How To Delete Files From Databricks

Deleting Files from Databricks

Databricks provides several methods to delete files from its file system, known as DBFS. Here are some common techniques:

Method 1: Using Databricks Notebooks

You can delete files using Databricks Notebooks with the dbutils.fs.rm() command. This method is interactive and allows for immediate feedback within the notebook environment.

Example:

dbutils.fs.rm("dbfs:/path/to/your/file.csv")

Method 2: Using Databricks CLI

The Databricks CLI offers a command-line interface to manage files in DBFS. You can use the dbfs rm command to delete files.

Example:

dbfs rm dbfs:/path/to/your/file.csv

Method 3: Using Databricks REST API

The Databricks REST API provides a programmatic way to delete files by sending a POST request to the /api/2.0/dbfs/delete endpoint.

Example:

      POST /api/2.0/dbfs/delete HTTP/1.1
      Content-Type: application/json
      {
        "path": "/path/to/your/file.csv",
        "recursive": false
      }
    

Method 4: Using Databricks UI

The Databricks UI allows you to delete files directly from the web interface. Navigate to the file in the Catalog section and use the delete option.

Frequently Asked Questions

• Q: What happens if I try to delete a non-empty directory without recursion?

  A: If you attempt to delete a non-empty directory without setting recursion to true, the operation will fail with an IO_ERROR.

• Q: How do I verify if a file has been deleted from DBFS?

  A: You can verify if a file has been deleted by listing the directory contents using %fs ls or checking the file’s path in the Databricks UI.

• Q: Can I use Databricks Notebooks to delete multiple files at once?

  A: Yes, you can delete multiple files by calling dbutils.fs.rm() for each file or by using a loop to iterate over a list of file paths.

• Q: What is the recommended method for deleting a large number of files?

  A: For large-scale deletions, it is recommended to use Databricks Notebooks or the Databricks CLI within a cluster environment for better control and manageability.

• Q: How do I handle errors when deleting files using the REST API?

  A: Error responses from the REST API include an error code and a human-readable message. You should handle these errors based on their codes (e.g., 400 for bad requests).

• Q: Can I recover deleted files from DBFS?

  A: Generally, files deleted from DBFS are not recoverable. It is important to back up critical data before deletion.

• Q: Are there any limitations on deleting files using the Databricks CLI?

  A: The Databricks CLI does not have specific limitations on file deletion, but it requires proper authentication and access permissions.

Bottom Line

Databricks offers versatile methods for deleting files from its file system, catering to different user preferences and operational needs. Whether you prefer interactive notebooks, command-line interfaces, REST APIs, or the user-friendly UI, Databricks provides a suitable approach for managing your files efficiently.

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