README.md

databricks - Use the Databricks API the Ruby way

Description

This Rubygem gives you access to the Databricks REST API using the simple Ruby way.

Requirements

databricks only needs Ruby to run.

Install

Via gem

$ gem install databricks

If using bundler, add this in your Gemfile:

gem 'databricks'

Usage

The API is articulated around resources hierarchy mapping the official Databricks API documentation. It is accessed using the Databricks#api method, giving both the host to connect to and an API token.

Example to list the root path of the DBFS storage of an instance:

require 'databricks'

databricks = Databricks.api('https://my_databricks_instance.my_domain.com', '123456789abcdef123456789abcdef')
databricks.dbfs.list('/').each do |file|
  puts "Found DBFS file: #{file.path}"
end

Here is a simple code snippet showing the most common examples of the API.

require 'databricks'

databricks = Databricks.api('https://my_databricks_instance.my_domain.com', '123456789abcdef123456789abcdef')

# ===== DBFS

databricks.dbfs.list('/').each do |file|
  puts "Found DBFS file: #{file.path} (size: #{file.file_size})"
  puts 'It is a directory' if file.is_dir
end

databricks.dbfs.put('/dbfs_path/to/file.txt', 'local_file.txt')
puts databricks.dbfs.read('/dbfs_path/to/file.txt')['data']
databricks.dbfs.delete('/dbfs_path/to/file.txt')

# ===== Clusters

databricks.clusters.each do |cluster|
  puts "Found cluster named #{cluster.cluster_name} with id #{cluster.cluster_id} using Spark #{cluster.spark_version} in state #{cluster.state}"
end
cluster = databricks.clusters.get('my-cluster-id')

new_cluster = databricks.clusters.create(
  cluster_name: 'my-test-cluster',
  spark_version: '7.1.x-scala2.12',
  node_type_id: 'Standard_DS3_v2',
  driver_node_type_id: 'Standard_DS3_v2',
  num_workers: 1,
  creator_user_name: 'me@my_domain.com'
)
new_cluster.edit(num_workers: 2)
new_cluster.delete

# ===== Jobs

databricks.jobs.list.each do |job|
  puts "Found job #{job.name} with id #{job.job_id}"
end

new_job = databricks.jobs.create(
  name: 'My new job',
  new_cluster: {
    spark_version: '7.3.x-scala2.12',
    node_type_id: 'r3.xlarge'
    num_workers: 10
  },
  libraries: [
    {
      jar: 'dbfs:/my-jar.jar'
    }
  ],
  timeout_seconds: 3600,
  spark_jar_task: {
    main_class_name: 'com.databricks.ComputeModels'
  }
)
puts "Job created with id #{new_job.job_id}"
new_job.reset(
  new_cluster: {
    spark_version: '7.3.x-scala2.12',
    node_type_id: 'r3.xlarge',
    num_workers: 10
  },
  libraries: [
    {
      jar: 'dbfs:/my-jar.jar'
    }
  ],
  timeout_seconds: 3600,
  spark_jar_task: {
    main_class_name: 'com.databricks.ComputeModels'
  }
)
new_job.delete
# Get a job from its job_id
found_job = databricks.jobs.get(666)

# ===== Instance pools

databricks.instance_pools.each do |instance_pool|
  puts "Found instance pool named #{instance_pool.instance_pool_name} with id #{instance_pool.instance_pool_id} and max capacity #{instance_pool.max_capacity}"
end
instance_pool = databricks.instance_pools.get('my-instance-pool-id')

new_instance_pool = databricks.instance_pools.create(
  instance_pool_name: 'my-pool',
  node_type_id: 'i3.xlarge',
  min_idle_instances: 10
)
new_instance_pool.edit(min_idle_instances: 5)
new_instance_pool.delete
# Get an instance pool from its instance_pool_id
found_pool = databricks.instance_pools.get('my-pool-id')

Change log

Please see CHANGELOG for more information on what has changed recently.

Testing

Automated tests are done using rspec.

To execute them, first install development dependencies:

bundle install

Then execute rspec

bundle exec rspec

Contributing

Any contribution is welcome:

• Fork the github project and create pull requests.
• Report bugs by creating tickets.
• Suggest improvements and new features by creating tickets.

Credits

• Muriel Salvan

License

The BSD License. Please see License File for more information.