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.
- Python Version > 2.7.9 or > 3.6
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.
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.
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...
$ databricks workspace ls /Users/example@databricks.com Usage Logs ETL Common Utilities guava-21.0
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
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 .
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.
dbfs cp test.txt dbfs:/test.txt # Or recursively dbfs cp -r test-dir dbfs:/test-dir
dbfs cp dbfs:/test.txt ./test.txt # Or recursively dbfs cp -r dbfs:/test-dir ./test-dir
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.
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"
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"
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.
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.
databricks clusters spark-versions
databricks clusters list-node-types
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.
databricks libraries install --cluster-id $CLUSTER_ID --jar dbfs:/test-dir/test.jar
databricks libraries list --cluster-id $CLUSTER_ID
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.
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.
# 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