
    insert_dogs(top)
end)

It is also possible to get more control over the progress of the transaction:

alias Mongo.Session

{:ok, session} = Session.start_session(top, :write, [])
:ok = Session.start_transaction(session)

Mongo.insert_one(top, "dogs", %{name: "Greta"}, session: session)
Mongo.insert_one(top, "dogs", %{name: "Waldo"}, session: session)
Mongo.insert_one(top, "dogs", %{name: "Tom"}, session: session)

:ok = Session.commit_transaction(session)
:ok = Session.end_session(top, session)

For more information see Mongo.Session and have a look at the test units as well.

Aborting a transaction

You have some options to abort a transaction. The simplest possibility is to return an :error. For nested function calls, the Mongo.abort_transaction/1 function call that throws an exception is suitable. That means, you can just generate a raise :should_not_happen exception as well.

Command Monitoring

You can watch all events that are triggered while the driver sends requests and processes responses. You can use the Mongo.EventHandler as a starting point. It logs the events from the topic :commands (by ignoring the :isMaster command) to Logger.info:

iex> Mongo.EventHandler.start()
iex> {:ok, top} = Mongo.start_link(url: "mongodb://localhost:27017/test")
{:ok, #PID<0.226.0>}
 iex> Mongo.find_one(top, "test", %{}) |> Enum.to_list()
[info] Received command: %Mongo.Events.CommandStartedEvent{command: [find: "test", ...
[info] Received command: %Mongo.Events.CommandSucceededEvent{command_name: :find, ...

Testing

Latest MongoDB is used while running the tests. Replica set of three nodes is created and runs all tests, except the socket and ssl test. If you want to run the test cases against other MongoDB deployments or older versions, you can use the mtools for deployment and run the test cases locally:

pyenv global 3.6
pip3 install --upgrade pip
pip3 install 'mtools[all]'
export PATH=to-your-mongodb/bin/:$PATH
ulimit -S -n 2048 ## in case of Mac OS X
mlaunch init --setParameter enableTestCommands=1 --replicaset --name "rs_1"
mongosh --host localhost:27017 --eval 'rs.initiate({_id: "rs_1", members: [{_id: 0, host: "127.0.0.1:27017"}, {_id: 1, host: "127.0.0.1:27018"}, {_id: 2, host: "127.0.0.1:27019"}]})'
mix test --exclude ssl --exclude socket

The SSL test suite is disabled by default.

Enable the SSL Tests

mix test --exclude ssl

Enable SSL on Your MongoDB Server

$ openssl req -newkey rsa:2048 -new -x509 -days 365 -nodes -out mongodb-cert.crt -keyout mongodb-cert.key
$ cat mongodb-cert.key mongodb-cert.crt > mongodb.pem
$ mongod --sslMode allowSSL --sslPEMKeyFile /path/to/mongodb.pem

For --sslMode you can use one of allowSSL or preferSSL
You can enable any other options you want when starting mongod

Additional articles

Connecting to MongoDB with Elixir
Using Network Compression with MongoDB in Elixir

Copyright and License

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 https://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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The Elixir Driver for MongoDB

Features

Usage

Installation

Simple Connection to MongoDB

Examples

Find

How to use the Mongo.Stream?

Inserts

mongodb_ecto

Data Representation

Preserve Document Key Order

Encoding from Elixir to BSON

Decoding from BSON to Elixir

Writing your own encoding info

Collections

Breaking changes

Using the Repo Module

Breaking changes

Logging

Telemetry

Network compression

Connection Pooling

Replica Sets

Migration

Configuration:

Supporting multiple topologies:

Auth Mechanisms

x509 and using a dedicated MongoDB Atlas server

AWS, TLS and Erlang SSL Ciphers

Timeout

Read Preferences

Change Streams

Indexes

Bulk Writes

GridFS

Transactions

Aborting a transaction

Command Monitoring

Testing

Enable the SSL Tests

Enable SSL on Your MongoDB Server

Additional articles

Copyright and License

How to use the `Mongo.Stream`?