Download Folder From DBFS: Databricks Guide

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Databricks: How to Download a Folder from DBFS

Hey guys! Ever found yourself needing to snag an entire folder from Databricks File System (DBFS) to your local machine? It's a common task, and I'm here to walk you through it step by step. Whether you're backing up important data, analyzing files locally, or just moving things around, knowing how to download a folder from DBFS is super handy. Let's dive in!

Understanding DBFS

Before we get into the nitty-gritty, let’s quickly cover what DBFS is. DBFS, or Databricks File System, is a distributed file system mounted into a Databricks workspace. Think of it as a convenient storage layer that allows you to store and access files much like a regular file system, but with the added benefits of cloud storage – scalability, durability, and accessibility from various compute resources within your Databricks environment.

Why is this important? Because DBFS is often where you'll store your datasets, models, and other essential files when working in Databricks. Being able to move these folders effectively is crucial for many data-related tasks.

Method 1: Using Databricks CLI

The Databricks Command-Line Interface (CLI) is a powerful tool that allows you to interact with your Databricks workspace from your local machine. One of its many uses is downloading folders from DBFS. Here’s how you can do it:

Step 1: Install and Configure Databricks CLI

First things first, you need to have the Databricks CLI installed on your computer. If you haven't already, you can install it using pip:

pip install databricks-cli

Once installed, you need to configure it to connect to your Databricks workspace. Open your terminal and run:

databricks configure

The CLI will prompt you for your Databricks host and a personal access token. Your host will typically look like https://<your-databricks-instance>.cloud.databricks.com. To generate a personal access token:

  1. Go to your Databricks workspace.
  2. Click on your username in the top right corner and select "User Settings".
  3. Go to the "Access Tokens" tab.
  4. Click "Generate New Token".
  5. Enter a description and lifetime for the token, then click "Generate".
  6. Copy the token and paste it into your terminal when prompted by the CLI.

Important: Treat your personal access token like a password. Keep it secret and don't share it with anyone.

Step 2: Download the Folder

With the CLI configured, downloading a folder is a breeze. Use the following command:

databricks fs cp -r dbfs:/path/to/your/folder /local/path/to/destination

Replace dbfs:/path/to/your/folder with the path to the folder you want to download from DBFS, and /local/path/to/destination with the local directory where you want to save the folder. The -r flag is crucial; it tells the CLI to recursively copy the entire folder and its contents.

For example, if you want to download a folder named my_data from the root of DBFS to a local directory named downloaded_data in your home directory, the command would look like this:

databricks fs cp -r dbfs:/my_data /Users/yourusername/downloaded_data

The CLI will then start downloading the folder and its contents. You'll see a progress indicator in your terminal, showing the files being copied.

Step 3: Verify the Download

Once the download is complete, it's always a good idea to verify that everything was copied correctly. Navigate to the local directory where you saved the folder and check if all the files and subfolders are there.

Method 2: Using %fs Magic Command in Databricks Notebook

If you're working within a Databricks notebook, you can use the %fs magic command to interact with DBFS. This method is handy for quick downloads, especially when you're already in a notebook environment.

Step 1: Accessing the File System

The %fs magic command allows you to run DBFS commands directly from a notebook cell. To download a folder, you can use the cp (copy) command with the -r flag for recursive copying:

%fs cp -r dbfs:/path/to/your/folder file:/local/path/to/destination

Again, replace dbfs:/path/to/your/folder with the path to the folder you want to download from DBFS, and file:/local/path/to/destination with the local directory where you want to save the folder. Note the file: prefix for the local path; this tells Databricks that you're referring to a local file system path.

For example:

%fs cp -r dbfs:/my_data file:/databricks/driver/downloaded_data

This command will download the my_data folder from DBFS to the /databricks/driver/downloaded_data directory on the driver node of your Databricks cluster. But there is an important consideration:

Step 2: Understanding the Download Location

When you use the %fs magic command, the files are downloaded to the driver node of your Databricks cluster, not your local machine directly. The driver node is a virtual machine in the cloud where the main process of your Databricks job runs.

To access the downloaded files on your local machine, you'll need to copy them from the driver node to your local machine. You can do this using the Databricks CLI or other file transfer methods.

Step 3: Copying from Driver Node to Local Machine

One simple method is to use the dbutils.fs.cp command to copy files from the driver node to DBFS, and then use the Databricks CLI to download them to your local machine.

First, copy the folder from the driver node to DBFS:

dbutils.fs.cp("file:/databricks/driver/downloaded_data", "dbfs:/user/yourusername/downloaded_data", recurse=True)

Replace yourusername with your Databricks username. Then, use the Databricks CLI to download the folder from DBFS to your local machine:

databricks fs cp -r dbfs:/user/yourusername/downloaded_data /Users/yourusername/downloaded_data

This will copy the folder from the driver node to DBFS, and then from DBFS to your local machine.

Method 3: Using shutil library and FUSE

This method involves using the shutil library in Python along with FUSE (Filesystem in Userspace) to mount DBFS as a local file system. This approach is more advanced but can be useful for seamless file operations.

Step 1: Install fuse-dbfs

First, you need to install fuse-dbfs. This package allows you to mount DBFS as a local file system using FUSE. You can install it using pip:

pip install fuse-dbfs

Step 2: Mount DBFS using FUSE

Mount DBFS to a local directory. You'll need your Databricks host and token for authentication. Replace <databricks-host> and <databricks-token> with your actual credentials:

fuse-dbfs mount /mnt/dbfs --dbfs-host <databricks-host> --dbfs-token <databricks-token>

Step 3: Use shutil to copy the folder

Now that DBFS is mounted, you can use the shutil library in Python to copy the folder from the mounted DBFS path to your local machine:

import shutil

shutil.copytree("/mnt/dbfs/path/to/your/folder", "/local/path/to/destination")

Replace /mnt/dbfs/path/to/your/folder with the path to the folder you want to download from DBFS, and /local/path/to/destination with the local directory where you want to save the folder.

Step 4: Unmount DBFS

Once you're done, unmount DBFS:

fuse-dbfs unmount /mnt/dbfs

Considerations and Troubleshooting

  • Large Folders: Downloading large folders can take a significant amount of time and consume a lot of bandwidth. Consider compressing the folder before downloading to speed up the process.
  • Permissions: Ensure you have the necessary permissions to access the folder in DBFS. If you encounter permission errors, contact your Databricks administrator.
  • Network Issues: A stable network connection is crucial for successful downloads. Check your internet connection if you experience interruptions.
  • File Size Limits: Be aware of any file size limits imposed by your Databricks environment or your local file system.

Conclusion

Downloading folders from DBFS is a fundamental skill for anyone working with Databricks. Whether you prefer the Databricks CLI, the %fs magic command, or the shutil library with FUSE, these methods provide flexibility for managing your data. Choose the method that best suits your workflow and enjoy the seamless data transfer! Remember to handle your credentials securely and optimize your downloads for efficiency. Happy data wrangling, folks!