Skip to content

alex-lopes-databricks/databricks_storage_analyzer

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

12 Commits
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

Databricks Storage Analyzer

The 'storage_analyzer' is a tool that allows the visualization of the Databricks tables size, it includes a workflow that will scan the tables and a Dashboard to display storage size Additionally it also contains a Dashboard to visualize UC objects inside catalogs

  • The images have been anonymized

How to configure scanning

Go to src/search_config.yaml and configure the search scope the syntax is similar to unix file system listing and allow to use '*' to include every object at certain level, you can also configure exclusions there are tables, schemas or catalogs you do not want to scan eg:

How to change the destionation schema where the tables will be created

Go to resources/storage_analyzer.job.yml and change the parameter below:

Steps to install and scan workspace

  1. Install the Databricks CLI from https://docs.databricks.com/dev-tools/cli/databricks-cli.html

  2. Authenticate to your Databricks workspace, if you have not done so already:

    $ databricks configure
    
  3. To deploy a development copy of this project, type:

    $ databricks bundle deploy --target dev
    

    (Note that "dev" is the default target, so the --target parameter is optional here.)

    This deploys everything that's defined for this project. For example, the default template would deploy a job called [dev yourname] storage_analyzer_job to your workspace. You can find that job by opening your workpace and clicking on Workflows.

  4. Similarly, to deploy a production copy, type:

    $ databricks bundle deploy --target prod
    

    Note that the default job from the template has a schedule that runs every day (defined in resources/storage_analyzer.job.yml). The schedule is paused when deploying in development mode (see https://docs.databricks.com/dev-tools/bundles/deployment-modes.html).

  5. To run a job or pipeline, use the "run" command:

    $ databricks bundle run
    
  6. Optionally, install developer tools such as the Databricks extension for Visual Studio Code from https://docs.databricks.com/dev-tools/vscode-ext.html.

  7. For documentation on the Databricks asset bundles format used for this project, and for CI/CD configuration, see https://docs.databricks.com/dev-tools/bundles/index.html.

    License: Free to use, support is not provided (best effort) please submit a github issue

About

Databricks Storage Analyzer

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages