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A command line interface for Databricks

Project description

Build Status

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.

PLEASE NOTE, this CLI is under active development and is released as an experimental client. This means that interfaces are still subject to change.

If you’re interested in contributing to the project please reach out. In addition, please leave bug reports as issues on our Github project.

Requirements

  • Python Version > 2.7.9 or > 3.6

Installation

To install simply run pip install --upgrade databricks-cli

Then set up authentication using username/password or authentication token. Credentials are stored at ~/.databrickscfg.

  • databricks configure (enter hostname/username/password at prompt)
  • databricks configure --token (enter hostname/auth-token at prompt)

Multiple connection profiles are also supported with databricks configure --profile <profile> [--token]. The connection profile can be used as such: databricks workspace ls --profile <profile>.

Then you’re all set to go! To test that your authentication information is working, try a quick test like databricks workspace ls.

Known Issues

AttributeError: 'module' object has no attribute 'PROTOCOL_TLSv1_2'

The Databricks web service requires clients speak TLSV1.2. The built in version of Python for MacOS does not have this version of TLS built in.

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.

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 section.

$ 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.

$ 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

Jobs CLI Examples

The implemented commands for the jobs CLI can be listed by running databricks jobs -h. Job run commands are handled by databricks runs -h.

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

  Utility to interact with jobs.

  This is a wrapper around the jobs API
  (https://docs.databricks.com/api/latest/jobs.html). Job runs are handled
  by ``databricks runs``.

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

Commands:
  create   Creates a job.
  delete   Deletes the specified job.
  get      Describes the metadata for a job.
  list     Lists the jobs in the Databricks Job Service.
  reset    Resets (edits) the definition of a job.
  run-now  Runs a job with optional per-run parameters.
$ databricks runs -h
Usage: databricks runs [OPTIONS] COMMAND [ARGS]...

  Utility to interact with job runs.

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

Commands:
  cancel  Cancels the run specified.
  get     Gets the metadata about a run in json form.
  list    Lists job runs.
  submit  Submits a one-time run.

Listing and finding jobs

The databricks jobs list command has two output formats, JSON and TABLE. The TABLE format is outputted by default and returns a two column table (job ID, job name).

To find a job by name

databricks jobs list | grep "JOB_NAME"

Copying a job

This example requires the program jq. See jq section for more details.

SETTINGS_JSON=$(databricks jobs get --job-id 284907 | jq .settings)
# JQ Explanation:
#   - peek into top level `settings` field.
databricks jobs create --json "$SETTINGS_JSON"

Deleting “Untitled” Jobs

databricks jobs list --output json | jq '.jobs[] | select(.settings.name == "Untitled") | .job_id' | xargs -n 1 databricks jobs delete --job-id
# Explanation:
#   - List jobs in JSON.
#   - Peek into top level `jobs` field.
#   - Select only jobs with name equal to "Untitled"
#   - Print those job ID's out.
#   - Invoke `databricks jobs delete --job-id` once per row with the $job_id appended as an argument to the end of the command.

Clusters CLI Examples

The implemented commands for the clusters CLI can be listed by running databricks clusters -h.

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

  Utility to interact with Databricks clusters.

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

Commands:
  create           Creates a Databricks cluster.
  delete           Removes a Databricks cluster given its ID.
  get              Retrieves metadata about a cluster.
  list             Lists active and recently terminated clusters.
  list-node-types  Lists possible node types for a cluster.
  list-zones       Lists zones where clusters can be created.
  restart          Restarts a Databricks cluster given its ID.
  spark-versions   Lists possible Databricks Runtime versions...
  start            Starts a terminated Databricks cluster given its ID.

Listing runtime versions

databricks clusters spark-versions

Listing node types

databricks clusters list-node-types

Libraries CLI

You run library subcommands by appending them to databricks libraries.

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

  Utility to interact with libraries.

  This is a wrapper around the libraries API
  (https://docs.databricks.com/api/latest/libraries.html).

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

Commands:
  all-cluster-statuses  Get the status of all libraries.
  cluster-status        Get the status of all libraries for a specified
                        cluster.
  install               Install a library on a cluster.
  list                  Shortcut to `all-cluster-statuses` or `cluster-
                        status`.
  uninstall             Uninstall a library on a cluster.

Install a JAR from DBFS

databricks libraries install --cluster-id $CLUSTER_ID --jar dbfs:/test-dir/test.jar

List library statuses for a cluster

databricks libraries list --cluster-id $CLUSTER_ID

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.

jq

Some Databricks CLI commands will output the JSON response from the API endpoint. Sometimes it can be useful to parse out parts of the JSON to pipe into other commands. For example, to copy a job definition, we must take the settings field of /api/2.0/jobs/get use that as an argument to the databricks jobs create command.

In these cases, we recommend you to use the utility jq. MacOS users can install jq through Homebrew with brew install jq.

For more information on jq reference its documentation.

Using Docker

# build image
docker build -t databricks-cli .

# run container
docker run -it databricks-cli

# run command in docker
docker run -it databricks-cli fs --help

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