2018 年 1 月January 2018

發行是暫存的。Releases are staged. 您的 Databricks 帳戶可能會在初始發行日期的一周後才更新。Your Databricks account may not be updated until a week after the initial release date.

Azure Blob 儲存體容器和 Data Lake Store 的掛接點Mount points for Azure Blob storage containers and Data Lake Stores

Jan 16-23,2018:版本2.63Jan 16-23, 2018: Version 2.63

我們已提供透過 Databricks 檔案系統裝載 Azure Blob 儲存體容器和 Data Lake 存放區 (DBFS) 的指示。We have provided instructions for mounting Azure Blob storage containers and Data Lake Stores through the Databricks File System (DBFS). 這會讓相同工作區中的所有使用者都能夠存取 Blob 儲存體容器或 Data Lake Store 容器內的 (或資料夾,或透過掛接點儲存) 。This gives all users in the same workspace the ability to access the Blob storage container or Data Lake Store (or folder inside the container or store) through the mount point. DBFS 會管理用來存取掛接 Blob 儲存體容器或 Data Lake Store 的認證,並自動處理 Azure Blob 儲存體的驗證,或在背景中 Data Lake Store。DBFS manages the credentials used to access a mounted Blob storage container or Data Lake Store and automatically handles the authentication with Azure Blob storage or Data Lake Store in the background.

裝載 Blob 儲存體容器和 Data Lake 存放區需要 Databricks Runtime 4.0 和更新版本。Mounting Blob storage containers and Data Lake Stores requires Databricks Runtime 4.0 and above. 裝載容器或存放區之後,您就可以使用執行時間3.4 或更高版本來存取掛接點。Once a container or store is mounted, you can use Runtime 3.4 or above to access the mount point.

如需詳細資訊,請參閱 Azure Blob 儲存體Azure Data Lake Storage Gen1See Azure Blob storage and Azure Data Lake Storage Gen1 for more information.

叢集標籤Cluster tags

Jan 4-11,2018:版本2.62Jan 4-11, 2018: Version 2.62

您現在可以指定將傳播至所有 Azure 資源的叢集標籤, (Vm、磁片、Nic 等) 與叢集相關聯的資源。You can now specify cluster tags that will be propagated to all Azure resources (VMs, disks, NICs, etc) associated with a cluster. 除了使用者提供的標記之外,資源也會自動以叢集名稱、叢集識別碼和叢集建立者使用者名稱標記。In addition to user-provided tags, resources will automatically be tagged with the cluster name, cluster ID, and cluster creator username.

如需詳細資訊,請參閱叢集 標記See Cluster tags for more information.

適用於 SQL 和 Python 的資料表存取控制 (個人預覽版)Table Access Control for SQL and Python (Private Preview)

Jan 4-11,2018:版本2.62Jan 4-11, 2018: Version 2.62

注意

這項功能處於個人預覽版狀態。This feature is in private preview. 請洽詢您的帳戶管理員以要求存取權。Please contact your account manager to request access. 這項功能也需要 Databricks Runtime 3.5 +。This feature also requires Databricks Runtime 3.5+.

去年,我們引進了 SQL 使用者的資料物件存取控制。Last year, we introduced data object access control for SQL users. 今天,我們很高興宣佈 SQL 和 Python 使用者的資料表存取控制 (ACL) 的個人預覽版。Today we are excited to announce the private preview of Table Access Control (ACL) for both SQL and Python users. 使用資料表存取控制,您可以限制對安全物件(例如資料表、資料庫、視圖或函數)的存取。With Table Access Control, you can restrict access to securable objects like tables, databases, views, or functions. 您也可以針對符合特定條件的資料列和資料行提供更精細的存取控制 (,例如) ,方法是在包含任意查詢的衍生視圖上設定許可權。You can also provide fine-grained access control (to rows and columns matching specific conditions, for example) by setting permissions on derived views containing arbitrary queries.

如需詳細資訊,請參閱 資料物件使用權限See Data object privileges for more information.

透過 API 匯出筆記本作業執行結果Exporting notebook job run results via API

Jan 4-11,2018:版本2.62Jan 4-11, 2018: Version 2.62

為了改善您在作業結果上共用和共同作業的能力,我們現在有新的工作 API 端點,可 jobs/runs/export 讓您在程式碼和儀表板視圖中,取得筆記本作業執行結果的靜態 HTML 標記法。To improve your ability to share and collaborate on the results of jobs, we now have a new Jobs API endpoint, jobs/runs/export that lets you retrieve the static HTML representation of a notebook job’s run results in both code and dashboard view.

如需詳細資訊,請參閱 執行匯出See Runs export for more information.

Apache Airflow 1.9.0 包含 Databricks 整合Apache Airflow 1.9.0 includes Databricks integration

Jan 2,2018Jan 2, 2018

去年,我們在空氣中發行了一項預覽功能,這是管理 ETL 排程的熱門解決方案,可讓客戶以原生方式建立可觸發 Databricks 在氣流 DAG 中執行的工作。Last year, we released a preview feature in Airflow—a popular solution for managing ETL scheduling—that allows customers to natively create tasks that trigger Databricks runs in an Airflow DAG. 我們很高興宣佈這些整合已在1.9.0 版本的空氣中公開發行。We’re pleased to announce that these integrations have been released publicly in the 1.9.0 release of Airflow.

如需詳細資訊,請參閱 Apache 空氣See Apache Airflow for more information.