2019 年 9 月September 2019

這些功能和 Azure Databricks 平臺改良已于2019年9月發行。These features and Azure Databricks platform improvements were released in September 2019.

注意

發行是暫存的。Releases are staged. 在初始發行日期之後,您的 Azure Databricks 帳戶可能不會更新到一周。Your Azure Databricks account may not be updated until up to a week after the initial release date.

Databricks Runtime 5.2 支援結束Databricks Runtime 5.2 support ends

2019年9月30日September 30, 2019

Databricks Runtime 5.2 的支援已于9月30日結束。Support for Databricks Runtime 5.2 ended on September 30. 請參閱 Databricks 執行時間支援生命週期See Databricks runtime support lifecycle.

啟動使用 Databricks Light 的集區支援自動化叢集 (公開預覽)Launch pool-backed automated clusters that use Databricks Light (Public Preview)

2019年9月26日-年10月1日:3.3 版September 26 - October 1, 2019: Version 3.3

當我們在 七月推出集 區時,當您為自動化作業設定集區支援的叢集時,您無法選取 Databricks Light 作為執行階段版本。When we introduced Pools in July, you couldn’t select Databricks Light as your runtime version when you configured a pool-backed cluster for an automated job. 現在您可以同時擁有快速叢集的開始時間和符合成本效益的叢集!Now you can have both quick cluster start times and cost-efficient clusters!

Azure SQL Database 閘道 IP 位址會在 2019 年 10 月 14 日變更Azure SQL Database gateway IP addresses will change on October 14, 2019

在10月14日,Microsoft 會將流量遷移至 這些區域中的新閘道。On October 14, Microsoft will migrate traffic to new gateways in these regions. 如果您的工作區位於這些區域的其中一個,且您已使用「VNet 插入」 ) ,從您自己的 Azure Databricks 虛擬網路 (為合併中繼存放區設定使用者定義的路由 (UDR) ,則當這些 ip 位址變更時,您可能需要更新中繼存放區的 IP 位址。If your workspace is in one of these regions and you have configured user-defined-routes (UDR) for the consolidated metastore from your own Azure Databricks virtual network (using “VNet injection”), you may need to update the IP address for the metastore when these IP addresses change. 請參閱 Azure SQL Database 閘道 ip 位址 表,以取得您區域最新的 ip 地址清單。Consult the Azure SQL Database gateway IP addresses table for the latest list of IP addresses for your region.

標準叢集和 Scala 現在支援 Azure Data Lake Storage 認證傳遞 (公開預覽)Azure Data Lake Storage credential passthrough now supported on standard clusters and Scala (Public Preview)

2019年9月12-17:版本3。2September 12-17, 2019: Version 3.2

認證傳遞 現在可在執行 Databricks Runtime 5.5 和更新版本的標準叢集上搭配 PYTHON、SQL 和 Scala 使用,也可以在 Databricks Runtime 6.0 Beta 上進行 SparkR。Credential passthrough can now be used with Python, SQL, and Scala on standard clusters running Databricks Runtime 5.5 and above, as well as SparkR on Databricks Runtime 6.0 Beta. 到目前為止,認證傳遞需要高平行存取叢集,但不支援 Scala。Until now, credential passthrough required high concurrency clusters, which do not support Scala.

啟用 Azure Data Lake Storage 認證傳遞的叢集時,在該叢集上執行的命令可以在 Azure Data Lake Storage 中讀取和寫入資料,而不需要使用者設定服務主體認證來存取儲存體。When a cluster is enabled for Azure Data Lake Storage credential passthrough, commands run on that cluster can read and write data in Azure Data Lake Storage without requiring users to configure service principal credentials to access the storage. 系統會自動從起始動作的使用者設定認證。The credentials are set automatically from the user initiating the action.

基於安全性,只有一位使用者可以在已啟用認證傳遞的標準叢集上執行命令。For security, only one user can run commands on a standard cluster that has Credential Passthrough enabled. 單一使用者 是在建立時設定的,而且可以由具有叢集管理許可權的任何人編輯。The single user is set at creation time and can be edited by anyone with manage permissions on the cluster. 系統管理員必須確定單一使用者至少具有叢集的附加許可權。Admins need to ensure that the single user has at least attach permission on the cluster.

認證傳遞單一使用者Credential passthrough single user

pandas 資料框架現在會不經調整就在筆記本中呈現pandas DataFrames now render in notebooks without scaling

2019年9月12-17:版本3。2September 12-17, 2019: Version 3.2

在 Azure Databricks 筆記本中, displayHTML 已調整一些框架的 HTML 內容,以符合所呈現筆記本的可用寬度。In Azure Databricks notebooks, displayHTML was scaling some framed HTML content to fit the available width of the rendered notebook. 雖然這是影像的理想行為,但其轉譯的寬 pandas 資料框架不佳。While this behavior is desirable for images, it rendered wide pandas DataFrames poorly. 但不再是!But not anymore!

Python 版本選取器現在會動態顯示Python version selector display now dynamic

2019年9月12-17:版本3。2September 12-17, 2019: Version 3.2

當您選取不支援 Python 2 (例如 Databricks 6.0) 的 Databricks 執行時間時,[叢集建立] 頁面會隱藏 Python 版本選取器。When you select a Databricks runtime that doesn’t support Python 2 (like Databricks 6.0), the cluster creation page hides the Python version selector.

Databricks Runtime 6.0 BetaDatabricks Runtime 6.0 Beta

2019年9月12日September 12, 2019

Databricks Runtime 6.0 Beta 帶來許多程式庫升級和新功能,包括:Databricks Runtime 6.0 Beta brings many library upgrades and new features, including:

  • 適用于 Delta Lake DML 命令的新 Scala 和 JAVA Api,以及清理和歷程記錄公用程式命令。New Scala and Java APIs for Delta Lake DML commands, as well as the vacuum and history utility commands.
  • 增強的 DBFS 保險絲 v2 用戶端,可在模型定型期間更快速且更可靠地讀取和寫入。Enhanced DBFS FUSE v2 client for faster and more reliable reads and writes during model training.
  • 支援每個筆記本儲存格的多個 matplotlib 繪圖。Support for multiple matplotlib plots per notebook cell.
  • Python 3.7 的更新,以及更新的 numpy、pandas、matplotlib 和其他程式庫。Update to Python 3.7, as well as updated numpy, pandas, matplotlib, and other libraries.
  • Python 2 支援的終止。Sunset of Python 2 support.

如需詳細資訊,請參閱完整的 Databricks Runtime 6.0 (不支援的) 版本資訊。For more information, see the complete Databricks Runtime 6.0 (Unsupported) release notes.