triton

a Cassandra ORM for Elixir

Monthly Downloads: 40

Programming language: Elixir

License: MIT License

Tags: ORM And Datamapping    

Latest version: v0.2.4

README

Triton

Pure Elixir Cassandra ORM built on top of Xandra.

Blog Post

Add Triton to your deps

Add triton to your deps.

def deps() do
  [{:triton, "~> 0.2"}]
end

Configure Triton

Single Cluster

config :triton,
  clusters: [
    [
      conn: Triton.Conn,
      nodes: ["127.0.0.1"],
      pool: Xandra.Cluster,
      underlying_pool: DBConnection.Poolboy,
      pool_size: 10,
      keyspace: "my_keyspace",
      health_check_delay: 2500,  # optional: (default is 5000)
      health_check_interval: 500  # optional: (default is 1000)
    ]
  ]

Multi-Cluster

config :triton,
  clusters: [
    [
      conn: Cluster1.Conn,
      nodes: ["127.0.0.1"],
      pool: Xandra.Cluster,
      underlying_pool: DBConnection.Poolboy,
      pool_size: 10,
      keyspace: "cluster_1_keyspace",
      health_check_delay: 2500,  # optional: (default is 5000)
      health_check_interval: 500  # optional: (default is 1000)
    ],
    [
      conn: Cluster2.Conn,
      nodes: ["127.0.0.1"],
      pool: Xandra.Cluster,
      underlying_pool: DBConnection.Poolboy,
      pool_size: 10,
      keyspace: "cluster_2_keyspace",
      health_check_delay: 2500,  # optional: (default is 5000)
      health_check_interval: 500  # optional: (default is 1000)
    ]
  ]

Health Check

If DB gets disconnected, resulting in a DBConnection error, Triton will attempt to reconnect.

You can specify the health_check_delay and health_check_interval via the config for each cluster.

Defining a Keyspace

First, define your keyspace. Triton will create the keyspace for your after compile if it does not exist.

defmodule Schema.Keyspace do
  use Triton.Keyspace

  keyspace :my_keyspace, conn: Triton.Conn do
    with_options [
      replication: "{'class' : 'SimpleStrategy', 'replication_factor': 3}"
    ]
  end
end

Defining a Table

You can define as many tables as you want. Triton will create tables for you if they do not exist.

If you would like Triton to auto-create tables for you after compile, you must require your Keyspace module.

defmodule Schema.User do
  require Schema.Keyspace  
  use Triton.Table

  table :users, keyspace: Schema.Keyspace do
    field :user_id, :bigint, validators: [presence: true]  # validators using vex
    field :username, :text
    field :display_name, :text
    field :password, :text
    field :email, :text
    field :phone, :text
    field :notifications, {:map, "<text, text>"}
    field :friends, {:set, "<text>"}
    field :posts, {:list, "<text>"}
    field :updated, :timestamp
    field :created, :timestamp, transform: &Schema.Helper.DateHelper.to_ms/1  # transform field data
    partition_key [:user_id]
  end
end

Defining a Materialized View

An example of a materialized view users_by_email with fields user_id, email, display_name, password.

Also demonstrates adding options like gc_grace_seconds and clustering_order_by.

defmodule Schema.UserByEmail do
  require Schema.User  # if you want to auto-create after compile
  use Triton.MaterializedView

  materialized_view :users_by_email, from: Schema.User do
    fields [
      :user_id,
      :email,
      :display_name,
      :password
    ]
    partition_key [:email]
    cluster_columns [:user_id]
    with_options [
      gc_grace_seconds: 172_800,
      clustering_order_by: [
        email: :asc,
        user_id: :desc
      ]
    ]
  end
end

An example of materialized view users_by_email with all fields

defmodule Schema.UserByEmail do
  require Schema.User  
  use Triton.MaterializedView

  materialized_view :users_by_email, from: Schema.User do
    fields :all
    partition_key [:email]
    cluster_columns [:user_id]
  end
end

Querying

First, import Triton.Query

alias Schema.User
import Triton.Query

Select a single user where user_id = using a prepared statement.

User
|> prepared(user_id: id)
|> select([:user_id, :username])
|> where(user_id: :user_id)
|> User.one

Select users with IDs of 1, 2, or 3

User
|> select([:user_id, :username])
|> where(user_id: [in: [1, 2, 3]])
|> limit(10)
|> allow_filtering  # you can allow filtering on any query
|> User.all

Select user with email [email protected]

UserByEmail
|> select([:display_name])
|> where(email: "[email protected]")
|> User.one

Comparison / Range Queries

Select messages created before timestamp

MessagesByDate
|> select([:message_id, :text])
|> where(channel_id: 1, created: ["<=": timestamp])
|> limit(20)
|> MessagesByDate.all

Select messages created between timestamp_a and timestamp_b

MessagesByDate
|> select([:message_id, :text])
|> where(channel_id: 1, created: [">=": timestamp_a], created: [<: timestamp_b])
|> MessagesByDate.all

Streaming

Stream all messages

MessagesByDate
|> select(:all)
|> where(channel_id: 1)
|> MessagesByDate.stream(page_size: 20)

Which returns {:ok, stream} or {:error, msg}

Inserting, Updating, & Deleting

Again, lets import Triton.Query for the necessary macros.

alias Schema.User
import Triton.Query

Add a user (if it doesn't already exist) with username username using a prepared statement that substitutes user_id into :user_id

User
|> prepared(user_id: user_id, username: username)
|> insert(user_id: :user_id, username: :username)
|> if_not_exists
|> User.save

Update a user's username, and make sure to check that their previous username was what we expected.

User
|> update(username: username)
|> where(user_id: user_id)
|> constrain(username: previous_username)
|> User.save

Lets delete a user given a user_id

User
|> prepared(user_id: user_id)
|> delete(:all)  # here :all refers to all fields
|> where(user_id: :user_id)
|> User.del

Lets delete that same user, with consistency: :quorum

User
|> prepared(user_id: user_id)
|> delete(:all)  # here :all refers to all fields
|> where(user_id: :user_id)
|> User.del(consistency: :quorum)

Batch update 4 users in 1 Cassandra request.

[
  User |> update(username: "username1") |> where(user_id: 1),
  User |> update(username: "username2") |> where(user_id: 2),
  User |> update(username: "username3") |> where(user_id: 3),
  User |> update(username: "username4") |> where(user_id: 4)
] |> User.batch_execute

Working with Collections

Update the notifications map to {'mentions': '3', 'replies': '3'}. Overwrites the entire map.

User
|> update(notifications: "{'mentions': '5', 'replies': '3'}")
|> where(user_id: 10)
|> User.save

Update notification mentions to '5'.

User
|> update("notifications['mentions']": "5")
|> where(user_id: 10)
|> User.save

Update the friends set

User
|> update(friends: "{'jill', 'bob', 'emma'}")
|> where(user_id: 10)
|> User.save

Add a friend_id to friends set

User
|> update(friends: "friends + {'oscar'}")
|> where(user_id: 10)
|> User.save

Remove friend from set

User
|> update(friends: "friends - {'oscar'}")
|> where(user_id: 10)
|> User.save

Update the posts list

User
|> update(posts: "['post1', 'post2', 'post3']")
|> where(user_id: 10)
|> User.save

Append to posts list

User
|> update(posts: "posts + ['post4']")
|> where(user_id: 10)
|> User.save

Prepend to posts list

User
|> update(posts: "['post0'] + posts")
|> where(user_id: 10)
|> User.save

Pre-populating data

You can pre-populate data with Triton at compile time with Triton.Setup

defmodule PrepopulateModule do
  use Triton.Setup
  import Triton.Query
  require Schema.User
  alias Schema.User

  # create an admin user if it doesn't exist

  setup do
    User
    |> insert(
      user_id: @admin_user_id,
      username: @admin_user_username,
      display_name: @admin_user_display_name,
      password: Bcrypt.hashpwsalt(@admin_user_password),
      email: @admin_user_email,
      created: @admin_user_created
    ) |> if_not_exists
  end
end

Automatic Schema Creation

Triton attempts to create your keyspace, tables, and materialized views after compile if they do not exist.

This means that your build server will need access to your production DB if you want to automatically create your schema in prod. The alternative is simply to create your production schemas yourself.

Consistency levels

For dev, you may want to consider running ccm with more than 1 node if you are doing queries at anything more than consistency: :one.