2020 年 11 月November 2020

这些功能和 Azure Databricks 平台的改进已于 2020 年 11 月发布。These features and Azure Databricks platform improvements were released in November 2020.


发布分阶段进行。Releases are staged. Azure Databricks 帐户可能要等到初始发布日期后的一周或更长时间才会更新。Your Azure Databricks account may not be updated until a week or more after the initial release date.

Databricks Runtime 6.6 系列支持结束Databricks Runtime 6.6 series support ends

2020 年 11 月 26 日November 26, 2020

对 Databricks Runtime 6.6、用于机器学习的 Databricks Runtime 6.6 以及用于基因组学的 Databricks Runtime 6.6 的支持已于 11 月 26 日结束。Support for Databricks Runtime 6.6, Databricks Runtime 6.6 for Machine Learning, and Databricks Runtime 6.6 for Genomics ended on November 26. 请参阅 Databricks 运行时支持生命周期See Databricks runtime support lifecycle.

MLflow 模型注册表正式版MLflow Model Registry GA

2020 年 11 月 18 日- 12 月 1 日:版本 3.33November 18 - December 1, 2020: Version 3.33

MLflow 模型注册表现已正式发布。MLflow Model Registry is now GA. 自从模型注册表发布公共预览版以来,已经进行了一些改进:Several improvements have been made since Model Registry was released for Public Preview:

  • 对模型注册表对象的操作的诊断日志记录。Diagnostic logging for actions on model registry objects. 现在,模型注册表中的操作会捕获到诊断日志中。Actions in Model Registry are now captured in diagnostic logs. 有关所记录的操作和参数,请参阅诊断日志事件See Diagnostic log events for the logged actions and parameters.

  • 模型版本的注释。Comments for model versions. 你现在可以添加对模型版本的注释,以便使用模型注册表进行团队讨论,帮助管理模型生产化管道。You can now add comments to model versions, allowing you to use Model Registry for team discussions to help manage your model productionization pipeline.

  • 有关模型和模型版本的标记。Tags on models and model versions. 你可以为模型和模型版本创建标记,并使用 API 搜索它们。You can create tags for models and model versions, and search for them using the API.

  • 已注册模型页的 URL 的改进。Improvements to the URL of the registered models page. 此页面的 URL 现在保留其历史记录,因此,在此页中进行查询和查看模型时,可以使用浏览器的后退和前进按钮进行导航。The URL of this page now keeps its history, so you can navigate with the browser back and forward buttons as you make queries and view models from this page. 你还可以将该 URL 与同事共享,同事会看到同一视图。You can also share the URL with colleagues who will see the same view.

根据注册的模型是否关联来筛选试验运行Filter experiment runs based on whether a registered model is associated

2020 年 11 月 18 日- 12 月 1 日:版本 3.33November 18 - December 1, 2020: Version 3.33

查看试验的运行时,现在可以根据运行是否创建了模型版本来筛选运行。When viewing runs for an experiment, you can now filter runs based on whether they created a model version or not. 有关详细信息,请参阅筛选运行For more information, see Filter runs.

2020 年 11 月 18 日- 12 月 1 日:版本 3.33November 18 - December 1, 2020: Version 3.33

“合作伙伴集成”库已从“帐户”菜单移动到“添加数据”选项卡。有关详细信息,请参阅合作伙伴数据集成The Partner Integrations gallery has moved from the Account menu to the Add Data tab. For more information, see Partner data integrations.

群集策略现使用“允许列表”和“阻止列表”作为策略类型名称 Cluster policies now use allowlist and blocklist as policy type names

2020 年 11 月 18 日- 12 月 1 日:版本 3.33November 18 - December 1, 2020: Version 3.33

群集策略现使用“允许列表”和“阻止列表”作为策略类型,替换了“白名单”和“黑名单”。Cluster policies now use “allowlist” and “blocklist” as policy types, replacing “whitelist” and “blacklist.” 请参阅群集策略定义See Cluster policy definitions. 请注意,这最初是作为 3.31 版功能发布的,这是不正确的。Note that this was originally announced as a version 3.31 feature, which was incorrect.

创建作业群集失败时自动重试Automatic retries when the creation of a job cluster fails

2020 年 11 月 18 日- 12 月 1 日:版本 3.33November 18 - December 1, 2020: Version 3.33

当发生特定的可恢复错误时,Azure Databricks 现在会自动重试创建作业群集。Azure Databricks now automatically retries the creation of job clusters when specific recoverable errors occur. 作业运行会保持 RunLifeCycleState:挂起状态,直到群集成功启动。Job runs remain in RunLifeCycleState: PENDING until successful cluster launch. 每次尝试都有不同的 cluster_id 和名称。Each attempt has a different cluster_id and name. 成功创建群集后,运行会转变为 RunLifeCycleState:正在运行状态。When cluster creation succeeds, the run transitions to RunLifeCycleState: RUNNING.

2020 年 11 月 18 日- 12 月 1 日:版本 3.33November 18 - December 1, 2020: Version 3.33

你现在可以查看笔记本的目录,并使用它在笔记本中快速导航。You can now view a table of contents for your notebooks and use it to quickly navigate within a notebook. 笔记本目录是基于 Markdown 标题自动创建的。The notebook table of contents is automatically created based on the Markdown headings. 有关详细信息,请参阅查看目录For more information, see View table of contents.

SQL Analytics(公共预览版)SQL Analytics (Public Preview)

2020 年 11 月 18 日November 18, 2020

Databricks 很高兴地推出 SQL Analytics,这是一个直观的环境,可用于运行临时查询和基于数据湖中存储的数据创建仪表板。Databricks is pleased to introduce SQL Analytics, an intuitive environment for running ad-hoc queries and creating dashboards on data stored in your data lake. SQL Analytics 可助力组织运行多云 lakehouse 体系结构,该体系结构可为数据仓库性能提供数据湖经济性,同时提供良好的 SQL Analytics 用户体验。SQL Analytics empowers your organization to operate a multi-cloud lakehouse architecture that provides data warehousing performance with data lake economics while providing a delightful SQL analytics user experience. SQL Analytics:SQL Analytics:

  • 与当前使用的 BI 工具(例如 Tableau 和 Microsoft Power BI)集成,查询数据湖中最完整和最新的数据。Integrates with the BI tools you use today, like Tableau and Microsoft Power BI, to query the most complete and recent data in your data lake.
  • 使用 SQL 原生接口对现有 BI 工具进行补充,该接口支持数据分析师和数据科学家直接在 Azure Databricks 中查询数据湖数据。Complements existing BI tools with a SQL-native interface that allows data analysts and data scientists to query data lake data directly within Azure Databricks.
  • 支持通过丰富的可视化效果和拖放式仪表板共享查询见解,以及自动在重要数据发生更改时发出警报。Enables you to share query insights through rich visualizations and drag-and-drop dashboards with automatic alerting for important data changes.
  • 使用 SQL 终结点为数据湖引入可靠性、质量、缩放、安全性和性能,以便用户使用最新和最完整的数据来运行常规的分析工作负载。Uses SQL endpoints to bring reliability, quality, scale, security, and performance to your data lake, so you can run traditional analytics workloads using your most recent and complete data.

有关详细信息,请参阅 Azure Databricks SQL Analytics 指南See the Azure Databricks SQL Analytics guide for details. 请联系 Azure Databricks 代表,以申请访问权限。Contact your Azure Databricks representative to request access.

单节点群集现支持 Databricks 容器服务Single Node clusters now support Databricks Container Services

2020 年 11 月 4-10 日:版本 3.32November 4-10, 2020: Version 3.32

你现在可以在单节点群集上使用 Databricks 容器服务。You can now use Databricks Container Services on Single Node clusters. 有关详细信息,请参阅单节点群集使用 Databricks 容器服务自定义容器For more information, see Single Node clusters and Customize containers with Databricks Container Services.

Databricks Runtime 7.4 正式版Databricks Runtime 7.4 GA

2020 年 11 月 3 日November 3, 2020

Databricks Runtime 7.4、Databricks Runtime 7.4 ML 和用于基因组学的 Databricks Runtime 7.4 现已正式发布。Databricks Runtime 7.4, Databricks Runtime 7.4 ML, and Databricks Runtime 7.4 for Genomics are now generally available.

有关信息,请参阅 Databricks Runtime 7.4用于机器学习的 Databricks Runtime 7.4用于基因组学的 Databricks Runtime 7.4 提供的完整发行说明。For information, see the full release notes at Databricks Runtime 7.4, Databricks Runtime 7.4 for Machine Learning, and Databricks Runtime 7.4 for Genomics.

Databricks JDBC 驱动程序更新Databricks JDBC driver update

2020 年 11 月 3 日November 3, 2020

发布新版本的 Databricks JDBC 驱动程序。A new version of the Databricks JDBC driver has been released. 新版本包含很多 bug 修复,最值得注意的是,驱动程序现在会返回通过 DML 操作修改的行的正确数目(如果 Databricks Runtime 提供该行数)。The new version contains a number of bug fixes, most notably, the driver now returns the correct number of modified rows from DML operations when it is provided by Databricks Runtime.

Databricks Connect 7.3(beta 版本)Databricks Connect 7.3 (Beta)

2020 年 11 月 3 日November 3, 2020

Databricks Connect 7.3 现在作为 Beta 版本提供。Databricks Connect 7.3 is now available as a Beta release.

Databricks Connect 7.3 允许你使用 Azure Active Directory 令牌向 Azure Databricks 进行身份验证,并支持 Azure Active Directory 凭据直通。Databricks Connect 7.3 lets you use Azure Active Directory tokens to authenticate to Azure Databricks and supports Azure Active Directory credential passthrough. 这样就可以通过 Databricks Connect 使用对 Azure Databricks 进行身份验证所用的 Azure Active Directory 标识对 Azure Data Lake Storage Gen1 和 Azure Data Lake Storage Gen2 自动进行身份验证。This enables you to authenticate automatically to Azure Data Lake Storage Gen1 and Azure Data Lake Storage Gen2 from Databricks Connect using the same Azure Active Directory identity that you use to authenticate to Azure Databricks.

有关详细信息,请参阅 Databricks ConnectDatabricks Connect 发行说明For more information, see Databricks Connect and Databricks Connect release notes.