- supports MongoDB versions 4.x, 5.x, 6.x, 7.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)
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.
# 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
}}
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()
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()
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"}
])
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
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{}
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.
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.
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"
}
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.
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)
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.
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.
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
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.
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 zstd compression, simply add {:ezstd, "~> 1.1"}
to the dependencies of your mix.exs
file.
The driver will provide the related code. After activating the zstd compressor can be used by appending
the compressors=zstd
to the URL connection string:
{:ok, top} = Mongo.start_link(url: "mongodb://localhost:27017/my_database?compressors=zstd&maxPoolSize=10")
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)
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.
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.
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()
ormix 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
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 namedmigrations
by default.:path
- thepriv
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 thepriv
folder, defaults to:mongodb_driver
. In most cases you use your application name.:topology
- the topology for running the migrations,:topology
defaults to:mongo
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.
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.
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.
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.
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.
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 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
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
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.
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:
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.
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.
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, ...
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.
mix test --exclude ssl
$ 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 ofallowSSL
orpreferSSL
- You can enable any other options you want when starting
mongod
Copyright 2015 Eric Meadows-Jönsson and Justin Wood
Copyright 2019 - present Michael Maier
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.