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`fsspec`-based file system interface for Databricks file system"s"

Project description

fsspec-databricks

PyPI - Version codecov

File system interface for Databricks file system"s".

fsspec-databricks provides a fsspec-compliant file system implementation that unifies access to Databricks file systems, including:

The library routes dbfs:/ and POSIX-style paths to the appropriate Databricks file system implementation and supports copying and streaming between them.

Features

  • Provides seamless access to files in different Databricks file systems with DBFS URLs (dbfs:/path/to/file) or POSIX paths (/path/to/file).
    • Automatically routes file operations to appropriate file systems based on file path patterns.
    • Implements file operations across different file systems, for example, copying a file from Workspace to Unity Catalog Volume or vice versa.
  • Fallback to the local file system access when running within a Databricks workspace.
  • Implemented on Databricks Python SDK.

Compatibility

  • Python 3.10 to 3.14
  • databricks-sdk: 0.99.0 or later
  • Databricks workspace: Tested on the following environments at the moment.
    • Azure Databricks
    • Databricks Free Edition

Getting started

Installation

You can install fsspec-databricks from PyPI.

# with pip
pip install fsspec-databricks
# with UV
uv add fsspec-databricks

Usage

Then you can directly instantiate DatabricksFileSystem in fsspec_databricks module.

from fsspec_databricks import DatabricksFileSystem

fs = DatabricksFileSystem()

Or, you can register DatabricksFileSystem as the default file system implementation for dbfs:/ URL scheme by calling fsspec_databricks.use().

import fsspec
import fsspec_databricks

fsspec_databricks.use()

fs = fsspec.filesystem("dbfs")  # DatabricksFileSystem

For more details on how to use the fsspec file system objects, see fsspec's documentation.

Supported file paths

fsspec-databricks supports file paths with dbfs:/ scheme.

It uses the same path patterns as Databricks to map dbfs:/ and POSIX paths to the appropriate file system implementation.

URL pattern Mapped file system
dbfs:/Volumes/(catalog)/(schema)/(volume)/path/to/file Unity Catalog Volume file system
dbfs:/Workspace/path/to/file Databricks Workspace file system
dbfs:/... (other than above) Legacy DBFS (deprecated)

Examples:

fs.ls("dbfs:/Volumes/my_catalog/my_schema/my_volume/path")  # Access Unity Catalog Volume files
fs.ls("dbfs:/Workspace/Users/user-a/path")  # Access workspace files
fs.ls("dbfs:/data/path")  # Access legacy DBFS files

fsspec-databricks supports also stripped, POSIX-like paths without dbfs:/ scheme.

Path pattern Mapped file system
/Volumes/(catalog)/(schema)/(volume)/path/to/file Unity Catalog Volume file system
/Workspace/path/to/file Databricks Workspace file system (only in DBFS-disabled workspace)
/... (other than above) Legacy DBFS (deprecated)

Examples:

fs.ls("/Volumes/my_catalog/my_schema/my_volume/path")  # Access Unity Catalog Volume files
fs.ls("/Workspace/Users/user-a/path")  # Access workspace files (only in DBFS-disabled workspace)
fs.ls("/data/path")  # Access legacy DBFS files

For more details aboutdbfs:/ and POSIX path support in Databricks, see the official documentation.

Authentication

fsspec-databricks uses Databricks Unified Authentication provided by Databricks Python SDK.

You can find information about supported authentication parameters and environment variables in the Databricks Python SDK documentation.

Default authentication

If Databricks Unified Authentication is configured, fsspec-databricks will pick up credentials from the default profile. For more, see the above Databricks SDK docs.

from fsspec_databricks.spec import DatabricksFileSystem

fs = DatabricksFileSystem()

with fs.open("dbfs:/Volumes/...") as f:
    ...

Via constructor parameters

You can programmatically configure authentication by passing parameters to DatabricksFileSystem constructor.

# Authentication with PAT
fs = DatabricksFileSystem(host=host_url, token=access_token)

# Use different profile
fs = DatabricksFileSystem(profile="production")

Via environment variables

Or, you can configure authentication via environment variables.

# Shell
export DATABRICKS_CONFIG_PROFILE=production
# Then in Python
fs = DatabricksFileSystem()  # will use the "production" profile

By fsspec configuration

You can use the fsspec's configuration model to configure and persist authentication parameters.

With WorkspaceClient

You can create DatabricksFileSystem by explicitly setting Databricks SDK's WorkspaceClient object. The created DatabricksFileSystem instance will use the authentication configured in the provided WorkspaceClient object.

from databricks.sdk import WorkspaceClient

client = WorkspaceClient(...)
...

fs = DatabricksFileSystem(client=client)

Note: a DatabricksFileSystem created with a WorkspaceClient will generally not be serializable, because WorkspaceClient instances are not serializable. Consider using other configuration methods for if you need serializable filesystem objects.

Configuration options

In addition to the authentication parameters, fsspec-databricks supports the following configuration options.

Options for general file system behavior

Parameter name Description Default
config An optional pre-configured Databricks SDK Config object. If provided, it will be used for authentication. None
client An optional pre-configured Databricks SDK WorkspaceClient object. If provided, it will be used for accessing the Databricks Workspace API. None
use_local_fs_in_workspace Access files from the local file system rather than the remote Databricks API when running within a Databricks workspace. True
verbose_debug_log Whether to enable verbose debug logging for file system operations. False

Options for Unity Catalog Volume file system

Parameter name Description Default
volume_fs_max_read_concurrency The maximum number of concurrent file read operations on a Unity Catalog Volume file. 10
volume_fs_min_read_block_size The minimum data size to read for each read operation on a Unity Catalog Volume file. 512 * 1024 (512 kb)
volume_fs_max_read_block_size The maximum data size to read for each read operation on a Unity Catalog Volume file. 8 * 1024 * 1024 (8 mb)
volume_fs_max_write_concurrency The maximum number of concurrent file write operations on a Unity Catalog Volume file. 10
volume_fs_min_write_block_size The minimum data size to write for each write operation on a Unity Catalog Volume file. 5 * 1024 * 1024 (5 mb)
volume_fs_max_write_block_size The maximum data size to write for each write operation on a Unity Catalog Volume file. 32 * 1024 * 1024 (32 mb)

Differences from the original DatabricksFileSystem in fsspec

fsspec provides its own implementation of DatabricksFileSystem ( fsspec.implementations.DatabricksFileSystem).

The main difference between DatabricksFileSystem in fsspec-databricks and the original one in fsspec is that the original one is for legacy DBFS (Databricks File System), which Databricks has already deprecated.

Databricks currently supports workspace files and Unity Catalog volumes in addition to the legacy DBFS, and it continues to use the dbfs:/ URL scheme for both legacy DBFS and the other file systems (documentation).

fsspec-databricks primarily aims to support new file systems (workspace files and Unity Catalog volumes) and enable seamless access to them using the same dbfs:/ URL scheme supported in Databricks workspaces.

Project status

The current status of this library is early beta. Its API and behavior are subject to change during further development and testing. In addition, the current version relies on the undocumented multipart upload API for Unity Catalog Volume file write, which Databricks does not officially support and may change without notice.

Limitations

In addition, the following features are not yet implemented or have not been tested well.

  • Resumable file upload for Unity Catalog Volume files (required for Databricks on GCP)
  • Legacy DBFS support (deprecated by Databricks and not recommended for use)
  • Compatibility with Databricks on AWS and Databricks on GCP

We are actively developing and testing the library, and we welcome contributions and feedback from the community.

Development

Some tests in this library require access to actual Databricks workspaces to verify its file system operations in the real Databricks environment. You need to configure access to a Databricks workspace and create work directories within it before running the tests.

Work directories in Databricks workspace

You need to create work directories in your Databricks workspace and Unity Catalog to use for the tests and set the POSIX paths (without the dbfs:/ scheme) of the test directories in the following environment variables.

Location Environment variable name default
Unity Catalog Volume FSSPEC_DATABRICKS_VOLUME_TEST_ROOT /Volumes/fsspec_test_catalog/fsspec_test_schema/test
Workspace files FSSPEC_DATABRICKS_WORKSPACE_TEST_ROOT /fsspec-databricks-test

Local development

Configure Databricks Unified authentication locally, and set environment variable FSSPEC_DATABRICKS_VOLUME_TEST_ROOT and FSSPEC_DATABRICKS_WORKSPACE_TEST_ROOT to specify the location of work directories to use.

You can set authentication parameters and the environment variables above to .env file in the project root directory.

GitHub Actions

You need a Databricks service principal that has read-write access to the work directories.

Set the following GitHub Actions secrets and variables in the repository settings.

Secret name Description
DATABRICKS_HOST The URL of the Databricks workspace
DATABRICKS_CLIENT_ID The client ID of the Databricks service principal to use for testing
DATABRICKS_CLIENT_SECRET The client secret of the Databricks service principal to use for testing
CODECOV_TOKEN The repository upload token for Codecov
Variable name Description
FSSPEC_DATABRICKS_VOLUME_TEST_ROOT The POSIX path of the work directory in Unity Catalog Volume to use for testing.
FSSPEC_DATABRICKS_WORKSPACE_TEST_ROOT The POSIX path of the directory in Databricks Workspace files to use for testing.

License

Apache License 2.0. See LICENSE for more details.

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