Azure Data Studio 的数据虚拟化扩展Data Virtualization extension for Azure Data Studio

Azure Data Studio 的数据虚拟化扩展为 ODBC 数据源的外部表向导提供支持。The Data Virtualization extension for Azure Data Studio provides support for the External Table Wizard with ODBC data sources.

安装数据虚拟化扩展Install the Data Virtualization extension

若要安装数据虚拟化扩展,请访问扩展 Azure Data Studio 的功能To install the Data Virtualization extension, visit Extend the functionality of Azure Data Studio.

版本 1.0 中的更改Changes in release 1.0

  • 扩展重命名为数据虚拟化。Extension renamed to Data Virtualization.
  • “创建外部表”向导:Create External Table wizard:
    • 包含了适用于虚拟化 MongoDB 和 Teradata 源的引导式笔记本。Included guided notebooks for virtualization MongoDB and Teradata sources.
    • 添加了用于填写 MongoDB 和 Teradata 虚拟化笔记本中的变量的对话框。Added dialog to fill out variables in MongoDB and Teradata virtualization notebooks.

版本 0.16 中的更改Changes in release 0.16

  • “创建外部表”向导:Create External Table wizard:
    • 改进了在对象映射页上加载表和视图时的错误处理。Improved error handling when loading tables and views on object-mapping page.

版本 0.15 变化Changes in release 0.15

  • “创建外部表”向导:Create External Table wizard:
    • 缩短了加载“对象映射”页面上的表和列信息所需的时间。Reduced time taken to load table and column information on the object-mapping page.
    • 修复了在“连接详细信息”页上加载现有数据库范围凭据时出现的 bug。Fixed a bug with loading existing database scoped credentials on the connection details page.
  • “从 CSV 文件创建外部表”向导:Create External Table from CSV Files Wizard:
    • 增加了用于 PROSE 分析的默认样本大小。Increased default sample size used for PROSE parsing.

版本 0.14.1 中的更改Changes in release 0.14.1

  • 支持 CTP 3.1 数据源支持Support for CTP 3.1 data source support

版本 0.12.1 中的更改Changes in release 0.12.1

  • 此版本中已删除 SQL Server 大数据群集连接类型。The SQL Server big data cluster connection type has been removed in this release. 之前 SQL Server 大数据群集连接提供的所有功能现在都可以在 SQL Server 连接中获取。All functionality previously available from the SQL Server big data cluster connection is now available in the SQL Server connection.
  • 可以在“数据服务”文件夹下找到 HDFS 浏览HDFS browsing can be found under the Data Services folder
  • 对于笔记本,PySpark 和其他大数据内核在连接到 SQL Server 大数据群集中的 SQL Server 主实例时可以正常工作。For notebooks, the PySpark and other big data kernels work when connected to the SQL Server master instance in your SQL Server big data cluster.
  • “创建外部表”向导:Create External Table wizard:
    • 支持使用现有外部数据源创建外部表。Support for creating External Table using existing External Data Source.
    • 对整个向导进行了性能改进。Performance improvements across the wizard.
    • 改进了对具有特殊字符的对象名称的处理效果。Improved handling of object names with special characters. 在某些情况下,这些字符曾导致向导发生故障In some cases, these caused the wizard to fail
    • 增强了“对象映射”页的可靠性。Reliability improvements for the Object-Mapping page.
    • 从数据库下拉列表中删除了系统数据库 - DWConfigurationDWDiagnosticsDWQueueRemoved system databases - DWConfiguration, DWDiagnostics, DWQueue - from the databases dropdown.
    • 支持在“从 CSV 文件创建外部表”向导中设置外部文件格式对象的名称。Support for setting the External File Format object's name in the Create External Table from CSV Files wizard.
    • 在“从 CSV 文件创建外部表”向导的第一页中添加了一个刷新按钮。Added a refresh button to the first page of the Create External Table from CSV Files wizard.

发行说明 (v 0.11.0)Release Notes (v0.11.0)

  • Jupyter Notebook 支持,特别是对 Python3 和 Spark 内核的支持,已转移到 Azure Data Studio 中。Jupyter Notebook support, specifically support for the Python3 and Spark kernels, has been moved into Azure Data Studio. 使用 Notebook 时不再需要此扩展。This extension is no longer required in order to use Notebooks.
  • 修复了外部数据向导中的多个 Bug:Multiple bug fixes in the External Data wizards:
    • Oracle 类型映射已更新,以匹配 SQL Server 2019 CTP 2.3 中的更改。Oracle type mappings have been updated to match changes shipped in SQL Server 2019 CTP 2.3.
    • 修复了在表映射控件中键入的新架构会丢失的问题。Fixed an issue where new schemas typed into the table-mapping controls were being lost.
    • 修复了检查表映射中的数据库节点时未检查全部表和视图的问题。Fixed an issue where checking a Database node in the table-mappings didn't result in all tables and views being checked.

发行说明 (v 0.10.2)Release Notes (v0.10.2)

SQL Server 2019 支持SQL Server 2019 support

对 SQL Server 2019 的支持已更新。Support for SQL Server 2019 has been updated. 在连接到 SQL Server 大数据群集实例后,资源管理器树中会显示一个新的“数据服务”文件夹。After connecting to a SQL Server Big Data Cluster instance, a new Data Services folder appears in the explorer tree. 该文件夹包含一些操作的启动点,这些操作包括针对连接打开新 Notebook、提交 Spark 作业以及使用 HDFS 等。The folder has launch points for actions such as opening a new notebook against the connection, submitting Spark jobs, and working with HDFS. 对于某些操作(例如通过 HDFS 文件/文件夹创建外部数据),必须安装 SQL Server 2019 扩展 。Some actions, such as Create External Data over an HDFS file/folder, the SQL Server 2019 extension must be installed.

Notebook 支持Notebook support

我们对笔记本用户界面进行了较大程度的更新。We have made significant updates to the notebook user interface. 我们的工作重点是让你能够轻松读取别人与你共享的笔记本。Our focus is on making it easy to read notebooks that are shared with you. 这意味着删除单元格周围的所有边框(已选中或鼠标悬停的单元格除外)、添加悬停支持以便于无需选择单元格即可轻松实施单元格级操作、通过添加执行计数和一个动态“停止运行”按钮等内容来明确执行状态。This meant removing all outline boxes around cells unless selected or hovered, adding hover support for easy cell-level actions without need to select a cell, and clarifying execution state by adding execution count, an animated stop running button and more. 我们还为后列操作添加了键盘快捷方式:新建笔记本 (Ctrl+Shift+N)、运行单元 (F5)、新代码单元 (Ctrl+Shift+C)、新文本单元 (Ctrl+Shift+T) 。We also added keyboard shortcuts for New Notebook (Ctrl+Shift+N), Run Cell (F5), New Code Cell (Ctrl+Shift+C), New Text Cell (Ctrl+Shift+T). 我们的目标是让你能够通过快捷方式实现所有关键操作,所以请告诉我们还缺少哪些吧!We aim to have all key actions launchable by shortcut so let us know what you're missing!

其他改进和修复包括:Other improvements and fixes include:

  • SQL Server 2019 扩展现会提示用户为 Python 依赖项选取安装目录。The SQL Server 2019 extension now prompts users to pick an install directory for Python dependencies. 它也不再在 .vsix file 中包含 Python,从而减少了整体扩展大小。It also no longer includes Python in the .vsix file, reducing overall extension size. Python 依赖项支持 Spark 和 Python3 内核。The Python dependencies support Spark and Python3 kernels.

  • 添加了对“从命令行启动新笔记本”的支持。Support for launching a new notebook from the command line has been added. 使用参数 --command=notebook.command.new --server=myservername 启动时应会打开一个新笔记本并连接到此服务器。Launch with the arguments --command=notebook.command.new --server=myservername should open a new notebook and connect to this server.

  • 对单元格中代码长度较长的笔记本进行了性能修复。Performance fixes for notebooks with a large code length in cells. 如果代码单元格超过 250 行,则会添加一个滚动条。If code cells are over 250 lines, a scrollbar is added.

  • 改进了 .ipynb 文件支持。Improved .ipynb file support. 现在支持版本 3 或更高版本。Version 3 or higher is now supported.

    备注

    保存文件更新到版本 4 或更高版本。Saving files updates to version 4 or higher.

  • 因为内置的 Notebook 查看器稳定,所以现在删除了 notebook.enabled 用户设置。The notebook.enabled user setting has been removed now that the built-in Notebook viewer is stable.

  • 现在支持高对比度主题,并在此前提下对对象布局进行了一些修复。High Contrast theme is now supported with a number of fixes to object layout in this case.

  • 修复了 #3680 问题:输出有时会错误地显示一些 ,,, 字符。Fixed #3680 where outputs sometimes showed a number of ,,, characters incorrectly.

  • 修复了#3602 问题:编辑器在离开 Azure Data Studio 后消失。Fixed #3602 Editor disappears for cells after navigating away from Azure Data Studio.

  • 添加了支持:为 application/vnd.dataresource+json 输出 MIME 类型使用“网格”视图。Support has been added to use Grid views for the application/vnd.dataresource+json output MIME type. 这意味着许多使用此选项的笔记本(例如通过在 Python 笔记本中设置 pd.options.display.html.table_schema)会具有更美观的表格输出。This means many notebooks that use this (for example by setting pd.options.display.html.table_schema in a Python notebook) have nicer tabular outputs.

已知问题Known issues

  • 打开 Notebook 时,会出现“安装 python”对话框。When opening a Notebook, the install python dialog appears. 取消此安装后,“内核”和“附加到”下拉列表不会显示预期值。Canceling this install results in the Kernels and Attach To dropdowns not showing expected values. 暂时的解决方法是完成 Python 安装。The workaround is to complete the Python installation.
  • 使用不受支持的内核打开笔记本时,“内核”和“附加到”下拉列表会导致 Azure Data Studio 停止响应。When a notebook is opened with a kernel that isn't supported, the kernels and attach to dropdowns causes Azure Data Studio to stop responding. 关闭 Azure Data Studio,并确保使用受支持的内核(Python3、Spark | R、Spark | Scala、PySpark、PySpark3)。Close Azure Data Studio and ensure you use a kernel that is supported (Python3, Spark | R, Spark | Scala, PySpark, PySpark3).
  • 当对 SQL Server 终结点使用 PySpark3 或其他 Spark 内核时,Spark UI 链接失败。Spark UI link fails when using PySpark3 or other Spark kernels against the SQL Server endpoint. 一个暂时的解决方法是,在仪表板中选择“Spark UI”,或使用 SQL Server 大数据群集连接类型进行连接,因为这会得到正确的 Spark UI 超链接。As a workaround, select on Spark UI from the Dashboard, or connect using the SQL Server big data cluster connection type as this has the correct Spark UI hyperlink.

扩展性改进Extensibility improvements

此版本中添加了许多可优化扩展程序控件的改进。A number of improvements that help extenders were added in this release.

  • 通过一个新的 ObjectExplorerNodeProvider API,扩展能够在 SQL Server 或其他连接节点下贡献文件夹。A new ObjectExplorerNodeProvider API allows extensions to contribute folders under SQL Server or other Connection nodes. 这是在 SQL Server 2019 实例下添加 Data Services 节点的方式,但可以用于将“监视”文件夹或其他文件夹轻松添加到 UI。This is how the Data Services node is added under SQL Server 2019 instances but could be used to add Monitoring or other folders easily to the UI.
  • 有两个新的上下文键值可用于帮助显示/隐藏对仪表板的贡献。Two new context key values are available to help show/hide contributions to the dashboard.
    • mssql:iscluster 指示这是否是 SQL Server 2019 大数据群集mssql:iscluster indicates if this is a SQL Server 2019 Big Data Cluster
    • mssql:servermajorversion 指示服务器版本(15 为 SQL Server 2019,14 为 SQL Server 2017,依此类推)。mssql:servermajorversion has the server version (15 for SQL Server 2019, 14 for SQL Server 2017, and so on). 如果只显示(例如)SQL Server 2017 或更高版本的功能,可以使用这个键。This can help if features should only be shown for SQL Server 2017 or greater, for example.

发行说明 (v 0.8.0)Release Notes (v0.8.0)

NotebooksNotebooks:

  • 现在是通过选择“更多操作”单元格按钮来支持在现有单元格之前/之后添加单元格Adding cells before / after existing cells are now supported by selecting the "More Actions" cell button
  • 已向“附加到”下拉列表中的连接中添加了“添加新连接”选项Add New Connection option has been added to the connections in the "Attach To" dropdown
  • 添加了“重新安装 Notebook 依赖项”命令,用于协助 Python 程序包更新,同时,可通过关闭应用程序解决安装过程中途停止的问题。A Reinstall Notebook Dependencies command has been added to assist with Python package updates, and solve cases where install was halted partway through by closing the application. 该命令可通过命令面板运行(使用 Ctrl/Cmd+Shift+P 并键入 Reinstall Notebook DependenciesThis can be run from the command palette (use Ctrl/Cmd+Shift+P and type Reinstall Notebook Dependencies)
  • PROSE python 包已更新到 1.1.0 并修复了许多 Bug。The PROSE python package has been updated to 1.1.0 and includes a number of bug fixes. 使用“重新安装 Notebook 依赖项”命令更新此包Use the Reinstall Notebook Dependencies command to update this package
  • 现在,选择“更多操作”单元格按钮,可使用“清除输出”命令 A Clear Output command is now supported by selecting the More Actions cell button
  • 修复了客户报告的以下问题:Fixed the following customer reported issues:
    • 由于 PATH 问题,笔记本会话无法在 Windows 上启动Notebook session couldn't start on Windows due to PATH issues
    • 无法从驱动器的根文件夹启动 Notebook,例如 C:\ 或 D:Notebook couldn't be started from the root folder of a drive, such as C:\ or D:\
    • #2820 无法在 VS Code 中编辑从 ADS 创建的笔记本#2820 Unable to edit notebooks created from ADS in VS Code
    • 现在,运行 Spark 内核时,Spark UI 链接可正常运行Spark UI link now works when running a Spark kernel
    • 将“托管包”重命名为“安装包”Renamed "Managed Packages" to "Install Packages"

创建外部数据Create External Data:

  • 错误消息可以复制,并已拆分为摘要和详细视图,以便于查看Error messages are copyable and have been separated into a summary and detailed view for easier
  • 改进了 UI 布局,还改进了可靠性和错误处理Improved UI layout and improved reliability and error handling
  • 修复了客户报告的以下问题:Fixed the following customer reported issues:
    • 具有无效列映射的表显示为“禁用”,并会显示一个说明错误的警告Tables with invalid column mappings are shown as disabled and a warning explains the error

发行说明 (v 0.7.2)Release Notes (v0.7.2)

  • Azure 资源浏览器现已内置于 Azure Data Studio 中,并已从此扩展中删除。Azure Resource Explorer is now built into Azure Data Studio and has been removed from this extension. 非常感谢你提供反馈!Thank you for your feedback on this!
  • 改进了具有许多 Markdown 单元格的笔记本的性能。Improved performance of notebooks with many Markdown cells.
  • 在 Notebook 中自动调整代码单元格的大小。Autosize code cells in Notebook. 该单元格仍具有基于单元格工具栏的最小大小。This still has a minimum size based on the cell toolbar.
  • 安装 Notebook 依赖项时通知用户。Notify user when installing Notebook dependencies. 特别是在 Windows 上,这可能需要很长时间,因此通知现在显示在“任务”视图中。On Windows in particular this can take a long time, so notifications are now shown in the Tasks view.
  • 支持重新安装 Notebook 依赖项。Support reinstalling Notebook dependencies. 如果用户之前在安装途中关闭了 Azure Data Studio,此功能会很有用。This is useful if the user previously closed Azure Data Studio partway through installation.
  • 支持在 Notebook 中取消单元格执行。Support canceling cell execution in Notebook.
  • 提高了使用“创建外部数据”向导时的可靠性,特别是在发生连接错误时。Improved reliability when using Create External Data wizard, specifically when connection errors occur.
  • 如果未在目标服务器中启用或运行 PolyBase,则阻止使用“创建外部数据”向导。Block use of Create External Data wizard if PolyBase isn't enabled or running in the target server.
  • 修复了与 SQL Server 2019 和创建外部数据相关的拼写和命名问题。Spelling and naming fixes related to SQL Server 2019 and Create External Data.
  • 消除了 Azure Data Studio 调试控制台中的大量错误。Removed a large number of errors from the Azure Data Studio debug console.