Manage files in volumes
This article provides examples for managing files in Unity Catalog volumes for various user interfaces, tools, libraries, and languages.
Databricks recommends using volumes for managing all access to non-tabular data in cloud object storage. Examples of non-tabular data include the following:
- Data files for ingestion such as CSV, JSON, and Parquet.
- Text, image, and audio files for data science, ML, and AI workloads.
- CSV or JSON artifacts written by Azure Databricks for integration with external systems.
You can use volumes for storing files such as libraries, init scripts, and build artifacts. See Recommendations for files in volumes and workspace files.
Work with files in volumes using the Catalog Explorer UI
Catalog Explorer provides options for common file management tasks for files stored with Unity Catalog volumes.
To interact with files in a volume, do the following:
- In your Azure Databricks workspace, click Catalog.
- Search or browse for the volume that you want to work with and select it.
For details on creating and managing volumes, see Create and manage volumes.
Upload files to a volume
The Upload to this volume button opens a dialog to upload files. See Upload files to a Unity Catalog volume.
Uploaded files cannot exceed 5 GB.
Download files from a volume
To download files from a volume, do the following:
- Select one or more files.
- Click Download to download these files.
Delete files from a volume
To delete files from a volume, do the following:
- Select one or more files.
- Click Delete.
- Click Delete to confirm in the dialog that appears.
Create a blank directory
To create a new directory in a volume, do the following:
- Click the to the right of the volume name.
- Select Create directory.
- Enter a directory name.
- Click Create.
Delete directories from a volume
To delete directories from a volume, do the following:
- Select one or more directories.
- Click Delete.
- Click Delete to confirm in the dialog that appears.
UI file management tasks for volumes
Click the kebab menu next to a file name to perform the following actions:
- Copy path
- Download file
- Delete file
- Create table
Create a table from data in a volume
Azure Databricks provides a UI to create a Unity Catalog managed table from a file, files, or directory of files stored in a Unity Catalog volume.
You must have CREATE TABLE
permissions in the target schema and have access to a running SQL warehouse.
Select one or more files or a directory. Files should have the same data layout.
Click Create table. The Create table from volumes dialog appears.
Use the provided dialog to review a preview of the data and complete the following configurations:
- Choose to Create new table or Overwrite existing table
- Select the target Catalog and Schema.
- Specify the Table name.
- (Optional) Override default column names and types, or choose to exclude columns.
Note
Click Advanced attributes to view additional options.
Click Create table to create the table with the specified attributes. Upon completion, Catalog Explorer displays the table details.
Programmatically work with files in volumes on Azure Databricks
You can read and write files in volumes from all supported languages and workspace editors using the following format:
/Volumes/catalog_name/schema_name/volume_name/path/to/files
You interact with files in volumes in the same way that you interact with files in any cloud object storage location. That means that if you currently manage code that uses cloud URIs, DBFS mount paths, or DBFS root paths to interact with data or files, you can update your code to use volumes instead.
Note
Volumes are only used for non-tabular data. Databricks recommends registering tabular data using Unity Catalog tables and then reading and writing data using table names.
Read and write data in volumes
You can use Apache Spark, pandas, Spark SQL, and other OSS libraries to read and write data files in volumes.
The following examples demonstrate reading a CSV file stored in a volume:
Python
df = spark.read.format("csv").load("/Volumes/catalog_name/schema_name/volume_name/data.csv")
display(df)
Pandas
import pandas as pd
df = pd.read_csv('/Volumes/catalog_name/schema_name/volume_name/data.csv')
display(df)
SQL
SELECT * FROM csv.`/Volumes/catalog_name/schema_name/volume_name/data.csv`
Utility commands for files in volumes
Databricks provides the following tools for managing files in volumes:
- The
dbutils.fs
submodule in Databricks Utilities. See File system utility (dbutils.fs). - The
%fs
magic, which is an alias fordbutils.fs
. - The
%sh
magic, which allows bash command against volumes.
For an example of using these tools to download files from the internet, unzip files, and move files from ephemeral block storage to volumes, see Download data from the internet.
You can also use OSS packages for file utility commands, such as the Python os
module, as shown in the following example:
import os
os.mkdir('/Volumes/catalog_name/schema_name/volume_name/directory_name')
Manage files in volumes from external tools
Databricks provides a suite of tools for programmatically managing files in volumes from your local environment or integrated systems.
SQL commands for files in volumes
Azure Databricks supports the following SQL keywords for interacting with files in volumes:
Note
Databricks notebooks or query editor only support the LIST
command.
The following Databricks SQL connectors and drivers support managing files in volumes:
- The Databricks SQL Connector for Python. See Manage files in Unity Catalog volumes.
- The Databricks SQL Driver for Go. See Manage files in Unity Catalog volumes.
- The Databricks SQL Driver for Node.js. See Manage files in Unity Catalog volumes.
- The Databricks JDBC driver. See Manage files in Unity Catalog volumes with the Databricks JDBC Driver.
- The Databricks ODBC driver. See Manage files in Unity Catalog volumes with the Databricks ODBC Driver.
Manage files in volumes with the Databricks CLI
Use the submcommands in databricks fs
. See fs command group.
Note
The Databricks CLI requires the scheme dbfs:/
to precede all volumes paths. For example, dbfs:/Volumes/catalog_name/schema_name/volume_name/path/to/data
.
Manage files in volumes with SDKs
The following SDKs support managing files in volumes:
- The Databricks SDK for Python. Use the available methods in WorkspaceClient.files. For examples, see Manage files in Unity Catalog volumes.
- The Databricks SDK for Java. Use the available methods in WorkspaceClient.files. For examples, see Manage files in Unity Catalog volumes.
- The Databricks SDK for Go. Use the available methods in WorkspaceClient.files. For examples, see Manage files in Unity Catalog volumes.
Manage files in volumes with the REST API
Use the Files API to manage files in volumes.
REST API examples for files in volumes
The following examples use curl
and the Databricks REST API to perform file management tasks in volumes.
The following example creates an empty folder named my-folder
in the specified volume.
curl --request PUT "https://${DATABRICKS_HOST}/api/2.0/fs/directories/Volumes/main/default/my-volume/my-folder/" \
--header "Authorization: Bearer ${DATABRICKS_TOKEN}"
The following example creates a file named data.csv
with the specified data in the specified path in the volume.
curl --request PUT "https://${DATABRICKS_HOST}/api/2.0/fs/files/Volumes/main/default/my-volume/my-folder/data.csv?overwrite=true" \
--header "Authorization: Bearer ${DATABRICKS_TOKEN}" \
--header "Content-Type: application/octet-stream" \
--data-binary $'id,Text\n1,Hello World!'
The following example lists the contents of a volume in the specified path. This example uses jq to format the response body’s JSON for easier reading.
curl --request GET "https://${DATABRICKS_HOST}/api/2.0/fs/directories/Volumes/main/default/my-volume/" \
--header "Authorization: Bearer ${DATABRICKS_TOKEN}" | jq .
The following example lists the contents of a folder in a volume in the specified path. This example uses jq to format the response body’s JSON for easier reading.
curl --request GET "https://${DATABRICKS_HOST}/api/2.0/fs/directories/Volumes/main/default/my-volume/my-folder" \
--header "Authorization: Bearer ${DATABRICKS_TOKEN}" | jq .
The following example prints the contents of a file in the specified path in a volume.
curl --request GET "https://${DATABRICKS_HOST}/api/2.0/fs/files/Volumes/main/default/my-volume/my-folder/data.csv" \
--header "Authorization: Bearer ${DATABRICKS_TOKEN}"
The following example deletes a file in the specified path from a volume.
curl --request DELETE "https://${DATABRICKS_HOST}/api/2.0/fs/files/Volumes/main/default/my-volume/my-folder/data.csv" \
--header "Authorization: Bearer ${DATABRICKS_TOKEN}"
The following example deletes a folder from the specified volume.
curl --request DELETE "https://${DATABRICKS_HOST}/api/2.0/fs/directories/Volumes/main/default/my-volume/my-folder/" \
--header "Authorization: Bearer ${DATABRICKS_TOKEN}"
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