Databricks Utilities (dbutils) reference

This article is a reference for Databricks Utilities (dbutils). dbutils utilities are available in Python, R, and Scala notebooks. You can use the utilities to:

• Work with files and object storage efficiently.
• Work with secrets.

How to: List utilities, list commands, display command help

Utilities: data, fs, jobs, library, notebook, secrets, widgets, Utilities API library

List available utilities

To list available utilities along with a short description for each utility, run dbutils.help() for Python or Scala.

This example lists available commands for the Databricks Utilities.

Python

dbutils.help()

Scala

dbutils.help()

This module provides various utilities for users to interact with the rest of Databricks.

credentials: DatabricksCredentialUtils -> Utilities for interacting with credentials within notebooks
data: DataUtils -> Utilities for understanding and interacting with datasets (EXPERIMENTAL)
fs: DbfsUtils -> Manipulates the Databricks filesystem (DBFS) from the console
jobs: JobsUtils -> Utilities for leveraging jobs features
library: LibraryUtils -> Utilities for session isolated libraries
meta: MetaUtils -> Methods to hook into the compiler (EXPERIMENTAL)
notebook: NotebookUtils -> Utilities for the control flow of a notebook (EXPERIMENTAL)
preview: Preview -> Utilities under preview category
secrets: SecretUtils -> Provides utilities for leveraging secrets within notebooks
widgets: WidgetsUtils -> Methods to create and get bound value of input widgets inside notebooks

List available commands for a utility

To list available commands for a utility along with a short description of each command, run .help() after the programmatic name for the utility.

This example lists available commands for the Databricks File System (DBFS) utility.

Python

dbutils.fs.help()

R

dbutils.fs.help()

Scala

dbutils.fs.help()

dbutils.fs provides utilities for working with FileSystems. Most methods in this package can take either a DBFS path (e.g., "/foo" or "dbfs:/foo"), or another FileSystem URI. For more info about a method, use dbutils.fs.help("methodName"). In notebooks, you can also use the %fs shorthand to access DBFS. The %fs shorthand maps straightforwardly onto dbutils calls. For example, "%fs head --maxBytes=10000 /file/path" translates into "dbutils.fs.head("/file/path", maxBytes = 10000)".

fsutils

cp(from: String, to: String, recurse: boolean = false): boolean -> Copies a file or directory, possibly across FileSystems
head(file: String, maxBytes: int = 65536): String -> Returns up to the first 'maxBytes' bytes of the given file as a String encoded in UTF-8
ls(dir: String): Seq -> Lists the contents of a directory
mkdirs(dir: String): boolean -> Creates the given directory if it does not exist, also creating any necessary parent directories
mv(from: String, to: String, recurse: boolean = false): boolean -> Moves a file or directory, possibly across FileSystems
put(file: String, contents: String, overwrite: boolean = false): boolean -> Writes the given String out to a file, encoded in UTF-8
rm(dir: String, recurse: boolean = false): boolean -> Removes a file or directory

mount

mount(source: String, mountPoint: String, encryptionType: String = "", owner: String = null, extraConfigs: Map = Map.empty[String, String]): boolean -> Mounts the given source directory into DBFS at the given mount point
mounts: Seq -> Displays information about what is mounted within DBFS
refreshMounts: boolean -> Forces all machines in this cluster to refresh their mount cache, ensuring they receive the most recent information
unmount(mountPoint: String): boolean -> Deletes a DBFS mount point
updateMount(source: String, mountPoint: String, encryptionType: String = "", owner: String = null, extraConfigs: Map = Map.empty[String, String]): boolean -> Similar to mount(), but updates an existing mount point instead of creating a new one

Display help for a command

To display help for a command, run .help("<command-name>") after the command name.

This example displays help for the DBFS copy command.

Python

dbutils.fs.help("cp")

R

dbutils.fs.help("cp")

Scala

dbutils.fs.help("cp")

/**
* Copies a file or directory, possibly across FileSystems.
*
* Example: cp("/mnt/my-folder/a", "dbfs:/a/b")
*
* @param from FileSystem URI of the source file or directory
* @param to FileSystem URI of the destination file or directory
* @param recurse if true, all files and directories will be recursively copied
* @return true if all files were successfully copied
*/
cp(from: java.lang.String, to: java.lang.String, recurse: boolean = false): boolean

Data utility (dbutils.data)

Commands: summarize

The data utility allows you to understand and interpret datasets. To list the available commands, run dbutils.data.help().

dbutils.data provides utilities for understanding and interpreting datasets. This module is currently in preview and may be unstable. For more info about a method, use dbutils.data.help("methodName").

summarize(df: Object, precise: boolean): void -> Summarize a Spark DataFrame and visualize the statistics to get quick insights

summarize command (dbutils.data.summarize)

Calculates and displays summary statistics of an Apache Spark DataFrame or pandas DataFrame. This command is available for Python, Scala and R.

This command analyzes the complete contents of the DataFrame. Running this command for very large DataFrames can be very expensive.

To display help for this command, run dbutils.data.help("summarize").

In Databricks Runtime 10.4 LTS and above, you can use the additional precise parameter to adjust the precision of the computed statistics.

• When precise is set to false (the default), some returned statistics include approximations to reduce run time.
  • The number of distinct values for categorical columns may have ~5% relative error for high-cardinality columns.
  • The frequent value counts may have an error of up to 0.01% when the number of distinct values is greater than 10000.
  • The histograms and percentile estimates may have an error of up to 0.01% relative to the total number of rows.
• When precise is set to true, the statistics are computed with higher precision. All statistics except for the histograms and percentiles for numeric columns are now exact.
  • The histograms and percentile estimates may have an error of up to 0.0001% relative to the total number of rows.

The tooltip at the top of the data summary output indicates the mode of current run.

This example displays summary statistics for an Apache Spark DataFrame with approximations enabled by default. To see the results, run this command in a notebook. This example is based on Sample datasets.

Python

df = spark.read.format('csv').load(
  '/databricks-datasets/Rdatasets/data-001/csv/ggplot2/diamonds.csv',
  header=True,
  inferSchema=True
)
dbutils.data.summarize(df)

R

df <- read.df("/databricks-datasets/Rdatasets/data-001/csv/ggplot2/diamonds.csv", source = "csv", header="true", inferSchema = "true")
dbutils.data.summarize(df)

Scala

val df = spark.read.format("csv")
  .option("inferSchema", "true")
  .option("header", "true")
  .load("/databricks-datasets/Rdatasets/data-001/csv/ggplot2/diamonds.csv")
dbutils.data.summarize(df)

Note that the visualization uses SI notation to concisely render numerical values smaller than 0.01 or larger than 10000. As an example, the numerical value 1.25e-15 will be rendered as 1.25f. One exception: the visualization uses "B" for 1.0e9 (giga) instead of "G".

File system utility (dbutils.fs)

Commands: cp, head, ls, mkdirs, mount, mounts, mv, put, refreshMounts, rm, unmount, updateMount

The file system utility allows you to access What is DBFS?, making it easier to use Azure Databricks as a file system.

In notebooks, you can also use the %fs magic command to access DBFS. For example %fs ls /Volumes/main/default/my-volume/ is the same as dbutils.fs.ls("/Volumes/main/default/my-volume/"). See magic commands.

To list the available commands, run dbutils.fs.help().

dbutils.fs provides utilities for working with FileSystems. Most methods in this package can take either a DBFS path (e.g., "/foo" or "dbfs:/foo"), or another FileSystem URI. For more info about a method, use dbutils.fs.help("methodName"). In notebooks, you can also use the %fs shorthand to access DBFS. The %fs shorthand maps straightforwardly onto dbutils calls. For example, "%fs head --maxBytes=10000 /file/path" translates into "dbutils.fs.head("/file/path", maxBytes = 10000)".

fsutils

cp(from: String, to: String, recurse: boolean = false): boolean -> Copies a file or directory, possibly across FileSystems
head(file: String, maxBytes: int = 65536): String -> Returns up to the first 'maxBytes' bytes of the given file as a String encoded in UTF-8
ls(dir: String): Seq -> Lists the contents of a directory
mkdirs(dir: String): boolean -> Creates the given directory if it does not exist, also creating any necessary parent directories
mv(from: String, to: String, recurse: boolean = false): boolean -> Moves a file or directory, possibly across FileSystems
put(file: String, contents: String, overwrite: boolean = false): boolean -> Writes the given String out to a file, encoded in UTF-8
rm(dir: String, recurse: boolean = false): boolean -> Removes a file or directory

mount

mount(source: String, mountPoint: String, encryptionType: String = "", owner: String = null, extraConfigs: Map = Map.empty[String, String]): boolean -> Mounts the given source directory into DBFS at the given mount point
mounts: Seq -> Displays information about what is mounted within DBFS
refreshMounts: boolean -> Forces all machines in this cluster to refresh their mount cache, ensuring they receive the most recent information
unmount(mountPoint: String): boolean -> Deletes a DBFS mount point
updateMount(source: String, mountPoint: String, encryptionType: String = "", owner: String = null, extraConfigs: Map = Map.empty[String, String]): boolean -> Similar to mount(), but updates an existing mount point instead of creating a new one

cp command (dbutils.fs.cp)

Copies a file or directory, possibly across filesystems.

To display help for this command, run dbutils.fs.help("cp").

This example copies the file named data.csv from /Volumes/main/default/my-volume/ to new-data.csv in the same volume.

Python

dbutils.fs.cp("/Volumes/main/default/my-volume/data.csv", "/Volumes/main/default/my-volume/new-data.csv")

# Out[4]: True

R

dbutils.fs.cp("/Volumes/main/default/my-volume/data.csv", "/Volumes/main/default/my-volume/new-data.csv")

# [1] TRUE

Scala

dbutils.fs.cp("/Volumes/main/default/my-volume/data.csv", "/Volumes/main/default/my-volume/new-data.csv")

// res3: Boolean = true

head command (dbutils.fs.head)

Returns up to the specified maximum number bytes of the given file. The bytes are returned as a UTF-8 encoded string.

To display help for this command, run dbutils.fs.help("head").

This example displays the first 25 bytes of the file data.csv located in /Volumes/main/default/my-volume/.

Python

dbutils.fs.head("/Volumes/main/default/my-volume/data.csv", 25)

# [Truncated to first 25 bytes]
# Out[12]: 'Year,First Name,County,Se'

R

dbutils.fs.head("/Volumes/main/default/my-volume/data.csv", 25)

# [1] "Year,First Name,County,Se"

Scala

dbutils.fs.head("/Volumes/main/default/my-volume/data.csv", 25)

// [Truncated to first 25 bytes]
// res4: String =
// "Year,First Name,County,Se"

ls command (dbutils.fs.ls)

Lists the contents of a directory.

To display help for this command, run dbutils.fs.help("ls").

This example displays information about the contents of /Volumes/main/default/my-volume/. The modificationTime field is available in Databricks Runtime 10.4 LTS and above. In R, modificationTime is returned as a string.

Python

dbutils.fs.ls("/Volumes/main/default/my-volume/")

# Out[13]: [FileInfo(path='dbfs:/Volumes/main/default/my-volume/data.csv', name='data.csv', size=2258987, modificationTime=1711357839000)]

R

dbutils.fs.ls("/Volumes/main/default/my-volume/")

# For prettier results from dbutils.fs.ls(<dir>), please use `%fs ls <dir>`

# [[1]]
# [[1]]$path
# [1] "/Volumes/main/default/my-volume/data.csv"

# [[1]]$name
# [1] "data.csv"

# [[1]]$size
# [1] 2258987

# [[1]]$isDir
# [1] FALSE

# [[1]]$isFile
# [1] TRUE

# [[1]]$modificationTime
# [1] "1711357839000"

Scala

dbutils.fs.ls("/tmp")

// res6: Seq[com.databricks.backend.daemon.dbutils.FileInfo] = WrappedArray(FileInfo(/Volumes/main/default/my-volume/data.csv, 2258987, 1711357839000))

mkdirs command (dbutils.fs.mkdirs)

Creates the given directory if it does not exist. Also creates any necessary parent directories.

To display help for this command, run dbutils.fs.help("mkdirs").

This example creates the directory my-data within /Volumes/main/default/my-volume/.

Python

dbutils.fs.mkdirs("/Volumes/main/default/my-volume/my-data")

# Out[15]: True

R

dbutils.fs.mkdirs("/Volumes/main/default/my-volume/my-data")

# [1] TRUE

Scala

dbutils.fs.mkdirs("/Volumes/main/default/my-volume/my-data")

// res7: Boolean = true

mount command (dbutils.fs.mount)

Mounts the specified source directory into DBFS at the specified mount point.

To display help for this command, run dbutils.fs.help("mount").

Python

dbutils.fs.mount(
  source = "wasbs://<container-name>@<storage-account-name>.blob.core.chinacloudapi.cn",
  mount_point = "/mnt/<mount-name>",
  extra_configs = {"<conf-key>":dbutils.secrets.get(scope = "<scope-name>", key = "<key-name>")})

Scala

dbutils.fs.mount(
  source = "wasbs://<container-name>@<storage-account-name>.blob.core.chinacloudapi.cn/<directory-name>",
  mountPoint = "/mnt/<mount-name>",
  extraConfigs = Map("<conf-key>" -> dbutils.secrets.get(scope = "<scope-name>", key = "<key-name>")))

For additional code examples, see Connect to Azure Data Lake Storage Gen2 and Blob Storage.

mounts command (dbutils.fs.mounts)

Displays information about what is currently mounted within DBFS.

To display help for this command, run dbutils.fs.help("mounts").

Python

dbutils.fs.mounts()

Scala

dbutils.fs.mounts()

For additional code examples, see Connect to Azure Data Lake Storage Gen2 and Blob Storage.

mv command (dbutils.fs.mv)

Moves a file or directory, possibly across filesystems. A move is a copy followed by a delete, even for moves within filesystems.

To display help for this command, run dbutils.fs.help("mv").

This example moves the file rows.csv from /Volumes/main/default/my-volume/ to /Volumes/main/default/my-volume/my-data/.

Python

dbutils.fs.mv("/Volumes/main/default/my-volume/rows.csv", "/Volumes/main/default/my-volume/my-data/")

# Out[2]: True

R

dbutils.fs.mv("/Volumes/main/default/my-volume/rows.csv", "/Volumes/main/default/my-volume/my-data/")

# [1] TRUE

Scala

dbutils.fs.mv("/Volumes/main/default/my-volume/rows.csv", "/Volumes/main/default/my-volume/my-data/")

// res1: Boolean = true

put command (dbutils.fs.put)

Writes the specified string to a file. The string is UTF-8 encoded.

To display help for this command, run dbutils.fs.help("put").

This example writes the string Hello, Databricks! to a file named hello.txt in /Volumes/main/default/my-volume/. If the file exists, it will be overwritten.

Python

dbutils.fs.put("/Volumes/main/default/my-volume/hello.txt", "Hello, Databricks!", True)

# Wrote 2258987 bytes.
# Out[6]: True

R

dbutils.fs.put("/Volumes/main/default/my-volume/hello.txt", "Hello, Databricks!", TRUE)

# [1] TRUE

Scala

dbutils.fs.put("/Volumes/main/default/my-volume/hello.txt", "Hello, Databricks!", true)

// Wrote 2258987 bytes.
// res2: Boolean = true

refreshMounts command (dbutils.fs.refreshMounts)

Forces all machines in the cluster to refresh their mount cache, ensuring they receive the most recent information.

To display help for this command, run dbutils.fs.help("refreshMounts").

Python

dbutils.fs.refreshMounts()

Scala

dbutils.fs.refreshMounts()

For additiional code examples, see Connect to Azure Data Lake Storage Gen2 and Blob Storage.

rm command (dbutils.fs.rm)

Removes a file or directory and optionally all of its contents. If a file is specified, the recurse parameter is ignored. If a directory is specified, an error occurs if recurse is disabled and the directory is not empty.

To display help for this command, run dbutils.fs.help("rm").

This example removes the directory /Volumes/main/default/my-volume/my-data/ including the contents of the directory.

Python

dbutils.fs.rm("/Volumes/main/default/my-volume/my-data/", True)

# Out[8]: True

R

dbutils.fs.rm("/Volumes/main/default/my-volume/my-data/", TRUE)

# [1] TRUE

Scala

dbutils.fs.rm("/Volumes/main/default/my-volume/my-data/", true)

// res6: Boolean = true

unmount command (dbutils.fs.unmount)

Deletes a DBFS mount point.

To display help for this command, run dbutils.fs.help("unmount").

dbutils.fs.unmount("/mnt/<mount-name>")

For additional code examples, see Connect to Azure Data Lake Storage Gen2 and Blob Storage.

updateMount command (dbutils.fs.updateMount)

Similar to the dbutils.fs.mount command, but updates an existing mount point instead of creating a new one. Returns an error if the mount point is not present.

To display help for this command, run dbutils.fs.help("updateMount").

This command is available in Databricks Runtime 10.4 LTS and above.

Python

dbutils.fs.updateMount(
  source = "wasbs://<container-name>@<storage-account-name>.blob.core.chinacloudapi.cn",
  mount_point = "/mnt/<mount-name>",
  extra_configs = {"<conf-key>":dbutils.secrets.get(scope = "<scope-name>", key = "<key-name>")})

Scala

dbutils.fs.updateMount(
  source = "wasbs://<container-name>@<storage-account-name>.blob.core.chinacloudapi.cn/<directory-name>",
  mountPoint = "/mnt/<mount-name>",
  extraConfigs = Map("<conf-key>" -> dbutils.secrets.get(scope = "<scope-name>", key = "<key-name>")))

Jobs utility (dbutils.jobs)

Subutilities: taskValues

The jobs utility allows you to leverage jobs features. To display help for this utility, run dbutils.jobs.help().

Provides utilities for leveraging jobs features.

taskValues: TaskValuesUtils -> Provides utilities for leveraging job task values

taskValues subutility (dbutils.jobs.taskValues)

Commands: get, set

Provides commands for leveraging job task values.

Use this sub utility to set and get arbitrary values during a job run. These values are called task values. You can access task values in downstream tasks in the same job run. For example, you can communicate identifiers or metrics, such as information about the evaluation of a machine learning model, between different tasks within a job run. Each task can set multiple task values, get them, or both. Each task value has a unique key within the same task. This unique key is known as the task value's key. A task value is accessed with the task name and the task value's key.

To display help for this subutility, run dbutils.jobs.taskValues.help().

get command (dbutils.jobs.taskValues.get)

Gets the contents of the specified task value for the specified task in the current job run.

To display help for this command, run dbutils.jobs.taskValues.help("get").

For example:

dbutils.jobs.taskValues.get(taskKey    = "my-task", \
                            key        = "my-key", \
                            default    = 7, \
                            debugValue = 42)

In the preceding example:

• taskKey is the name of the task that set the task value. If the command cannot find this task, a ValueError is raised.
• key is the name of the task value's key that you set with the set command (dbutils.jobs.taskValues.set). If the command cannot find this task value's key, a ValueError is raised (unless default is specified).
• default is an optional value that is returned if key cannot be found. default cannot be None.
• debugValue is an optional value that is returned if you try to get the task value from within a notebook that is running outside of a job. This can be useful during debugging when you want to run your notebook manually and return some value instead of raising a TypeError by default. debugValue cannot be None.

If you try to get a task value from within a notebook that is running outside of a job, this command raises a TypeError by default. However, if the debugValue argument is specified in the command, the value of debugValue is returned instead of raising a TypeError.

set command (dbutils.jobs.taskValues.set)

Sets or updates a task value. You can set up to 250 task values for a job run.

To display help for this command, run dbutils.jobs.taskValues.help("set").

Some examples include:

dbutils.jobs.taskValues.set(key   = "my-key", \
                            value = 5)

dbutils.jobs.taskValues.set(key   = "my-other-key", \
                            value = "my other value")

In the preceding examples:

• key is the task value's key. This key must be unique to the task. That is, if two different tasks each set a task value with key K, these are two different task values that have the same key K.
• value is the value for this task value's key. This command must be able to represent the value internally in JSON format. The size of the JSON representation of the value cannot exceed 48 KiB.

If you try to set a task value from within a notebook that is running outside of a job, this command does nothing.

Library utility (dbutils.library)

Most methods in the dbutils.library submodule are deprecated. See Library utility (dbutils.library) (legacy).

You might need to programmatically restart the Python process on Azure Databricks to ensure that locally installed or upgraded libraries function correctly in the Python kernel for your current SparkSession. To do this, run the dbutils.library.restartPython command. See Restart the Python process on Azure Databricks.

Notebook utility (dbutils.notebook)

Commands: exit, run

The notebook utility allows you to chain together notebooks and act on their results. See Run a Databricks notebook from another notebook.

To list the available commands, run dbutils.notebook.help().

exit(value: String): void -> This method lets you exit a notebook with a value
run(path: String, timeoutSeconds: int, arguments: Map): String -> This method runs a notebook and returns its exit value.

exit command (dbutils.notebook.exit)

Exits a notebook with a value.

To display help for this command, run dbutils.notebook.help("exit").

This example exits the notebook with the value Exiting from My Other Notebook.

Python

dbutils.notebook.exit("Exiting from My Other Notebook")

# Notebook exited: Exiting from My Other Notebook

R

dbutils.notebook.exit("Exiting from My Other Notebook")

# Notebook exited: Exiting from My Other Notebook

Scala

dbutils.notebook.exit("Exiting from My Other Notebook")

// Notebook exited: Exiting from My Other Notebook

run command (dbutils.notebook.run)

Runs a notebook and returns its exit value. The notebook will run in the current cluster by default.

To display help for this command, run dbutils.notebook.help("run").

This example runs a notebook named My Other Notebook in the same location as the calling notebook. The called notebook ends with the line of code dbutils.notebook.exit("Exiting from My Other Notebook"). If the called notebook does not finish running within 60 seconds, an exception is thrown.

Python

dbutils.notebook.run("My Other Notebook", 60)

# Out[14]: 'Exiting from My Other Notebook'

Scala

dbutils.notebook.run("My Other Notebook", 60)

// res2: String = Exiting from My Other Notebook

Secrets utility (dbutils.secrets)

Commands: get, getBytes, list, listScopes

The secrets utility allows you to store and access sensitive credential information without making them visible in notebooks. See Secret management and Use the secrets in a notebook. To list the available commands, run dbutils.secrets.help().

get(scope: String, key: String): String -> Gets the string representation of a secret value with scope and key
getBytes(scope: String, key: String): byte[] -> Gets the bytes representation of a secret value with scope and key
list(scope: String): Seq -> Lists secret metadata for secrets within a scope
listScopes: Seq -> Lists secret scopes

get command (dbutils.secrets.get)

Gets the string representation of a secret value for the specified secrets scope and key.

To display help for this command, run dbutils.secrets.help("get").

This example gets the string representation of the secret value for the scope named my-scope and the key named my-key.

Python

dbutils.secrets.get(scope="my-scope", key="my-key")

# Out[14]: '[REDACTED]'

R

dbutils.secrets.get(scope="my-scope", key="my-key")

# [1] "[REDACTED]"

Scala

dbutils.secrets.get(scope="my-scope", key="my-key")

// res0: String = [REDACTED]

getBytes command (dbutils.secrets.getBytes)

Gets the bytes representation of a secret value for the specified scope and key.

To display help for this command, run dbutils.secrets.help("getBytes").

This example gets the byte representation of the secret value (in this example, a1!b2@c3#) for the scope named my-scope and the key named my-key.

Python

dbutils.secrets.getBytes(scope="my-scope", key="my-key")

# Out[1]: b'a1!b2@c3#'

R

dbutils.secrets.getBytes(scope="my-scope", key="my-key")

# [1] 61 31 21 62 32 40 63 33 23

Scala

dbutils.secrets.getBytes(scope="my-scope", key="my-key")

// res1: Array[Byte] = Array(97, 49, 33, 98, 50, 64, 99, 51, 35)

list command (dbutils.secrets.list)

Lists the metadata for secrets within the specified scope.

To display help for this command, run dbutils.secrets.help("list").

This example lists the metadata for secrets within the scope named my-scope.

Python

dbutils.secrets.list("my-scope")

# Out[10]: [SecretMetadata(key='my-key')]

R

dbutils.secrets.list("my-scope")

# [[1]]
# [[1]]$key
# [1] "my-key"

Scala

dbutils.secrets.list("my-scope")

// res2: Seq[com.databricks.dbutils_v1.SecretMetadata] = ArrayBuffer(SecretMetadata(my-key))

listScopes command (dbutils.secrets.listScopes)

Lists the available scopes.

To display help for this command, run dbutils.secrets.help("listScopes").

This example lists the available scopes.

Python

dbutils.secrets.listScopes()

# Out[14]: [SecretScope(name='my-scope')]

R

dbutils.secrets.listScopes()

# [[1]]
# [[1]]$name
# [1] "my-scope"

Scala

dbutils.secrets.listScopes()

// res3: Seq[com.databricks.dbutils_v1.SecretScope] = ArrayBuffer(SecretScope(my-scope))

Widgets utility (dbutils.widgets)

Commands: combobox, dropdown, get, getArgument, multiselect, remove, removeAll, text

The widgets utility allows you to parameterize notebooks. See Databricks widgets.

To list the available commands, run dbutils.widgets.help().

combobox(name: String, defaultValue: String, choices: Seq, label: String): void -> Creates a combobox input widget with a given name, default value and choices
dropdown(name: String, defaultValue: String, choices: Seq, label: String): void -> Creates a dropdown input widget a with given name, default value and choices
get(name: String): String -> Retrieves current value of an input widget
getAll: map -> Retrieves a map of all widget names and their values
getArgument(name: String, optional: String): String -> (DEPRECATED) Equivalent to get
multiselect(name: String, defaultValue: String, choices: Seq, label: String): void -> Creates a multiselect input widget with a given name, default value and choices
remove(name: String): void -> Removes an input widget from the notebook
removeAll: void -> Removes all widgets in the notebook
text(name: String, defaultValue: String, label: String): void -> Creates a text input widget with a given name and default value

combobox command (dbutils.widgets.combobox)

Creates and displays a combobox widget with the specified programmatic name, default value, choices, and optional label.

To display help for this command, run dbutils.widgets.help("combobox").

This example creates and displays a combobox widget with the programmatic name fruits_combobox. It offers the choices apple, banana, coconut, and dragon fruit and is set to the initial value of banana. This combobox widget has an accompanying label Fruits. This example ends by printing the initial value of the combobox widget, banana.

Python

dbutils.widgets.combobox(
  name='fruits_combobox',
  defaultValue='banana',
  choices=['apple', 'banana', 'coconut', 'dragon fruit'],
  label='Fruits'
)

print(dbutils.widgets.get("fruits_combobox"))

# banana

R

dbutils.widgets.combobox(
  name='fruits_combobox',
  defaultValue='banana',
  choices=list('apple', 'banana', 'coconut', 'dragon fruit'),
  label='Fruits'
)

print(dbutils.widgets.get("fruits_combobox"))

# [1] "banana"

Scala

dbutils.widgets.combobox(
  "fruits_combobox",
  "banana",
  Array("apple", "banana", "coconut", "dragon fruit"),
  "Fruits"
)

print(dbutils.widgets.get("fruits_combobox"))

// banana

SQL

CREATE WIDGET COMBOBOX fruits_combobox DEFAULT "banana" CHOICES SELECT * FROM (VALUES ("apple"), ("banana"), ("coconut"), ("dragon fruit"))

SELECT :fruits_combobox

-- banana

dropdown command (dbutils.widgets.dropdown)

Creates and displays a dropdown widget with the specified programmatic name, default value, choices, and optional label.

To display help for this command, run dbutils.widgets.help("dropdown").

This example creates and displays a dropdown widget with the programmatic name toys_dropdown. It offers the choices alphabet blocks, basketball, cape, and doll and is set to the initial value of basketball. This dropdown widget has an accompanying label Toys. This example ends by printing the initial value of the dropdown widget, basketball.

Python

dbutils.widgets.dropdown(
  name='toys_dropdown',
  defaultValue='basketball',
  choices=['alphabet blocks', 'basketball', 'cape', 'doll'],
  label='Toys'
)

print(dbutils.widgets.get("toys_dropdown"))

# basketball

R

dbutils.widgets.dropdown(
  name='toys_dropdown',
  defaultValue='basketball',
  choices=list('alphabet blocks', 'basketball', 'cape', 'doll'),
  label='Toys'
)

print(dbutils.widgets.get("toys_dropdown"))

# [1] "basketball"

Scala

dbutils.widgets.dropdown(
  "toys_dropdown",
  "basketball",
  Array("alphabet blocks", "basketball", "cape", "doll"),
  "Toys"
)

print(dbutils.widgets.get("toys_dropdown"))

// basketball

SQL

CREATE WIDGET DROPDOWN toys_dropdown DEFAULT "basketball" CHOICES SELECT * FROM (VALUES ("alphabet blocks"), ("basketball"), ("cape"), ("doll"))

SELECT :toys_dropdown

-- basketball

get command (dbutils.widgets.get)

Gets the current value of the widget with the specified programmatic name. This programmatic name can be either:

• The name of a custom widget in the notebook, for example fruits_combobox or toys_dropdown.
• The name of a custom parameter passed to the notebook as part of a notebook task, for example name or age. For more information, see the coverage of parameters for notebook tasks in the jobs UI or the notebook_params field in the Trigger a new job run (POST /jobs/run-now) operation in the Jobs API.

To display help for this command, run dbutils.widgets.help("get").

This example gets the value of the widget that has the programmatic name fruits_combobox.

Python

dbutils.widgets.get('fruits_combobox')

# banana

R

dbutils.widgets.get('fruits_combobox')

# [1] "banana"

Scala

dbutils.widgets.get("fruits_combobox")

// res6: String = banana

SQL

SELECT :fruits_combobox

-- banana

This example gets the value of the notebook task parameter that has the programmatic name age. This parameter was set to 35 when the related notebook task was run.

Python

dbutils.widgets.get('age')

# 35

R

dbutils.widgets.get('age')

# [1] "35"

Scala

dbutils.widgets.get("age")

// res6: String = 35

SQL

SELECT :age

-- 35

getAll command (dbutils.widgets.getAll)

Gets a mapping of all current widget names and values. This can be especially useful to quickly pass widget values to a spark.sql() query.

This command is available in Databricks Runtime 13.3 LTS and above. It is only available for Python and Scala.

To display help for this command, run dbutils.widgets.help("getAll").

This example gets the map of widget values and passes it as parameter arguments in a Spark SQL query.

Python

df = spark.sql("SELECT * FROM table where col1 = :param", dbutils.widgets.getAll())
df.show()

# Query output

Scala

val df = spark.sql("SELECT * FROM table where col1 = :param", dbutils.widgets.getAll())
df.show()

// res6: Query output

getArgument command (dbutils.widgets.getArgument)

Gets the current value of the widget with the specified programmatic name. If the widget does not exist, an optional message can be returned.

To display help for this command, run dbutils.widgets.help("getArgument").

This example gets the value of the widget that has the programmatic name fruits_combobox. If this widget does not exist, the message Error: Cannot find fruits combobox is returned.

Python

dbutils.widgets.getArgument('fruits_combobox', 'Error: Cannot find fruits combobox')

# Deprecation warning: Use dbutils.widgets.text() or dbutils.widgets.dropdown() to create a widget and dbutils.widgets.get() to get its bound value.
# Out[3]: 'banana'

R

dbutils.widgets.getArgument('fruits_combobox', 'Error: Cannot find fruits combobox')

# Deprecation warning: Use dbutils.widgets.text() or dbutils.widgets.dropdown() to create a widget and dbutils.widgets.get() to get its bound value.
# [1] "banana"

Scala

dbutils.widgets.getArgument("fruits_combobox", "Error: Cannot find fruits combobox")

// command-1234567890123456:1: warning: method getArgument in trait WidgetsUtils is deprecated: Use dbutils.widgets.text() or dbutils.widgets.dropdown() to create a widget and dbutils.widgets.get() to get its bound value.
// dbutils.widgets.getArgument("fruits_combobox", "Error: Cannot find fruits combobox")
//                 ^
// res7: String = banana

multiselect command (dbutils.widgets.multiselect)

Creates and displays a multiselect widget with the specified programmatic name, default value, choices, and optional label.

To display help for this command, run dbutils.widgets.help("multiselect").

This example creates and displays a multiselect widget with the programmatic name days_multiselect. It offers the choices Monday through Sunday and is set to the initial value of Tuesday. This multiselect widget has an accompanying label Days of the Week. This example ends by printing the initial value of the multiselect widget, Tuesday.

Python

dbutils.widgets.multiselect(
  name='days_multiselect',
  defaultValue='Tuesday',
  choices=['Monday', 'Tuesday', 'Wednesday', 'Thursday',
    'Friday', 'Saturday', 'Sunday'],
  label='Days of the Week'
)

print(dbutils.widgets.get("days_multiselect"))

# Tuesday

R

dbutils.widgets.multiselect(
  name='days_multiselect',
  defaultValue='Tuesday',
  choices=list('Monday', 'Tuesday', 'Wednesday', 'Thursday',
    'Friday', 'Saturday', 'Sunday'),
  label='Days of the Week'
)

print(dbutils.widgets.get("days_multiselect"))

# [1] "Tuesday"

Scala

dbutils.widgets.multiselect(
  "days_multiselect",
  "Tuesday",
  Array("Monday", "Tuesday", "Wednesday", "Thursday",
    "Friday", "Saturday", "Sunday"),
  "Days of the Week"
)

print(dbutils.widgets.get("days_multiselect"))

// Tuesday

SQL

CREATE WIDGET MULTISELECT days_multiselect DEFAULT "Tuesday" CHOICES SELECT * FROM (VALUES ("Monday"), ("Tuesday"), ("Wednesday"), ("Thursday"), ("Friday"), ("Saturday"), ("Sunday"))

SELECT :days_multiselect

-- Tuesday

remove command (dbutils.widgets.remove)

Removes the widget with the specified programmatic name.

To display help for this command, run dbutils.widgets.help("remove").

This example removes the widget with the programmatic name fruits_combobox.

Python

dbutils.widgets.remove('fruits_combobox')

R

dbutils.widgets.remove('fruits_combobox')

Scala

dbutils.widgets.remove("fruits_combobox")

SQL

REMOVE WIDGET fruits_combobox

removeAll command (dbutils.widgets.removeAll)

Removes all widgets from the notebook.

To display help for this command, run dbutils.widgets.help("removeAll").

This example removes all widgets from the notebook.

Python

dbutils.widgets.removeAll()

R

dbutils.widgets.removeAll()

Scala

dbutils.widgets.removeAll()

text command (dbutils.widgets.text)

Creates and displays a text widget with the specified programmatic name, default value, and optional label.

To display help for this command, run dbutils.widgets.help("text").

This example creates and displays a text widget with the programmatic name your_name_text. It is set to the initial value of Enter your name. This text widget has an accompanying label Your name. This example ends by printing the initial value of the text widget, Enter your name.

Python

dbutils.widgets.text(
  name='your_name_text',
  defaultValue='Enter your name',
  label='Your name'
)

print(dbutils.widgets.get("your_name_text"))

# Enter your name

R

dbutils.widgets.text(
  name='your_name_text',
  defaultValue='Enter your name',
  label='Your name'
)

print(dbutils.widgets.get("your_name_text"))

# [1] "Enter your name"

Scala

dbutils.widgets.text(
  "your_name_text",
  "Enter your name",
  "Your name"
)

print(dbutils.widgets.get("your_name_text"))

// Enter your name

SQL

CREATE WIDGET TEXT your_name_text DEFAULT "Enter your name"

SELECT :your_name_text

-- Enter your name

Databricks Utilities API library

To accelerate application development, it can be helpful to compile, build, and test applications before you deploy them as production jobs. To enable you to compile against Databricks Utilities, Databricks provides the dbutils-api library. You can download the dbutils-api library from the DBUtils API webpage on the Maven Repository website or include the library by adding a dependency to your build file:

• SBT

  libraryDependencies += "com.databricks" % "dbutils-api_TARGET" % "VERSION"
  

• Maven

  <dependency>
      <groupId>com.databricks</groupId>
      <artifactId>dbutils-api_TARGET</artifactId>
      <version>VERSION</version>
  </dependency>
  

• Gradle

  compile 'com.databricks:dbutils-api_TARGET:VERSION'
  

Replace TARGET with the desired target (for example 2.12) and VERSION with the desired version (for example 0.0.5). For a list of available targets and versions, see the DBUtils API webpage on the Maven Repository website.

Once you build your application against this library, you can deploy the application.

Limitations

Calling dbutils inside of executors can produce unexpected results or potentially result in errors.

If you need to run file system operations on executors using dbutils, there are several faster and more scalable alternatives available:

• For file copy or move operations, you can check a faster option of running filesystem operations described in Parallelize filesystem operations.
• For file system list and delete operations, you can refer to parallel listing and delete methods utilizing Spark in How to list and delete files faster in Databricks.

For information about executors, see Cluster Mode Overview on the Apache Spark website.