August 2021

  • Article

These features and Azure Databricks platform improvements were released in August 2021.

Note

Releases are staged. Your Azure Databricks account may not be updated until a week or more after the initial release date.

Databricks Repos GA

August 31, 2021

Databricks Repos is now generally available. With Repos you can create new or clone existing Git repositories in Azure Databricks, work with notebooks in these repositories, follow Git-based development and collaboration best practices, and integrate your CI/CD workflows with Repos APIs. Databricks Repos integrates with GitHub, Bitbucket, GitLab, and Azure DevOps. For details, see Git integration with Databricks Git folders and Repos API.

Increased timeout for long-running notebook jobs

Aug 23-30, 2021: Version 3.53

You can now run notebook workflow jobs that take up to 30 days to complete. Previously, only notebook workflow jobs taking up to 48 hours to complete were supported. See Run a Databricks notebook from another notebook for more information.

Jobs service stability and scalability improvements

Aug 23-30, 2021: Version 3.53

The following changes increase the stability and scalability of the Jobs service:

  • Each new job and run is assigned a longer, unique, numeric, non-sequential identifier. Clients that use the Jobs API and depend on a fixed identifier length or sequential or monotonically increasing identifiers must be modified to accept identifiers that are longer, non-sequential, and unordered. The identifier type of int64 remains unchanged, and compatibility is preserved for clients that use IEEE 754 64-bit floating-point numbers, for example, JavaScript clients.
  • The value of the number_in_job field, included in the response to some Jobs API requests, is now set to the same value as run_id.

Note

This feature was delayed to February 2022.

User entitlements granted by group membership are displayed in the admin console

Aug 23-30, 2021: Version 3.53

User entitlements granted by group membership are now displayed for each user on the Users tab in the admin console.

Manage MLflow experiment permissions (Public Preview)

Aug 23-30, 2021: Version 3.53

You can now now manage the permissions of an MLflow experiment from the experiment page. For details, see Change permissions for experiment.

Improved job creation from notebooks

Aug 23-30, 2021: Version 3.53

You can now edit and clone jobs associated with a notebook. For details, see Create and manage scheduled notebook jobs.

Ddsv4-series VMs (Public Preview)

Aug 23-30, 2021: Version 3.53

Azure Databricks now supports the Ddsv4-series VMs. For more information about these VMs, see Ddv4 and Ddsv4-series.

Improved support for collapsing notebook headings

Aug 23-30, 2021: Version 3.53

You can now collapse or expand all collapsible headings in a notebook. Previously, you could only collapse or expand a single heading at a time. For details, see Collapsible headings.

Databricks Runtime 9.0 and 9.0 ML are GA; 9.0 Photon is Public Preview

August 17, 2021

Databricks Runtime 9.0 and 9.0 ML are now generally available. 9.0 Photon is in Public Preview.

For information, see the full release notes at Databricks Runtime 9.0 (unsupported) and Databricks Runtime 9.0 for ML (unsupported).

Databricks Runtime 9.0 (Beta)

August 10, 2021

Databricks Runtime 9.0 and Databricks Runtime 9.0 ML are now available as Beta releases.

For information, see the full release notes at Databricks Runtime 9.0 (unsupported) and Databricks Runtime 9.0 for ML (unsupported).

Manage repos programmatically with the Databricks CLI (Public Preview)

Aug 9-16, 2021: Version 3.52

You can now manage remote Git repos by using the Databricks Command Line Interface (CLI). See Repos CLI (legacy).

Manage repos programmatically with the Databricks REST API (Public Preview)

Aug 9-16, 2021: Version 3.52

You can now manage remote Git repos by using the Databricks REST API. See Repos API.

Databricks Runtime 7.6 series support ends

August 8, 2021

Support for Databricks Runtime 7.6, Databricks Runtime 7.6 for Machine Learning, and Databricks Runtime 7.6 for Genomics ended on August 8. See Databricks runtime support lifecycles.

Audit events are logged when you interact with Databricks Repos

August 9-13, 2021: Version 3.52

When audit logging is enabled, an audit event is now logged when you create, update, or delete a Databricks Repo, when you list all Databricks Repos associated with a workspace, and when you sync changes between a Databricks Repo and a remote repo. For more information, see Git folder events.

Improved job creation and management workflow

August 9-13, 2021: Version 3.52

You can now view and manage jobs associated with a notebook. Specifically, you can start a job run, view the current or most recent run, pause or resume the job’s schedule, and delete the job.

The notebook job creation UI has been revised and new configuration options added. For details, see Create and manage scheduled notebook jobs.

Photon runtimes now available (Public Preview)

August 9-13, 2021: Version 3.52

Photon is the new native vectorized engine on Azure Databricks, directly compatible with Apache Spark APIs. To provision clusters with Photon you must use a Photon image.

Simplified instructions for setting Git credentials (Public Preview)

August 9-13, 2021: Version 3.52

The instructions on the Git integration tab of the User Settings page have been simplified.

Import multiple notebooks in .html format

August 9-13, 2021: Version 3.52

You can now import multiple notebooks in .html format in a .zip file. Previously, you could only import a single notebook in .html format at a time.

The .zip file can contain folders and notebooks in either .html format or source file format (Python, Scala, SQL, or R). A .zip file cannot include both formats.

Usability improvements for Delta Live Tables

August 9-13, 2021: Version 3.52

This release includes the following enhancements to the Delta Live Tables runtime and UI:

  • When creating a pipeline, you can now specify a target database for publishing your Delta Live Tables tables and metadata. See the Publish data from Delta Live Tables to the Hive metastore for more information on publishing datasets.
  • Notebooks now support syntax highlighting for keywords in SQL dataset definitions. You can use this syntax highlighting to ensure the correctness of your Delta Live Tables SQL statements. See the SQL language reference for details on the Delta Live Tables SQL syntax.
  • The Delta Live Tables runtime now emits your pipeline graph before running the pipeline, allowing you to see the graph in the UI sooner.
  • All Python libraries configured in your notebooks are now installed before running any Python code, ensuring that libraries are globally accessible to any Python notebook in your pipeline. See [_]](../../../delta-live-tables/external-dependencies.md).