Databricks CLI

The Databricks Command Line Interface (CLI) is an open source tool which provides an easy to use interface to the Databricks platform. The CLI is built on top of the Databricks Rest APIs. Currently, the CLI fully implements the DBFS API and the Workspace API.

The project is currently hosted on Github.

Requirements

  • Python Version > 2.7.9
  • Python 3 is not supported

Warning

The default Python installation for MacOS does not implement the TLSv1_2 protocol. Running the CLI on these Python versions will result in the error AttributeError: 'module' object has no attribute 'PROTOCOL_TLSv1_2'.

To use databricks-cli you should install a version of Python which has ssl.PROTOCOL_TLSv1_2. For MacOS, the easiest way may be to install Python with Homebrew.

Installation

To install simply run pip install databricks-cli

In order to upgrade your databricks-cli installation please run pip install --upgrade databricks-cli

Setting Up Authentication

There are two ways to authenticate to Databricks. The first way is to use your username and password pair. To do this run databricks configure and follow the prompts. The second and recommended way is to use an access token generated from Databricks. To configure the CLI to use the access token run databricks configure --token. After following the prompts, your access credentials will be stored in the file ~/.databrickscfg.

Read Token Management for more information about Databricks Access Tokens.

Workspace CLI Examples

The implemented commands for the Workspace CLI can be listed by running databricks workspace -h. Commands are run by appending them to databricks workspace. To make it easier to use the workspace CLI, feel free to alias databricks workspace to something shorter. For more information reference Aliasing Command Groups and Workspace API.

$ databricks workspace -h
Usage: databricks workspace [OPTIONS] COMMAND [ARGS]...

  Utility to interact with the Databricks Workspace. Workspace paths must be
  absolute and be prefixed with `/`.

Options:
  -v, --version
  -h, --help     Show this message and exit.

Commands:
  delete      Deletes objects from the Databricks...
  export      Exports a file from the Databricks workspace...
  export_dir  Recursively exports a directory from the...
  import      Imports a file from local to the Databricks...
  import_dir  Recursively imports a directory from local to...
  list        List objects in the Databricks Workspace
  ls          List objects in the Databricks Workspace
  mkdirs      Make directories in the Databricks Workspace.
  rm          Deletes objects from the Databricks...

Listing Workspace Files

$ databricks workspace ls /Users/example@databricks.com
Usage Logs ETL
Common Utilities
guava-21.0

Importing a local directory of notebooks

The databricks workspace import_dir command will recursively import a directory from the local filesystem to the Databricks workspace. Only directories and files with the extensions of .scala, .py, .sql, .r, .R are imported. When imported, these extensions will be stripped off the name of the notebook.

To overwrite existing notebooks at the target path, the flag -o must be added.

$ tree
.
├── a.py
├── b.scala
├── c.sql
├── d.R
└── e
$ databricks workspace import_dir . /Users/example@databricks.com/example
./a.py -> /Users/example@databricks.com/example/a
./b.scala -> /Users/example@databricks.com/example/b
./c.sql -> /Users/example@databricks.com/example/c
./d.R -> /Users/example@databricks.com/example/d
$ databricks workspace ls /Users/example@databricks.com/example -l
NOTEBOOK   a  PYTHON
NOTEBOOK   b  SCALA
NOTEBOOK   c  SQL
NOTEBOOK   d  R
DIRECTORY  e

Exporting a workspace directory to the local filesystem

Similarly, it is possible to export a directory of notebooks from the Databricks workspace to the local filesystem. To do this, the command is simply

$ databricks workspace export_dir /Users/example@databricks.com/example .

DBFS CLI Examples

The implemented commands for the DBFS CLI can be listed by running databricks fs -h. Commands are run by appending them to databricks fs and all dbfs paths should be prefixed with dbfs:/. To make the command less verbose, we’ve gone ahead and aliased dbfs to databricks fs. For more information reference DBFS API.

$ databricks fs -h
Usage: databricks fs [OPTIONS] COMMAND [ARGS]...

  Utility to interact with DBFS. DBFS paths are all prefixed
  with dbfs:/. Local paths can be absolute or local.

Options:
  -v, --version
  -h, --help     Show this message and exit.

Commands:
  configure
  cp         Copy files to and from DBFS.
  ls         List files in DBFS.
  mkdirs     Make directories in DBFS.
  mv         Moves a file between two DBFS paths.
  rm         Remove files from dbfs.

Copying a file to DBFS

dbfs cp test.txt dbfs:/test.txt
# Or recursively
dbfs cp -r test-dir dbfs:/test-dir

Copying a file from DBFS

dbfs cp dbfs:/test.txt ./test.txt
# Or recursively
dbfs cp -r dbfs:/test-dir ./test-dir

Aliasing Command Groups

Sometimes it can be inconvenient to prefix each CLI invocation with the name of a command group. Writing databricks workspace ls can be quite verbose! To make the CLI easier to use, you can alias different command groups to shorter commands. For example to shorten databricks workspace ls to dw ls in the Bourne again shell, you can add alias dw="databricks workspace" to the appropriate bash profile. Typically, this file is located at ~/.bash_profile.